Enhancing the Population Census: a Time Series for Sub-National Areas with Age, Sex, and Ethnic Group Dimensions In

Enhancing the population census: a time series for sub-national areas with age, sex, and ethnic group dimensions in

England and Wales, 1991-2001

CCSR Working Paper 2007-11 Albert Sabater and Ludi Simpson Albert.sabater@manchester.ac.uk

Ethnicity data from successive censuses are used to compare population change. This paper shows that such comparisons are often impossible, wrong or misleading. Distortions become more severe as the scale of areal units become smaller. The paper outlines the four main sources of confusion and applies solutions for England and Wales for 1991-2001. The paper presents methods that can be used to resolve these difficulties and produce more accurate results, and produces a consistent time series for single years of age, ethnic group and sex that can be aggregated from the smallest census output areas.

www.ccsr.ac.uk

0 UK Data Archive Study Number 6043 - Population Estimates by Single Year of Age, Sex and Ethnic Group for Sub-national Areas in England and Wales, 1991-2001 Enhancing the population census: a time series for sub-national areas with age, sex, and ethnic group dimensions in England and Wales, 1991- 2001 Albert Sabater and Ludi Simpson [email protected] Cathie Marsh Centre for Census and Survey Research (CCSR), University of Manchester, Manchester, M13 9PL, UK

Albert Sabater: Post-Doctoral Research Fellow Ludi Simpson: Professor of Population Studies

1 Enhancing the population census: a time series for sub-national areas with age, sex, and ethnic group dimensions in England and Wales, 1991- 2001

Abstract Ethnicity data from successive censuses are used to compare population change. This paper shows that such comparisons are often impossible, wrong or misleading. Distortions become more severe as the scale of areal units become smaller. The paper outlines the four main sources of confusion and applies solutions for England and Wales for 1991-2001. (1) Classifications including ethnic group and age changed between censuses; (2) non-response varies between ethnic groups, areas and ages and its treatment differs in each census; (3) students were counted at their home address in 1991 and at their educational address in 2001; (4) geographical boundaries used for standard census outputs changed. Each of these factors operates differentially on the outcome. Finally there is an additional problem of projecting census data taken on different dates of census years to comparable mid-year estimates each year.

The paper presents methods that can be used to resolve these difficulties and produce more accurate results, and produces a consistent time series for single years of age, ethnic group and sex that can be aggregated from the smallest census output areas. The enhanced dataset will be used for projections, assessment of employment and health trends, and estimation of migration in the intercensal decade. As an indication, after adjustment, Birmingham district’s total population showed a 2% loss rather than the 1.7 percent gain derived from the direct 1991-2001 comparison; the Black Caribbean population shows a decrease rather than an increase.

Keywords: sub-national areas; ethnic groups; population change; England and Wales; non-response

2 Enhancing the population census: a time series for sub-national areas with age, sex, and ethnic group dimensions in England and Wales, 1991- 2001

Introduction Ethnic origin, age, sex and locality are fundamental dimensions for social analysis. Not only demographers are interested in how population composition is changing along these dimensions. Workforce participation, care of the elderly, political engagement, incidence of disease, the demand for housing, and the impact of increasingly diverse societies cannot be understood without relation to the composition of the population and its development over time. To the extent that counts of people and their age, sex and ethnic characteristics are unavailable, inaccurate or incompatible over time, all these analyses suffer. While ethnic origin (or race, ethnicity, ethnic group or heritage as it may be termed in different contexts) is more debateable as a demographic category than age or sex, it has become commonplace to prepare population tabulations differentiated by ethnic origin because of its centrality to policy debates and public services and the social analyses that inform them.

In the UK as in other countries where ethnic origin is a category used in population and social analysis the population census is the main source of comprehensive published statistics concerning the changing composition of the population both nationally and for smaller areas. The 1991 and 2001 Censuses of Population in England and Wales have provided comprehensive data of ethnic groups from national to local areas, thus stimulating analytical new research about the characteristics and distribution of the population (Dorling and Rees, 2003; Lupton and Power, 2004; Parkinson et al, 2006; Simpson, 2007).

However, census statistics are neither wholly accurate nor comparable over time. In order to judge social polarisation over time, Dorling and Rees use “1991 Census data which have both bee re-aggregated to 2001 local authority boundaries and meticulously adjusted for over a million people who were not recorded by that census” in order to make the two censuses “broadly comparable” (2003: 1289). Lupton and Power introduce their briefing on minority ethnic groups in Britain from

3 the censuses of 1991 and 2001 with warnings of several problems that beset an attempt to make use of the opportunity that a census time series appears to offer:

“One is the problem of the use of different ethnic categories in 1991 and 2001, principally the introduction of 'mixed race' options in 2001. … Other problems arise … because comparisons of 1991 and 2001 Census data probably show greater increases in population than actually occurred, especially in urban areas where undercounting was worst. They also show artificially high increases in urban areas because the 2001 Census counted students at their term addresses, while the 1991 Census counted them at their vacation addresses. … For example, Liverpool's population declined by 3% according to the Census figures, and 7% according to the MYEs” (2004: 2-3).

Lupton and Power note that government Mid-Year Estimates (MYEs) provide consistent population definition over time but are not produced separately for 1991 for characteristics of population such as ethnic group, although these are more likely to be undercounted in the census. Their solution for neighbourhood analysis to adopt a set of population estimates funded by the Economic and Social Research Council which for 1991 included an element for non-response (Simpson S, 2002), but these are not consistent with the latest thinking on the total 1991 population from statistical agencies.

Some comparisons between censuses are misleading if inconsistencies between censuses are not allowed for. Later in this paper we shall show that some minority ethnic population increases according to the census are in fact decreases when full populations are compared over time. As well as changes in population definition, nonresponse and variable categories, Britain’s predilection for changing boundaries for census output has misled analysts. A major government report on the state of English cities singled out Blackburn as the area with a significant increase in ethnic segregation, but the apparent increase was entirely an artefact of different boundaries used in the 1991 and 2001 Censuses (Parkinson et al, 2006; Simpson, 2007).

The contributions of this paper are to specify the problems of census tabulations as indicators of population change, and to overcome them. By providing complete and

4 consistent sub-national mid-1991 and mid-2001 population estimates for very small areas and single years of age, with sex and ethnic group disaggregation, we allow social researchers to undertake more analyses and to avoid misleading analyses.

Other countries face similar problems in constructing accurate time series of full population estimates with an ethnic group dimension, here reviewed through the experience of the USA, Canada, New Zealand and Australia. However, different approaches are taken. For example in the U.S., the mid-2000 population estimates are derived from the census usually resident population using a cohort component method, thus accounting demographic change (births, deaths and net migration) between Census day and mid-year in sub-national areas for each age, sex and race, and Hispanic origin group. The approach also takes into consideration the net movement of U.S Armed Forces overseas. One of the main challenges appears to be the recoding of each of the persons who identified themselves in the ‘Some other race’ category in the 2000 Census categories to one or more of the five Office of Management and Budget (OMB) race categories, which is used for the presentation of population estimates. Underenumeartion and duplication of persons were thought to balance each other, so that no adjustment was made (Siegel, 2002; USCB, 2006).

In Canada, quarterly population estimates are produced but without ethnic group (SC, 2006). However, population projections for visible minority populations for provinces and regions by age and sex for census years are generated by microsimulation. The base population used consists of a 20% census sample of permanent residents, which is adjusted for underenumeration (Bélanger and Caron Malenfant, 2005).

In New Zealand, population estimates are produced from the census usually resident population. The method is based on a cohort component method which takes into account demographic change between Census night and mid-year by ethnicity, age and sex for sub-national areas. Adjustments for residents temporarily overseas and for non-response are also made to the population estimates following a post-enumeration survey, taking into account national differentials by age, sex and ethnic group, but without area differentials (SNZ, 2007).

5 In Australia, population estimates of the resident population by age, sex and indigenous status are similarly derived from the census and from a census post- enumeration survey for sub-national areas. The latter is used to include an adjustment of census non-response to the population estimates by area, sex, age, country of birth and indigenous status, before an additional allowance for change between census day and mid-year is included (ABS, 2006).

In the UK, mid-year population estimates with an ethnic group dimension have rarely been produced. This was attributable to the lack of data classified by ethnic group prior to the 1991 Census (Haskey, 1988). The availability of 1991 Census data by ethnic groups led a number of researchers to the question of devising methods of estimating the ethnic composition of sub-national areas in 1981 by calculating the ethnic breakdown of the population by country of birth to provide disaggregated estimates of population change by ethnic group over the decade 1981-1991 (Owen, 1996, Rees and Phillips, 1996, Peloe and Rees, 1999). Estimation of 1991 census undercount for each ethnic group in sub-national areas was estimated in various ways (Simpson S, 2002; Mitchell et al, 2002).

The release of 2001 Census data with an ethnic group dimension represents the second time for which data for local areas with an ethnic group dimension is available to analyse the changing composition of ethnic groups in the UK. The Office for National Statistics (ONS) has published estimates of the mid-2001 population for ethnic groups for each local authority area of England (Large and Ghosh, 2006), and have revised their estimates of overall 1991 Census undercount (ONS, 2002) making previous work on this with an ethnic origin dimension less useful.

The next section of this paper specifies four challenges in creating consistent population estimates for 1991 and 2001, and our methods to overcome them. The resulting dataset is not only consistent with ONS population estimates for 1991 and 2001 but contains much more age and geographical detail. We then quality assure the results through their internal consistency and the external plausibility of the adjustments that have been made.

6 Examples of the impact on census analysis are given, using the example of Birmingham the largest local authority area of England and Wales, followed by a discussion of the general applicability of the methods and of the results.

Method The four challenges for comparing 1991 and 2001 Census output Although the 1991 and 2001 Censuses in Great Britain have measured the principal variables to compare populations over time and space, four standard but difficult problems of data harmonisation over time remain. These four problems are general to any country when comparing population estimates over time. Their impact for England and Wales for the period 1991-2001 is highlighted in the text and in Table 1, and described below with an indication of the solutions adopted to overcome them.

(1) Population definition. Who is included in the definition of population affects the population estimate published, even where several different ‘population bases’ have been used in fieldwork (UN, 1998). In England and Wales, two differences between practice in the censuses of 1991 and 2001 are significant, the enumeration of students and population date. Whilst the 2001 Census enumerated the whole population at the address of ‘usual residence’ including students at their term-time address, the 1991 Census enumerated students at their vacation address. The transfer of students from their vacation address to their term-time address in 1991 has a significant impact on assessment of population change, by increasing the 1991 population in areas with student campuses (often but not always within urban areas), and decreasing other areas from which students leave to study elsewhere. Because population estimates are usually made for mid-year (30th June) rather than Census day (a different day of April in 1991 and 2001), an additional allowance for timing is necessary to bring them both to the same population date. Although the net effect of timing is small nationally, its impact locally can be significant.

7 Table 1 Enhancements to comparisons between successive censuses Enhancement, 1991 and 2001 censuses Global impact, England and Wales Examples of extreme impact 1. Population definition 53,975 net addition a. Students, transferred from 213,628 net gain for 103 districts 14,500 net gain to Oxford vacation address to term-time 159,653 net loss for 273 districts 2,600 net loss from Wirrall address (1991 only)

b. Population date, change from census day to mid-year 1991: April 21 to June 30 43,094 net addition 974 net gain to Lambeth, 442 net loss to Brent 2001: April 29 to June 30 41,006 net addition 1,081 net gain to East Riding of Yorkshire, 1,746 net loss to Birmingham

2. onresponse not estimated within census In 1991, 1.6% addition Pakistani addition of 6.7% in 1991, 2.1% in 2001. output In 2001, 0.5% addition Manchester addition of 4.0% in 1991, 7.4% in 2001.

3. Demographic classifications a. Age, distribute broad age groups No net impact on population Largest approximations in smallest areas where 5 to individual ages age groups published for each ethnic group in 1991, 7 in 2001.

b. Ethnic groups 10 in 1991; 6 extra Of those in both censuses, 3.2% changed 77% of those recorded as Black Caribbean in 1991 in 2001. categories were recorded as Black Caribbean in 2001, while a similar number moved from other groups to Black Caribbean.

4. Harmonisation of geographical units. 139 of 403 local authority boundaries and 4,398 of The 2001 boundary of the district of York was Smallest 1991 areas converted to 2001 9,527 electoral ward boundaries changed involving created from the 1991 district boundary and parts Census units more than 1% of their population of Harrogate, Ryedale and Selby in 1991.

(2) Treatment of nonresponse. Since it is widely accepted that no census will count the whole population, adjustments are usually made for undercount and in some countries for compensating overcount. In England and Wales in 1991 and 2001 the treatment of non-response in 1991 and 2001 was substantially different. In 1991 extra records for people in missed households were included in the census database and published output but a further 2% were estimated as missed from the census output (OPCS, 1993). In 2001 the One Number Census (ONC) integrated a more complete estimate of non-response in the published census counts for all areas, with further non-response limited to about 0.5% (Simpson, 2007). In both years, the non-response missed from census output was skewed towards young men, urban areas and minority ethnic groups. Plausible estimates based on evidence from post-enumeration surveys can been used to make allowances for this non-response.

(3) Demographic classifications. While not resulting any change to the total count of population, changes in recording and coding practices can render censuses incompatible, as happened in England and Wales with ethnic identification and age group categories. Whilst the 2001 Census recorded 16 ethnic group categories, including four mixed categories, the 1991 Census output included 10 ethnic group categories, with no mixed categories (Aspinall, 2008). Analyses of ethnic group stability over time using the ONS Longitudinal Study (LS) data showed that reliable comparisons over time can be made for five groups: White, Indian, Pakistani, Bangladeshi and Chinese and less reliable comparisons for the Black Caribbean and Black African groups (Bosveld et al, 2006; Simpson and Akinwale, 2007). The residual (‘Other’) ethnic groups of both 1991 and 2001 exhibit very low stability and, therefore, are not appropriate for comparisons. Classifications in which more groups are combined (such as ‘Black’) offer greater stability but less meaningful interpretation as they combine groups with very different demographic trajectories. Although date of birth is captured during census fieldwork, published output uses age bands which are not compatible between censuses. For example age 85 and over in 1991 and 90 and over in 2001 for electoral ward and further discrepancies for smaller areas.

(4) Harmonisation of geographical units. The geographical boundaries of most countries’ administrative units change over time, in ways that prevent calculation of

population change directly from output of successive censuses In England and Wales, small geographical units have been most affected by geographical boundary changes. To achieve harmonisation of these geographical areas 1991 population estimates for the smallest census areas are proportionally converted, using the 2001 Census boundaries for districts, Standard Table (ST) wards and Output Areas (OAs) as target geographies.

In this paper, we describe a framework to solve these problems when comparing ethnic group populations across time and space for districts and smaller areas (wards and OAs) in England and Wales.

Solutions to create a consistent time series When making population estimates consistent, there are choices regarding the target for consistency. Each estimate could refer to population on census day, to larger geographical areas which are common in both censuses, and to the broadest age groups which are consistent between censuses, to name three options which were not chosen but might have been appropriate had the aim been to create a small set of population estimates with greatest accuracy without regard to official population estimates.

Instead the population estimates created have been planned to be consistent with midyear official population estimates and to be disaggregated to fine classifications of age and geography to allow re-aggregation for a variety of general uses. These decisions have resulted in the following constraints:

a) The population estimates are consistent with (i.e they add up to) the population estimates published by ONS without an ethnic group dimension, in 1991 for local authority districts and in 2001 for districts and electoral wards (ONS, 2002). This implies for example that census output must be adjusted in both censuses to include the impact of moving from the April Census day to midyear, and that the 1991 Census must include an adjustment to transfer students from vacation to term-time address.

b) The population estimates are also consistent with the 2001 population estimates published by ONS with an ethnic group dimension for districts in England (Large and Ghosh, 2006). These assume for the same non-response rate for each ethnic group to distribute the extra 0.5% or 276,000 population estimated by ONS after the 2001 Census results were released, including in particular young men in urban local authorities. In order to examine a differential allocation of this extra non-response between ethnic groups, a second set of estimates for districts and wards have been derived too, which apply differential non-response rates based on those estimated within in the One Number Census.

c) 1991 population estimates are converted to the boundaries used in the 2001 Census output, including the smallest geographical unit, the OA. These include all electoral boundary reviews agreed by the end of 2003; although they are referred to here for example as ‘2001 areas’ they in fact use boundaries existing in 2003 that may have changed since 2001. The population figures for each OA are not as accurate as for larger areas and are not intended to be used directly for estimates of population change but as the building bricks for larger scale analyses.

d) Single year of age to 90 and over is estimated for both 1991 and 2001, to allow subsequent aggregation to suitable age bands. Again, the estimates of population for single years of age in small areas for each ethnic group are not considered accurate in themselves, but enable the construction of age bands relevant to particular services and policies.

e) Ethnic group categories for 1991 and 2001 are maintained in their respective full detail for each set of estimates. The matching of categories to compare 1991 and 2001 is made subsequently by users of the data. In this paper an eight-category classification is used as advised by ONS (Bosveld et al, 2006) and Simpson and Akinwale (2007).

Meeting these constraints involves a set of technical solutions which are detailed in Sabater (2008). The appendix Tables 1-4 summarise the methods, which involve two

basic principles: (a) incorporating relevant evidence, and (b) scaling incomplete evidence to more reliable information, usually for larger areas. Prime relevant evidence is the census output itself, which is not rejected but is the rock which is built upon to fill its imperfections. Tabulations from the census and its post-enumeration surveys also provide information about the ethnic composition of students, the transfer of students from vacation address to term-time address, migration rates to estimate population change between census day and mid-year and differential levels of non-response by age, sex and ethnic group. Extensive work during the 1990s census by the Estimating with Confidence research programme, which created an accepted set of small area population estimates for mid-1991 (Simpson et al, 1997; Simpson L, 2002) has also been incorporated, improving on its internal consistency, extending its age detail and using revised estimates for larger areas of the level of non-response in the 1991 census.

Much of the evidence indicates the nature of adjustments required to the census, often in terms of rates and distributions, and for broad population categories, rather than absolute figures to apply directly to the detailed local age-sex-ethnic group categories which are the target of the exercise. The technique of scaling initial estimates based on such incomplete evidence to other more reliable information known for larger population categories is frequently used, and is termed ‘fitting’. Where the more reliable information is known for more than one set of marginal sub-totals of a more complex cross-classification, the technique of Iterative Proportional Fitting is used.

To appreciate the complexity of combining data through use of fitting a variety of relevant evidence, the single example of ONS’ downward revisions to non-response in 1991 will suffice. We shared these between local areas by adjusting only the previous estimate of non-response within each age-sex-ethnic group. Had the population as a whole been adjusted directly then the geographical pattern of nonresponse would have been implausibly changed.

Quality assurance How can one give assurance about the quality of the results? Many of the assumptions made are plausible rather than certain, and subject to error. This error adds to the errors of recording, processing and imputation involved in the Census itself. The

potential for error in any one estimate will be greater for smaller populations, at least in percentage terms. This part of the paper argues that although there is no measured truth against which the accuracy of the results can be measured, internal checks and post-hoc validation can provide reassurance for users of the results.

First, we discuss the importance of plausible construction of the estimates to their validity, and the variety of checks which have been made to ensure that the results are internally consistent, and thus have a degree of internal validity. Second, we present results to allow users to judge whether the datasets and adjustments made to the census ‘make sense’ of what they expect. This provides a degree of face validity or external validity. These approaches to quality assurance are taken from notions of statistical responsibility (expressed well in Radical Statistics Education Group, 1982, which in turn draws on Cook and Campbell, 1979 and Bross, 1960).

Internal validity Each element of the methods explained earlier on was subject to constraints to ensure internal consistency. In addition to full consistency with ONS estimates as discussed earlier, there are no negative populations although adjustments to census output may be negative, for example the net adjustments for transferring students from vacation to term-time address in 1991, and the impact of population change between each Census day and mid-year. All procedures have been constrained so that there are no negative populations in the final data sets using methods adapted from the treatment of marginal totals with positive and negative entries (Bryan, 2004).

In addition, wherever possible individual adjustments are estimated separately and in small areas, retaining their own coherence and maintaining known patterns of age, locality, sex and ethnic group. The treatment of non-response in 1991 described above is one example. Another is the conversion from 1991 to 2001 Census geographical boundaries, which has used the lowest geographical source unit possible (the 1991 Census Enumeration District) so that spatial differences in age-sex-ethnic group patterns are respected when constructing the 1991 population for 2001 boundaries.

Internal validity is also shown by using assumptions that are equally or more plausible than other possible assumptions, and by showing that where other assumptions are

equally or more plausible (but perhaps impossible to implement) the outcome would not have a misleading effect on users of the data. As an illustration, we were concerned that the extra 0.5% or non-response estimated after 2001 census output was finalised was distributed to ethnic groups in proportion their existing populations within census output, in the ONS estimates which we have used as a constraint. However, most of this extra non-response was due to incomplete enumeration which might be expected to show the same patterns of non-response as for the much larger volume of non-response already estimated by ONS within the census output. In particular a disproportionate omission of minority ethnic groups has been noted by ONS (ONS, 2003) such that nationally Indian, Pakistani, Bangladeshi, Caribbean, African and Chinese were each omitted from census enumeration at a rate more than twice the average, and that this differential was repeated in most local authority areas. Table 2 shows the population of England and Wales according to the ONS estimates and an alternative set which assumes the extra non-response was distributed to ethnic groups in the same way as estimated by ONS (2003). It shows that the difference in population estimates is small and does not make a significant difference to the assessment of population change over time. Nonetheless the assessment of population change for sub-national areas and in particular for age groups most affected by the extra non-response (men aged 20-39) may be significantly affected by this assumption.

External validity There is no external truth by which to judge the time series, but its analysis may provide some ‘face validity’ of the results if it agrees with expectations. In this section we provide three analyses of the results, one highlighting the impact on population growth with and without enhancing 1991 and 2001 census totals for four minority ethnic populations in Britain, one focusing on national totals for each ethnic group and with detail of age and sex structure, and the other illustrating the impact of adjustments to ethnic groups locally. For the latter, population estimates for each ethnic group in Birmingham are shown.

Table 2: Impact of alternative 2001 population estimates, England and Wales, total population and men aged 2039 Population in 2001 % change in population 1991-2001 (a) Total population ONS estimate Alternative estimate ONS estimate Alternative estimate Total 52,359,979 52,359,979 3.18% 3.18% White 47,747,355 47,716,647 0.67% 0.61% Black Caribbean 572,212 576,850 0.45% 1.27% Black African 494,669 502,667 93.73% 96.87% Indian 1,053,302 1,059,351 18.11% 18.78% Pakistani 727,727 734,585 47.02% 48.41% Bangladeshi 286,693 289,488 62.05% 63.63% Chinese 233,346 236,090 34.74% 36.32% Other 1,244,677 1,244,301 64.39% 64.34% Population in 2001 % change in population 1991-2001 (b) Men aged 20-39 ONS estimate Alternative estimate ONS estimate Alternative estimate Total 7,386,875 7,386,875 -2.23% -2.23% White 6,565,396 6,547,140 -4.59% -4.86% Black Caribbean 92,583 95,300 -26.09% -23.92% Black African 101,225 106,775 41.11% 48.85% Indian 189,420 193,071 12.24% 14.40% Pakistani 130,173 134,045 54.02% 58.60% Bangladeshi 51,683 53,288 99.50% 105.70% Chinese 47,453 48,996 6.99% 10.47% Other 208,942 208,260 36.05% 35.60% The alternative estimate assumes different rates of non-response for each ethnic group (see text).

Figure 1 uses data reproduced from Peach (1996) and 2001 Census data as published to represent population growth between 1951 and 2001 for four separate ethnic minority populations. Additionally, the figure highlights the differences using corrected data for 1991 and 2001, with a significant decrease particularly among the Black Caribbean, slowing down rather than accelerating mainly as a result of the adjustment due to non-response not included in the 1991 Census. This adjustment also contributes to the more expected figure of growth of the Indian group in 1991. Figure 1: Growth of minority ethnic populations in Britain, 19512001

1200

1000

800

600

400 ` Population in Thousands

200

0 1951 1961 1971 1981 1991 2001

Black Caribbean Black Caribbean - corrected Indian Indian - corrected Pakistani Pakistani - corrected Bangladeshi Bangladeshi - corrected

Source: Adapted from Lupton and Power (2004) using 1951-1991 data reproduced from Peach (1996: 9). 2001 data (without correction) from 2001 Census Key Statistics Table 6.

The following figures illustrate how the 2001 population estimates were derived from Census output, after aggregating the results for all districts to country totals. Figures 2 and 3 show the adjustments due to migration between England and the rest of the United Kingdom (UK) and international migration respectively during the 9 weeks between census day in April and mid-year, which is the element of change that has greatest impact on the population. These reveal the importance of emigration from England of the Irish group to other areas of the UK, most likely to Northern Ireland, as well to outside the UK (‘international migration’), probably mainly to the Republic of Ireland. These together deduct between 1 and 5% of the Irish population aged in their mid-twenties, and will include the return of graduates after study in England.

Figure 2: 2001 percentage adjustment due to migration between England and the rest of the UK from Census day to midyear by age, sex and ethnic group

0.2

0.1

0.0

-0.1

Percentage -0.1

` -0.2

-0.2

-0.3 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese 0.2

0.1

0.0

-0.1

-0.2 Percentage

-0.3 `

-0.4

-0.5 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese

The rises of population during this nine weeks period are principally due to net international immigration of Chinese men and women, Bangladeshi women and Black African men, also focused on young adult ages. The results in Figures 2 and 3 illustrate the assumptions used by ONS for estimates of mid-2001 population for districts of England, which we have replicated.

Figure 3: 2001 percentage adjustment due to international migration between Census day and midyear by age, sex and ethnic group in England

6.0

4.0

2.0

0.0

-2.0

Percentage -4.0

` -6.0

-8.0

-10.0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese 6.0

4.0

2.0

0.0

-2.0 Percentage

-4.0 `

-6.0

-8.0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese

Figure 4 shows the adjustment of extra non-response identified by ONS after release of census results. The differences between ethnic groups are due to the concentration of each group in particular types of districts with different levels of extra nonresponse (the White British population is found more often in districts of lower nonresponse). As expected, this extra non-response is mainly concentrated among young male adults. The largest adjustment is for extra non-response among the Black

African group, with an increase over the published census population of more than 10% for those in their twenties and early thirties, solely due to their location mainly in London districts with high allocation of extra non-response. Figure 4: 2001 percentage adjustment due to extra nonresponse as published by OS experimental statistics by age, sex and ethnic group in England

12.0

10.0

8.0

6.0

4.0

Percentage 2.0

0.0

-2.0

-4.0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Percentage -0.5 -1.0 -1.5 -2.0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age - Males

White British White Irish Black Caribbean Black African Indian Pakistani Bangladeshi Chinese

Figure 5 displays the percentage adjustment to the 1991 Census due to the student transfer from vacation to term-time address. Aggregated over all districts in England and Wales, this net impact of students otherwise resident outside England and Wales

presumably comprises mainly overseas students. The Chinese group experiences the largest addition of students with home address outside England and Wales, with an addition to the initial census population aged 20-24 of about 40% for both males and females. Figure 5: 1991 percentage adjustment due to net student transfer by age, sex and ethnic group in England and Wales

50.0 45.0 40.0 35.0 30.0 25.0 20.0

Percentage 15.0 10.0 5.0 0.0 -5.0 0-4 5-9 10- 15- 20- 25- 30- 35- 40- 45- 50- 55- 60- 65- 70- 75- 80- 85+ 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 Age - Males

White Black Caribbean Black African Indian Pakistani Bangladeshi Chinese 40.0

35.0

30.0

25.0

20.0

15.0

Percentage 10.0

5.0

0.0

-5.0 0-4 5-9 10- 15- 20- 25- 30- 35- 40- 45- 50- 55- 60- 65- 70- 75- 80- 85+ 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 Age - Males

White Black Caribbean Black African Indian Pakistani Bangladeshi Chinese

In order to interpret sub-national population change between 1991 and 2001, Figure 6 shows the impact of adjusting each census for a consistent treatment of students, non-

response and population definition. The map showing census output is adjusted only so that 1991 figures refer to 2001 district boundaries. For this purpose we use a Universal Data Map (UDM) as this allows a more clear representation of those areas with large populations such as cities than conventional maps, which tend to highlight patterns in sparsely populated areas where few people live (Dorling and Durham, 2006).

Both the census and the full population estimates displayed in Figure 6 depict a widespread population growth of the non-White groups in districts in England and Wales. Many districts experience a growth in the total non-White populations of over 60%. The only areas showing a decrease are three districts where the USA armed forces have withdraw in significant numbers during the 1990s (Suffolk Coastal, Cherwell, and Forest Heath). The spreading out of cultural diversity is clear from the greater growth experienced outside the urban centres of London, the West Midlands and Yorkshire. Both maps show these two trends of minority population growth and spreading diversity, but a comparison of the two maps shows that the census output would be misleading on both trends. First, there are many more areas of slower population change indicated on the map of full population estimates because the better capture of non-response in the 2001 census wrongly appears to be population growth. The unadjusted census over-estimates increases in the non-White population. Second, the over-estimation of non-White population growth is mainly in the urban areas where census undercount is greatest. Thus the spreading of diversity is under-stated by the census. The full population estimates show more clearly that minority population growth is faster outside the urban areas.

Generally, when full estimates are used, the tendency is to slow population growth, with a shift towards less population increase, in particular because the 1991 Census is boosted by students living in the UK only during term time, and by a full allowance for non-response. The use of full estimates makes some districts not only reduce their population growth but suggest a population decrease rather than an increase. One such district is Birmingham, used in Tables 3 to 5 illustrate the local impact on population comparisons between 1991 and 2001 for each ethnic group. For this purpose ethnic groups are aggregated to eight categories as advised by ONS (Bosveld et al, 2006)

and Simpson and Akinwale (2007).1 Birmingham is an ethnically diverse district, whose boundary changed during the decade, with significant non-response in the census, and which gains several thousand students overall in the transfer between vacation and term-time address in 1991. Figure 6: Percentage population change between 1991 and 2001 for nonWhite groups for 2001 districts in England and Wales

Census output Full estimates

171 24 95 95 76 76 76 76 131 69 63 63 59 59 59 59

89 111 111 105 95 95 95 76 73 73 105 101 101 78 63 63 63 59 53 53

49 49 90 90 72 72 95 89 89 89 73 73 18 18 69 69 63 63 63 70 70 70 53 53

83 83 57 77 89 89 65 65 65 65 58 58 67 44 70 70 40 40 40 40

89 89 159 47 77 43 140 140 65 65 65 65 141 54 44 45 60 60 40 40

51 51 47 47 37 37 17 17 67 67 73 73 37 37 54 54 36 36 13 13 56 56 64 64

110 87 87 87101101 96 94 94 94 96 96 96127 73 73 97 37 37 37 90 90 79 55 55 55 82 82 82 75 64 64

92 92 92 110 98 98 46 67 53 53 47 47 47 47 144 144 144 171 54 54 37 37 63 63 63 97 78 78 29 51 48 48 18 18 18 18 71 71 71 118 48 48 22 22

82 82 108 108 124 124 46 46 46 46 47 47 47 47 47 47 47 47 61 61 54 37 70 70 92 92 98 98 29 29 43 43 39 39 18 18 18 18 18 18 41 41 48 22

68 52 76 76 66 66 35 35 44 44 44 53 48 48 43 43 47 47 47 47 47 47 112 112 143 143 76 76 42 31 54 54 54 54 24 24 41 41 41 44 41 41 30 30 18 18 18 18 18 18 91 91 116 116 37 37

68 68 52 52 76 76 66 66 35 35 69 69 48 48 43 43 43 43 43 43 41 59 59 59 44 44 143 143 76 76 42 42 31 31 54 54 54 54 24 24 55 55 41 41 30 30 30 30 30 30 31 43 43 43 28 28 116 116 37 37

68 68 46 46 66 66 35 35 69 69 47 47 61 61 53 53 43 43 41 41 59 59 59 59 44 44 143 143 76 76 42 42 13 13 54 54 24 24 55 55 26 26 53 53 45 45 30 30 31 31 43 43 43 43 28 28 116 116 37 37

68 68 46 46 66 71 71 71 47 47 31 31 61 61 53 53 41 41 41 41 78 78 61 61 44 44 143 54 42 42 13 13 54 27 27 27 26 26 20 20 53 53 45 45 31 31 31 31 39 39 40 40 28 28 116 40

46 46 46 46 71 71 47 47 81 81 31 31 31 31 41 41 78 78 78 78 78 78 61 61 61 61 54 54 48 48 13 13 13 13 27 27 26 26 61 61 20 20 20 20 31 31 39 39 39 39 39 39 40 40 40 40 40 40 38 38

57 57 57 57 46 46 51 51 51 51 47 47 81 81 108 108 51 51 78 78 78 78 51 51 51 51 51 51 43 43 43 43 48 48 36 36 36 36 13 13 36 36 36 36 26 26 61 61 79 79 38 38 39 39 39 39 42 42 42 42 42 42 18 18 18 18 38 38

57 57 57 57 49 49 71 71 71 71 47 47 81 81 101 101 71 71 33 33 64 91 91 67 67 67 54 54 43 43 128 128 36 36 36 36 35 35 54 54 54 54 26 26 61 61 81 81 61 61 25 25 56 71 71 57 57 57 46 46 18 18 103 103

99 99 80 80 80 80 68 68 68 68137137 58 58 42 42 98 98 64 64 65 65 44 44 94 94 32 32 59 59 82 82 74 62 62 91 85 85 79 79 72 72 72 72 58 58 58 58 136 136 55 55 27 27 69 69 56 56 57 57 28 28 68 68 21 21 43 43 72 72 63 53 53 40 71 71

71 71 87 87 78 78 56 56 56 97 97 97 57 57 76 76 92 92 32 32 32 32 84 84 44 44 32 32 32 32 81 81 82 74134134 91 91 72 72 52 52 67 67 65 65 33 33 33 98 98 98 42 42 60 60 73 73 24 24 24 24 61 61 28 28 21 21 21 21 54 54 72 63 125 125 40 40 60 60

71 71 124 169 88 88 70 70 17 17 38 38 38 38 40 40 88 88 82 142 142 100 43 141 87 87 159 159 127 127 71 71 116 116 3.9 64 64 101 101 46 102 102 52 52 105 122 58 58 34 34 7.8 7.8 30 30 30 30 26 26 70 70 68 121 121 78 40 81 76 76 124 124 89 89 62 62 32 32 -37 49 49 85 85 29 74 74

84 84 74 74 64 64 17 17 17 17 38 38 40 40 40 40 63 63 37 37 36 112 112 42 30 30 30 42 42 42 139 139 139 178 178 113 82 82 46 46 -16 -16 59 59 53 53 40 40 7.8 7.8 7.8 7.8 30 30 26 26 26 26 65 65 27 27 28 92 92 30 9 9 9 32 32 32 112 112 112 158 158 96 68 68 29 29 -56 -56

26 26 54 54 74 74 64 64 41 41 35 35 35 35 40 40 40 40 86 86 52 52 57 57 52 52 26 26 26 42 42 42 27 27 48 48 118 63 63 63 79 79 79 124 124 124 26 26 30 30 53 53 40 40 29 29 27 27 27 27 26 26 26 26 61 61 33 33 51 51 46 46 12 12 12 30 30 30 22 22 40 40 96 50 50 50 50 50 50 110 110 110

54 54 72 72 64 64 41 41 35 35 40 40 40 40 38 38 28 28 52 52 89 89 52 52 97 97 38 38 38 27 126 126 134 134 52 52 73 73 73 89 30 30 63 63 40 40 29 29 27 27 26 26 26 26 23 23 20 20 33 33 77 77 46 46 80 80 30 30 30 22 80 80 104 104 41 41 56 56 56 68

37 37 37 37 102 49 94 94 41 41 41 35 40 40 40 40 38 38 23 23 149 39 89 89 74 74 74 51 51 51 72 72 72 72 72 72 131 131 102 102 120 52 52 52 70 51 8.9 8.9 8.9 8.9 75 29 81 81 29 29 29 27 26 26 26 26 23 23 14 14 128 29 77 77 60 60 64 42 42 42 62 62 62 62 62 62 117 117 93 93 107 40 40 40 50 52

40 40 53 53 53 53 86 86 143 143 40 40 40 40 85 85 85 85 38 38 36 36 20 20 72 72 74 74 51 51 27 27 27 27 43 43 43 43 78 78 120 120 56 56 70 70 51 51 2.7 2.7 36 36 36 36 60 60 117 117 26 26 26 26 67 67 67 67 23 23 21 21 -27 -27 52 52 60 64 42 42 17 17 17 17 35 35 35 35 62 62 107 107 52 52 50 50 52 52

52 52 76 76 76 76 50 50 50 50 86 86 168 168 81 81 105 105 148 148 42 42 102 102 72 72 72 72 59 59 51 51 76 76 76 76 41 41 35 35 43 43 82 82 82 82 47 47 42 42 62 62 62 62 37 37 37 37 60 60 127 127 59 59 105 105 131 131 30 30 96 96 56 56 52 52 54 54 42 42 48 48 48 48 22 22 27 27 35 35 72 72 72 72 40 40

52 76 29 29 53 53 84 84 45 45 159 159 135 135 42 42 113113 95 95 70 70 81 75 75 75 95 95 59 59 36 36 36 36 41 41 35 35 65 65 65 65 125 125 125 125 47 47 42 62 6.7 6.7 36 36 63 63 22 22 138 138 121 121 19 19 95 95 51 51 23 23 56 19 19 19 82 82 54 54 32 32 32 32 22 22 27 27 57 57 57 57 106 106 106 106 40 40

38 38 41 41 26 26 27 27 45 45 136 136 136 61 61 61 61 61 79 79 63 63 81 81 105 105 49 49 78 78 37 37 36 36 56 31 31 144 67 67 67 65 89 89 89 49 47 47 7.4 7.4 22 22 17 17 21 21 22 22 106 106 106 33 33 33 33 33 55 55 48 48 56 56 83 83 38 38 65 65 32 32 32 32 34 23 23 98 56 56 56 57 70 70 70 41 40 40

38 38 38 38 41 41 26 26 50 50 50 50 61 61 61 61 90 90 63 63 73 73 73 53 53 53 102 102 78 78 37 42 56 56 36 36 69 69 69 69 89 89 49 49 49 49 7.4 7.4 7.4 7.4 22 22 17 17 25 25 25 25 33 33 33 33 43 43 48 48 53 53 53 28 28 28 96 96 65 65 32 25 34 34 22 22 56 56 56 56 70 70 41 41 41 41

42 42 42 42 41 41 50 50 50 50 89 89 89 89 90 90 86 86 95 95 94 94 54 54 128 128 78 78 37 37 42 42 13 13 36 36 36 69 80 80 80 80 29 29 103 103 136 108 26 26 26 26 22 22 25 25 25 25 72 72 72 72 43 43 48 48 51 51 73 73 48 48 73 73 65 65 32 32 25 25 1.2 1.2 22 22 22 56 63 63 63 63 23 23 96 96 65 75

52 52 52 52 66 66 73 125 125 172 172 172 52 52 68 68 69 69107107 83 83 76 76 50 50 74 99 13 13 13 13 66 66 66 66 80 80 45 45 64 103 136 136 108 108 42 42 42 42 43 43 60 120 120 123 123 123 40 40 50 50 51 51 85 85 69 69 70 70 43 43 55 76 1.2 1.2 1.2 1.2 49 49 49 49 63 63 38 38 50 96 65 65 75 75

97 97 151 151 126 126 255 84 100 100 133 133 59 59 59 59 133 133 50 50 74 74 99 99 71 71 71 71 66 66 79 79 34 34 64 64 148 148 72 72 68 68 95 95 117 117 182 91 84 84 108 108 45 45 45 45 75 75 43 43 55 55 76 76 60 60 60 60 49 49 70 70 23 23 50 50 126 126 59 59

96 198 82 121 121 121 169 169 130 104 84 96 87 87 91 91 11 76 76 76 66 66 79 79 54 54 95 95 95 95 79 79 79 79 63 34 34 34 84 84 111 134 66 98 98 98 142 142 127 82 91 84 72 72 53 53 33 68 68 68 57 57 73 73 45 45 82 82 82 82 70 70 70 70 60 23 23 23 74 74

112 112 80 80 104 104 70 130 104 104 71 71 87 87 75 75 121 121 89 89 106 106 118 118 99 99 70 70 114 114 70 70 63 63 81 81 82 82 48 48 38 38 63 127 82 82 43 43 72 72 58 58 49 49 76 76 76 76 97 97 89 89 66 66 85 85 61 61 60 60 59 59

127 134 134 102 85 85 130 80 132 132 132 132 71 71 48 48 111 111 121 121 72 72 72 150 150 150 64 64 95 95 113 113 100 100 100 100 106 135 135 84 40 40 92 48 70 70 70 70 43 43 43 43 95 95 49 49 61 61 61 133 133 133 54 54 84 84 107 107 66 66 88 88

67 127 67 67 85 85 85 130 49 49 89 89 89 121 101 101 101 101 101 101 91 91 39 106 22 22 40 40 40 92 51 51 66 66 66 92 45 45 45 45 45 45 71 71 350 66 88 88 509 57 82 82

Population Change: Change, <30% Increase, 30-60% Increase, >60%

Table 3 shows the adjustments to the 1991 Census output by ethnic group. Overall, the impact of adjustments adds forty four thousand residents to the 1991 Census as published, pushing the total population over 1 million. A significant enlargement to the area of Birmingham added almost nine thousand residents from neighbourhoods that were almost entirely White. The largest contributor to the adjustments is nonresponse, particularly among ethnic groups other than White, which adds twenty-eight thousand residents missed by the census in 1991. This represents 65% of the total

1 The tables use the following allocation of 1991 and 2001 categories. White: 1991 White, 2001 White British, White Irish and White Other. Caribbean, African, Indian, Pakistani, Bangladeshi, Chinese: in both 1991 and 2001 the single categories with these labels. Other: in both 1991 and 2001 the remaining categories which are residuals or Mixed. 22

addition to the 1991 Census as published, and is presented in the table together with the much smaller timing adjustment.2

The impact of transferring students from vacation to term-time address represents a gain too for all ethnic groups in Birmingham, adding in total six thousand residents. The differences between ethnic groups partly reflect their different age structures, and partly the procedure used to add students which recognises that students moving to Birmingham will not reflect the local ethnic composition. Table 3: Adjustments to the 1991 Census output by ethnic group, Birmingham district Census 1991 as published Full population estimate with 2001 boundaries Total 960,686 1,004,502 White 753,937 772,094 Black Caribbean 44,769 53,717 Black African 2,797 3,627 Indian 51,057 55,512 Pakistani 66,081 71,055 Bangladeshi 12,733 13,693 Chinese 3,318 3,961 Other 25,994 30,843

Table 4: Adjustments to the 2001 Census output by ethnic group, Birmingham district Census 2001 Full population estimate Alternative as published with 2001 boundaries estimate Total 977,105 984,642 984,642 White 687,406 691,952 689,703 Black Caribbean 47,832 48,075 48,442 Black African 6,205 6,430 6,542 Indian 55,749 56,245 56,517 Pakistani 104,018 105,137 106,188 Bangladeshi 20,836 21,062 21,257 Chinese 5,110 5,230 5,273 Other 49,949 50,511 50,720 The alternative estimate assumes different rates of non-response for each ethnic group (see text).

Table 4 shows the same information but for adjustments to the 2001 Census output. Here there is no impact of boundary change or student transfers as these are already included in the Census output. Overall, the impact of adjustments adds only seven thousand residents to the 2001 Census as published. This is mainly the result of extra non-response not included in the census output, which adds nine thousand residents to

2 Non-response and the adjustment from census day to mid-year were not distinguished in the method as applied to ethnic groups in 1991. For the total population timing accounted for 384 residents and non-response for 28,212 in Birmingham. 23

the initial census output, and adds slightly greater proportions to the minority ethnic groups than to the White population.

Table 5 illustrates the impact of the work on population comparisons in Birmingham between 1991 and 2001. The changes when using a full population estimate are significant, giving a different – and we would argue more accurate – assessment of population change. In particular, the census output for Birmingham as a whole suggests a gain in population of 1.7%, but after taking into account the adjustments, this is seen to be a slight loss of 2.0%. The reduction in growth noted above is apparent for all minority groups. An apparent Black Caribbean increase of 7% is seen with full population estimates to be a loss of 10%, while a Black African increase of 122% is reduced to 80%. A White loss of 9% becomes a loss of 11% when using the full population estimates. A study of Tables 3 and 4 shows that the minority ethnic groups’ growth is over-estimated by the published census largely because of the greater non-response in the 1991 Census, while the under-estimated loss of the White population is due largely to the enlargement in district boundary. Table 5: Population change by ethnic group, Birmingham district Censuses 1991 and Full population Full population with 2001 as published estimates with 2001 alternative estimate boundaries and 2001 boundaries Total 1.7% -2.0% -2.0% White -8.8% -10.4% -10.7% Black Caribbean 6.8% -10.5% -9.8% Black African 121.8% 77.3% 80.4% Indian 9.2% 1.3% 1.8% Pakistani 57.4% 48.0% 49.4% Bangladeshi 63.6% 53.8% 55.2% Chinese 54.0% 32.1% 33.1% Other 92.2% 63.8% 64.4% The alternative estimate assumes different rates of non-response for each ethnic group (see text).

The estimates as building bricks The dataset provided as full population estimates contains far too more detail than can be reasonably expected to be validated in every respect. The detail of single years of age, and of very fine geographical detail is provided instead to allow aggregation to larger populations. Larger populations, because they incorporate more of the evidence directly available for broader age groups and larger areas, are more likely to be accurately estimated. The aggregation to appropriate age groups is straightforward. This short section addresses a means of aggregating the estimates to areas with ad hoc

geographical boundaries that may be of interest to particular policy programmes and urban studies but are not those used in the 2001 census output. In this way, the time series of population estimates for ethnic groups is available for any area and any requirement of age groups.

A common example of non-census geographical units required for many purposes is provided by boundary reviews agreed after 2003, the year reflected in 2001 Census output and these estimates. However, updating such estimates for current boundaries can be a straightforward procedure using an appropriate Geographical Conversion Table (GCT). Simpson (2002b) and Norman et al (2003) have devised methods to convert between different geographical systems which can be used in the face of boundary changes over time, and shown that the accuracy is good so long as the source units (in this case the 2001 census OAs of around 200 households) are small compared to the target geographical units. The following example is taken from Birmingham, a district whose ward boundaries changed in 2004. A GCT defined and constructed by Norman (2007), containing weights from postcodes points and a count of addresses at each valid postcode was used to transfer data from the source area (OAs) to the target areas (2004 wards).

Table 6 gives an example of this transfer for the full mid-1991 estimates. The table shows that the 2001 OA 00CNGM0106, which was fully included in Sutton New Hall ward, is re-allocated in two different 2004 wards, Sutton New Hall and Sutton Trinity. The table has an extract from the OA 2001 to ward 2004 GCT. The count of the address-weighted postcodes in the source-target overlaps indicate that 0.025 of data for 00CNGM0106 be allocated to 00CNJE and 0.975 of 00CNGM0106 be allocated to 00CNJF. Since the OA overlap is mostly with Sutton Trinity, the intersection estimate is almost entirely allocated in this ward (4 * 0.975).

Table 6: GCT extract: 2001 OAs to 2004 electoral wards, Birmingham district

a.) Source/target links and conversion weights

Source geography Ward 2001 Ward 2001 Target geography Name Source / Target Source unit Conversion OA01 code name Ward 2004 Ward 2004 intersection address total addresses weight 00CGM0106 00CGM Sutton ew Hall 00CJE Sutton ew Hall 3 120 0.025 00CGM0106 00CGM Sutton ew Hall 00CJF Sutton Trinity 117 120 0.975 00CNGM0107 00CNGM Sutton New Hall 00CNJF Sutton Trinity 124 124 1 00CNGM0108 00CNGM Sutton New Hall 00CNJF Sutton Trinity 130 130 1 00CNGM0109 00CNGM Sutton New Hall 00CNJF Sutton Trinity 116 116 1 etc. etc. etc. etc. etc. etc. etc. etc. b.) Converting OA data to 2004 ward geography

Source Mid-1991 estimate Conversion weight Intersection estimate for OA01 White males aged 20 to 00CNJE and 00CNJF White males aged 20 in 00CNJE and 00CNJF 00CNGM0106 4 0.025 0.096 00CNGM0106 4 0.975 3.744

Discussion We have presented methodological issues and solutions to enable robust comparisons of population composition between the 1991 and 2001 censuses. Here we discuss the nature of the advances represented by this paper and its outputs, the potential that its outputs imply for other studies, and implications for future censuses and demographic studies.

This paper has shown that census data as published are not suited to analyse population change of ethnic groups in districts and smaller areas in England and Wales. The introduction of adjustments which take into account changes in the population definition, changes in the treatment of non-response, changes in ethnic identification and age group categories and boundary harmonisation, can significantly change the interpretation of population change of ethnic groups over time and space. In the work reported here, we have demonstrated that full population estimates can be used to improve analysis of population change over time and space.

The production of a quality-assured time series is challenging, especially when an ethnic group dimension is included. The work presented demonstrates that it is possible to address these issues and incorporate detailed age and ethnic group information into a set of consistent population estimates for very small areas. This detail allows aggregation to areas and age bands appropriate for any applied study. The population estimates together with data quantifying the adjustments made to the censuses have been deposited for general research use.

This paper provides ‘face validity’ for its mid-1991 and mid-2001 population estimates, giving evidence of how population change can be misleading without taking into account the adjustments for timing, non-response and students transferred at their term-time address. The results support the case that analysis of population change between 1991 and 2001 is clearly improved by including adjustments to census output and creating a consistent population time series. The demonstration that the data set makes a difference to sub-national comparison of population change of ethnic groups over time represents a wakeup call to those who have used raw census publications uncritically, and a positive one because a solution is provided by these new data sets.

General trends are altered, including the more rapid spread of population diversity. But specific conclusions are changed too; Birmingham’s apparent population growth in the 1990s and Blackburn’s increasing segregation in that decade are both false results based solely on census output. However, the census is by no means rejected. Its local detail is an irreplaceable ingredient of good social science. The message is rather one of caution, and of advice to construct improved analyses wherever that is possible.

Population studies and a broad range of social, employment and health studies gain from the improved data resource provided by consistent mid-year population estimates. Population studies of fertility, migration and mortality are enabled at a subnational scale by estimates of age-structure and its change over time, of which Finney and Simpson (2008) is one example. Apart from these analyses, consistent estimates serve as the base for population projections and forecasts.

Many social science applications require population denominators in epidemiology, employment, crime and other substantive studies. Any study of service demand or of discrimination relies on an appropriate population for each group compared. Many analyses of change over time are simply not possible without a consistent and detailed set of population estimates using the same age and area classifications for more than on time period. Research measuring residential segregation and diversity at different points in time is sensitive to the changing boundaries of residential areas, as shown by Simpson (2007).

The UK 2001 Census was the first worldwide to attempt to measure non-response so completely that a full allowance could be incorporated in the census outputs themselves (ONS, 2003; Brown et al, 1999). It was largely successful and the estimates presented in this paper for 2001 gain significantly from those efforts which are being extended the next UK Census in 2011. Without the inclusion in the census of an allowance for non-response, published output would be biased in particular against men, young adults, and minority ethnic groups. This paper has shown that estimates of population change suffer when bias in the census enumeration is not fully corrected.

However, even if a consistent approach to non-response is included in census and equivalent outputs in the future, it may be too much to expect area boundaries and ethnic group classifications to remain static over time. Methods of harmonisation will remain a priority, highlighting the importance of longitudinal resources which allow the impact of boundary and classification changes to be quantified and at least approximately overcome. The availability of updated boundary and address files for statistical purposes, and of the linked census records over time will be essential to future harmonisation of population estimates just as they were to the current work.

The methods used in this paper focused on estimation of the greatest detail possible, for the smallest census areas of around one hundred households, for single years of age, and for the fullest ethnic group classification available in each census year. While the estimates of population are less reliable for smaller populations, and certainly not reliable for each cell of a cross-classification of age, sex, area and ethnic group, the advantage of this detailed approach to detail is evident when considering comparison to results from the next census. Its output cannot be predicted in advance, so the flexibility given by detailed estimates is the only means of coping with this uncertainty. A similar approach has begun to be taken by the ONS itself, whose small area population estimates since 2001 have extended to sub-district levels and are now held as a database of estimates attached to each unit postcode and single year of age, ready for aggregation to the unpredictable boundaries set by government neighbourhood social programmes (ONS, 2007). At present these do not extend to an ethnic group dimension between census years, although government reports have suggested that there is demand for such detail (Social Exclusion Unit’s PAT18; Community Cohesion Panel, 2004).

The production of very detailed population estimates does however beg the question of their accuracy for differently sized populations. There is a need to develop statistical approaches which add a measure of reliability to each estimate. Only then will the relationship between population size, characteristics and accuracy of population estimates be available to guide users of population statistics towards robust results.

Acknowledgements

• The original Estimating with Confidence (EwC) data are copyright of the EwC project which was funded by the ESRC, award number H519255028.

• The research uses 1991 and 2001 Censuses, the National Statistics Postcode Directory (NSPD) and GIS boundary data obtained via MIMAS CASWEB and EDINA UKBORDERS which are academic services supported by ESRC and JISC.

• The Census, official Mid-Year Estimates, NSPD and vital statistics data for England and Wales have been provided by the Office for National Statistics and the digital boundary data by Ordnance Survey. These data are copyright of the Crown and are reproduced with permission of the Controller of HMSO.

Appendix: Technical summary Precise details of datasets and methods adopted to create mid-1991 and mid-2001 population estimates are contained in Sabater (2008). This appendix contains the essential details to establish the strategies and prior research on which the estimates are based.

Table A1: 1991 population for 2001 OAs by age and sex without an ethnic group dimension. The research makes use of the EwC population estimates for mid-1991 and its adjustments to the census, provided for census EDs (Enumeration Districts) and fiveyear age groups (Simpson et al, 1997). These are transferred to the 2001 census geography of OAs, ONS’ revised estimate of non-response is included and single years of age added.

Table A2: 1991 population for 2001 OAs by age and sex: adding the ethnic group dimension. Non-response in the census is assumed to be greater for minority ethnic groups, in line with the evidence contained in the 1991 SOCPOP dataset (Simpson, 2002a). The ethnic composition of students living away from home, and the single year of age structure within five-year age groups is based on relevant evidence.

Table A3: 2001 population for 2001 districts by age and sex with an ethnic group dimension. The ONS estimates are used for districts in England (Large and Ghosh, 2006), which separately allocate to ethnic groups change between census day and mid-year, and the 257 thousand extra non-response not included in census outputs. For Wales, timing and non-response were allocated together. For all districts, the ethnic group composition of non-response is the same as the population ethnic group composition, for each age and sex group within each LAD. A separate set of estimates using disproportionate non-response among minority ethnic groups as evidenced by imputation within the Census has also been prepared (Sabater, 2008).

Table A4. 2001 population for 2001 electoral wards and OAs by age and sex with an ethnic group dimension. Census tables and ONS population estimates with aggregated information on one dimension (age groups rather than single year of age, the total rather than separate ethnic groups) are combined using Iterative Proportional Fitting. The change of date to mid-year, and extra non-response, are in effect allocated proportionately to smaller sub-populations, from the district ethnic group estimates (Table 3) and ward estimates without and ethnic group dimension published by ONS (2007).

References ABS (2006) Indigenous Estimated Resident Population – Method of Calculation. Canberra: Australian Bureau of Statistics publication.

Aspinall, P. (forthcoming - 2008) ‘The future of ethnicity classifications’, Journal of Ethnic and Migration Studies.

Bélanger, A. and Caron Malenfant, É. (2005) Population projections of visible ethnic groups, Canada, provinces and regions, 20012017. Ottowa: Statistics Canada publication.

Bosveld, K., Connolly, H. and Raha, C. (2006) ‘Measurement and classification’, in Dobbs, J., Green, H. and Zealey, L. (eds) Focus on Ethnicity and Religion. London: HMSO, 1-18.

Bross, I. (1960) ‘Statistical criticism’, Cancer, 13: 394-400.

Brown, J., Diamond, I., Chambers, R., Buckner, L. and Teague, A. (1999) ‘A methodological strategy for a one number census in the UK’, Journal of the Royal Statistical Society Series A, 162(2): 247-267.

Bryan, T. (2004) ‘Population Estimates’, in Siegel, J. and Swanson, D. (eds) The methods and materials of demography. San Diego: Elsevier Academic Press, 523-560.

Community Cohesion Panel (2004) The End of Parallel Lives? The Report of the Community Cohesion Panel, London: Home Office, online at http://www.communities.gov.uk/documents/communities/pdf/153866, accessed 14 January 2008.

Cook, T. D. and Campbell, D. T. (1979) Experimental and quasiexperimental designs for research, Chicago: Rand McNally.

Dorling, D. and Durham, H. (2006) Universal Data Map cartogram of the UK. Sheffield: Social and Spatial Inequalities Research Group, University of Sheffield.

Dorling, D. and Rees, P. (2003) ‘A nation still dividing: the British census and social polarisation 1971 – 2001’, Environment and Planning A, 35(7): 1287-1313.

Haskey, J. (1988) ‘The ethnic minority populations of Great Britain: their size and characteristics’, Population Trends, 54: 29-31.

Large, P. and Ghosh, K. (2006) Population Estimates by Ethnic Group. Methodology Paper. London: Office for National Statistics, online at http://www.statistics.gov.uk/downloads/theme_population/MethodologyforPEEG.pdf, accessed 14 January 2008.

Mitchell, R., Dorling, D., Martin, D. and Simpson, L. (2002) ‘Bringing the missing million home: correcting the 1991 census small area statistics for undercount’, Environment and Planning A, 34(6): 1021-1035.

Norman, P. (2007) Geographical Conversion Table for 2001 to 2004 electoral wards in Birmingham. Leeds: School of Geography, University of Leeds.

Norman, P., Rees, P. and Boyle, P. (2003) ‘Achieving data compatibility over space and time: creating consistent geographical zones’, International Journal of Population Geography, 9(5): 365-386.

Norman, P., Simpson, L. and Sabater, A. (forthcoming, 2008) ‘Estimating with Confidence and hindsight: new UK small area population estimates for 1991’, Population, Space and Place.

ONS (2002) Methods used to revise the 19822000 annual midyear population estimates for England and Wales. London: Office for National Statistics, online at http://www.statistics.gov.uk/downloads/theme_population/Meth_PopES_82_2000.pdf, accessed 14 January 2008.

ONS (2003) Imputation rates by variable. London: Office for National Statistics, online at http://www.statistics.gov.uk/census2001/imputation_rates_by_variable.asp, accessed 14 January 2008.

ONS (2007) Project on Small Area Population Estimates for England and Wales. London: Office for National Statistics, online at http://www.statistics.gov.uk/about/methodology_by_theme/sape/default.asp, accessed 14 January 2008.

Owen, D. (1996) ‘Estimating local change in the population of minority ethnic groups, 1981 to 1991’, Warwick: Centre for Research in Ethnic Relations, University of Warwick, Working Paper No. 1.

Parkinson, M., Champion, T., Evans, R., Simmie, J., Turok, I., Crookston, M., Katz, B., Park, A., Berube, A., Coombes, M., Dorling, D., Glass, N., Hutchins, M., Kearns, A., Martin, 32

R. and Wood, P. (2006) The state of the English cities. London: Office of the Deputy Prime Minister, Vol. 1.

Peach, C. (1996) ‘Introduction’, in Peach, C. (ed) Ethnicity in the 1991 Census. London: HMSO, 2: 1-24.

Peloe, A. and Rees, P. (1999) ‘Estimating ethnic change in London, 1981-91, using a variety of census data’, International Journal of Population Geography, 5(3): 179-194.

Radical Statistics Education Group (1982) Reading between the numbers, a critical guide to educational research. London: British Society for Social Responsibility in Science.

Rees, P. and Phillips, D. (1996) ‘Geographical spread: the national picture’, in Ratcliffe, P. (ed) Ethnicity in the 1991 Census: Social geography and ethnicity in Britain. London: HMSO, Vol. 3.

Sabater, A. (2008) Estimation of ethnic groups in subnational areas for analysis of population change, England and Wales, 19912001. Manchester: Cathie Marsh Centre for Census and Survey Research, University of Manchester, PhD Thesis.

Siegel, J. (2002) Applied Demography. Applications to Business, Government, Law, and Public Policy. San Diego: Academic Press.

Simpson, L. (2002) ‘Geography conversion tables: a framework for conversion of data between geographical units’, International Journal of Population Geography, 8: 69–82.

Simpson, L. (2007) ‘Ghettos of the mind: the empirical behaviour of indices of segregation and diversity’, Journal of the Royal Statistical Society A, 170(2): 405-424.

Simpson, L. (forthcoming - 2008) ‘Title to be confirmed’, Journal of Ethnic and Migration Studies.

Simpson, L. and Akinwale, B. (2007) ‘Quantifying stability and change in ethnic group’, Journal of Official Statistics, 23(2): 185-208.

Simpson, L., Cossey, R. and Diamond, I. (1997) ‘1991 population estimates for areas smaller than districts’, Population Trends, 90: 31-39.

Simpson, S. (2002) ‘Dealing with census undercount’, in Rees, P., Martin, D. and Williamson, P. (eds) The Census Data System. London: HMSO, 171-184.

SC (2007) Difference between Statistics Canada’s census counts and population estimates. Statistics Canada, online at http://www12.statcan.ca/english/census06/reference/Census_briefs_census_vs_estimates. cfm , accessed 14 January 2008.

SNZ (2007) Population Base at 30 June 1996, 2001 and 2006. Statistics New Zealand, online at http://www.stats.govt.nz/tables/population-estimates.htm, accessed 14 January 2008.

UN (1998) ‘Principles and Recommendations for Population and Housing Censuses’, Statistical Papers, New York: Department of Economic and Social Affairs, Statistics Division, Series M, 67.

USCB (1998) United States Population Estimates by Age, Sex, Race, and Hispanic Origin Method. U.S. Census Bureau, online at http://www.census.gov/popest/topics/methodology/2006_nat_meth.html, accessed 14 January 2008. 33

TABLE A1: 1991 population for 2001 OAs by age and sex and without an ethnic group dimension

Issues Strategies Methods / assumptions

Population definition Student transfer Move students from vacation to term- The EwC transfers for students are used based on student location and government estimates time address. for districts, for each ED.

The EwC adjustment for timing is used. This assumes the same proportional demographic Timing Move from census day (21 April) to change (ageing, births, deaths and migration) between Census day and mid-year as for the mid-year (30th June). containing district.

Boundary harmonisation Census counts and EwC adjustments A GCT is used to convert EwC data from the 1991 EDs to 2001 OAs. The ED-OA GCT is for 1991 EDs are transferred to 2001 constructed from a postcode list provided by ONS, linked to both 1991 EDs and 2001 OAs OAs, and summed to larger areas. and a count of addresses at each valid postcode. Overlaid ED and OA digital boundaries improve the quality of the allocation (Norman et al, 2008).

Non-response The difference between EwC mid- The ONS revision to 1991 non-response in each 5-year age-sex group (mostly a reduction 1991 population and ONS revised among men aged under 40) is distributed to a 2001 district’s OAs in proportion to the original mid-1991 population (estimated by non-response estimated by EwC. ONS only for 2001 districts) constitutes the ONS revision to nonresponse.

Ethnic group categories Not applicable: Table 2 shares the population to ethnic groups. Age group categories Each OA five-year age-sex group is spread to single years of age using Iterative Proportional Single year of age (91 categories) is Fitting (IPF) to maintain consistency with the district single year of age from ONS. Initial created from 5-year age groups. values include births 1990-91 to represent those aged under 1 at mid-1991, and the more detailed composition of those aged 15-19 and 85+ given in 1991 census output.

TABLE A2: 1991 population for 2001 OAs by age and sex: adding the ethnic group dimension

Issues Strategies Methods / assumptions Non-response The pattern of different non-response The SOCPOP dataset for wards includes a non-response adjustment based on differential non- rates for each group is taken from the response specific to each 5-year age group, sex, ethnic group and ward. This is distributed to ward SOCPOP estimates (5-year ages, EDs assuming the same rate of age-sex non-response in each of the ward’s EDs. It is further sex, ethnic group). adjusted in the next step after conversion to OAs by making consistency with the all-group non-response in the OA.

Boundary harmonisation Estimates for 1991 EDs are transferred As Table 1. The population estimates from the previous step, now for OAs, are scaled to agree to 2001 OAs. with the OA all-group population estimates estimated from Table 1 after deducting the student adjustment.

Population definition Student transfer Move students from vacation to term- For districts, OPCS adjustments to add and to remove students from each 1991 district are time address. converted to 2001 district boundaries using suitable GCTs. The ethnic group composition of

students removed because studying elsewhere is assumed the same as the resident population.

The ethnic group composition of students added because at vacation elsewhere is assumed to

be that of the 2001 ethnic group distribution of students, separately for males and females and

ages 18-24 and 25+. These adjustments are distributed to wards and OAs, rather crudely but

maintaining consistency both with the all-group student adjustment in each OA, and the ethnic

group student adjustment in each higher level. Lack of evidence prevents a more precise

Timing allowance for each group. Move from census day to mid-year (30th June). The timing adjustment is subsumed into the adjustment for non-response; it is small relative to each of the other adjustments.

Ethnic group categories Target categories are those used in Student information from 2001 uses allocation to the 10 1991 groups advised by Simpson and 1991 (10 categories). Akinwale (2007)

Age group categories Single year of age (91 categories) is created from 5-year age groups. Using IPF, the OA 5-year age-sex-ethnic groups are made consistent with the OA all-group single year of age-sex totals (Table 1), the interaction (single-year by ethnic group) coming

from the demographically smoothed SOCPOP data for the 1991 electoral ward containing the OA.

TABLE A3: 2001 population for 2001 districts by age and sex with an ethnic group dimension

Issues Strategies Methods / assumptions Ethnic group categories Target categories are those used in 2001 None needed. (16 categories). For districts in England, ONS Commissioned Census table C0533 has single year of age. For Age group categories Target categories are available for districts Wales, the 22 age categories of Census table ST101 are spread to single year of age to 89 and in England (91 categories), and estimated 90+, by demographic smoothing and then constrained to the single year of age published for for districts in Wales. the all-groups total.

Population definition Student transfer Students already at term-time address in None needed. 2001.

Timing Move from census day (29th April 2001) to For districts in England each component of change between Census day and mid-2001 (births, mid-year (30th June). deaths migration) was estimated by ONS by single year of age, sex and with an ethnic group dimension.

For Wales, 2001 Mid-year estimates by single year of age and sex, without an ethnic group dimension, consistent with those released by ONS in September 2004 are used. The timing transfer is subsumed to the allocation of extra non-response, assuming equal proportional impact on each group, within each age-sex-district category.

Non-response Extra non-response as estimated by ONS For all districts, the ethnic group composition of non-response is the same as the population (September 2004) assuming same non- ethnic group composition, for each age and sex group within each LAD. response rates for each ethnic group. A separate set of estimates using disproportionate non-response among minority ethnic groups as evidenced by imputation within the Census has also been prepared.

Boundary harmonisation Target geographies are those used in 2001 None needed. (376 districts).

TABLE A4: 2001 population for 2001 electoral wards and OAs by age and sex with an ethnic group dimension

Issues Strategies Methods / assumptions Boundary harmonisation The targets are 2001 standard output (ST) ONS estimates for CAS wards are aggregated to ST wards. wards, and OAs

Ethnic group categories Target categories are those used in 2001 None needed. (16 categories). Age group categories Single year of age (91 categories) is IPF is used to estimate more detailed cross-tabulations consistent with less detailed created from 5-year age groups (wards) information. For example, the ward all-group 5-year age-sex group population estimates from and 7 broad age groups (OAs). ONS and the all group district single year of age-sex totals from ONS are constraints to the interaction (single-year by wards) from the Census table ST001.

Population definition Student transfer Students already at term-time address in None needed. 2001.

Timing Move from census day to mid-year (30th The use of IPF as above, allocates the timing adjustment already in district estimates to smaller June). Timing already incorporated in ONS areas proportionately. ward population estimates (September 2004)

Non-response Extra non-response already incorporated in The use of IPF as above, allocates the non-response adjustment already in district estimates to ONS ward population estimates smaller areas proportionately. (September 2004)

Estimation of ethnic groups in sub-national areas for analysis of population change, England and Wales 1991-2001

A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy Ph.D. in the Faculty of Humanities

2007

Albert Coll SABATER

School of Social Sciences

Cathie Marsh Centre for Census and Survey Research

LIST OF CONTENTS

Abstract...... 16 Declaration...... 17 Copyright statement ...... 17 Acknowledgements ...... 18 List of abbreviations and acronyms...... 19

Chapter 1: Research context ...... 22 1.1: Introduction...... 22 1.2: Research aims and research question ...... 24 1.3: Motivation ...... 25 1.4: Thesis structure...... 27 1.5: Research parameters ...... 30 1.6: Research ethos ...... 31 1.7: Starting point: why do we need consistent population time series?...... 32 1.8: Why do we need an ethnic group dimension?...... 34 1.9: Defining the population base ...... 37 1.10: Conclusions...... 41

Chapter 2: Problems when analysing population change by ethnic group...... 42 2.1: Introduction...... 42 2.2: An overview of the problems ...... 42 2.3: Population definition: the enumeration of students and timing..... 45 2.3.1: The enumeration of students...... 45 2.3.2: Students: pending issues and perspectives...... 48 2.3.3: Timing transfer (from Census day to midyear)...... 50 2.3.4: Timing: pending issues and perspectives ...... 51 2.4: The treatment of nonresponse ...... 53 2.4.1: Adjustments for nonresponse in 1991...... 53 2.4.2: Adjustments for nonresponse in 2001...... 57 2.4.3: Nonresponse: pending issues and perspectives...... 62 2.5: Ethnic identification...... 64 2.5.1: Defining ethnicity...... 64 2.5.2: Changing ethnic group categories...... 65 2.5.3: Changes to ethnic identification ...... 72 2.5.4: Changes to ethnic group answer categories ...... 74 2.5.5: Target ethnic categories for thesis ...... 74 2.6: Age group categories ...... 75 2.6.1: The aggregation of age in census statistics ...... 75 2.6.2: Age with an ethnic breakdown for small areas...... 77 2.6.3: Target age categories for the thesis...... 79 2.7: The harmonisation of geographical boundaries...... 79 2.7.1: Census geography...... 79 2.7.2: The electoral geography ...... 82 2.7.3: Consistent geographies ...... 84 2.7.4: The Modifiable Areal Unit Problem (MAUP)...... 88 2.7.5: Target geographies for the thesis...... 90 3

2.8: A precedent: Linking Censuses through Time (LCT)...... 91 2.8.1: The focus of LCT...... 91 2.8.2: Ethnicity and adjustments in LCT...... 91 2.9: Conclusions...... 95

Chapter 3: Notation, data and tools ...... 98 3.1: Introduction...... 98 3.2: Specification of adjustments to create a time series...... 98 3.3: General Notation ...... 100 3.4: Summary of data sources...... 105 3.5: Statistical and geographical tools ...... 107 3.5.1: Applying Iterative Proportional Fitting (IPF)...... 107 3.5.2: Applying Geographical Conversion Tables (GCTs)...... 115 3.6: Conclusions...... 129

Chapter 4: Mid2001 population estimates for Districts in England and Wales ...... 130 4.1: Introduction...... 130 4.2: Objective and overview ...... 130 4.3: Background ...... 132 4.4: Data sources ...... 138 4.5: Method ...... 139 4.6: Validation...... 142 4.7: Conclusions and summary ...... 154

Chapter 5: Mid2001 population estimates for Wards in England and Wales ...... 157 5.1: Introduction...... 157 5.2: Objective and overview ...... 157 5.3: Background ...... 160 5.4: Data sources ...... 161 5.5: Method ...... 162 5.6: Validation...... 165 5.7: Conclusions and summary ...... 171

Chapter 6: Mid2001 population estimates for Output Areas in England and Wales ...... 174 6.1: Introduction...... 174 6.2: Objective and overview ...... 174 6.3: Background ...... 177 6.4: Data sources ...... 178 6.5: Method ...... 179 6.6: Validation...... 184 6.7: Conclusions and summary ...... 187

Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group) .... 190 7.1: Introduction...... 190 7.2: Objective and overview ...... 190 7.3: Background ...... 194 4

7.4: Data sources ...... 196 7.5: Method ...... 197 7.6: Validation...... 207 7.7: Conclusions and summary ...... 211

Chapter 8: 1991 student transfer for Output Areas and above in England and Wales...... 214 8.1: Introduction...... 214 8.2: Objective and overview ...... 214 8.3: Background ...... 216 8.4: Data sources ...... 218 8.5: Method ...... 219 8.6: Validation...... 223 8.7: Conclusions...... 229

Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales...... 230 9.1: Introduction...... 230 9.2: Objective and overview ...... 230 9.3: Background ...... 234 9.4: Data sources ...... 235 9.5: Method ...... 236 9.6: Validation...... 243 9.7: Conclusions and summary ...... 246

Chapter 10: Quality assurance ...... 250 10.1: Introduction...... 250 10.2: Internal validity ...... 251 10.3: External validity ...... 252 10.4: Conclusions...... 266

Chapter 11: Analysing population change in Birmingham: a case study...... 267 11.1: Introduction...... 267 11.2: Why Birmingham?...... 268 11.3: Time series data for 2004 electoral Wards...... 268 11.4: Overview of the impact of adjustments by ethnic group in the District of Birmingham...... 275 11.5: Enhancements to the 1991 and 2001 Censuses...... 278 11.5.1: Enhancements in 2004 electoral Wards for allgroups...... 278 11.5.2: Enhancements in 2004 electoral Wards for selected ethnic groups...... 282 11.5.3: Enhancements by age and sex for allgroups ...... 288 11.5.4: Enhancements by age and sex for selected ethnic groups...... 291 11.6: Population change 19912001...... 297 11.6.1: Population change in 2004 electoral Wards for allgroups ...... 297 11.6.2: Population change in 2004 electoral Wards by ethnic group ...... 300 5

11.6.3: Population change by age and sex for allgroups ...... 307 11.6.4: Population change by age and sex for selected ethnic groups...... 307 11.7: Conclusions...... 313

Chapter 12: Conclusions...... 317 12.1: Introduction...... 317 12.2: The problem statement and research questions ...... 318 12.3: Review of research findings ...... 319 12.3.1: Population definition...... 319 12.3.2: Treatment of nonresponse...... 320 12.3.3: Ethnic group and age classifications...... 322 12.3.4: Boundary harmonisation ...... 323 12.3.5: Revisiting the research questions ...... 324 12.4: Dissemination of data and results ...... 325 12.5: Further investigation by the candidate...... 327 12.6: Implications for social sciences in the UK ...... 329 12.6.1: Population denominators ...... 329 12.6.2: Migration ...... 330 12.6.3: Population projections...... 330 12.6.4: The 2011 Census...... 331 Bibliography ...... 334 Glossary...... 352 Appendix ...... 360

Word count: 80,031

List of tables

Table 1.1: Categories where the place of usual residence requires attention ...... 40 Table 2.1: Problems when comparing ethnic groups between 1991 and 2001 ...... 43 Table 2.2: Student adjustments to small area counts by EwC ...... 47 Table 2.3: Largest net gains and largest net losses of students...... 48 Table 2.4: Percentage distribution between ethnic groups of those aged 2024...... 49 Table 2.5: OPCS nonresponse adjustments to derive mid1991 population estimates ...... 54 Table 2.6: ONS extra nonresponse adjustments to derive mid2001 population estimates ...... 59 Table 2.7: The size of the Local Authority Studies adjustment...... 60 Table 2.8: Conversion of 1991 and 2001 ethnic group categories ...... 66 Table 2.9: Example of tencategory classification ...... 68 Table 2.10: Example of eightcategory classification ...... 69 Table 2.11: Example of fivecategory classification...... 70 Table 2.12: Example of twocategory classification...... 71 6

Table 2.13: Census age detail for males and females and with an ethnic breakdown for Wards...... 78 Table 2.14: Census age detail with an ethnic breakdown without sex for 1991 Enumeration Districts and 2001 Output Areas.. 79 Table 2.15: Percentage adjustments to population counts by age group in selected Districts ...... 92 Table 3.1: Data sources to create complete mid1991 population estimates...... 105 Table 3.2: Data sources to create complete mid2001 population estimates...... 106 Table 3.3: Example of using IPF (initial table)...... 109 Table 3.4: Example of using IPF (amended table) ...... 109 Table 3.5: Example of data file prepared for IPF in SPSS...... 111 Table 3.6: Example of census subtotals from which the margins variable is derived ...... 112 Table 3.7: An extract of the GCT used to link 1991 EDs with 2001 OAs.. 123 Table 3.8: List of GCTs used to harmonise data over time and space..... 125 Table 4.1: 2001 Census and adjustments by ethnic group in England..... 144 Table 4.2: 2001 Census and adjustments by ethnic group in two metropolitan Districts...... 145 Table 4.3: 2001 Census and adjustments by ethnic group in Wales...... 150 Table 4.4: 2001 Census and adjustments of ageing and timing by age and sex for allgroups in England...... 152 Table 4.5: Adjustment of extra nonresponse to mid2001 (Nov02) by age and sex for allgroups in England ...... 153 Table 4.6: Summary to create full mid2001 population estimates for Districts in England and Wales ...... 156 Table 5.1: Mid2001 population estimates by ethnic group in England and Wales (derived from the Ward data set)...... 168 Table 5.2: Mid2001 population estimates by age and sex for allgroups in England and Wales (derived from the Ward data set)...... 169 Table 5.3: Summary to create full mid2001 population estimates for ST Wards in England and Wales ...... 173 Table 6.1: Mid2001 population estimates by ethnic group in England and Wales (derived from the OA data set) ...... 186 Table 6.2: Mid2001 population estimates by age and sex for allgroups in England and Wales (derived from the OA data set) ...... 187 Table 6.3: Summary to create full mid2001 population estimates for Output Areas in England and Wales ...... 189 Table 7.1: EwC and revised 1991 undercount by age and sex in England and Wales ...... 208 Table 7.2: Revised mid1991 population estimates by age and sex in England and Wales ...... 210 Table 7.3: Summary to create full mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)...... 213 Table 8.1: Percentage distribution between ethnic groups of those aged 2024...... 217 Table 8.2: 1991 net student transfer to termtime address by ethnic group in England and Wales ...... 223 7

Table 8.3: 1991 net student transfer to termtime address by age and sex in England and Wales ...... 225 Table 8.4: Districts with greatest 1991 student transfer in England and Wales ...... 226 Table 9.1: Revised mid1991 population estimates by ethnic group in England and Wales ...... 245 Table 9.2: Revised mid1991 population estimates by age and sex in England and Wales ...... 246 Table 9.3: Summary to create full mid1991 population estimates for Output Areas and above in England and Wales ...... 248 Table 11.1: An extract of GCT07: 2001 Output Areas to 2004 Electoral Wards, Birmingham District...... 271 Table 11.2: Ward distribution from 2001 to 2004 in Birmingham District ...... 274 Table 11.3: The impact of adjustments on the 1991 Census, Birmingham District ...... 275 Table 11.4: The impact of adjustments on the 2001 Census, Birmingham District ...... 277 Table 11.5: Population change 19912001 with and without adjustments, Birmingham District...... 278 Table 11.6: Estimates of absolute population change 19912001 in 2004 electoral Wards, Birmingham District...... 299 Table 11.7: Estimates of population change 19912001 with the largest populations for each ethnic group (in five 2004 electoral Wards) ...... 302

List of figures

Figure 2.1: The timing transfer from Census day to midyear using a cohort component model ...... 51 Figure 2.2: Percentage of revised nonresponse not included within the 1991 Census output by ethnic group in England and Wales ...... 56 Figure 2.3: Percentage of extra nonresponse not estimated within the 2001 Census output by ethnic group in England and Wales ...... 61 Figure 2.4: 1991 original and revised nonresponse after the 2001 Census by age and sex in England and Wales...... 63 Figure 2.5: The tension between demographic data and geographical scale...... 77 Figure 2.6: The ONS 2001 Census hierarchy of building block geographies ...... 81 Figure 2.7: Changing boundaries in electoral Wards ...... 84 Figure 2.8: The two interrelated parts of the MAUP ...... 88 Figure 3.1. Postcodes used to link geographies and weight data conversion...... 119 Figure 3.2: Postcodes linked with ED (KHF13) ...... 121 Figure 3.3: Postcodes linked with OA (26UGGQ0005) ...... 121 Figure 3.4: Relationship between address counts and 1991 Ward SAS populations...... 128 8

Figure 4.1: Transition to create full mid2001 population estimates for Districts in England and Wales ...... 132 Figure 4.2: ONS imputation rates by sex and ethnic group in England and Wales ...... 134 Figure 4.3: ONS imputation rates by sex and ethnic group in Manchester District...... 134 Figure 4.4: ONS imputation rates by sex and ethnic group in Birmingham District ...... 135 Figure 4.5: ONS imputation rates by sex and ethnic group in East Dorset District...... 135 Figure 4.6: 2001 percentage adjustment due to extra nonresponse using ONS experimental statistics by age, sex and ethnic group in Manchester District...... 146 Figure 4.7: 2001 percentage adjustment due to extra nonresponse using ONS experimental statistics by age, sex and ethnic group in Birmingham District ...... 147 Figure 4.8: 2001 percentage adjustment due to extra nonresponse using ONS imputation rates by age, sex and ethnic group in Manchester District...... 148 Figure 4.9: 2001 percentage adjustment due to extra nonresponse using ONS imputation rates by age, sex and ethnic group in Birmingham District ...... 149 Figure 4.10: Districts with greatest adjustments between census and midyear in England and Wales ...... 154 Figure 5.1: Transition to create full mid2001 population estimates for ST Wards in England and Wales ...... 159 Figure 5.2: Total difference between the mid2001 population estimates obtained after IPF (version 1) and the known subtotals in England and Wales by Wards...... 166 Figure 5.3: Total difference between the mid2001 population estimates obtained after IPF (version 2) and the known subtotals in England and Wales by Wards...... 167 Figure 5.4: A selection of Wards with greatest adjustments between census and midyear in England and Wales ...... 170 Figure 6.1: Transition to create full mid2001 population estimates for Output Areas in England and Wales ...... 176 Figure 6.2: Total difference between the mid2001 population estimates obtained after IPF and the known subtotals in England and Wales by Wards (derived from the OA data set) ...... 185 Figure 7.1: Transition to create revised mid1991 population estimates for Output Areas and above in England and Wales ...... 193 Figure 7.2: Total difference between the mid1991 population estimates obtained after IPF and the known subtotals in England and Wales by Districts...... 207 Figure 8.1: Transition to create a 1991 student adjustment with ethnic group for Output Areas and above in England and Wales ...... 215 Figure 8.2: 1991 net student transfer to termtime address by age and sex for the White group in two Wards...... 227 9

Figure 8.3: 1991 net student transfer to termtime address by age and sex for the nonWhite groups in two Wards...... 228 Figure 9.1: Transition to create full mid1991 population estimates for Output Areas and above in England and Wales ...... 233 Figure 9.2: Total difference between the mid1991 population estimates obtained after IPF and the known subtotals in England and Wales by Districts...... 244 Figure 10.1: 2001 percentage adjustment due to timing by age, sex and ethnic group in England...... 254 Figure 10.2: 2001 percentage adjustment due to migration between England and the rest of the UK by age, sex and ethnic group...... 255 Figure 10.3: 2001 percentage adjustment due to international migration by age, sex and ethnic group in England ...... 256 Figure 10.4: 2001 percentage adjustment due to extra nonresponse as published by ONS experimental statistics by age, sex and ethnic group in England...... 257 Figure 10.5: 2001 percentage adjustment due to extra nonresponse (using ONS imputation rates) by age, sex and ethnic group in England ...... 258 Figure 10.6: 2001 percentage adjustment due to extra nonresponse and timing by age, sex and ethnic group in Wales...... 259 Figure 10.7: 1991 percentage adjustment due to students, timing, modification and nonresponse by age and sex in England and Wales ...... 260 Figure 10.8: 1991 percentage adjustment due to student transfer by age, sex and ethnic group in England and Wales ...... 261 Figure 10.9: 1991 percentage adjustment due to revised nonresponse and timing by age, sex and ethnic group in England and Wales ...... 262 Figure 10.10: Percentage population change between 1991 and 2001 for allgroups for 2001 Districts in England and Wales...... 264 Figure 10.11: Percentage population change between 1991 and 2001 for nonWhite groups for 2001 Districts in England and Wales ...... 265 Figure 11.1: An example of OA crossing a 2004 Ward in Birmingham District ...... 270 Figure 11.2: Ward boundaries in 2001 and 2004 in Birmingham District ...... 272 Figure 11.3: The intersection of Birmingham’s Ward boundaries between 2001 and 2004...... 273 Figure 11.4: Enhancements to the 1991 Census: 2004 electoral Wards, Birmingham District...... 279 Figure 11.5: Enhancements to the 2001 Census: 2004 electoral Wards, Birmingham District...... 281 Figure 11.6: Enhancements to the 1991 Census in 2004 electoral Wards for the White group (census categories), Birmingham District ...... 283 10

Figure 11.7: Enhancements to the 1991 Census in 2004 electoral Wards for the Black Caribbean group (census categories), Birmingham District ...... 285 Figure 11.8: Enhancements to the 2001 Census in 2004 electoral Wards for the White British group (census categories), Birmingham District ...... 286 Figure 11.9: Enhancements to the 2001 Census in 2004 electoral Wards for the Pakistani group (census categories), Birmingham District ...... 287 Figure 11.10: Enhancements to the 1991 Census: age and sex, Birmingham District ...... 289 Figure 11.11: Enhancements to the 2001 Census: age and sex, Birmingham District ...... 290 Figure 11.12: Enhancements to the 1991 Census by age and sex for the White group (census categories), Birmingham District ...... 293 Figure 11.13: Enhancements to the 1991 Census by age and sex for the Indian group (census categories), Birmingham District ...... 294 Figure 11.14: Enhancements to the 2001 Census by age and sex for the White British group (census categories), Birmingham District ...... 295 Figure 11.15: Enhancements to the 2001 Census by age and sex for the Chinese group (census categories), Birmingham District ...... 296 Figure 11.16: Estimates of population change 19912001 in 2004 electoral Wards, Birmingham District ...... 298 Figure 11.17: Estimates of absolute population change 19912001 in 2004 electoral Wards for the White and Black groups (eightcategory classification), Birmingham District...... 305 Figure 11.18: Estimates of absolute population change 19912001 in 2004 electoral Wards for the South Asian and Chinese groups (eightcategory classification), Birmingham District... 306 Figure 11.19: Estimates of population change 19912001 by age and sex, Birmingham District...... 308 Figure 11.20: Estimates of population change 19912001 by age and sex for the White group (eightcategory classification), Birmingham District ...... 309 Figure 11.21: Estimates of population change 19912001 by age and sex for the Black Caribbean group (eightcategory classification), Birmingham District...... 310 Figure 11.22: Estimates of population change 19912001 by age and sex for the Pakistani group (eightcategory classification), Birmingham District...... 311 Figure 11.23: Estimates of population change 19912001 by age and sex for the Bangladeshi group (eightcategory classification), Birmingham District...... 312

List of appendices

Appendix 1: The 1991 Census ethnic group question asked in England, Wales and Scotland ...... 360 Appendix 2: The 2001 Census ethnic group question asked in England and Wales ...... 361 Appendix 3: Enhancements to the 1991 Census in 2004 electoral Wards for the White group (census categories), Birmingham District ...... 362 Appendix 4: Enhancements to the 1991 Census in 2004 electoral Wards for the Black Caribbean group (census categories), Birmingham District ...... 363 Appendix 5: Enhancements to the 1991 Census in 2004 electoral Wards for the Black African group (census categories), Birmingham District ...... 364 Appendix 6: Enhancements to the 1991 Census in 2004 electoral Wards for the Black Other group (census categories), Birmingham District ...... 365 Appendix 7: Enhancements to the 1991 Census in 2004 electoral Wards for the Indian group (census categories), Birmingham District ...... 366 Appendix 8: Enhancements to the 1991 Census in 2004 electoral Wards for the Pakistani group (census categories), Birmingham District ...... 367 Appendix 9: Enhancements to the 1991 Census in 2004 electoral Wards for the Bangladeshi group (census categories), Birmingham District ...... 368 Appendix 10: Enhancements to the 1991 Census in 2004 electoral Wards for the Chinese group (census categories), Birmingham District ...... 369 Appendix 11: Enhancements to the 1991 Census in 2004 electoral Wards for the Asian Other (census categories), Birmingham District ...... 370 Appendix 12: Enhancements to the 1991 Census in 2004 electoral Wards for the Other group (census categories), Birmingham District ...... 371 Appendix 13: Enhancements to the 2001 Census in 2004 electoral Wards for the White British group (census categories), Birmingham District ...... 372 Appendix 14: Enhancements to the 2001 Census in 2004 electoral Wards for the White Irish group (census categories), Birmingham District ...... 373 Appendix 15: Enhancements to the 2001 Census in 2004 electoral Wards for the Other White group (census categories), Birmingham District ...... 374 Appendix 16: Enhancements to the 2001 Census in 2004 electoral Wards for the Mixed White and Caribbean group (census categories), Birmingham District ...... 375 12

Appendix 17: Enhancements to the 2001 Census in 2004 electoral Wards for the Mixed White and African group (census categories), Birmingham District ...... 376 Appendix 18: Enhancements to the 2001 Census in 2004 electoral Wards for the Mixed White and Asian group (census categories), Birmingham District ...... 377 Appendix 19: Enhancements to the 2001 Census in 2004 electoral Wards for the Other Mixed group (census categories), Birmingham District ...... 378 Appendix 20: Enhancements to the 2001 Census in 2004 electoral Wards for the Indian group (census categories), Birmingham District ...... 379 Appendix 21: Enhancements to the 2001 Census in 2004 electoral Wards for the Pakistani group (census categories), Birmingham District ...... 380 Appendix 22: Enhancements to the 2001 Census in 2004 electoral Wards for the Bangladeshi group (census categories), Birmingham District ...... 381 Appendix 23: Enhancements to the 2001 Census in 2004 electoral Wards for the Other Asian group (census categories), Birmingham District ...... 382 Appendix 24: Enhancements to the 2001 Census in 2004 electoral Wards for the Black Caribbean group (census categories), Birmingham District ...... 383 Appendix 25: Enhancements to the 2001 Census in 2004 electoral Wards for the Black African group (census categories), Birmingham District ...... 384 Appendix 26: Enhancements to the 2001 Census in 2004 electoral Wards for the Other Black group (census categories), Birmingham District ...... 385 Appendix 27: Enhancements to the 2001 Census in 2004 electoral Wards for the Chinese group (census categories), Birmingham District ...... 386 Appendix 28: Enhancements to the 2001 Census in 2004 electoral Wards for the Other group (census categories), Birmingham District ...... 387 Appendix 29: Enhancements to the 1991 Census by age and sex for the White group (census categories), Birmingham District ...... 388 Appendix 30: Enhancements to the 1991 Census by age and sex for the Black Caribbean group (census categories), Birmingham District ...... 389 Appendix 31: Enhancements to the 1991 Census by age and sex for the Black African group (census categories), Birmingham District ...... 390 Appendix 32: Enhancements to the 1991 Census by age and sex for the Black Other group (census categories), Birmingham District ...... 391 13

Appendix 33: Enhancements to the 1991 Census by age and sex for the Indian group (census categories), Birmingham District ...... 392 Appendix 34: Enhancements to the 1991 Census by age and sex for the Pakistani group (census categories), Birmingham District ...... 393 Appendix 35: Enhancements to the 1991 Census by age and sex for the Bangladeshi group (census categories), Birmingham District ...... 394 Appendix 36: Enhancements to the 1991 Census by age and sex for the Chinese group (census categories), Birmingham District ...... 395 Appendix 37: Enhancements to the 1991 Census by age and sex for the Asian Other group (census categories), Birmingham District ...... 396 Appendix 38: Enhancements to the 1991 Census by age and sex for the Other group (census categories), Birmingham District ...... 397 Appendix 39: Enhancements to the 2001 Census by age and sex for the White British group (census categories), Birmingham District ...... 398 Appendix 40: Enhancements to the 2001 Census by age and sex for the White Irish group (census categories), Birmingham District ...... 399 Appendix 41: Enhancements to the 2001 Census by age and sex for the Other White group (census categories), Birmingham District ...... 400 Appendix 42: Enhancements to the 2001 Census by age and sex for the Mixed White and Caribbean group (census categories), Birmingham District ...... 401 Appendix 43: Enhancements to the 2001 Census by age and sex for the Mixed White and African group (census categories), Birmingham District ...... 402 Appendix 44: Enhancements to the 2001 Census by age and sex for the Mixed White and Asian group (census categories), Birmingham District ...... 403 Appendix 45: Enhancements to the 2001 Census by age and sex for the Other Mixed group (census categories), Birmingham District ...... 404 Appendix 46: Enhancements to the 2001 Census by age and sex for the Indian group (census categories), Birmingham District ...... 405 Appendix 47: Enhancements to the 2001 Census by age and sex for the Pakistani group (census categories), Birmingham District ...... 406 Appendix 48: Enhancements to the 2001 Census by age and sex for the Bangladeshi group (census categories), Birmingham District ...... 407 14

Appendix 49: Enhancements to the 2001 Census by age and sex for the Other Asian group (census categories), Birmingham District ...... 408 Appendix 50: Enhancements to the 2001 Census by age and sex for the Black Caribbean group (census categories), Birmingham District ...... 409 Appendix 51: Enhancements to the 2001 Census by age and sex for the Black African group (census categories), Birmingham District ...... 410 Appendix 52: Enhancements to the 2001 Census by age and sex for the Other Black group (census categories), Birmingham District ...... 411 Appendix 53: Enhancements to the 2001 Census by age and sex for the Chinese group (census categories), Birmingham District ...... 412 Appendix 54: Enhancements to the 2001 Census by age and sex for the Other group (census categories), Birmingham District ...... 413 Appendix 55: Estimates of population change 19912001 in 2004 electoral Wards for the White group (eightcategory classification), Birmingham District...... 414 Appendix 56: Estimates of population change 19912001 in 2004 electoral Wards for the Indian group (eightcategory classification), Birmingham District...... 415 Appendix 57: Estimates of population change 19912001 in 2004 electoral Wards for the Pakistani group (eightcategory classification), Birmingham District...... 416 Appendix 58: Estimates of population change 19912001 in 2004 electoral Wards for the Bangladeshi group (eightcategory classification), Birmingham District...... 417 Appendix 59: Estimates of population change 19912001 in 2004 electoral Wards for the Black Caribbean group (eightcategory classification), Birmingham District...... 418 Appendix 60: Estimates of population change 19912001 in 2004 electoral Wards for the Black African group (eightcategory classification), Birmingham District...... 419 Appendix 61: Estimates of population change 19912001 in 2004 electoral Wards for the Chinese group (eightcategory classification), Birmingham District...... 420 Appendix 62: Estimates of population change 19912001 in 2004 electoral Wards for the Other group (eightcategory classification), Birmingham District...... 421 Appendix 63: Estimates of population change 19912001 by age and sex for the White group (eightcategory classification), Birmingham District ...... 422 Appendix 64: Estimates of population change 19912001 by age and sex for the Indian group (eightcategory classification), Birmingham District ...... 423 15

Appendix 65: Estimates of population change 19912001 by age and sex for the Pakistani group (eightcategory classification), Birmingham District...... 424 Appendix 66: Estimates of population change 19912001 by age and sex for the Bangladeshi group (eightcategory classification), Birmingham District...... 425 Appendix 67: Estimates of population change 19912001 by age and sex for the Black Caribbean group (eightcategory classification), Birmingham District...... 426 Appendix 68: Estimates of population change 19912001 by age and sex for the Black African group (eightcategory classification), Birmingham District...... 427 Appendix 69: Estimates of population change 19912001 by age and sex for the Chinese group (eightcategory classification), Birmingham District...... 428 Appendix 70: Estimates of population change 19912001 by age and sex for the Other group (eightcategory classification), Birmingham District ...... 429 Appendix 71: Summary of 1991 and 2001 readymade data sets for dissemination ...... 430

Abstract

The University of Manchester Albert Coll SABATER For the degree of Doctor of Philosophy Ph.D. Estimation of ethnic groups in subnational areas for analysis of population change, England and Wales 19912001 Year of submission 2007

Although census output from both 1991 and 2001 provides a detailed account of the population with an ethnic group dimension, and with detail of age and sex, accurate analyses of population change for subnational areas are subjected to four separate problems that make comparisons of populations over time difficult: changes in the population definition, changes in the treatment of nonresponse, changes in ethnic group classification and age standard outputs, and changes in geographical boundaries for standard census output.

The thesis reviews these problems and provides empirical evidence of the impact of these four issues. A standard methodology is used to overcome these four challenges, and to derive a consistent population time series 19912001, by single year of age, sex and ethnic group, as recorded in both censuses. These estimates are made available for each District, Ward and Output Area in England and Wales as defined in the 2001 Census. Each adjustment to the published census output is dealt with separately wherever possible and subject to constraints to maintain known patterns of age, sex, locality and ethnic group. The methods are focused on ensuring consistency with the statistical agencies’ latest estimates of mid1991 and mid2001 populations published in 2004 without an ethnic group dimension, as well as with the mid2001 populations published in 2006 with an ethnic group dimension.

A validation of the results is provided through the analysis of national totals by age, sex and ethnic group for England and Wales, and a case study focused on population change in the District of Birmingham and its constituent Wards. The impact of the adjustments to address one or other of the census’ four deficiencies is highlighted, and the thesis illustrates how these analyses are made more plausible, and in some cases made possible, by a consistent population time series.

Keywords: Population time series; population change; ethnic group; sub national areas; England and Wales.

Declaration

No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

Copyright statement i. The author of this thesis (including any appendices and/or schedules to this thesis) owns any copyright in it (the “Copyright”) and he has given The University of Manchester the right to use such Copyright for any administrative, promotional, educational and/or teaching purposes. ii. Copies of this thesis, either in full or in extracts, may be made only in accordance with the regulations of the John Rylands University Library of Manchester. Details of these regulations may be obtained from the Librarian. This page must form part of any such copies made. iii. The ownership of any patents, designs, trade marks and any and all other intellectual property rights except for the Copyright (the “Intellectual Property Rights”) and any reproductions of copyright works, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property Rights and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property Rights and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and exploitation of this thesis, the Copyright and any Intellectual Property Rights and/or Reproductions described in it may take place is available from the Head of School of Social Sciences.

Acknowledgements

This thesis would not have been possible without the kind support, the trenchant critiques, the probing questions, and the remarkable patience of my thesis supervisor Prof. Ludi Simpson. I cannot thank him enough.

I am also very grateful to Dr. Nissa Finney, for her commonsense, knowledge, and perceptiveness. I would also like to thank Dr. Paul Norman and Richard Kingston, for sharing with me their wealth of knowledge and ideas.

I am extremely grateful to the academic and support staff of the Cathie Marsh Centre for Census and Survey Research at the University of Manchester for their continuous support and assistance, and for making the period that the research was conducted productive and enjoyable. My special thanks go to the POPLA (Population and Places) Research group for the joined work that kept my head above water and the numerous discussions on demographic issues.

I wish to extend my thanks to my colleagues at the Centre d’Estudis Demogràfics in the University Autonomous of Barcelona. They helped me immensely by nurturing my intellectual curiosity during the early stages of my career as a demographer. All your generous input is in here somewhere.

This thesis would not appear in its present form without the kind assistance and financial support of the City Council of Birmingham.

Finally, I would like to express my appreciation to my two examiners Prof. David Voas (University of Manchester) and Prof. David Martin (University of Southampton) for their valuable insights and suggestions.

I am forever indebted to my family, teachers and friends for providing me with the means to learn and understand.

Last, but certainly not least, special thanks go to my partner Georgina Lloyd for her endless love and encouragement throughout this entire journey.

List of abbreviations and acronyms

AFPD All Fields Postcode Directory BCFE Boundary Committee for England BCW Boundary Committee for Wales CAS Census Area Statistics CASWEB Census Aggregate Outputs Web interface CCS Census Coverage Survey CDU Census Dissemination Unit CRE Commission for Racial Equality CVS Census Validation Survey DASA Defence Analytical Services Agency ED Enumeration District ESRC Economic and Social Research Council EwC Estimating with Confidence GCT Geographical Conversion Table GIS Geographical Information Systems IPF Iterative Proportional Fitting IPS International Passenger Survey LA Local Authority LBS Local Base Statistics LCT Linking Censuses through Time LGA Local Government Association LGCE Local Government Commission for England LS ONS Longitudinal Study MAUP Modifiable Areal Unit Problem MIMAS Manchester Information and Associated Services NeSS Neighbourhood Statistics NGR National Grid Reference NSO National Statistical Office NSPD National Statistics Postcode Directory NUTS Nomenclature Units for Territorial Statistics OA Output Area ONC One Number Census ONS Office for National Statistics OPCS Office of Population Censuses and Surveys OS Ordnance Survey SAPE Small Area Population Estimates SARs Samples of Anonymised Records SAS Small Area Statistics SOA Super Output Area SPSS Statistical Package for the Social Sciences ST Standard Table UA Unitary Authority UN United Nations UNECE United Nations Economic Commission for Europe UPTAP Understanding Population Trends and Processes

Nothing endures but change

Heraclitus (540 BC – 480 BC)

PART I: INTRODUCTION AND BACKGROUND PART I: INTRODUCTION AND BACKGROUND 22

Chapter 1: Research context

1.1: Introduction

The 1991 and 2001 Censuses of Population in England and Wales have provided comprehensive data on ethnic groups from national to local areas, thus making available a large array of data for various analytical practices and for use in ‘new’ research about the characteristics and distribution of the population (Coleman and Salt, 1996). The availability of census data online as part of the Census Dissemination Unit constitutes a fundamental step forward for census users. Within this context, tables of decennial census data with information on the associated administrative boundaries now exists in electronic formats from 1971 to 2001 through the CASWEB (2006) interface, thus enabling the analysis of large and complex census data sets for various geographical units. However, while many users of demographic statistics will find census data sufficiently useful for various applications such as the calculation of socioeconomic rates, the additional production of consistent midyear estimates is a standard method to allow comparisons with estimates for previous and later years.

The main problem is that midyear population estimates with an ethnic group dimension have been scarcely produced. First, it was attributable to the lack of data classified by ethnic group prior to the 1991 Census (Haskey, 1988). The availability of 1991 Census data by ethnic group, led a number of researchers back to the question of devising methods of estimating the ethnic composition of Districts1 in 1981 by calculating the ethnic breakdown of the population by country of birth so as to provide disaggregated estimates of population change by ethnic group over the decade 19811991 (Owen, 1996, Rees and Phillips, 1996, Peloe and Rees, 1999).

1 Any reference to Districts in this thesis can refer to local authority districts or unitary authorities in England and Wales. PART I: INTRODUCTION AND BACKGROUND 23 Chapter 1: Research context

The release of 2001 Census data with an ethnic group dimension represents the second time for which data for local areas with an ethnic group dimension are available to analyse the changing composition of ethnic groups in the United Kingdom (UK). Having two consecutive censuses asking for data by ethnic group should allow for various comparisons to be made, for example, to find out whether nonWhite groups are more clustered in large urban areas or to know the extent to which some ethnic minority groups are ageing in local areas over the recent decade.

However, such comparisons are not an easy task as 1991 and 2001 Census outputs contain four types of bias that make comparisons of populations over time difficult (Simpson et al., 1997; Sabater and Simpson, 2007): (1) the population definition, which defines who is a resident, has changed between the 1991 and 2001 Censuses; (2) the treatment of nonresponse in the census in 1991 and 2001 was different, and varied between ethnic groups, areas and ages; (3) key classifications changed between 1991 and 2001, including ethnic group and age in standard outputs; and (4) geographical boundaries used for standard census outputs changed, after local government reviews between 1991 and 2001.

This doctoral research takes into account the four types of bias and the latest available data post2001 Census. This allows the revision of 1991 census data sets created by the ‘Estimating with Confidence’ (EwC) project without an ethnic group dimension for subDistrict geographies (Simpson, 2002d), so that the ‘new’ 1991 population estimates by ethnic group are consistent and comparable with the timeseries of revised official subnational estimates. The methods used follow previous research produced by the EwC project to produce 1991 small area population estimates together with agesex and subgroupspecific adjustments to the published census output (Simpson et al., 1997). The EwC estimates became accepted as the ‘gold standard’ for mid1991 population estimates for small area populations and have been widely used in local government and academic research (Penhale et al., 2000; Rees et al., 2004). PART I: INTRODUCTION AND BACKGROUND 24 Chapter 1: Research context

After the publication of the initial mid2001 population estimates, the Office for National Statistics (ONS) concluded that the previous adjustments to 1991 populations were too large. In this respect, ONS made downward revisions to 1991 nonresponse, which resulted in further revisions to the mid1991 population estimates in England and Wales (Duncan et al., 2002; ONS, 2002).

Second, the doctoral research makes use of mid2001 population estimates for Districts by ethnic group produced by ONS for England (Large and Ghosh, 2006) and for Wales without ethnic group. Mid2001 population estimates for Wards without an ethnic group dimension are also used from the ONS Small Area Population Estimates (SAPE) unit (2006a). These estimates incorporate an allowance of extra nonresponse for Districts not included in the initial mid2001 population estimates (ONS, 2004b, 2004c).

The creation of consistent population time series relies heavily on the ‘new’ base midyear estimate created after each census, as the previously published time series is normally revised in the light of the latest available data. Hence, the latest Districtlevel revisions to mid1991 and mid2001 population estimates must be applied to subDistrict geographies accordingly.

1.2: Research aims and research question

The first aim is to achieve consistent midyear population estimates with the latest ONS midyear estimates, at census years 1991 and 2001, with single year of age, sex and ethnic group as recorded in each census and for each of the following geographical areas in England and Wales: Districts, Wards and Output Areas (OAs) as defined in the 2001 Census geography.

The second aim is to analyse population change between 1991 and 2001 in one District and its constituent electoral Wards with consistent age, sex and ethnic group. For this practical application, the District of Birmingham and its PART I: INTRODUCTION AND BACKGROUND 25 Chapter 1: Research context

constituent electoral Wards have been chosen as a case study to test the usefulness of analysing population change with consistent midyear estimates.

The problem statement posed by this doctoral research is as follows:

It is possible to compare populations over time and space, if population bases are made consistent, as demonstrated by a time series 1991-2001 of the usually resident population disaggregated by age, sex, ethnic group and small areas.

The thesis statement is closely linked to a number of specific research questions which are addressed in this doctoral research. These are as follows:

• Are data published from both 1991 and 2001 Censuses suitable to analyse population change of ethnic groups over time in Districts and smaller areas in England and Wales?

• Can the introduction of adjustments accounting for changes in the population definition, in the treatment of nonresponse, in ethnic and age classifications, and boundary harmonisation, enhance published census data from both 1991 and 2001?

• Can consistent midyear population estimates be used as a way to improve comparability of ethnic group populations over time and space?

1.3: Motivation

It is clear that whilst the demand for investigating and understanding the ethnic character of local areas has increased (National Strategy for Neighbourhood Renewal, 2000), the availability of comparable data over time PART I: INTRODUCTION AND BACKGROUND 26 Chapter 1: Research context

and space with an ethnic group dimension remains insufficient. Although the population census has traditionally been the main source of small area data for government service planning and resource allocation, as no other data source comes close to the nearcomplete coverage of the census for small areas, a consistent population time series is needed to obtain comparability. This clearly represents an important motivation factor within this doctoral research. Nonetheless, the production of such statistical output is hard to calculate for a variety of reasons, including changes in the definition of the population, changes of data quality between censuses and changes in geographical boundaries.

This doctoral thesis is primarily motivated by the desire to demonstrate that these problems surrounding comparisons of population subgroups for sub national areas over time can be overcome if consistent population time series are constructed. From this point of view, the doctoral research aims to represent a wakeup call specifically to those who use ethnicity data from both 1991 and 2001 Censuses as published uncritically.

Although the focus of the doctoral research is to contribute to a better understanding of the impact of the problems affecting analyses of population change of ethnic groups over time and space, it is understood that a variety of other analyses are likely to benefit from knowledge of the trajectory of population change. Some contexts are as follows: when estimates are used as the denominators in rates; or when estimates are used as a base population for projections or estimates for postcensal years. Therefore, if small area estimates are revised then any calculations which have used the previous version are liable to be affected.

Additionally, other persistent geographyrelated problems with census statistics in the UK have made it very difficult to measure changing conditions between two points in time. For example, a new geographical methodology based on grouping postcodes using computerbased geographical information systems (GIS) has been implemented through the 2001 Census, thus making previous censuses small area data incompatible with the newly PART I: INTRODUCTION AND BACKGROUND 27 Chapter 1: Research context

created census OAs. The new smallest census areas, the OAs, are being used as building bricks for the creation of larger geographical units such as the Super Output Areas (SOAs), but the previous smallest census geographies in the 1991 Census, the Enumeration Districts (EDs), have not been updated to the new census geography. The plan for updating information contained in the old smallest census areas to the new OAs is certainly another important motivation factor within this doctoral research.

The provision of new data sets for small areas through this doctoral thesis will not only allow the analysis of population change of ethnic groups in England and Wales between 1991 and 2001, but will also constitute a significant input within social sciences in the UK. From the standpoint of current debates on residential segregation of ethnic groups in England and Wales, for example, the doctoral thesis will provide unique data sets to calculate key measures of social polarisation for a wide range of small areas. As such, this also constitutes an important motivational factor that may help to understand more appropriately the level and direction of change in residential segregation and diversity of ethnic groups over the last decade.

1.4: Thesis structure

The doctoral thesis has been organised in three main parts. An overview of the contents for each part and its constituent chapters is given in this section.

Part I (Chapters 1 and 2) contains the various aspects of introduction and background of the research and clarifies the research aims and research question. General background and a review of the main problems are provided along with the implications for comparing populations over time and space. An outline of the content for each chapter is as follows:

• Chapter 1 is the introduction to the thesis. It gives general context for the doctoral research, describing the main aims as well as the research question. It also provides information about the general PART I: INTRODUCTION AND BACKGROUND 28 Chapter 1: Research context

structure of the thesis, and the parameters and ethos. Finally, it gives background about the need for having comparable time series with an ethnic group dimension as well as a review of the population bases used in the last two censuses in England and Wales.

• Chapter 2 provides a review of the main problems when analysing population change between 1991 and 2001 by age, sex and ethnic group for subnational areas in England and Wales. As such, the chapter examines the problems derived from changes in the population definition, changes in the treatment of nonresponse, changes in ethnic identification, changes in age group categories and the harmonisation of geographical boundaries. The review is focused on explaining the different solutions applied to solve these problems as well as pending issues still to be tackled.

Part II (Chapters 3 to 9) gives the methodological framework for carrying out qualityassured population estimates. This comprises a sequence of methods which builds on previous work and leads to the creation of consistent 1991 and 2001 midyear population estimates by age, sex and ethnic group for each District, Ward and OA in England and Wales as defined in the 2001 Census. An outline of the content for each chapter is as follows:

• Chapter 3 establishes a general methodological framework from which a consistent population time series by single year of age, sex and ethnic group, as recorded in the censuses, are obtained. Specification of the adjustments regarding the target for consistency is given as well as the general notation and data sources used for the creation of consistent population estimates with an ethnic group dimension. A description of the geographical and statistical tools is also supplied in this chapter.

• Chapter 4 provides a full description of the methods used to create 2001 midyear estimates for each District in England and Wales as PART I: INTRODUCTION AND BACKGROUND 29 Chapter 1: Research context

defined in the 2001 Census by single year of age, sex and ethnic group.

• Chapter 5 gives a full description of the methods implemented to create 2001 midyear estimates for each Ward in England and Wales as defined in the 2001 Census by single year of age, sex and ethnic group.

• Chapter 6 provides a full account of the methods undertaken to create 2001 midyear estimates for each OA in England and Wales as defined in the 2001 Census by single year of age, sex and ethnic group.

• Chapter 7 provides a full description of the methods used to create 1991 midyear estimates using the 2001 Census geography for each District, Ward and OA in England and Wales by single year of age and sex, without an ethnic group dimension.

• Chapter 8 provides a full account of the methods implemented to derive a student transfer from vacation to termtime address for each 2001 OA in England and Wales by fiveyear age, sex and ethnic group.

• Chapter 9 gives a full description of the methods carried out to create 1991 midyear estimates using the 2001 Census geography for each District, Ward and OA in England and Wales by single year of age, sex and ethnic group.

Part III (Chapters 10 to 12) provides information about implementation and quality assurance, first for the estimation outputs nationally and second by looking at population change with an ethnic breakdown between 1991 and 2001 in the District of Birmingham and its constituent electoral Wards as a practical application. Finally the conclusions, which give an account of the main research findings, dissemination, further research and the potential impact of the thesis. PART I: INTRODUCTION AND BACKGROUND 30 Chapter 1: Research context

An outline of the content for each chapter is as follows:

• Chapter 10 focuses on giving assurance about the quality of the results, to allow users to judge the validity of the previously created midyear population estimates for 1991 and 2001, providing results on national totals by single year of age, sex for each ethnic group.

• Chapter 11 provides a case study of analyses of population change by age, sex and ethnic group in the District of Birmingham and its constituent electoral Wards. This constitutes a practical application of using the qualityassured midyear estimates with consistent age, sex and ethnic group in order to illustrate the impact of making population comparisons between 1991 and 2001 with and without adjustments.

• Chapter 12 describes the main research findings, the dissemination of statistical outputs and journal articles derived from the thesis, and details of further research by the candidate building on this doctoral research. Finally, a discussion of the potential research impact of the thesis for social sciences in the UK is given.

1.5: Research parameters

Study geography. For the population estimation reported in Part II, and the quality assurance reported in Chapter 10, the study geography is England and Wales and subnational areas. For the case study reported in Chapter 11, the study geography is the District of Birmingham and its constituent electoral Wards. The reasons for choosing different sets of geography are explained in due course.

Time period. The thesis focuses on end points of the ten year period 1991 to 2001. This time period is used because of the availability of census data for these two years, which provides information on a uniform basis about the PART I: INTRODUCTION AND BACKGROUND 31 Chapter 1: Research context

country as a whole and about individual small areas and subgroups of the population in relation to one another.

Geographical scale. The subnational areas in England and Wales reported in the population estimation in Part II are: Districts, Wards and OAs as defined in the 2001 Census. The areas smaller than the District of Birmingham reported in Chapter 11, are current electoral Wards as defined in 2004 which are not coterminous with any census units. These aspects are expanded later.

Unit of study. The unit of study is the individual person. The thesis uses the same unit that the Registrar General takes into account to produce current series of subnational population estimates.

Dimensions. The thesis focuses on three dimensions: age (fiveyear age groups and single year of age), sex (males and females) and ethnic group as recorded in the 1991 and 2001 Censuses (matching of categories is made subsequently).

1.6: Research ethos

Data acquisition. Census data sets used for this thesis have been accessed through CASWEB (web based interface to census data), a service free to any members of a UK Higher Education Institution. Additionally, data freeof charge from the Office for National Statistics (ONS) and the Estimating with Confidence (EwC) project to produce population estimates for 1991 and 2001 have been used.

Methods. This doctoral research has produced a standard estimation methodology for subnational areas in England and Wales. Although analysis of population change is developed for the District of Birmingham and its constituent electoral Wards, the same analysis is applicable for any sub national area in England and Wales. PART I: INTRODUCTION AND BACKGROUND 32 Chapter 1: Research context

Acknowledgement of data sources. In this thesis, a variety of data sources have been used from the Office of Population Censuses and Surveys (OPCS), the Estimating with Confidence (EwC) project, and the Office for National Statistics (ONS). Census data are Crown copyright.

1.7: Starting point: why do we need consistent population time series?

This section highlights the significance of having population time series and why it is useful to provide consistency over time and space.

Population time series are used by a broad spectrum of users, from central government, local authorities and health bodies, to other public bodies and commercial companies as well as individuals in the private and academic sector. The consequences of not having consistency over time for these users is likely to determine resource allocation from central government, as population time series are widely used as denominators for the calculations of rates and ratios (ONS, 2002a).

In order to derive population time series, the census is used as the primary source of data, as it is the only time when data are collected nationally at a very local level. The census provides a detailed account of the population structure each decade, a valuable array of information that it is also available by ethnic group since 1991. The release of the 2001 Census represents the second time when this comprehensive information on the characteristics of ethnic group populations was collected, thus being the first time when population change by ethnic group over a decade can be directly analysed.

However, analysing population change by ethnic group is not a straightforward operation and measuring population change of ethnic groups directly from the census would be misleading.

A number of issues regarding changes in the population definition, changing levels of census undercount, changes in the ethnic group categories and boundary changes between censuses need to be taken into account so as to PART I: INTRODUCTION AND BACKGROUND 33 Chapter 1: Research context

provide accurate insights into how the population by ethnic group is changing for subnational areas over time.

The importance of the harmonisation of timeseries attributes and geographical data is crucial in many aspects of analysing population change through time and space.

For example, research measuring residential patterns using indices of segregation at different points in time can be further reviewed by applying consistent population time series where geographical boundaries and population definitions are harmonised across time. The sensitivity of each index of segregation and diversity to these issues can vary significantly as shown by Simpson (2007).

For alternative approaches to measuring population change, this research will also be important as it allows for demographic analysis of migration, ethnic group and population dynamics when studying the processes of dispersal of ethnic minority groups (Rees and Phillips, 1996; Simpson, 2004, Simpson et al., 2006a).

The creation of an estimated unbiased and consistent population time series by ethnic group at different subnational levels will also provide more information to study the impact of undercount for different areas. This can be relevant for research investigating those most likely to be missed by the census, such as young adults and those recently migrated and racially or culturally discriminated against, at different subnational levels (Simpson and Middleton, 1997).

The production of accurate population estimates will also be important in population projections, as they can be used as the starting population to project the population forward as well as to inform assumptions from recent change. As such, they allow the assessment of future prospects on, for example, housing and employment need, in small areas, thus facilitating the estimation of trends in the many demographic rates and inform assumptions about future change by ethnic group. PART I: INTRODUCTION AND BACKGROUND 34 Chapter 1: Research context

1.8: Why do we need an ethnic group dimension?

In this section, a discussion about the importance of having comparable population statistics with an ethnic group dimension is provided.

Britain is the only EU member state to ask about ethnicity in censuses, and the inclusion of the ethnic group question in the 1991 Census is considered as a landmark in British social statistics (Coleman and Salt, 1996; Langevin, et al., 1992). However, the question of ethnicity was not included in the census without controversy; in fact, ethnicity was included in the 1991 Census after being excluded from the 1981 Census because pilot tests suggested that the question was too sensitive to obtain a high response (Bulmer, 1986; Diamond, 1999).

The concept and measurement of ethnic identity is often seen as situational, mainly as different factors such as culture, heritage, language, religion, and geographical origin as well as other elements are subject to change over time. Within this context, the development of questions identifying ethnic origin has proved to be difficult (Booth, 1985; Fennema, 2004; Sillitoe and White, 1992). For example, the capture of the ethnic identity of those of mixedethnicity parentage demonstrates some of these complexities (Berthoud, 1998). Some of the aspects of stability and change of ethnic groups over time and its implications using census categories from the 1991 and 2001 Censuses are later discussed in detail.

The collection of data on ethnic groups to estimate their number and geographical distribution and to describe their characteristics has become an essential part of the formulation, monitoring and evaluation of antidiscrimination policies in the UK. The support for the collection of ethnic group data in the last two censuses has enabled national and local government and health authorities to allocate resources at both local and national levels, taking into consideration the special needs of different ethnic groups (Ahmad and Sheldon, 1993). PART I: INTRODUCTION AND BACKGROUND 35 Chapter 1: Research context

Having data on ethnic groups has become an invaluable aid to researchers investigating the issues of differences in the labour market, education, housing, health, etc, and to those responsible, nationwide, for developing and implementing appropriate policies (Modood et al., 1997). In addition, public authorities and charities such as the Commission for Racial Equality and the Runnymede Trust also support ethnic data collection in the census to ensure equity of employment and access to services as a general duty within the Race Relations (Amendment) Act 2000 to reduce discrimination. These objectives have increased the demand for more frequent and comprehensive data by ethnicity, thus recognising that, without small area data with an ethnic breakdown, not enough is known about their particular circumstances. Some examples are initiatives such as the New Deal for Communities, the Best Value and the National Strategy for Neighbourhood Renewal (2000).

The addition of ethnic groups from the 1991 Census (10 categories) to the 2001 Census (16 categories) can be seen as a way to promote race equality and social cohesion, to inform about changing composition of immigration as well as to identify those areas where inequality needs to be tackled. Within this context, the release of 1991 Census data confirmed widespread variations between ethnic groups with regard to labour market and employment patterns, housing conditions and education. For example, the 1991 Census showed that in general, ethnic minority populations showed higher unemployment rates than the White population. The employment rates among men showed that 51 per cent of Bangladeshi and 54 per cent of Pakistani were found in employment, compared to 78 per cent of the White population among the economically active. Similar differences were found among women, with employment rates of about 15 per cent of Bangladeshi and 20 per cent of Pakistani women in employment compared to 64 per cent of the White population (Fieldhouse and Gould, 1998; Holdsworth and Dale, 1997; Owen, 1997).

The release of 2001 Census data has also allowed other empirical analyses to confirm whether differences are greater or have declined at the same time some ethnic groups have become established. For example, between 1991 PART I: INTRODUCTION AND BACKGROUND 36 Chapter 1: Research context

and 2001, male and female unemployment rates fell, with a rise of male employment rates among the Black African, Pakistani and Bangladeshi groups, as well as with a generalised increase for females in almost all ethnic groups with the largest increases among the Bangladeshi, Indian and Pakistani groups. However, in 2001, unemployment rates in many ethnic minority groups were more than double those of the White British group. For example, male unemployment rates were particularly high for the Black African, Black Caribbean, Bangladeshi, Pakistani and Mixed groups and, among women, unemployment was significantly high for the Pakistani and Bangladeshi groups (Bosveld et al., 2006a; Dale et al., 2002).

In fact, the population increases of ethnic minority groups between 1991 and 2001 mean that labour market disadvantages between ethnic groups are experienced by a larger group of people, thus affecting more people even though employment, economic activity and inactivity rates have increased or remained stable during this period (Simpson et al., 2006b).

Differences are also found in the level of educational qualification between ethnic groups. Evidence from the 1991 Census showed that among 19 year olds, 74 per cent of Chinese and 63 per cent of Black Africans were in full time education, compared to 21 per cent of White and 22 per cent of Bangladeshis. These differences were also significant when compared between males and females. For example, 62 per cent of Pakistani males were in fulltime education compared to 51 per cent of Pakistani females (Drew et al., 1997). Evidence from the 2001 Census showed that 19 per cent of the White British among men of working age had a qualification to degree or equivalent level compared to 43 per cent of the Black Africans and 38 per cent of the Chinese (Bosveld et al., 2006a).

The largest concentrations of ethnic groups are found in the major cities, as a result of the postwar migration to Britain to areas with availability of low and semiskilled jobs and access to housing. Some of these areas have experienced a population growth of the ethnic minority groups which, in some cases, makes the White British a minority. Some examples are the Indian PART I: INTRODUCTION AND BACKGROUND 37 Chapter 1: Research context

group, which represents a majority in some areas of Leicester, similarly the Pakistani group, which forms a majority within areas of Bradford, Birmingham and Rochdale (Bosveld et al., 2006a). Data from the 1991 and 2001 Censuses have helped to indicate that population growth of ethnic minorities in the original settlement areas with limited housing is leading to the dispersal of these populations. The dispersal of affluent ethnic minorities away from the original settlement areas with the majority of social and familiar support reflects the lack of new housing as well as poor health conditions in these areas (Simpson et al., 2006b).

Therefore, with detailed and appropriate statistics with an ethnic group dimension it is possible to provide evidence of diversity and different trajectories over time, a crucial aspect to tackle disadvantages between ethnic groups.

1.9: Defining the population base

In this section, information is given about the set of criteria that is used to define who is included in the population when a census is held and when the midyear population is estimated in the UK.

In general, when a census is taken the principal aim is to cover the entire population. For this purpose, decisions are taken in order to determine who is counted and where they are counted (Dale et al., 2000). In that sense, the definition of the population base, the set of criteria that decides who is included in the count of the population, is a basic step both to avoid blurriness in the total count of individuals and to understand the way in which the population is counted.

Traditionally, the ‘usual residence’ and ‘persons present’ have been the choices available for the enumeration of the population in censuses (UN, 1998a and 1998b). In the UK, censuses have concentrated on ‘population present’ as the population base at enumeration and output, with a restricted PART I: INTRODUCTION AND BACKGROUND 38 Chapter 1: Research context

use of the ‘usual residence’ until 1981. In fact, the 1991 Census used, as in the 1981 Census, two population bases at enumeration, the usual residence and population present. For the population base at output, a count of usual residents in 1991 was made from the doubleenumeration which included the population on wholly absent households from the population present at the time of the census. In 2001, however, census questionnaires were only collected at the place of usual residence (Baker, 2004).

Decisions about which population base should be used are not exempt from problems. In 1991, a survey to validate the results of the census (Census Validation Survey) was carried out to identify the main problems related to the population base at enumeration (OPCS, 1994a and 1994b). Three problems were highlighted: (1) confusion about entering information on people away from home; (2) no legal obligation for wholly absent households to complete a census questionnaire; and (3) double enumeration of people who were away from their usual residence who ended up filling in the census questionnaire twice.

In order to avoid these problems, decisions were taken for the 2001 Census to collect data only on a usually resident basis. This meant that people only had to fill in the census questionnaire at the place of their usual residence. Therefore, the place where respondents were asked to fill in their census questionnaire varied between 1991 and 2001. Whilst the doubleenumeration in the 1991 Census allowed a few tables to be added about persons present, 2001 Census statistics only relate to where people usually live. Due to the fact that no substantive information on visitors was collected, comparisons with figures other than the usual resident population cannot be made (ONS, 2004a).

Nonetheless, the test undertaken during the development of the 2001 Census in England and Wales indicated that the use of the usual resident base was the most secure method of obtaining the required data for most users. In addition, the measures in place to compensate for census PART I: INTRODUCTION AND BACKGROUND 39 Chapter 1: Research context

undercount were based on the sole use of usual residence as the population base at enumeration (Baker, 2004).

Another advantage of the population base used in 2001 is that it underpins the midyear population estimates resident base, making the population definition in line with that of the Registrar General and which is used to produce the current series of subnational population estimates (ONS, 2002a: 12): ‘The estimated population of an area includes all those usually resident in the area, whatever their nationality; members of Her Majesty’s armed forces stationed in England and Wales are included at their place of residence but those stationed outside England and Wales are not included. Members of the US armed forces stationed in England and Wales are included at their place of residence. Students are taken to be resident at their termtime address. Prisoners are regarded as usually resident at an institution if they have served 6 months or more of a custodial sentence’.

The concern about the choice of population bases is also present in other countries. According to the UN Expert Group Meeting, it is one of the emerging issues that should be considered for the planning of the 2010 round of population and housing censuses (UN, 2004).

In the UK, although the 2001 approach has proved to have many advantages, it has also highlighted the ambiguity of the concept of usual residence. The difficulty of defining usual residence represents an important blurriness for counting a population when it is based on the usual residence population base at enumeration, as it is not always possible to collect information about each individual at his or her usual residence when residents are away at the time of the census (UN, 2000). For example, in the UK, the enumeration of students requires special attention as a result of definitional differences in the enumeration of students in the 1991 and 2001 Census. In 1991, students were counted as being usually resident at their home address and recorded again at their termtime address as visitors if present there on Census night. In 2001, students away from home were counted as being usually resident at their termtime address, as a way to PART I: INTRODUCTION AND BACKGROUND 40 Chapter 1: Research context

provide a better description of those in fulltime education and away from the family home (ONS, 2004a).

Therefore, although the concept of usual residence is generally straightforward, there are a number of cases where special attention is required. Table 1.1 provides a list of categories where this situation is likely to apply.

Table 1.1: Categories where the place of usual residence requires attention

(1) Persons who maintain more than one residence, e.g. a town house and a country house; (2) Students who live in a school or university residence, as boarders in a household or as a oneperson household for part of the year and elsewhere during vacations; (3) Persons who live away from their homes during the working week and return at weekends; (4) Persons in compulsory military service; (5) Members of the regular armed forces who live in a military barrack or camp but maintain a private residence elsewhere; (6) Persons who have been an inmate of a hospital, welfare institution, prison, etc., for a sufficiently long time to weaken their ties with their previous residence to which they may return eventually; (7) Persons who have been at the place where they are enumerated for some time but do not consider themselves to be residents of this place because they intend to return to their previous place of residence at some future time; (8) Persons who have recently moved into an area and may not feel that they have lived there long enough to claim it as their place of usual residence this may apply in particular to immigrants from abroad; (9) Persons who have left the country temporarily but are expected to return after some time.

Source: Adapted from UN (1998a: 12).

These aspects highlight the importance of taking into consideration changing definitions in census taking and assist users on comparability over time. The growing complexities in living arrangements and increasing trends towards geographical mobility, are already making National Statistical Offices (NSOs) plan the various uses and applications of different population bases. For example, in the process of selection of the population base for the 2011 Census enumeration, ‘ONS recommend that the 2011 Census in England PART I: INTRODUCTION AND BACKGROUND 41 Chapter 1: Research context

and Wales should collect information from usual residents, with some information collected on visitors present on Census Night’ (ONS, 2005b: 1).

The focus of this thesis is to be consistent with the population definition of the Registrar General when producing series midyear population estimates, thus taking into account the usually resident of an area.

1.10: Conclusions

The context of the research and research aims have been discussed in this chapter. Various aspects relating to the research structure, parameters and ethos have also been clarified. In addition, an account is given of different ideas about the need for consistent population time series, and with an ethnic group dimension. In the next chapter, the problems arising from analysing population change by ethnic group between 1991 and 2001 in England and Wales are reviewed.

PART I: INTRODUCTION AND BACKGROUND 42

Chapter 2: Problems when analysing population change by ethnic group

2.1: Introduction

This chapter discusses the four main problems restricting analysis of population change by age, sex and with an ethnic group dimension in sub national areas in England and Wales between 1991 and 2001. A review is given for each of the separate problems. Section 2.3 reviews the changes in the population definition, mostly affecting students. Within the same section the timing transfer between Census day and midyear is also taken into consideration. Section 2.4 reviews the problem of nonresponse in censuses with special emphasis on the different treatment of nonresponse between 1991 and 2001. Section 2.5 provides information about changes in ethnic identification between 1991 and 2001, highlighting different possibilities to compare ethnic groups over time. Similarly, Section 2.6 provides information about changes in age group categories between 1991 and 2001. Finally, Section 2.7 deals with the harmonisation of geographical boundaries. To conclude, Section 2.8 gives a review of the Linking Censuses through Time (LCT) project as a major precedent dealing to a limited extent with the majority of these problems.

2.2: An overview of the problems

Although census output from both 1991 and 2001 provides a detailed account of the population, accurate analyses of population change with detail of age and sex and an ethnic group dimension for Districts and smaller areas are restricted due to four main separate problems. Table 2.1 enumerates these problems which are also identified by ONS (Bosveld et al., 2006b). PART I: INTRODUCTION AND BACKGROUND 43 Chapter 2: Problems when analysing population change by ethnic group

Table 2.1: Problems when comparing ethnic groups between 1991 and 2001

(1) Problem 1. Population definition (enumeration of students and timing).

(2) Problem 2. Treatment of nonresponse.

(3) Problem 3. Ethnic identification and age group categories.

(4) Problem 4. Boundary harmonisation.

Population definition: the enumeration of students and timing. Whilst the 2001 Census enumerated the whole population at their usual residence address, including students at their termtime address, the 1991 Census enumerated students at their vacation address, thus making necessary the transfer of students from their vacation address to their termtime address in 1991. Because population estimates are usually made for midyear (30th June) rather than Census day, an allowance for timing is necessary. In addition, since the census was held in a different day of April in 1991 and 2001, a routine account is usually made for the births, deaths and migration (at the various ages) in the interval, thus allowing the production of midyear population estimates. Nationally, timing is small although its impact locally could be relevant.

Treatment of nonresponse. Since it is widely accepted that no census will count the whole population, adjustments are usually made for undercount. The treatment of nonresponse in 1991 and 2001 was substantially different. In 1991 a full adjustment was made by OPCS (1993) to published census counts for Districts through imputation of missing households, yet about 2 per cent were missed from the census output. In 2001 the One Number Census (ONC) intended to integrate a full estimation of nonresponse directly to the published census counts for all areas. However, quality assurance demonstrated that an extra nonresponse of about 0.5 per cent was missed in the census output affecting, in particular, 15 Districts where a better PART I: INTRODUCTION AND BACKGROUND 44 Chapter 2: Problems when analysing population change by ethnic group

estimate of population has been made (ONS, 2004b). Hence, the treatment of nonresponse between 1991 and 2001 is different, and because it also varies between areas and is differential between ethnic groups, consistent and complete treatment of nonresponse is necessary.

Ethnic identification and age group categories. Whilst the 2001 Census recorded 16 ethnic group categories, including the mixed categories, the 1991 Census included 10 ethnic group categories. This different recording of ethnic group categories on the census forms and changed categories used in the output with detail of age and sex make comparisons over time more difficult. Analyses of ethnic group stability over time using the ONS Longitudinal Study (LS) data showed that reliable comparisons can be made with the following groups: White, Indian, Pakistani, Bangladeshi and Chinese (Bosveld et al., 2006a; Simpson and Akinwale, 2006). Since the Black African and Black Caribbean groups displayed less stability between Censuses than the other main groups, comparisons can be made although with less reliability. The ‘Other’ ethnic groups of both 1991 and 2001 exhibit very low stability and, therefore, are not appropriate for comparisons. Classifications in which more groups are combined offer greater stability. Although changes to age group categories between 1991 and 2001 have less impact, an adjustment needs to be made for different age classifications used in census output, for example age 85 and over in 1991 and 90 and over in 2001 at Ward level.

Boundary harmonization. Since small geographies, and more specifically Wards and the smallest census areas, have been affected by many geographical boundary changes, harmonisation of these geographical areas is necessary. Here, the 2001 Census boundaries for Districts and Standard Table (ST) Wards and OAs are used as target geographies for comparisons.

Therefore, although the 1991 and 2001 Censuses have fulfilled one of the principal requirements to compare populations over time and space, a number of standard but difficult problems of data harmonisation over time including changing geography, changing census nonresponse and changing PART I: INTRODUCTION AND BACKGROUND 45 Chapter 2: Problems when analysing population change by ethnic group

variable definitions need to be taken into account. Providing a framework to solve these problems when comparing ethnic group populations across time and space for Districts and smaller areas (Wards and OAs) in England and Wales constitutes the most significant part of this research.

2.3: Population definition: the enumeration of students and timing

2.3.1: The enumeration of students

In 1991, the census enumerated students at their vacation address. Since it was acknowledged that a great majority of students are resident in halls of residence or in private accommodation during termtime, the 2001 Census enumerated fulltime students and schoolchildren at their termtime address. In addition, the 1991 Census was conducted during holiday time, which has proven to be a major factor of uncertainty over completion of the census, resulting in some students being missed completely (Thorogood and Codd, 1997).

From this perspective, the importance of the location of students from their parental address to their termtime address has been acknowledged as a fundamental issue for comparisons over time (Mitchell et al., 2002). Furthermore, updates of the 1991 Census of small area population estimates in Britain have shown that although the net effect of transferring students to termtime address is small, ‘the gross number of students in their teens and early twenties who moved from one District to another is of the same order as underenumeration at those ages’ (Simpson et al., 1997: 31).

Students are one of the three particular groups (others are the institutional populations and armed forces and their dependants), which are given special attention by producers of local statistics, as areas with many students are hard to estimate accurately, and especially ages 1524, which are particularly affected (Lunn et al., 1998). Therefore, such areas need an adjustment to avoid large estimation inaccuracies. PART I: INTRODUCTION AND BACKGROUND 46 Chapter 2: Problems when analysing population change by ethnic group

Taking into consideration the differences in the population definition between the 1991 and 2001 Censuses regarding the enumeration of students, students enumerated at their vacation address in 1991 need to be transferred to their termtime address to produce meaningful analyses of population change for subnational areas.

In this respect, the EwC project produced an adjustment for students to the published census output with detail of age and sex (Simpson et al., 1997). This adjustment comprised a transfer of students from their home address to their termtime address, and which was based on two steps: (1) removing students from their home District, if their termtime District was different; (2) adding students to their termtime District, if their home District was different.

A transfer of students directly from one address to another was not possible from census output. However, the number of resident students counted by the census at a vacation address which was not their termtime address was used as a proxy of the number of students who needed to be removed from an area for the population estimates. In the same way, the number of student visitors at their termtime address was used as an indicator of the number of students who were added to that area.

Table 2.2 shows the indicators used to distribute students and school boarders from their vacation address (normally their parents address) to their termtime address in local areas. The EwC project used information from the 1991 Census of the number of students whose vacation address was in a different District from their termtime address, to allocate students at their termtime address to Wards and Enumeration Districts (EDs) within each District. There remains on EwC outputs the net adjustment for each Ward and ED, by age and sex produced consistently with the information from OPCS of the number of students whose vacation address was in a different District from their termtime address (Simpson et al., 1997).

PART I: INTRODUCTION AND BACKGROUND 47 Chapter 2: Problems when analysing population change by ethnic group

Table 2.2: Student adjustments to small area counts by EwC

Adjustment Indicator used to distribute the District adjustment to local areas

Students removed from Student residents with term time address elsewhere, from their home address area census table S10. Separately for those aged under 18 and because they study 18+, sex disaggregated according to table S37. elsewhere

Student nonresidents with term time address at this address, from census table S10. Separately for those ages 15–17 and 18+, sex disaggregated according to table S37. Students added to their termtime address area For those aged under 15, often boarding pupils in preparatory schools. The number of visitors in educational establishments minus the number of student visitors aged 16+, so long as the number of visitors aged 5–14 is 5 or more. Uses tables S03, S10, S02 and S11.

Source: Adapted from Simpson et al. (1997: 32).

Table 2.3 shows how the largest net gains were to university Districts and the largest net losses were to nonUniversity Districts. The table also shows how there were considerable transfers without a large net change. In general, over half the students transferred to a termtime address from a different District vacation address are aged 2024 and another fifth are aged 1819.

PART I: INTRODUCTION AND BACKGROUND 48 Chapter 2: Problems when analysing population change by ethnic group

Table 2.3: Largest net gains and largest net losses of students

District name Added Removed Net transfer

Largest net gains

OXFORD 15,611 1,073 14,538

MANCHESTER 15,282 1,246 14,036

Largest net losses

WIRRAL 346 2,988 2,642

STOCKPORT 197 2,359 2,162

Largest total flows with net change less than 1000

KENSINGTON AND CHELSEA 3,368 2,548 820 KIRKLEES 3,066 2,446 620

2.3.2: Students: pending issues and perspectives

The strategy used by the EwC project has been acknowledged as a practical procedure to transfer students from their vacation address to their termtime address. However, the student adjustment did not incorporate information on ethnic groups (Simpson, 2002a). The lack of data to identify the ethnic group composition of students studying in a different District from their census vacation address directly restricted the sharing of flows of students into and out of each District to each 1991 ethnic group.

In order to overcome this issue, the doctoral research uses information from the 1991 Samples of Anonymised Records (SARs), which has a variable with an ethnic breakdown showing whether the termtime address of students was the same as vacation address or a different address, in the same or different region, and not known.

Table 2.4 gives this information for students aged 2024. These figures are very similar for age 1824 although these include school students aged 18. The results show how the great majority of students reside at their termtime address. They also show how the ethnic composition of students whose PART I: INTRODUCTION AND BACKGROUND 49 Chapter 2: Problems when analysing population change by ethnic group

termtime address was the same as the vacation address is noticeably less White. This would highlight the idea that ethnic minority students are more likely than others to live at home. Generally it can be noted that the ethnic composition of those studying away from their vacation address is more similar to the ethnic composition of the population as a whole. This evidence suggests that the removal of students from the 1991 population should take into consideration the ethnic composition of residents of the same age. Since this approach is unlikely to apply to the addition of students, which also includes overseas students, the ethnic composition of students at termtime address from the 2001 Census is used.

Table 2.4: Percentage distribution between ethnic groups of those aged 20-24

Ethnic group Population Termtime address of students 16 categories Same as vacation Not vacation address address 1 White 93.1 85.8 93.8 2 Black Caribbean 1.1 1.1 0.3 3 Black African 0.5 1.3 0.3 4 Black Other 0.4 0.5 0.2 5 Indian 1.8 3.8 2.6 6 Pakistani 1.1 2.1 0.6 7 Bangladeshi 0.3 0.4 0.2 8 Chinese 0.5 2.0 0.7 9 Asian Other 0.5 1.6 0.4 10 Other Other 0.7 1.3 0.8 Total 121,820 16,642 7,076

Source: 1991 SARs.

A full description of the method to transfer students from vacation to term time address is provided in Chapter 8. The approach incorporates an ethnic group dimension to the student transfer for Districts, Wards and OAs as defined in the 2001 Census. PART I: INTRODUCTION AND BACKGROUND 50 Chapter 2: Problems when analysing population change by ethnic group

2.3.3: Timing transfer (from Census day to mid-year)

Although it has much smaller impact for most areas, the other issue that requires attention within the population definition is timing. The timing adjustment is the sum of demographic change (the excess of births over deaths plus net migration) and the effect of ageing between Census day and midyear.

Since the reference date for collection of information for the 2001 Census was the 29th of April and for the 1991 Census was the 21st of April, and since demographic change may be different in each year, comparability between these two censuses is affected unless a timing transfer is applied. The timing transfer to midyear is important because it would be misleading to relate changes to different Census days. In addition, it allows the creation of the most convenient approximation to the population at risk, as midyear is assumed to be the point by which half the annual demographic events have occurred (Rowland, 2003).

Figure 2.1 shows a common routine to adjust for this difference by accounting for the demographic change and the effect of ageing between Census day and midyear (30th June). This approach is based on a cohort component model, where P(t) is the population at the start of the period (i.e. Census day) and P(t+1/6) refers to the population at the end of the period (i.e. midyear). The components of demographic change and ageing are applied for about ten weeks in 1991 and nine weeks in 2001. For the calculations, this would basically mean that all survivors are one sixth of a year older approximately. This procedure allows the creation of standard mid year estimates, thus being comparable with the Registrar General’s annual population estimates (ONS, 2002a).

PART I: INTRODUCTION AND BACKGROUND 51 Chapter 2: Problems when analysing population change by ethnic group

Figure 2.1: The timing transfer from Census day to mid-year using a cohort component model

P(t91) = 1991 P(t91+1/6) = 1991 Census day Mid-year (21st April) (30th June)

P(t) + (B – D) + (Min – Mout) + (I – E) = P(t+1/6)

P(t) = Population at the start of the period B = Births; and D = Deaths (natural change) Min = In-migration; and Mout = Out-migration (internal migration) I = Immigration; and E = Emigration (international migration) P(t+1/6) = Population at the end of the period

P(t01) = 2001 P(t01+1/6) = 2001 Census day Mid-year st th (21 April) (30 June)

2.3.4: Timing: pending issues and perspectives

The EwC project used information on births, deaths and migration to produce a 1991 timing adjustment with an agesex structure for each District in England and Wales. In addition, a timing adjustment was also derived for EDs and Wards within each District pro rata to the number of residents in each small area by age and sex counted in the census (Simpson et al., 1997).

Although no revisions are to be made to the 1991 timing adjustment as it is still assumed to apply, an adjustment taking into account intercensal boundary changes is necessary to make 1991 data consistent with the 2001 Census boundary definitions (Norman, et al., 2007). This task is undertaken in Chapter 7 when producing consistent mid1991 population estimates by age and sex for each 2001 District, Ward and OA in England and Wales.

Additionally, since the available 1991 Census data do not include timing with an ethnic group dimension, an appropriate allowance subsumed in the PART I: INTRODUCTION AND BACKGROUND 52 Chapter 2: Problems when analysing population change by ethnic group

revision to nonresponse is incorporated. This task is carried out in Chapter 9 when producing consistent mid1991 population estimates by age, sex and ethnic group for each 2001 District, Ward and OA in England and Wales.

Since data from the 2001 Census also requires a timing adjustment, data of births, deaths and net migration should be applied to the starting population. For this purpose, data from ONS experimental statistics, containing a commissioned table of 2001 Census counts and data of the components of change modelled by single year of age, sex and ethnic group for each District in England, are used (Large and Ghosh, 2006).

Subsequently, a cohort component model is applied, through which the starting population (2001 Census counts) is rolled forward to midyear (30th June) taking into account each component of population change and ageing. In addition, it should be noted that ONS subtracted special populations (members of the armed forces, prisoners and pupils in boarding schools) from the midyear population estimates before applying the components of change and ageing the population (Large and Ghosh, 2006: 2). Therefore, these groups are not agedon with the rest of the population as they have specific age structures which remain fairly constant over time.

The use of 2001 Census counts and components of change, constrained to the mid2001 population estimates is undertaken in Chapter 4 to derive consistent mid2001 population estimates by age, sex and ethnic group for each 2001 District in England. For this purpose, information from the cohort component model from ONS for Districts in England is used (Large and Ghosh, 2006). The timing adjustment for Unitary Authorities (UA) in Wales is subsumed in the revision of extra nonresponse not included in the 2001 Census output, in the light of the latest available data post2001 Census. Since information on the components of change from ONS is not available for smaller areas, a method is developed where the timing adjustment is allocated in line with extra nonresponse.

PART I: INTRODUCTION AND BACKGROUND 53 Chapter 2: Problems when analysing population change by ethnic group

2.4: The treatment of non-response

2.4.1: Adjustments for non-response in 1991

No census is perfect and some people are missed. Census nonresponse, also known as census undercount or undercoverage, refers to the difference between the census count and its true size (Simpson and Middleton, 1997). Whilst the impact of nonresponse on the population total can be small, the effects of differential nonresponse can be significant. It is assumed that if nonresponse was uniform by geography and subgroups of the population and households then it could effectively be ignored. But census response rates are not constant across areas or between groups of the population and, therefore, appropriate measures are needed to obtain an estimate of the complete population (Holt et al., 2001).

In 1991, census nonresponse in England and Wales was about 2 per cent (OPCS, 1993). The initial estimate of people not covered by the census included the following: (1) people living in private households that were wholly absent at the time of the Census but later returned a form voluntarily; (2) households that were known to exist but did not return the census household form; and (3) communal establishments such as hotels, prisons and halls of residence (Heady et al., 1994: 3). This resulted in some 2 per cent missed but imputed (households that were missed altogether in the census).

Further research comparing the numbers expected from the 1981 Census and adding births, deaths and international migration (i.e. demographic change) for the intervening years demonstrated that a gap of nearly a million people were missed by the census, half of them in their twenties and early thirties (Simpson and Dorling, 1994).

The 1991 nonresponse adjustments made by the OPCS to the census counts generated several different population counts for the 1991 Census (OPCS, 1994a and 1994b), including the published census and census counts updated according to the Census Validation Survey (CVS). However, PART I: INTRODUCTION AND BACKGROUND 54 Chapter 2: Problems when analysing population change by ethnic group

concerns were raised from both academics and those working in local government that the CVS did not indicate any geographical variation of non response (Heady et al., 1994). This issue was considered unsatisfying for the user community, and it was recognised to jeopardise estimates of population characteristics in those areas of high nonresponse (Holt et al., 2001; Simpson and Dorling, 1994; Simpson, 1994).

Table 2.5 gives an account of the OPCS adjustments of nonresponse to derive mid1991 population estimates. More detailed information about these adjustments can be found in other relevant literature (OPCS, 1993; Heady et al., 1994; Simpson and Dorling, 1994; Thompson, 1995; Tye, 1995).

Table 2.5: OPCS non-response adjustments to derive mid-1991 population estimates

(1) Adjustments from the Census Validation Survey, including people missed or mis classified dwellings or missed from households that did respond.

(2) Enhancements of the census count of infants using data from birth and death registration and migration indicators.

(3) Enhancement of the census count of armed forces using Ministry of Defence data.

(4) Modification of census count of elderly residents using pensioner data from Department of Social Security.

Following the OPCS adjustments of nonresponse, the EwC project used the OPCS 1991 District midyear population estimates and applied three non response adjustments to derive 1991 midyear population estimates for smaller areas (the EWCPOP estimates). These adjustments were made by age, sex as follows: (1) modification adjustment; (2) armed forces adjustment; and (3) residual nonresponse adjustment.

The census modification adjustment was applied due to the fact that the published small area census counts did not sum to the District census count as a result of confidentiality measures in place for areas smaller than PART I: INTRODUCTION AND BACKGROUND 55 Chapter 2: Problems when analysing population change by ethnic group

Districts, as it is widely accepted that geographical detail is a key factor in identifying individuals (Marsh, 1993).

The armed forces adjustment was taken from the OPCS adjustment for each District, based on numbers of armed forces from the Defence Analytical Services Agency (DASA) by sex stationed at each base in England and Wales. According to Simpson et al. (1997: 33) ‘the armed forces on bases were more likely to be omitted from census counts than armed forces personnel in accommodation outside bases’. As a consequence, the EwC project made a distinction for Districts whose armed forces nonresponse was more than 15 per cent, and allocated the excess above 15 per cent only in Districts with defence establishments within them. Subsequently, the EwC allocated the OPCS armed forces adjustment to Wards on the basis of the number of armed forces in a Ward using a census Ward distribution.

The residual nonresponse adjustment was distributed to Wards on the basis of two indicators of nonresponse, imputed residents and unemployed males aged 20 to 34. It was considered that the number of imputed residents was a good indicator of the difficulty in enumerating people; the number of unemployed males 2034 was felt to be appropriate as an indication of the socioeconomic condition of areas with higher levels of nonresponse.

Each adjustment was defined using Small Area Statistics (SAS), thus allowing the creation of mid1991 population estimates with adjustments for each ED in England and Wales. The process of the EwC project in producing population estimates for electoral Wards in England and Wales and postal sectors in Scotland, reviewed and evaluated methods used in Britain, which allowed the development of plausible and accepted methods (Simpson et al., 1997). As the OPCS District adjustments were accepted by central and local government, the EwC ‘Gold Standard’ estimates were constrained to the final OPCS revised mid1991 population estimates (OPCS, 1993).

The EwC project also produced estimates of nonresponse for each ethnic group (SOCPOP) for Wards. These estimates were produced consistently PART I: INTRODUCTION AND BACKGROUND 56 Chapter 2: Problems when analysing population change by ethnic group

with the EWCPOP. The SOCPOP estimates allocated nonresponse using plausible differentials of nonresponse for each ethnic group, using consistent evidence from the UK and other countries that ethnic minority groups, unemployed, and those renting private accommodation are most likely to be missed from the Census (Simpson and Middleton, 1997).

Following the revision of the initial nonresponse allowance included in SOCPOP data, in the light of the latest available data post2001 Census, a revised adjustment of census nonresponse by ethnic group consistent and comparable with the time series of revised official subnational estimates has been derived as part of this doctoral research. The methods used to update the previous estimate of nonresponse are shown in Chapters 7 and 9.

Figure 2.2: Percentage of revised non-response not included within the 1991 Census output by ethnic group in England and Wales

0.0 5.0 10.0 15.0 20.0 25.0

1 White

2 Black Caribbean

3 Black African

4 Black Other

5 Indian

6 Pakistani

7 Bangladeshi

8 Chinese

9 Asian Other

10 Other

Total

PART I: INTRODUCTION AND BACKGROUND 57 Chapter 2: Problems when analysing population change by ethnic group

Figure 2.2 shows the percentage of revised nonresponse after taking into account the latest mid1991 population estimates post2001 Census. The figure highlights the size of nonresponse not included within the 1991 Census output by ethnic group in England and Wales as estimated in this doctoral research. It illustrates how overall the downward revision of non response not estimated within census output was 1.6 per cent in 1991. It also shows how the highest percentages of nonresponse are found among ethnic groups other than White. In general, all ethnic minority groups have a census nonresponse higher than 5 per cent, with three ethnic groups with percentages of more than 10 per cent: the Black Other, the Black African and the Black Caribbean groups.

2.4.2: Adjustments for non-response in 2001

The increased difficulties in conducting censuses in the UK and evidence from other countries (Simpson and Middleton, 1997), showed that in order to estimate the whole population, new initiatives needed to be undertaken (ONS, 2001a). It was also proven that encouraging people to post back their census forms, by making the census forms easier to complete, and more publicity and awareness of the importance of the census were not sufficient measures. The decline in response rates was expected, in conjunction with those observed in other countries (ONS, 2003b). Therefore, following the problems encountered with nonresponse in the 1991 Census, new measures aimed to achieve maximum coverage and that the differential nature of any nonresponse was reduced (Thorogood and Codd, 1997).

Within this context, 2001 Census nonresponse in England and Wales was about 4 per cent, thus 2 per cent higher than in 1991. However, this time coverage of the census was 100 per cent as a result of adopting a new strategy known as the One Number Census (ONC). The ONC was based on the traditional census and a sample reenumeration (the Census Coverage Survey, CCS), so rather than relying on a single enumeration there were two operations to derive census estimates. This allowed an estimation of 4 per cent of the population living in households from whom no completed census PART I: INTRODUCTION AND BACKGROUND 58 Chapter 2: Problems when analysing population change by ethnic group

form was returned and whose characteristics were constructed using statistical techniques.

Within the ONC approach, the primary source in estimating the level of non response was the CCS, which was notably different from the CVS undertaken following the 1991 Census. Whilst the CVS relied on a relatively small sample size due to the costs involved in measuring data quality to make adjustments for underenumeration at District level, the CCS increased sample size to provide more accurate estimates to be made for smaller areas (ONS, 2001a). According to ONS (1995), it became clear that ‘a post enumeration survey was the most effective approach, but that the survey would need to be redesigned and larger than used in 1991’.

The CCS consisted of an independent face to face survey of a sample (of over 16,000 postcodes containing 320,000 households in England and Wales) which allowed the estimation of the number and characteristics of nonrespondents. The result was an expanded census database including records representing nonrespondents, thus representing an estimate of the full population (Pereira, 2002).

One of the main advantages of the ONC is that census nonresponse was directly included within the census output. As a result, the Local Government Association (LGA) recommended that local authorities should use the detailed census results as published, because the addition of the estimated census nonresponse makes the census much less biased than it would have been without incorporating this adjustment directly to census output (Simpson et al., 2003).

Nonetheless, the ONC has not removed concerns about the estimation of nonresponse in some specific areas (Simpson et al., 2003), particularly: (1) areas of transient population (students, armed forces, seasonal labour, recent migration, and inner city multipleoccupied dwellings); (2) areas with low response rates; and (3) the inability to fully disentangle estimates of migration and estimates of nonresponse. PART I: INTRODUCTION AND BACKGROUND 59 Chapter 2: Problems when analysing population change by ethnic group

Although there is a general view from both the Statistics Commission (2003) and the LGA (Simpson et al., 2003) that no alternative approach would have produced more reliable results overall, further studies and adjusments were applied. Midyear estimates derived from the ONC figure of 52.0m published in November 2002 were revised after ONS concluded that undercount had been underestimated by the ONC. Quality assurance continued for a further two years, culminating in a figure of 52.4m for England and Wales published in September 2004 (ONS, 2004b).

Table 2.6: ONS extra non-response adjustments to derive mid-2001 population estimates

(a) Longitudinal Study adjustment, which added 187,100 to the ONC population of England and Wales across 68 Districts. Later, the Consequential adjustment reduced the size of this adjustment to 164,000. Indicators used: (1) Demographic analysis of sex ratios, fertility and mortality.

(b) Local Authority Studies adjustment, which added 107,600 to the ONC population of 15 Districts. Indicators used: (1) Percentage reduction in population between the original 2001 and revised mid2001 population estimates. (2) Census response rates. (3) Comparisons with administrative sources (e.g. Council Tax, Electorate Roll, Patient Registers). (4) Factors associated with difficulty of enumeration, including the number of vacant properties and proportion of multioccupied addresses.

(c) The Manchester and Westminster Matching Studies (as part Local Authority Studies adjustment), which added 26,200 to the ONC population of Manchester and 17,500 to the ONC population of Westminster. Indicators used: (1) Discrepancies between the administrative address lists from City Councils and the address lists collated by ONS for the 2001 Census.

Table 2.6 shows the adjustments for extra nonresponse to derive mid2001 population estimates. The allowance for extra nonresponse included: (a) the Longitudinal Study adjustment, which corrected for underenumeartion of (mostly) males aged 2549; (b) the Local Authorities Studies adjustment, which concluded that in 15 Districts in England the census based population estimates could be at risk as a result of high nonresponse indicators in local PART I: INTRODUCTION AND BACKGROUND 60 Chapter 2: Problems when analysing population change by ethnic group

areas; and (c) the Manchester and Westminster Matching Studies, which investigated potential discrepancies derived from different address lists which resulted in large population differences between the census results and the midyear estimates (ONS, 2004b).

Table 2.7 shows the total size of the Local Authority Studies adjustment (107,600) and the contribution of this adjustment by Districts. The revisions were confined to 15 Districts, including Manchester and Westminster.

Table 2.7: The size of the Local Authority Studies adjustment

Local Authority Adjustment Bristol 6,700 Cardiff 3,000 Derby 7,800 Hartlepool 1,500 Kingston upon Hull 6,600 Manchester 26,200 Middlesborough 5,800 Milton Keynes 3,800 Newcastle upon Tyne 5,300 Southwark 6,600 StocktononTees 5,200 Sunderland 3,800 Wandsworth 5,000 Westminster 17,500 Wirral 2,800 Total 107,600

The three adjustments have provided a better estimate of the population for hardtocount areas, and the results have been included in the mid2001 population estimates. However, the census output has not been revised following the publication of these adjustments, which is likely to affect some areas more than others, thus making the mid2001 population estimates the best source of population estimates.

In recognition of the different nonresponse rates between areas and subgroups of the population, the 2001 Census was the first time in which different measures were put in place to reduce bias in the results caused by PART I: INTRODUCTION AND BACKGROUND 61 Chapter 2: Problems when analysing population change by ethnic group

any differences between characteristics of respondents and non respondents. In this respect, the CCS gave special attention to a Hardto Count (HtC) index, and a series of variables which were associated with non response such as multioccupancy, unemployment, language difficulty, private rented accommodation, number of households imputed and ethnic group.

Following the allocation of extra nonresponse, in the light of the latest available data post2001 Census, an adjustment of census nonresponse by ethnic group consistent and comparable with the time series of revised official subnational estimates has been derived as part of this doctoral research. The methods used to update the previous estimate of non response are shown in Chapter 4.

Figure 2.3: Percentage of extra non-response not estimated within the 2001 Census output by ethnic group in England and Wales

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

1 White British

2 WhiteIrish

3 Other White

4 Mixed White / Caribbean

5 Mixed White / African

6 Mixed White / Asian

7 Other Mixed

8 Indian

9 Pakistani

10 Bangladeshi

11 Other Asian

12 Black Caribbean

13 Black African

14 Other Black

15 Chinese

16 Other

Total

PART I: INTRODUCTION AND BACKGROUND 62 Chapter 2: Problems when analysing population change by ethnic group

Figure 2.3 shows the percentage of extra nonresponse not included within the 2001 Census output by ethnic group in England and Wales as published by ONS (Large and Ghosh, 2006). It illustrates how the overall nonresponse not estimated within census output was 0.5 per cent in 2001. It also provides evidence of the differential nonresponse by ethnic group with percentages generally higher among ethnic groups other than White. For example, the Black African, the Chinese, the Bangladeshi, the Black Caribbean and the Pakistani groups show percentages of total extra nonresponse between 2 and 3.5 per cent.

2.4.3: Non-response: pending issues and perspectives

As shown in the two previous sections, every time a census is held, numerous initiatives are put in place to ensure that everyone is counted. However, no census is perfect and some people are missed. The treatment of nonresponse is one of the strategic aims and key research areas in England and Wales official statistics (ONS, 2004e). In terms of resource allocation, it is considered to be a fundamental issue as the population missed by the census can be those which attract higher levels of funding. Thus, when census counts are not adjusted by applying nonresponse rates, monies may be wrongly allocated.

The publication of the 2001 Census results created a new base for the population estimates, meaning that population time series need to be revised so as to be consistent with both the past and the most recent census (Duncan et al., 2002). Figure 2.4 gives evidence of the impact of complete mid2001 population estimates on the original estimates of nonresponse by fiveyear age group and sex in England and Wales. The graph clearly shows how the revised nonresponse (without an ethnic group dimension) is subjected to a downward revision after the publication of revised mid1991 population estimates. As expected, the greatest downward revisions have special impact on males in their twenties and early thirties (ONS, 2002b).

PART I: INTRODUCTION AND BACKGROUND 63 Chapter 2: Problems when analysing population change by ethnic group

Figure 2.4: 1991 original and revised non-response after the 2001 Census by age and sex in England and Wales

The use of population estimates from complete mid1991 population estimates should therefore allow a revision of previous estimates of non response. As the revised ONS estimates of 1991 for subnational areas are only available down to Districts, rescaling previous population estimates for smaller areas (Wards and EDs) is necessary.

Although a simple solution would be to apply an ‘evenspread’ to distribute the difference between census and midyear estimates for a District across constituent smaller areas pro rata to the original census count, this approach is inappropriate because: (1) students and armed forces are locally concentrated; (2) nonresponse is concentrated in certain population sub PART I: INTRODUCTION AND BACKGROUND 64 Chapter 2: Problems when analysing population change by ethnic group

groups (e.g. young adult men); and (3) response rates vary according to the difficulty of enumeration of each subDistrict area (Norman et al., 2007).

The strategies used to overcome these issues for areas smaller than Districts are explained in Chapters 7 and 9 when revising 1991 population estimates by age, sex and ethnic group using data from the EwC project and revised mid1991 population estimates for Districts.

The use of population estimates from complete mid2001 population estimates should also allow the allocation of extra nonresponse not included in census outputs. For this purpose, two different strategies are tested: (1) allocating extra nonresponse taking the characteristics of the population of each District by age and sex as whole, without ethnic group differentials; (2) allocating extra nonresponse using differential nonresponse rates by age, sex and ethnic group for each District in England and Wales. In other words, the first strategy consists of allocating extra nonresponse as published by ONS experimental statistics (Large and Ghosh, 2006); and the second strategy is based on using ONS imputation rates to allocate the same extra nonresponse.

In addition, since complete mid2001 population estimates are not available for the smallest census areas, a strategy is implemented in Chapter 6 to disaggregate information from complete Ward mid2001 population estimates to OAs.

2.5: Ethnic identification

2.5.1: Defining ethnicity

The concept of ethnic identity is subjective and situational, subject to different factors and no less discussion. In fact, there is no consensus on what constitutes an 'ethnic group', and generally the factors (i.e. defining aspects) used to describe an ethnic group can change significantly over time (Coleman and Salt, 1996; Bulmer, 1996; Ballard, 1996; Solomos and Back, PART I: INTRODUCTION AND BACKGROUND 65 Chapter 2: Problems when analysing population change by ethnic group

1996). Some of these defining aspects are: country of birth, nationality, language spoken at home, parents’ country of birth in conjunction with country of birth, skin colour, national or geographical origin, racial group and religion. In some ways, ethnicity can be considered as a multifaceted phenomenon based on physical appearance, subjective identification, cultural and religious affiliation as well as social exclusion (Modood et al., 1997).

The ethnicity question in the UK Census is based on a combination of factors such as race, skin colour, national and regional origins and language. As such, the ethnic group classification reflects a juxtaposition of categories of colour (e.g. White, Black), nationality (e.g. British, African, Asian), as well as combinations of these aspects (e.g. White British) and the growing ethnic diversity (e.g. Mixed categories). The Race Relations legislation is motivated by political advocacy of racial equality, taking into account many of these factors (Aspinall, 2000; Coleman and Salt, 1996).

It is because of this complexity of factors defining the meaning of an ethnic group that collecting data on ethnicity is a challenge. In addition, since ethnic group may vary between people and over time, this represents adding an extra challenge to measurement (Simpson and Akinwale, 2006). Some of the aspects affecting comparability of ethnic groups using data from the 1991 and 2001 Censuses are discussed in the next sections.

2.5.2: Changing ethnic group categories

When checking how questions about one topic have been asked in successive censuses, a crucial step is to find out whether continuity on the chosen topic exists. Generally, ‘there is an inherent tension in the decisions over introducing new topics and dropping old ones, reflecting changing needs for information whilst retaining comparability with previous censuses’ (Dale and Marsh, 1993: 7). Within this context, one fundamental way in which the recording of an ethnic or racial category may vary is in relation to the social political construct designed for collecting data on ethnicity of broad PART I: INTRODUCTION AND BACKGROUND 66 Chapter 2: Problems when analysing population change by ethnic group

population groups, as ‘any ethnic group label is only valid for the period and context in which it is used’ (ONS, 2003c: 11).

In England and Wales, data with an ethnic group dimension from the 2001 Census are not directly comparable with those from the 1991 Census due, primarily, to the introduction of new choices on ethnicity (Bosveld et al., 2006a; Simpson and Akinwale, 2006; Platt et al., 2005). The differences in the number of categories recorded in 1991 (10) and 2001 (16) require compatibility between both Censuses (Simpson, 2002b). As in other countries where data on ethnicity are recorded, the question asked respondents to report the ethnic group they considered themselves to be, so questions were based on selfidentification.2

Table 2.8: Conversion of 1991 and 2001 ethnic group categories

2001 Census 2001 Census 1991 Census broad categories fine categories categories

White White British White White Irish White Other White White Mixed White and Black Caribbean Other Black White and Black African Other Black White and Asian Other Other Mixed Other Asian or Asian British Indian Indian Pakistani Pakistani Bangladeshi Bangladeshi Other Asian Other Asian Black or Black British Black Caribbean Black Caribbean Black African Black African Other Black Other Black Chinese or Other Ethnic Group Chinese Chinese Other Other

Source: Adapted from Simpson and Akinwale (2006).

2 Ethnic group questions as recorded in both censuses are included in Appendix 1 and 2. PART I: INTRODUCTION AND BACKGROUND 67 Chapter 2: Problems when analysing population change by ethnic group

Table 2.8 shows one suggested conversion table (Simpson and Akinwale, 2006) with full detail of the ethnic group categories used in the censuses in 1991 and 2001 in England and Wales. The conversion table displays some important differences for White and Mixed groups: (1) whilst in the 1991 Census there was only one category for all White respondents, in the 2001 Census the number of White categories was increased to three, with respondents having the possibility to choose between White British, White Irish and Any Other White background; and (2) whilst in the 1991 Census there was not a specific ‘mixed’ ethnic group category, in the 2001 Census four new ethnic group categories reflecting the main Mixed groups were included (White and Black Caribbean, White and Black African, White and Asian, and Any Other Mixed Background).

As a result of the changes in the classification of ethnic groups in the 1991 and 2001 Censuses, ONS provides four approaches for combining ethnic group categories in order to make more suitable comparisons between 1991 and 2001: (1) a tencategory classification; (2) an eightcategory classification; (3) a fivecategory classification; and (4) a twocategory classification (Bosveld et al., 2006a).

Table 2.9 illustrates one suggested tencategory classification by ONS (Bosveld et al., 2006b) producing new White, Other Black and Other Ethnicity groups in the presentation group. This classification includes the following conversion: (1) respondents identifying themselves in 2001 as White British, White Irish and Other White are amalgamated into a single category under the White label, thus allowing comparisons with the 1991 White group; (2) respondents identifying themselves in 2001 as Other Black, Mixed White and Black Caribbean, and Mixed White and Black African are combined into a single category under the Other Black label, thus allowing comparisons with the 1991 Other Black group; and (3) respondents identifying themselves in 2001 as Other Ethnicity, Mixed White and Asian and Other Mixed are combined into a single category under the Other Ethnicity label, thus allowing comparisons with the 1991 Other Ethnicity group. PART I: INTRODUCTION AND BACKGROUND 68 Chapter 2: Problems when analysing population change by ethnic group

Table 2.9: Example of ten-category classification

Presentation group 1991 Census categories 2001 Census categories

White White White British White Irish Other White

Indian Indian Indian Pakistani Pakistani Pakistani Bangladeshi Bangladeshi Bangladeshi Other Asian Other Asian Other Asian

Black Caribbean Black Caribbean Black Caribbean Black African Black African Black African Other Black Other Black Other Black Mixed White and Black Caribbean Mixed White and Black African

Chinese Chinese Chinese

Other Other Other Mixed White and Asian Other Mixed

Source: Adapted from Bosveld et al. (2006b).

Studies using a similar tencategory classification are various although the allocation of Mixed groups can be different, such as adding the 2001 category Mixed White and Asian to Asian Other. For example, the latter approach is used in Dorling and Rees (2003) to analyse the degree to which the population of Britain in 2001 has become more or less geographically polarised, as compared with 1991 and earlier censuses. Similarly, Thomas and Dorling (2004) analyse aspects of the human geography of the UK, such as the percentage of population change from 1991 to 2001 and the spatial distribution of ethnic groups using the same classification too. Other studies comparing ethnic change and diversity from 19812001 use common groups based on the 1991 classification, but present other alternatives within the ten category classification, where the Mixed group is split back into its constituent parentages and the Other group (Rees and Butt, 2003). In addition, this study creates ethnic group data for 1981 based on countryofbirth information. PART I: INTRODUCTION AND BACKGROUND 69 Chapter 2: Problems when analysing population change by ethnic group

Table 2.10: Example of eight-category classification

Presentation group 1991 Census categories 2001 Census categories

White White White British White Irish Other White

Indian Indian Indian Pakistani Pakistani Pakistani Bangladeshi Bangladeshi Bangladeshi

Black Caribbean Black Caribbean Black Caribbean Black African Black African Black African

Chinese Chinese Chinese

Other Other Asian Other Asian Other Black Other Black Other Mixed White and Black Caribbean Mixed White and Black African Mixed White and Asian Other Mixed Other

Source: Adapted from Bosveld et al. (2006b).

Table 2.10 illustrates another example of collapsing categories which results in an eightcategory classification as suggested by ONS (Bosveld et al., 2006b). This classification includes the following conversion: (1) respondents identifying themselves as White British, White Irish and Other White in 2001 are again amalgamated into the White label; (2) respondents identifying themselves in either census as Other Black, Other Asian and Other Ethnic group are included in the new Other category; (3) respondents identifying themselves with any of the Mixed ethnic groups are also included in the new Other category.

According to Simpson and Akinwale (2006), this classification is preferred to the tencategory classification when comparing ethnic groups between 1991 and 2001, as it is simpler and avoids the use of three residual groups poorly defined and unstable over time, thus making it more suitable for comparisons between 1991 and 2001. PART I: INTRODUCTION AND BACKGROUND 70 Chapter 2: Problems when analysing population change by ethnic group

Table 2.11: Example of five-category classification

Presentation group 1991 Census categories 2001 Census categories

White White White British White Irish Other White

Asian Indian Indian Pakistani Pakistani Bangladeshi Bangladeshi Mixed White and Asian

Black Black Caribbean Black Caribbean Black African Black African Other Black Other Black Mixed White and Black Caribbean Mixed White and Black African

Chinese Chinese Chinese

Other Other Other Other Asian Other Asian Other Mixed

Source: Adapted from Bosveld et al. (2006b).

Table 2.11 illustrates a different alternative which results in a fivecategory classification as suggested by ONS (Bosveld et al., 2006b), producing five main ethnic groups: White, Asian, Black, Chinese, and Other. This classification includes the following conversion: (1) as with the previous classifications, respondents identifying themselves as White British, White Irish and Other White in 2001 are again amalgamated into the White label; (2) respondents identifying themselves as Indian, Pakistani and Bangladeshi in either census and, Mixed White and Asian in 2001 are combined into the Asian label; (3) respondents identifying themselves with one of the three main Black groups (including Other Black) and, Mixed White and Black Caribbean and Mixed White and Black African in 2001 are amalgamated into the Black label; (4) respondents identifying themselves with any of the ‘Other’ group which includes Other Asian, Other Mixed Ethnicity and Other Ethnicity are combined under the Other label. It has to be noted that the Chinese PART I: INTRODUCTION AND BACKGROUND 71 Chapter 2: Problems when analysing population change by ethnic group

group is not combined with any other group, as happens with the other classifications presented above.

Table 2.12: Example of two-category classification

Presentation group 1991 Census categories 2001 Census categories

White White White British White Irish Other White

NonWhite Indian Indian Pakistani Pakistani Bangladeshi Bangladeshi Black Caribbean Black Caribbean Black African Black African Other Black Other Black Chinese Chinese Other Other Other Asian Other Asian Mixed White and Black Caribbean Mixed White and Black African Mixed White and Asian Other Mixed

Source: Adapted from Bosveld et al. (2006b).

Table 2.12 illustrates the simplest example of collapsing categories as suggested by ONS (Bosveld et al., 2006b) which results in a twocategory classification, producing a White category and a nonWhite category. This classification includes the following conversion: (1) respondents identifying themselves as White British, White Irish and Other White in 2001 are amalgamated under the White label; (2) respondents identifying themselves all other ethnic groups are combined under the NonWhite label.

In general, classifications which combine more groups offer more reliability, particularly as reporting ethnicity by the same individuals in two different time points can be different, which complicates the making of direct comparisons over time (Bosveld et al., 2006a; Simpson and Akinwale, 2006; Platt et al., 2005). This aspect is discussed in the next section with more detail. PART I: INTRODUCTION AND BACKGROUND 72 Chapter 2: Problems when analysing population change by ethnic group

The use of classifications combining categories also implies that some assumptions are made, for example that some individuals identify themselves in a way that can be very different from chosen in the census (Simpson, 2002b). In addition, by combining more groups detail of specific ethnic groups is lost. Therefore, adopting one or other classification depends on the balance between reliability and ethnic group detail.

The amalgamation of groups for specific analysis is unavoidable. For example, numbers in each of the individual ethnic minority groups are sometimes too small to analyse independently. Sometimes data need to be compared using a twocategory classification to investigate differences between White and nonWhite groups, for example for analysis of segregation and diversity of ethnic groups. However, it is understandable that combining across the main ethnic groups categories such as any of the Black and Asian respondents is not particularly sensible because it implies that any differences between these groups are removed by the amalgamation.

2.5.3: Changes to ethnic identification

As seen earlier, ethnicity is an aspect of identity which is subjective as well as based on biography and dependent on socioeconomic and political events. However, it is generally assumed that ethnicity is a stable feature for individuals throughout the life course (Blackwell, 2000, Modood et al., 1997).

Nonetheless, establishing the nature and extent of individual’s change in recorded ethnicity from one census to the next is a key issue when charting minority group processes over time. Studies aiming to estimate those self identifying in 2001 who would choose each of the 1991 categories and vice versa, have highlighted the usefulness of the ONS Longitudinal Study (LS) as an exceptional resource for exploring dynamic processes in individual lives. The LS was used to examine instability of ethnic identification between 1991 and 2001 (Bosveld et al., 2006a; Simpson and Akinwale, 2006; Platt et al., 2005). The method included all records linked between the two censuses, one per cent sample of the resident population of England and Wales across PART I: INTRODUCTION AND BACKGROUND 73 Chapter 2: Problems when analysing population change by ethnic group

a thirty year period (about 500,000 individuals, at each census since 1971), which allows quantification of the stability of responses to the ethnic group question between 1991 and 2001.

For this purpose, a transition matrix of members in 1991 and 2001 by ethnic group was constructed. This matrix made it possible to work out whether LS members responded with the same ethnic group label at both censuses. The results showed that some categories had higher proportions of individuals responding with the same ethnic group at both censuses than others. For example, the results confirmed that people recording their ethnicity as White, Chinese or with one of the South Asian groups in 1991 showed greater consistency than other groups in ethnic identification between the 1991 and 2001 Censuses. Generally, over 90 per cent of these groups in 1991 gave the same response in 2001, whilst one in four of Black Caribbeans and Black Africans gave a different response category in 2001 (Platt et al., 2005: 38).

This difference between 1991 Black Africans and Black Caribbeans in the probability of individuals changing their reported ethnicity to a different response category (mainly to a mixed White and Black category) may be associated with a greater probability of Black Caribbeans being in interethnic partnerships (Berrington, 1996; ONS, 2004d).

The greater instability among the residual categories is something to take into account when comparing ethnic groups between 1991 and 2001. Less than a third of the ethnic group categories in 1991 labelled ‘Other Black’, ‘Other Asian’ and ‘Other’ remained with the same label in 2001. Hence, for analyses of time series of these categories, the eightcategory classification is preferable, as residual categories do not contain a stable set of people from one census to the next.

Generally, the instability is impossible to avoid with changing ethnic group categories. In addition, changing questions offer respondents different possibilities over time, thus leading to different responses when asked the PART I: INTRODUCTION AND BACKGROUND 74 Chapter 2: Problems when analysing population change by ethnic group

same question on different occasions (Simpson and Akinwale, 2006). This aspect is discussed with more detail in the next section.

2.5.4: Changes to ethnic group answer categories

In 2001, the ethnic group question in England and Wales included the new categories White British, White Irish, Other White and Other Asian in addition to the four new Mixed ethnic group categories, consequently, sixteen categories were admitted. The inclusion of mixed groups in 2001 was a major change, which was recognised as relevant after undertaking fieldwork to determine a revised ethnic group question for the 2001 Census (ONS, 2003e).

The options of writein categories for ethnic groups were also different between 1991 and 2001. Whilst in the 1991 Census, respondents were given two writein categories (BlackOther and Any Other Ethnic Group), in the 2001 Census, this option was increased to five (Other White, Other Mixed, Other Black, Other Asian, and Any Other categories).

In 1991, one category, ‘Other Asian’, was created postcensus from answers provided in the writein boxes, thus providing a final classification of ten ethnic groups. In 2001, ‘Other Asian’ was included as an ethnic group category on the Census form.

In addition, the 2001 Census incorporated for the first time the use of sub headings to recognise the strong British identity of many Black and Asian people. Although the subheadings did not represent categories that respondents could tick, Black and Asian categories included the sub headings ‘Black or Black British’ and ‘Asian or Asian British’.

2.5.5: Target ethnic categories for thesis

The objective of this doctoral research is to maintain the ethnic group categories as recorded in 1991 and 2001 Censuses for the creation of consistent midyear population estimates and with detail of age and sex. This strategy will allow full flexibility in the subsequent amalgamation of ethnic PART I: INTRODUCTION AND BACKGROUND 75 Chapter 2: Problems when analysing population change by ethnic group

categories as shown earlier in the previous sections with the tencategory classification, the eightcategory classification and so forth.

The use of an eightcategory classification is implemented in Chapter 11 of this thesis to analyse population change between 1991 and 2001 by age, sex and ethnic group in the District of Birmingham and its constituent 2004 electoral Wards.

2.6: Age group categories

2.6.1: The aggregation of age in census statistics

Age categories in census statistics are generally derived from the date of birth question on the census questionnaire, which refers to the person’s last birthday. This procedure allows NSOs to provide population estimates with detail of single year of age for various purposes. For example, for actuarial analysis of the probability of survival and of related lifetable functions (UN, 1998a).

Additionally, NSOs also create other age groupings with a view to flexibility to other applications. This can be particularly relevant for the following groups: (1) with young children under age 5 to distinguish between those under one year of age (infants) and those aged 14; and (2) for youths aged 1519 to distinguish between those 1517 years of age and those 1819 years of age, or a similar distinction to allow the distinction between minor and adult population.

Within this context, the aggregation of single year ages within each of the fiveyear age groups in census statistics is a common procedure adopted by many NSOs. The fiveyear age groups are frequently used to analyse population change, for the preparation of current population estimates and of projections, the calculation of agespecific vital rates, analysis of labour supply and dependency ratios. PART I: INTRODUCTION AND BACKGROUND 76 Chapter 2: Problems when analysing population change by ethnic group

Generally, the census grouped age classifications are determined by the crossclassifications by other variables. As is shown in the next section with the 1991 and 2001 Censuses in England and Wales, the release of census data by broad age group is a general strategy when crossclassifications combine multiple dimensions such as age and ethnic group. This ensures that the risk of disclosure is small, as the fear of disclosing information about identifiable individuals is generally greater when census table cells refer to only a few people (Marsh, 1993).

This general strategy for ensuring the statistical confidentiality is stated in the Government’s March 1999 White Paper (Cm. 4253), with special precautions to statistical output for small areas ‘restricting the number of output categories into which a variable may be classified, such as aggregated age groups’ (White Paper, 1999: 29).

Although it represents a well established strategy, it is nonetheless subject to scrutiny as the aggregation of census statistics can always result in a lack in value of the published data, thus hampering data analysis or forcing a poor analysis on users of census data (Openshaw, 1994).

Three common issues arise from the aggregation of age:

• First, the choice of age group categories can vary over time. For example, the oldest age group has been for many years for those persons aged 85 and over, however, due to the increasing life expectancy and ageing populations, the latest release of census data is available for ages 8589 and 90 and over.

• Second, the detail for which age is released may not be the detail required for a study. Generally, census data users expect to obtain age detail for fine scaled geographies that are most appropriate to their own needs, however, what is desirable can go well beyond what NSOs provide. Here the most desirable solution is to have census data by single year of age to allow the user to custom make their own PART I: INTRODUCTION AND BACKGROUND 77 Chapter 2: Problems when analysing population change by ethnic group

age groups for comparisons over time and between different data sets.

• Third, the age groups can also differ from the same census output. This latter issue is generally subject to geographical constraints and is illustrated in Figure 2.5 through the inherent tension between detailed demographic data and detailed geographical scale. For example, age detail is generally released at national and regional levels in census area tables but census data are generally grouped for Districts and smaller areas. This is generally done because the number of resident persons is greater for larger areas, which means that the risk of disclosure is far smaller in these areas too.

Figure 2.5: The tension between demographic data and geographical scale

DETAILED DEMOGRAPHIC DATA BANDED DEMOGRAPHIC DETAIL

COARSE GEOGRAPHICAL SCALE DETAILED GEOGRAPHICAL SCALE

2.6.2: Age with an ethnic breakdown for small areas

The 1991 and 2001 Censuses released data by age and with an ethnic breakdown for small areas (Wards and 1991 EDs and 2001 OAs). 1991 Census data are available for each Ward in England and Wales by fiveyear age, sex and ethnic group as recorded in the 1991 Census through Local Base Statistics (LBS) with census table L06. 2001 Census data are also available for each Ward in England and Wales by fiveyear age, sex and ethnic group through a Standard Table with census table ST101.

PART I: INTRODUCTION AND BACKGROUND 78 Chapter 2: Problems when analysing population change by ethnic group

Table 2.13: Census age detail for males and females and with an ethnic breakdown for Wards

1991 2001 0 4 0 4 5 9 5 7 8 9 10 14 10 14 15 15 16 17 16 17 18 19 18 19 20 24 20 24 25 29 25 29 30 34 30 34 35 39 35 39 40 44 40 44 45 49 45 49 50 54 50 54 55 59 55 59 60 64 60 64 65 69 65 69 70 74 70 74 75 79 75 79 80 84 80 84 85 and over 85 89 90 and over

Although both census tables provide fiveyear age groups with an ethnic breakdown separately for males and females, there are some differences as a result of the extra age categories used in 1991 and 2001. Table 2.13 shows the census age detail for the 1991 Census table L06 with ages to 84 and 85 and over with extra breaks for those aged 15, 1617 and 1819, and for the 2001 Census table ST101 with ages to 89 and 90 and over with extra breaks at 57, 89, 15, 1617 and 1819.

1991 Census data were also published for each ED in England and Wales by age and with an ethnic breakdown through SAS with census table S02, but without sex detail and for five broad age groups. 2001 Census data are available for each OA in England and Wales by age and with an ethnic breakdown through CAS Theme Tables with census table CT003, but without sex detail and for seven broad age groups. Table 2.14 shows the census age PART I: INTRODUCTION AND BACKGROUND 79 Chapter 2: Problems when analysing population change by ethnic group

detail for the 1991 Census table SAS06 with ages to pensionable age and over, and for the 2001 Census table CT003 with ages to 75 and over.

Table 2.14: Census age detail with an ethnic breakdown without sex for 1991 Enumeration Districts and 2001 Output Areas

1991 2001 Age 0 4 Age 0 4 5 15 5 15 16 29 16 29 30 up to pensionable age 30 49 50 to pensionable age Pensionable age and over Pensionable age to 74 75 and over

2.6.3: Target age categories for the thesis

Although it is possible to provide fiveyear age group detail for Wards using appropriate 1991 and 2001 Census tables, the age detail for smaller areas (EDs and OAs) is only available by broad age group.

Chapters 5, 6, 7 and 9 show the use of a strategy to create single year of age separately for males and females with an ethnic breakdown for 1991 and 2001 midyear population estimates for Wards and OAs.

2.7: The harmonisation of geographical boundaries

2.7.1: Census geography

The census geography in the UK is far from simple and has undergone many changes in the last decade, particularly for subnational areas. Although these changes are well documented in specific literature (Norman et al., 2001; ONS, 2001b; Rees and Martin, 2002) it is advisable to have a good knowledge of the fundamental parts of the census geography. PART I: INTRODUCTION AND BACKGROUND 80 Chapter 2: Problems when analysing population change by ethnic group

The two forms directly associated with the census geography in the UK are EDs and OAs. In 1991, the EDs were the smallest units for output for the 1991 Census. These were initially used for both data collection and output, and their size and shape was designed for the requirements of data collection (Clark and Thomas, 1990). As a result, EDs were found to contain populations that fell below the confidentiality thresholds and so some EDs needed to be combined before the output data could be published (Martin, 1997, 1998b and 2000).

Since 2001, EDs are only used for data collection and OAs are used as the building bricks for Census data releases. For the 2001 Census, England and Wales had 116,895 EDs with an average population size of about 450 people (ONS, 2007). The majority of these EDs used in 2001 are different from their 1991 equivalents. The base unit for 2001 Census data releases in England and Wales, the OAs, were introduced in the 1991 Census in Scotland (Exeter et al., 2005). OAs are smaller than EDs, thus allowing a finer resolution of data analysis. In addition, they have been conceived to have similar population sizes (the minimum OA size is 100 resident persons) to ensure the confidentiality of data, and are designed to be as socially homogeneous as possible which can be of special significance in the context of local service planning and resource allocation (Martin, 2002). For the 2001 Census, there are 175,434 OAs in England (165,665) and Wales (9,769). The data from OAs can be aggregated to any level of spatial unit. The layers of the OA hierarchy relate to each other and to the electoral geography. At the top of the hierarchy are Local Authority Districts.

Figure 2.6 displays the ONS hierarchy of building block geographies, where OAs are the base unit for higher levels of aggregation. The 2001 Census geography with OAs makes available 2 layers of Super Output Areas (SOAs). The same figure shows both the range of different sizes of area at which data can be presented and how SOAs are mechanically formed. For example, the Lower Layer SOA are aggregations of OAs and the Middle Layer SOA are aggregations of Lower Layer SOAs. PART I: INTRODUCTION AND BACKGROUND 81 Chapter 2: Problems when analysing population change by ethnic group

Figure 2.6: The ONS 2001 Census hierarchy of building block geographies

Local Authority Districts or Unitary Authorities/London Boroughs (building up to higher area – counties, GORS, etc.)

Upper Layer SOAs minimum population around 25,000 whole scheme nests within LAs

Middle Layer SOAs 7,193 units will nest within Upper Layer minimum population 5,000 average population 7,200

Wards Lower Layer SOAs 34,378 units 8,800 units nest within Middle Layer minimum population 1,000 average population 6,000 average population 1,500

Output Areas and Lower Layer SOAs nest within Census ST Wards (January 2003) Output Areas 175,434 units (E&W) nest within Lower Layer minimum population 100 Ward boundary change will average population 300 progressively break the relationship target 125 households with Wards from Census 2001

Source records grid referenced allocated to higher - ideally from addresses units using NeSS tools

Source: Adapted from ONS (2005a).

NB: Although the figure includes the Upper Layer SOAs as planned, these were never created.

The geography of OAs was created with the aim of achieving maximum consistency with postal geography (Martin et al., 2002). In this respect, in England and Wales 2001 Census OAs are based on postcodes as at Census day and fit within the boundaries of 2003 electoral Wards. In England and Wales, the 2003 electoral Wards are identical to the Census Area Statistics (CAS) Wards used in the 2001 Census with the exception of 18 Wards with fewer than 100 person residents where aggregation to other Wards has been applied to avoid the confidentiality risks of releasing data for these small PART I: INTRODUCTION AND BACKGROUND 82 Chapter 2: Problems when analysing population change by ethnic group

areas. In England and Wales, there are 7,969 CAS Wards in England and 881 CAS Electoral Divisions (EDiv) in Wales in total.

Additionally, there are the Census ST Wards in England and ST Electoral Divisions in Wales, for which the 2001 Census Standard Tables are available. The ST Ward geography is a subset of CAS divisions in England and Wales to ensure confidentiality of data in the Standard Tables. For this procedure, a total of 113 statistical Wards were merged to produce the ST Wards. There are a total of 7,932 ST Wards in England and 868 ST Electoral Divisions in Wales (Wood, 2004).

The new 2001 Census geography based on OAs developed by ONS is to facilitate comparisons of small area statistics. For example via CASWEB (Martin et al., 1998; Harris et al., 2002b), 2001 aggregate statistics data sets for this geography and SOA are available at http://census.ac.uk/casweb/. The ONS development of Neighbourhood Statistics (NeSS) available at http://neighbourhood.statistics.gov.uk/dissemination/ is also a key electronic platform that allows census users to find detailed statistics with specific geographic areas such as Districts, Wards, OAs, SOAs. This avoids the complexity of dealing with electoral Wards, a wellestablished geography for presenting local statistical information but subject to frequent boundary changes (Martin, 1998a).

2.7.2: The electoral geography

The UK geography is said to have more administrative boundary change than the rest of Europe put together. For example, in 2002 the boundaries of 1,549 electoral Ward and divisions were changed in the UK (Martin, 2000).

The electoral geography in England and Wales is defined by the electoral Wards (England) and divisions (Wales), which constitute the spatial units used to elect local government councillors. They are also used to construct other geographies such as parliamentary constituencies, health authorities or the European Union classification of statistical administrative areas; Nomenclature of Units for Territorial Statistics (NUTS). Since electoral Wards PART I: INTRODUCTION AND BACKGROUND 83 Chapter 2: Problems when analysing population change by ethnic group

cover the whole of the UK, they have traditionally been an ideal base unit for collating and presenting statistics (ONS, 2001b).

Electoral Wards are frequently changed in order to ensure electoral equality so that each Ward in every District has a broadly equal representation in both local elections and local authority decision making (i.e. a similar councillor:elector ratio). Therefore, electoral Ward boundaries are under regular review and once agreed are usually enacted to coincide with the local government elections on the first Thursday in May each year (ONS, 2007). The Boundary Committee for England (BCFE) and the Boundary Commission for Wales (BCW) work with local authorities to make recommendations for change, which must be approved by the Electoral Commission, and finally specified in Statutory Instrument.

Since each British census is required to produce population data for each of the geographical units of the contemporary statutory geography, change in the electoral geography is one of the main processes that cause change in the census geography. As such, it represents a major influence on the geographical units for census organisation and publication and, consequently, a continuous challenge for intercensal analysis (Martin and Gascoigne, 1994).

Figure 2.7 shows an example of a hypothetical District with two Wards whose boundaries are rearranged to be as close as possible to the District average in response to population changes.

Electoral Wards are also affected by changes in the local government structure. For example, in the UK this was considerably altered during the last decade, particularly during the period 19951998, when the Local Government Commission for England (LGCE) –currently the BCFE and BCW reviewed the administrative structure of nonmetropolitan areas by both retaining the existing twotier structure in some areas and setting up a singletier of UAs (Unitary Authorities) in other areas. As a result, both the number of Wards changed and the electoral Ward geography was altered PART I: INTRODUCTION AND BACKGROUND 84 Chapter 2: Problems when analysing population change by ethnic group

significantly, thus making it necessary to use consistent geographical zones to compare Ward statistics (Rees et al., 2004).

Figure 2.7: Changing boundaries in electoral Wards

1. Ward A Ward B 2. Ward A Ward B 3. Ward A Ward B

1. Ward A and B have equal populations: electoral equality; 2. Ward B has a much higher population than Ward A: electoral inequality results (individuals in Ward B have far less councillor representation); 3. Ward A and B have equal populations: electoral equality is restored through boundary changes.

2.7.3: Consistent geographies

A fundamental issue for this research is to make the geographies comparable across time and space. For example, when making a temporal comparison of data from two censuses it is crucial to investigate whether the boundaries subject to the analysis have changed (ONS, 2001b). It is also important to see whether the association of census data with some other areal units is assembled from the same elemental units or is independently constructed (Martin, 2000).

Boundary changes over time and matching together data when the boundaries of the areal units are not coincident requires harmonisation of both the attribute data and the geography (Norris and Mounsey, 1983; Norman et al., 2001). Within the framework of this doctoral research, unless PART I: INTRODUCTION AND BACKGROUND 85 Chapter 2: Problems when analysing population change by ethnic group

a consistent geographical approach with time series data are taken, it is difficult to know whether changing trends are taking place or whether observed changes are simply an artefact of a boundary change. Different approaches are generally used in the UK to address the problem of harmonising time series data on a consistent geographical basis (Norman et al., 2001). Some of these approaches are:

Freeze history. A common approach is by fixing the geographical system at a point in time. This basically consists of ´freezing´ the geography, so that comparability of data for time series has to be adjusted to the original boundaries. For example, this approach has been adopted by EUROSTAT for monitoring population trends at the most detailed NUTS boundaries NUTS5, broadly corresponding to Wards (Blake et al., 2000). A disadvantage of this approach can be that the original boundaries can become unsuitable for applications which seek to be relevant to current administrative structures.

Update to contemporary zones. This approach consists of updating the data collected for a previous spatial system to a set of contemporary zones. This approach is widely used in the UK to create consistent geographies. Within this approach there are various ways of updating the geographical system: (1) remodelling the data to some underlying surfacebased representation (Bracken and Martin, 1995); (2) using areal interpolation techniques to achieve consistency of specific data sets (Goodchild et al., 1993); and (3) applying generic longterm solutions, also based on the mechanism of data interpolation, such as Geographical Conversion Tables (GCTs) (Simpson, 2002c; Simpson and Yu, 2003).

The main feature of surfacebased population representation is that data are modelled as a continuous field. Raster cell values are used as buildingbricks to be aggregated into userdefined zones. The main advantage of this approach is that it allows data aggregation to nearly any desired areal unit (Bracken, 1993). Although this does not enable one to avoid the Modifiable PART I: INTRODUCTION AND BACKGROUND 86 Chapter 2: Problems when analysing population change by ethnic group

Areal Unit Problem (MAUP), it provides a framework to see how far results are sensitive to the choice of scale and zones.

An application of this approach in the UK dealt with the problems involving the comparative analysis of data for the 1981 and 1991 Censuses (Bracken and Martin (1995). However, the potential of this approach is mainly valid during a census year when detailed and nationally consistent small area sociodemographic data become available and the UK population surface can be generated. In addition, the complexity of linking data certainly has a disadvantage in establishing a standard geography for comparisons over time (Norman et al., 2001).

The use of various areal interpolation techniques (Goodchild et al., 1993) can also be applied to the transformation of population data, areal weighting being the most common technique. In this approach, the size of the source and target zones is used to weight the values of the source in a GCT taking into account the area of overlap. The use of a GCT allows the link of building bricks from a previous geography to the current system (Wilson and Rees 1998, 1999). Although the use of Geographical Information Systems (GIS) can be used to highlight common boundaries in different years (Blake et al., 2000) for areal interpolation, it can be particularly demanding on relatively large study regions, as the necessary digital boundary sets must be available for all time points and geographies relevant to the research (Norman et al., 2003).

The use of more generic solutions such as GCTs for creating harmonised geographies (Simpson, 2002c; Simpson and Yu, 2003) has been used to convert data between different geographical systems (e.g. census and postal) and to harmonise time series on a consistent geographical basis. This approach is based on a proportional allocation in which a weight shows the proportion of the source geography that lies in the target geography unit. An advantage of this approach is that the summation of population data of the source geography is preserved in the transformation of the new target geography (Simpson, 2002c). For the application of this approach, a PART I: INTRODUCTION AND BACKGROUND 87 Chapter 2: Problems when analysing population change by ethnic group

geographical unit that comprises the source and target geography is necessary. The most common procedure to apply this method in the UK is to use postcode directories such as the National Statistics Postcode Directory (NSPD) with links to census and/or administrative geographies. By using postcodes, it is assumed that the residential postcode distribution is a reasonable proxy for population distribution (Norman et al., 2003).

The increasing availability of matching and conversion tools based on postcode directories simplifies this task. For example, GeoConvert which follows previous work in the same direction (Simpson and Yu, 2003) is a project that is being undertaken at the CDU (Census Dissemination Unit), MIMAS (Manchester Information and Associated Services), as part of the ESRC’s Census of Population Programme (http://www.census.ac.uk/).

Constructing designer zones. Another solution is to create designer zones from smaller buildingbricks by harmonising the zonal system based on boundaries that are common in different years. For example, in order to analyse interregional migration in Australia, Blake et al. (2000) generate designer zones by assembling small buildingbricks with coincident outer boundaries across a number of censuses. Other designer zones approaches include the use of algorithms to create a new set of areas to represent data from the 1991 Census in a customised way and not using administrative geographies (Openshaw and Rao, 1995). Constructing designer zones is complex and, as some of the previous work shows, the harmonised boundary solutions may not match current geography.

The approaches described above exemplify different ways of creating consistent geographies through which the problem of harmonising time series can be addressed on a consistent geographical basis. In practical terms, deciding which approach is more suitable to apply largely depends on which problem needs to tackled. For this doctoral research census data for two time points are available but not for the required geography for different comparisons. The use of GCTs with references to the source and target geographies and a weight to indicate the extent of overlap represents a PART I: INTRODUCTION AND BACKGROUND 88 Chapter 2: Problems when analysing population change by ethnic group

generic solution, as various projects have carried out the necessary work (Hayes, 2006; Norman, 2007a, 2007b; Simpson, 2007a, 2007b, 2007c).

2.7.4: The Modifiable Areal Unit Problem (MAUP)

The MAUP is recognised as the sensitivity of statistical results to the definition of areal units (Fotheringham and Wong, 1991) and it is recognised as an endemic problem to all spatially aggregated data, such as census data (Openshaw and Taylor, 1979; Fotheringham and Rogerson, 1993). The MAUP has been identified as a problem when using census data since the 1930s, when Gehlke and Biehl (1934) showed the tendency for correlation coefficients to increase as areal regions are aggregated into fewer numbers of larger regions.

Figure 2.8: The two interrelated parts of the MAUP

A. n = 8 m = 8 B. n = 8 m = 4 C. n = 8 m = 2

2 1 1 3 1.5 2 1.75

4 2 2 6 3 4 3.5

D. n = 8 m = 2 E. n = 8 m = 2 F. n = 8 m = 2

2.33 2.25 3 2.8 2 3.66

1. The scaling problem (A, B, C) occurs when spatial data are aggregated to fewer larger units; 2. The zonation problem (D, E, F) results from alternative combinations of elements (n), when the number of aggregates (m) is held constant. 3. Numbers in aggregates show the effects of different combinations on mean values when n is held constant at 8 and m is changed.

Source: Adapted from Armhein (1995).

PART I: INTRODUCTION AND BACKGROUND 89 Chapter 2: Problems when analysing population change by ethnic group

The MAUP is composed of two separate but interrelated problems: the scaling problem and the zonation problem. In other words, when the scale and/or zones of data aggregation are modified, the results of spatial data analysis are likely to be affected (Openshaw, 1983). Figure 2.8 shows these two interrelated problems of the MAUP using three possible scenarios adapted from Armhein (1995).

The scale problem occurs when data from one scale of areal units are aggregated into more or fewer areal units. For example, the variation in Wards is lost when data are aggregated to the District. The zoning problem appears when we face a variety of different possible areal units for aggregation at a given scale.

This second problem follows from the uncertainty in choosing zonal units, as different areal arrangements of the same data produce different results. As a result, it becomes unreadable whether the results of census data may represent some reality about the individuals living in that region or, on the contrary, they are only a function of the particular areal unit used in the analysis (Openshaw, 1984).

In general, the MAUP is assumed to be a potential source of error that can affect spatial studies which employ aggregate data sources (Unwin, 1996). In the process of aggregating or disaggregating data some variations are not visible at the larger aggregate levels. However, it is crucial for smaller areas that the population data of the original set of areal units is preserved in the transformation to a new set of areal units, which means that ‘people are not destroyed or manufactured during the redistribution process’ (Langford and Unwin, 1994: 24).

Openshaw (1984) argues that the most effective response to the MAUP is to design purposespecific zonal systems. An example is the Automated Zoning Procedure (AZP), which is based on the iterative recombination of building block zones into output regions from an initial random aggregation (Openshaw, 1984). For example, Openshaw and Rao (1995) exemplified the PART I: INTRODUCTION AND BACKGROUND 90 Chapter 2: Problems when analysing population change by ethnic group

use of these zone design methodologies using a 1991 Census data and taking the EDs as input building blocks to assemble larger zones. However, the use of EDs for output has had a number of weaknesses, particularly wide variations in population size and poor match to the widely used postal geography (Martin, 1997 and 1998a).

These difficulties have been reduced significantly in the design of 2001 OAs for the 2001 Census geography in England and Wales, which incorporated the use of AZP with the smallest units in the postal geography (i.e. postcodes). For this purpose, ONS produced synthetic polygons for the smallest divisions of postal geography through the generation of Thiessen polygons around each individual address (information available from the Ordnance Survey ADDRESSPOINT data locations) and taking into account some additional topographic information. The result allowed the creation of a set of synthetic boundaries for postcodes. The implementation of an AZP algorithm facilitated a grouping of postcodes into OAs, using a consistent shape and explicit target population objective and a minimum population threshold. As a consequence, it is acknowledged that OAs are more suitable as userspecific geographies than the EDs (Martin, 2000 and 2002).

The use of GIS, digital data from the Ordnance Survey (OS) and advances in affordable computer power have contributed significantly to the creation of OAs. The automated zone design methodologies are used to produce other zonal geographies associated with the smallest census outputs in 2001 such as Wards and SOAs.

Therefore, even though the MAUP has been generally treated as an intractable problem, the use of designer zones can help minimise (rather than remove) the generic problems associated with zonal geographies (Openshaw, 1984; Martin, 2000).

2.7.5: Target geographies for the thesis

For this doctoral research, the target geographies are the boundaries used in the 2001 Census output for Districts, Wards and OAs. Chapters 4 to 9 PART I: INTRODUCTION AND BACKGROUND 91 Chapter 2: Problems when analysing population change by ethnic group

describe in full detail the creation of consistent 1991 and 2001 midyear population estimates for these geographies. In Chapter 11, the 2004 electoral Ward geography of the District of Birmingham is also used. The transfer of population data to the current Ward geography is implemented using an appropriate GCT. This approach allows the analysis of population change between 1991 and 2001 by age, sex and ethnic group for the District of Birmingham and smaller areas.

2.8: A precedent: Linking Censuses through Time (LCT)

2.8.1: The focus of LCT

The Linking Censuses through Time (LCT) project was designed to provide integrated online access to census data from the 1971, 1981 and 1991 Censuses for England, Wales and Scotland. Access is available to registered users of the census data at http://census.ac.uk/cdu/software/lct/ (Martin et al., 2002).

The importance of the LCT project is that it took into consideration the harmonisation of historical time series of population and geographical data with the aim to provide more comparable census statistics with the 2001 Census results (Martin et al., 2002). As such, it is the first major project which has addressed in various ways the principal areas of change from 1971 to 1991, including changes in the population definition, census undercount and boundary changes.

2.8.2: Ethnicity and adjustments in LCT

Although the number of variables comprising the 1971, 1981 and 1991 Censuses is extremely abundant, the LCT project focused on approximately 100 key variables, defined in comparable ways across censuses and believed to be suitable for comparisons with 2001 key statistics. One of the key variables for the 1991 Census within the subject Migration, country of PART I: INTRODUCTION AND BACKGROUND 92 Chapter 2: Problems when analysing population change by ethnic group

birth and ethnicity was ethnicity with four ethnic group categories (White, Asian, Black and Other).

The LCT project introduced a number of adjustments, which are as follows:

Population definition. Since the 1971, 1981 and 1991 Censuses used a different population base, an approach to reconcile census counts from each census was applied, which involved the addition and subtraction of counts in each of the census SAS tables in order to obtain comparable counts.

Correcting for undercount. This was considered the single most important impact to 1991 Census data. The LCT project used three sources of information to implement the correction for undercount: (1) the age/sex distribution of each SAS cell, estimated using the sample of individual census returns in the Sample of Anonymised Records (SARs); (2) the age/sex counts of persons missed at the Ward level obtained from EwC data; and (3) the base figures to be corrected from the SAS cells. Table 2.15 shows the change in population counts for various age groups in six Districts in order to give evidence of the typical range of adjustment values.

Table 2.15: Percentage adjustments to population counts by age group in selected Districts

Total 1519 2024 2529 3044 4549 6064 6574 75+

Manchester 8 15 29 16 4 1 0 0 3 Leicester 58 23 9 3 0 1 0 2 Taunton Deane 2 9 4 3 1 1 0 0 3 Carlisle 11 2 4 1 1 1 1 2 Gillingham 1 2 1 2 1 1 0 0 2 Woking 074 3 2 0 1 0 3

Source: Adapted from Martin et al. (2002: 88).

The correction allowed an estimation of the number of people of each age and sex missing from the SAS in each Ward. As shown in Table 2.15, the population count was reduced from some age groups after the correction, PART I: INTRODUCTION AND BACKGROUND 93 Chapter 2: Problems when analysing population change by ethnic group

thus reflecting the discrepancies between the 1991 Census counts and the EwC population estimates. Since the latter located students at their termtime address and 1991 Census counts had students at their vacation address some percentage adjustments appear to be negative as a result of this adjustment. This is most significant among the young groups.

Generally, the EwC and LCT adjustments are very similar, even though the final outputs did not agree because the LCT transferred students at their termtime address for four ethnic groups (White, Asian, Black and Other), giving students the characteristics of the local population. As a result, the LCT’s student adjustment assumes that students tend to live nearer to ethnic minority groups than the wider population (Mitchell et al., 2002).

Boundary changes. The focus of this project was to deliver census information at geographical levels above Wards for the purpose of analysing intercensal change. Over 30 different geographical systems were constructed from the 1981 Ward geography, which was initially derived from 1991 ED data using traditional pointinpolygon techniques. Since the 1981 Ward geography was used as the base for all the areal aggregations, it constitutes the most geographically detailed output available in LCT, and from which other geographies such as Districts, parliamentary constituencies, health authorities and travel to work areas have been approximately derived.

An example of estimating ethnic groups using LCT as part of a harmonised census time series is made by Rees and Butt (2003). This study compares two decades (19812001) of ethnic composition of England’s population to examine the changing pace of ethnic changes. The main data and estimation method characteristics are: the use of common groups and area definitions, and the construction of comparable estimates of ethnic group populations for three successive censuses from 1981 to 2001 for Districts. The use of LCT data was of crucial importance in the creation of revised 1991 midyear population estimates for Districts as defined in the 2001 Census. The strategy was based on: (1) multiplying the 1991 Census populations by the ratio of the 1991 LCT population in the four broad ethnic groups (White, PART I: INTRODUCTION AND BACKGROUND 94 Chapter 2: Problems when analysing population change by ethnic group

Black, Asian and Other); and (2) adjust the ethnic group populations for 1991 Districts to the revised 1991 midyear population estimates for 2001 Districts (ONS, 2003d).

Although the LCT project does not directly provide ethnic group data cross tabulated by age and sex, different adjustments can be applied to obtain such populations as demonstrated by Rees and Butt (2003) with the creation of 1991 midyear population estimates. The LCT project therefore constitutes an enhancement of previous census estimates for comparisons of intercensal change. Nonetheless, the revision of 1991 Census nonresponse in the light of the latest available data post2001 Census is likely to affect some of corrections made by the LCT project. In addition, the new output geography for 2001 offers a different geographical framework than that previously available and used by the LCT project. The design of 2001 OAs based on addresslevel geographical databases provide the base for updating and reaggregation of census counts to various types of geography, including new statutory areas.

Consequently, although the LCT was recognised as a potentially useful tool to provide more comparable census statistics with the 2001 Census results, a number of limitations have been identified when using 1991 Census data with an ethnic group dimension from the LCT interface. The main limitations which this doctoral research attempts to overcome are as follows:

Limitation 1: Population definition. Although a correction for students from vacation to termtime address was included in LCT for ethnic groups, this adjustment is only available for four ethnic groups (White, Asian, Black and Other). This doctoral research provides a student adjustment with an ethnic group dimension as recorded in the 1991 Census (10 categories). Full detail of this adjustment is given in Chapter 8.

Limitation 2: Revision of undercount. Although a correction for undercount was incorporated in LCT, the ‘new’ revision of undercount in the light of the latest mid1991 population estimates post2001 Census has not been PART I: INTRODUCTION AND BACKGROUND 95 Chapter 2: Problems when analysing population change by ethnic group

included. This doctoral research provides mid1991 population estimates with the final revision of 1991 undercount distributed to the 1991 Census ethnic group categories.

Limitation 3: Detail of age, sex and ethnic group. Although 1991 Census data from LCT are available with an ethnic group dimension, this is not cross tabulated by age and sex. This doctoral research provides mid1991 population estimates by single year of age, sex and ethnic group as recorded in the 1991 Census (10 categories).

Limitation 4: Boundary harmonisation. 1991 Census data from LCT are for 1981 Wards and larger areas are not directly comparable with the 2001 Census geography due to boundary changes between 1991 and 2001. This doctoral research provides a boundary harmonisation for mid1991 population estimates for Districts, Wards and OAs using the 2001 Census geography.

Full detail of the strategies used to overcome limitations 2 to 4 is given in Chapters 7 and 9.

2.9: Conclusions

The four main problems for constructing a subnational census time series of age, sex and ethnic group have been reviewed in this chapter. Various aspects relating to changes in the population definition, changes in the treatment of nonresponse, changes in ethnic identification and age group categories, and boundary changes have been clarified. A review of the main approaches to date to tackle these issues have been presented and evaluated. Analysis of population change between 1991 and 2001 is a complex task as a consequence of the problems described in the previous sections. The main result is that without fully addressing these problems it is practically impossible to know what proportion of observed population PART I: INTRODUCTION AND BACKGROUND 96 Chapter 2: Problems when analysing population change by ethnic group

change is due to these problems and what proportion reflects genuine population change.

In the next chapter, a specification of adjustments, data sources and methods to create a time series with consistent age, sex and ethnic group for Districts, Wards and OAs in England and Wales is described.

PART II: METHODOLOGY

PART II: METHODOLOGY 98

Chapter 3: Notation, data and tools

3.1: Introduction

This chapter gives basic information about the notation, data and tools employed to derive later in Chapters 4 to 9, consistent mid1991 and mid 2001 population estimates by single year of age, sex and ethnic group for Districts, Wards and OAs as defined in the 2001 Census geography.

First, the specification of adjustments to create a time series is provided in Section 3.2. Section 3.3 gives the general notation, which is used throughout the methodology and is based on algebraic notation. Section 3.4 gives a summary of the data sources used to create a time series with detail of age, sex and ethnic group for Districts and smaller areas. Finally, the main statistical and geographical tools used in the doctoral research are explained in Section 3.5. This represents the framework through which consistent mid year estimates are created in subsequent chapters.

3.2: Specification of adjustments to create a time series

When making population estimates consistent, there are choices regarding the target for consistency. Each estimate could refer to 1991 population definition, or to larger geographical areas which are common in both censuses, or to the broadest age groups which are consistent between censuses, to name three options which were not chosen but might have been appropriate had the aims been different.

The population estimates created have been planned to be consistent with the most current population estimates and be disaggregated to fine classifications for general use. These decisions, in line with the discussion provided in Chapter 2, have resulted in the following constraints: PART II: METHODOLOGY 99 Chapter 3: Notation, data and tools

(a) Mid1991 population estimates are consistent with the population estimates published by ONS post2001 Census for Districts without an ethnic group dimension. Mid2001 population estimates are consistent with the population estimates published in 2004 by ONS for Wards without an ethnic group dimension. This implies for example that census output must be adjusted in both censuses to include the impact of moving from the April Census day to midyear, and that the 1991 Census must include an adjustment to transfer students from vacation to termtime address.

(b) The resulting estimates are also consistent with the 2001 population estimates by ONS with an ethnic group dimension, first published in 2006, for Districts in England only. These assume no allowance for differential nonresponse between ethnic groups, which affects the distribution to ethnic groups of the extra 276,000 population estimated by ONS after the 2001 Census results were released, including in particular young men in urban Districts. In order to examine a differential allocation of non response between ethnic groups, a set of estimates for Districts and Wards have been derived too, which apply the ONS imputation rates used in the ONC.

(c) 1991 population estimates are converted to the boundaries used in the 2001 Census output. These include all boundary reviews agreed by the end of 2003, and although they are referred to here for example as ‘2001 Districts’ they in fact use boundaries existing in 2003 that may have changed since 2001.

(d) Single year of age to 90 and over is estimated for both 1991 and 2001, to allow subsequent aggregation to suitable age bands.

(e) Ethnic group categories for 1991 and 2001 are maintained in their respective full detail for each set of estimates. The matching of categories to compare 1991 and 2001 is made subsequently. For this purpose, an eightcategory classification is used as advised by ONS (Bosveld et al., 2006) and Simpson and Akinwale (2006). PART II: METHODOLOGY 100 Chapter 3: Notation, data and tools

3.3: General Notation

The following notation is used throughout the methodology. This has been designed for the implementation of the methods using algebraic terms.

A Census aged to midyear

B Births

C Census as published

CS Ethnic composition of students from census

F Armed forces adjustment

H Hierarchy adjustment

I Intersection of geographical areas

M Census modification adjustment

N Census nonresponse, extra to the census output in 1991 and 2001 (not equal to PC, due to timing and definition and data modification)

NI Nonresponse indicated by imputation from EwC

NU Nonresponse indicated by unemployed from EwC

NP Nonresponse, even spread from EwC

P Population estimate at midyear

R Nonresponse indicated by imputation from ONS

Sa Addition of students from vacation to termtime address

Sr Removal of students from vacation to termtime address

T Timing adjustment (demographic change between Census day and midyear) PART II: METHODOLOGY 101 Chapter 3: Notation, data and tools

U Census undercount (only applies to 1991, after including armed forces adjustment for nonresponse)

Subscript

Year: 91 or 01

Area: d91 (District boundaries used in the 1991 Census output)

d01 (District boundaries used in the 2001 Census output)

d01E (District boundaries for England only)

d01W (District boundaries for Wales only)

SASw91 (Small Area Statistics Ward boundaries used in the 1991 Census output)

LBSw91 (Local Base Statistics Ward boundaries used in the 1991 Census output)

CASw01 (Census Area Statistics Ward boundaries used in the 2001 Census output)

STw01 (Standard Table Ward boundaries used in the 2001 Census output)

ed91 (Enumeration District boundaries used in the 1991 Census output)

oa01 (Output Area boundaries used in the 2001 Census output)

di91di01 (intersection of 1991 District and 2001 District)

ed91oa91 (intersection of 1991 ED and 2001 OA)

Age: a91 (91 categories, 0, 1, 2,, 90 and over)

a86 (86 categories, 0, 1, 2, , 85 and over) PART II: METHODOLOGY 102 Chapter 3: Notation, data and tools

a22 (22 categories, fiveyear age groups, 04, , 90 and over; with extra detail for 57, 89, 15, 1617, 1819)

a21 (21 categories, fiveyear age groups, 04, , 90 and over; with extra detail for 15, 1617, 1819)

a19 (19 categories, fiveyear age groups, 04, , 90 and over)

a18 (18 categories, fiveyear age groups, 04, , 85 and over)

a11 (11 categories, fiveyear age groups, 59 to 5054; with extra detail for 1718)

a10 (10 categories, fiveyear age groups, 59 to 5054)

a7 (7 categories, broad age groups, 04, 515, 1629, 3049, 50 to pensionable age, pensionable age to 74, 75 and over)

a5 (5 categories, broad age groups, 04, 515, 1629, 30 to pensionable age, pensionable age and over)

a1618 (ages between 16 and 18)

a1624 (ages between 16 and 24)

a(<45) (ages up to 44)

a(45+) (ages 45 and over)

Sex: s (males, females)

Ethnic group: e

Whenever used with 1991 data, this refers to ten ethnic groups (1 White, 2 Indian, 3 Pakistani, 4 Bangladeshi, 5 Black Caribbean, 6 Black African, 7 Chinese, 8 Other Asian, 9 Other Black, 10 Other Ethnic Group) PART II: METHODOLOGY 103 Chapter 3: Notation, data and tools

Whenever used with 2001 data, this refers to sixteen ethnic groups (1 White British, 2 White Irish, 3 Other White, 4 White and Black Caribbean, 5 White and Black African, 6 White and Asian, 7 Other Mixed, 8 Indian, 9 Pakistani, 10 Bangladeshi, 11 Other Asian, 12 Black British Caribbean, 13 Black British African, 14 Other Black British, 15 Chinese, 16 Other Ethnic Group)

The order of the following subscripts is standard:

● A dot in the appropriate position indicates a figure referring to the population aggregated over that subscript. For example,

R01,d01,●,s,e refers to imputation rates across all ages within each 2001 District , sex and ethnic group in England and Wales.

( ) The use of brackets within the geography position indicates a figure referring to the population aggregated over that

geography. For example, P91,d(oa)01,a18,s,e are derived by summing

P91,oa01,a18,s,e within each 2001 District , age, sex and ethnic group.

N The use of N indicates the number of units within a higher geographical unit. For example, oa(w)_N refers to the number of OAs within that Ward.

Superscript

A Adjustment

I Initial value

II Intermediate value

R Revised value

RF Revised value after removal of negative values

PART II: METHODOLOGY 104 Chapter 3: Notation, data and tools

Other operational characters p Population proportion

Saep Ethnic group proportion for students added

Srep Ethnic group proportion for students removed

Lag Value from previous case

Wt Weight

GCT01 GCT to transfer data from 1991 EDs to 2001 OAs

GCT02 GCT to transfer data from 1991 SAS Wards to 2001 CAS Wards

GCT03 GCT to transfer data from 1991 SAS Wards to 1991 LBS Wards

GCT04 GCT to transfer data from 1991 SAS Wards to 2001 Districts

GCT05 GCT to transfer data from 1991 Districts to 2001 Districts

GCT06 GCT to transfer data from 2001 CAS Wards to 2001 ST Wards

GCT07 GCT to transfer data from 2001 OAs to 2004 electoral Wards

Some examples are as follows:

P01,d01,a91,s,● Mid2001 population estimates (P01) for 2001 Districts (d01),

with 91 age categories (a91) and sex (s) for allgroups (●) in England and Wales.

C91,ed91,a5,●,e 1991 Census counts for 1991 EDs (ed91), with 5 age

categories (a5), for both sexes (●) and with detail of ethnic

group (e) as recorded in the census in England and Wales.

PART II: METHODOLOGY 105 Chapter 3: Notation, data and tools

3.4: Summary of data sources

Table 3.1 and Table 3.2 give a summary of the data sources used in this doctoral research.

Table 3.1: Data sources to create complete mid-1991 estimates

Ethnic Time Data set Source Age detail Sex Spatial unit categories 5year age group to 84 and Males / 1991 LBS 1991 Census Table L06 OPCS 85+, with extra breaks at 10 Females Ward 15,1617,1819

5year age group to 8589 Males / 1991 Census Table S02 OPCS None 1991 ED and 90+ Females 5 groups (04, 515, 1629, 30 to pensionable age and 1991 Census Table S06 OPCS None 10 1991 ED pensionable age and over) but without sex detail Males / 1991 Census Table S06 OPCS None 10 1991 ED Females

EWCPOP mid 5year age group to 84 and Males / 1991 EwC None 1991 ED year estimates 85+ Females

EWCPOP mid 5year age group to 84 and Males / 1991 SAS 1991 EwC None year estimates 85+ Females Ward

EWCPOP non 5year age group to 84 and Males / 1991 response and EwC None 1991 ED 85+ Females adjustments EWCPOP non 5year age group to 84 and Males / 1991 SAS 1991 response and EwC None 85+ Females Ward adjustments

Midyear 5year age group to 84 and Males / 1991 ONS None 2001 District estimates 85+ Females

Midyear Single year of age to 84 and Males / 1991 ONS None 2001 District estimates 85+ Females

5year age group to 84 and Males / 1991 LBS 1991 SOCPOP EwC 10 85+ Females Ward

SOCPOP Single year of age to 84 and Males / 1991 LBS 1991 EwC 10 smoothed 85+ Females Ward

5year age group 59 to 5054 Males / 1991 Student addition OPCS with additional split at age None 1991 District Females 17/18

1991 SAS 1991 Student addition EwC None None None Ward

5year age group 59 to 5054 Males / 1991 Student removal OPCS with additional split at age None 1991 District Females 17/18

1991 SAS 1991 Student removal EwC None None None Ward

Males / 1991 VS4 ONS Births from mid90 to mid91 None 2001 OA Females

PART II: METHODOLOGY 106 Chapter 3: Notation, data and tools

Table 3.2: Data sources to create complete mid-2001 estimates

Ethnic Time Data set Source Age detail Sex Spatial unit categories

Census Table Single year of age to 24 and Males / 2001 ONS None 2001 OA CS001 5year age group to 90+ Females

Census Table Males / 2001 CAS 2001 ONS School pupils aged 16,17,18 None CT002 Females Ward

7 groups (04, 515, 1629, Census Table 3049, 50 to pensionable 2001 ONS None 16 2001 OA CT003 age, pensionable age to 74, 75 and over)

Census Table Males / 2001 ONS None 16 2001 OA CT003 Females

Census Table Single year of age to 89 and Males / 2001 ST 2001 ONS None ST001 90+ Females Ward

5year age group to 89 and Census Table Males / 2001 ST 2001 ONS 90+ with extra breaks at 57, 16 ST101 Females Ward 89, and 15, 1617, 1819

Census Table Males / 2001 CAS 2001 ONS Students aged 1624 16 ST108 Females Ward

Census Table Males / 2001 ONS Students aged 1624 10 2001 District ST108 Females

Full time students and Males / 2001 Census Table T02 ONS schoolchildren aged 16, 17 None 2001 District Females and 18 Census Single year of age to 89 and Males / 2001 Commissioned ONS 16 2001 District 90+ Females Table C0533

Midyear 5year age group to 84 and Males / 2001 CAS 2001 ONS None estimates 85+ Females Ward

Midyear Single year of age to 89 and Males / 2001 ONS None 2001 District estimates 90+ Females

Midyear ONS (only Single year of age to 89 and Males / 2001 16 2001 District estimates England) 90+ Females

Males / 2001 Imputation rates ONS None 16 2001 District Females

ONS (only Single year of age to 89 and Males / 2001 Timing 16 2001 District England) 90+ Females

PART II: METHODOLOGY 107 Chapter 3: Notation, data and tools

3.5: Statistical and geographical tools

The use of statistical and geographical tools represents one of the focal points of current research dealing with census data (UNECE, 2001). Since events of statistical interest happen in space over time, the interactions between data items in space matter. Although this represents a wellestablished idea, it has nonetheless been constrained by limited supporting technology (Calder, 2000).

However, given the continuing advances in software applications, the potential for measuring those events in space over time is more feasible. The statistical production of large data sets is increasing as demonstrated by the availability of census data in electronic formats (e.g. CASWEB). Additionally, public access to conversion of data between geographies, to enable the transfer of data from one set of geographical units to another constitutes a key issue for the current demand of small area statistical requirements.

Within this context, the next two sections exemplify the use of a standard statistical technique to estimate small area crossclassifications of interest using Iterative Proportional Fitting (IPF) and a generic solution to create harmonised geographies using GCTs.

3.5.1: Applying Iterative Proportional Fitting (IPF)

IPF is a mathematical procedure that is used when reliable estimates for a desired crossclassification cannot be obtained directly but estimates of the variables of interest are available at a higher level of aggregation. A requirement for the use of IPF is that information on the relationship between the variables is available at the desired level of crossclassification. For example, IPF can be used to estimate a crossclassification of mid2001 population estimates for Wards with detail of single year of age, sex and ethnic group using information from available mid2001 population estimates for Districts with the desired crossclassification and marginal totals for Wards.

IPF ensures that a multidimensional table is scaled so that it agrees in its total with row and column totals supplied separately, thus allowing combination of PART II: METHODOLOGY 108 Chapter 3: Notation, data and tools

information from two or more data sets. The application was originally presented by Deming and Stephan (1940) and it has been included in standard statistical texts for many decades (Bishop et al., 1975). Versatile routines have been developed to handle any twodimensional array in Excel (Norman, 1999) and to tables of any dimensions applying loglinear procedures in SPSS (Simpson and Tranmer, 2003).

The use of IPF for censusbased applications has been demonstrated by previous research (Birkin, 1987; Birkin and Clarke, 1995), and has proved very useful in demographic and geographical studies to make the age and sex structure for small populations consistent with more reliable data (Myers, 1992; Rees, 1994; Simpson, 1998). Similarly, it has also been used to provide more detail in migration data by combining alternative sources with data published from the census (Rogers et al., 2003).

The mathematical definition of IPF in two dimensions follows the set of equations below (Wong, 1992):

(kPij ) kPij + )1( = ∗Qi ∑ kPij )( (1) j

kPij +1( ) kPij )2( =+ ∗Qj ∑ kPij + )1( (2) i

Where Pij(k) is the matrix element in row i, column j, and iteration k. Qi and Qj are the predefined row totals and column totals respectively. The new cell values are obtained by using equations (1) and (2), which perform iteratively and stop at iteration m when:

∑ )( = QimPij and ∑ )( = QjmPij j i PART II: METHODOLOGY 109 Chapter 3: Notation, data and tools

An example of IPF making small area statistics consistent with those for larger areas is provided in the following tables. Table 3.3 contains an initial estimate of the population across two areas by age, sex and ethnic group (White and NonWhite). The table margins supply information on the total Ward population and the total in each ethnic group by age (1849 and 50 and over) and sex for the District. Since the agesex structure for each area is neither consistent with the District agesex structure nor with the Ward area total population, the interior of the table, which contains an initial estimate of the population for the mentioned areas by age, sex and ethnic group, should be amended. IPF allows an adjustment of the initial estimates keeping each area’s specific agesex pattern relative to other areas and bringing consistency with both the Ward total and the District agesex pattern.

Table 3.3: Example of using IPF (initial table)

White Non-White 1849 50+ 1849 50+ 1849 50+ 1849 50+ Ward Males Males Females Females Males Males Females Females Total North area 10.00 8.00 10.00 8.00 4.00 2.00 4.00 2.00 50 South area 6.00 8.00 6.00 8.00 5.00 2.00 5.00 2.00 50 Local authority 16 18 16 18 10 6 10 6 100

Table 3.4: Example of using IPF (amended table)

White Non-White 1849 50+ 1849 50+ 1849 50+ 1849 50+ Ward Males Males Females Females Males Males Females Females Total North area 9.55 8.47 9.55 8.47 4.16 2.82 4.16 2.82 50 South area 6.45 9.53 6.45 9.53 5.85 3.18 5.85 3.18 50 Local authority 16 18 16 18 10 6 10 6 100

Source: Adapted from Rees (1994).

NB: the procedure has been performed on an automated spreadsheet using Visual Basic (Norman, 1999). Maximum iterations (100); convergence statistic (0.01).

Table 3.4 shows the initial table amended, in which IPF has performed the weighting process by repeating the onedimensional scaling first to meet the PART II: METHODOLOGY 110 Chapter 3: Notation, data and tools

District ethnicagesex structure and then to meet the small area totals, then again the District ethnicagesex structure, and so on iteratively. IPF brings the estimates closer and closer until they are consistent with both sets of marginal totals.

The application of IPF in SPSS (2004) can be done using HILOGLINEAR and GENLOG commands, both referring to loglinear modelling procedures that approximate tabular data and that are not limited to two dimensions but any number of categories within each dimension (termed factors in SPSS documentation). The implementation of IPF using both commands to combine sample and census data in small area estimates is detailed in Simpson and Tranmer (2003), favouring the use of GENLOG. The latter command allows the expected values (termed predicted values) to be saved, while HILOGLINEAR only prints expected values to the text output file, thus making difficult its use and, above all, the export of data. The implementation of IPF in SPSS with GENLOG is also accompanied with the CSTRUCTURE command, equivalent to CWEIGHT in HILOGLINEAR, to supply the initial values which are adjusted to the marginal subtotals.

Table 3.5 illustrates how data should be arranged so as to implement IPF in SPSS, with one record per each of the characteristics that represent a dimension of the table, a variable with the initial values and a variable representing the marginal subtotals. To organise the data in a database format the VARSTOCASES command has been used before the estimation. The table of age by sex and ethnic group for each of the 175,434 OAs in England and Wales can be considered as a fourway table of dimensions 7 x 2 x 10 x 175,434. The marginal subtotals known for each OA consist of three twoway tables of size 7 x 175,434 (age by OA), 2 x 175,434 (sex by OA) and 10 x 175,434 (ethnic group by OA). This is equivalent to the estimation of 175,434 separate 7 x 2 x 10 tables, each with 1 x 7, 1 x 2 and 1 x 10 marginal subtotal tables. The use of the two SPSS loglinear procedures makes this approach more efficient, applying to tables of any dimensions. PART II: METHODOLOGY 111 Chapter 3: Notation, data and tools

The initial estimates can be in the form of proportions of one of the marginal factors or simply counts. In the table, they refer to Wardlevel data which results in some cells being equal for those OA within that Ward with the same agesex combination. The margins variable represents a variable that contains any set of values which sum to the marginal subtotals. The computation of this variable is made under the assumption that the margins are independent of each other, a procedure that is facilitated by the fact that many spatial data sets, including U.K. censuses, are available with a single record for each area.

The margins variable is obtained as follows (Simpson and Tranmer, 2003):

Marginsijk = Total * (Margin1i / Total)

* (Margin2j / Total)

* (MarginNk / Total)

Table 3.5: Example of data file prepared for IPF in SPSS

Output Area age sex ethnic group initial margins 1 1 1 1 66 8.70 1 1 2 1 51 10.30 1 2 1 1 190 20.14 1 2 2 1 179 23.86 1 3 1 1 122 13.27 1 3 2 1 124 15.73 1 4 1 1 330 33.42 1 4 2 1 354 39.58 1 5 1 1 288 30.21 1 5 2 1 218 35.79 1 6 1 1 139 17.39 1 6 2 1 220 20.61 1 7 1 1 87 6.87 1 7 2 1 126 8.13

Table 3.6 displays the data used to compute the first record of the variable margins in Table 3.5, which was derived as follows:

284 * (19/284)*(130/284) = 8.70 PART II: METHODOLOGY 112 Chapter 3: Notation, data and tools

Table 3.6: Example of census subtotals from which the margins variable is derived

Values for Ouput Area = 1 and ethnic group = 1

Age=1 Age=2 Age=3 Age=4 Age=5 Age=6 Age=7 Sex=1 Sex=2 total 19 44 29 73 66 38 15 130 154 284

This constitutes a key advance in adjusting the interior of the tables with multiple dimensions. The following commands are displayed as an example to implement IPF using the GENLOG command in SPSS. The example is taken directly from SPSS syntax to amend a census table for 2001 by broad age (7 categories), sex and ethnic group for each OA in England and Wales. The SPSS syntax for the file above would be as follows:

COMPUTE initial=c91w91a5se + 0.5. SPLIT FILE BY oa01_code eth01_16. WEIGHT BY margins. TEMP. SELECT IF margins > 0. GENLOG age7 sex /CSTRUCTURE = initial /DESIGN age7 sex /PRINT=NONE /PLOT=NONE /CRITERIA = CIN(95) ITERATE(20) CONVERGE(.01) DELTA(0) /SAVE = PRED (c01oa01a7se). WEIGHT OFF. SPLIT FILE OFF. IF margins=0 c01oa01a7se=0.

The example shows how IPF operates across seven age categories (a7) and sex within each OA by ethnic group (eth01_16). It assumes that within those categories, the agesex interaction is as in the Wards as a whole. The 2way IPF is performed within each OAethnic group category using the SPLIT FILES command. It can also be noted that the GENLOG command accepts PART II: METHODOLOGY 113 Chapter 3: Notation, data and tools

variables with string values such as the OA code, while these need to be converted to consecutive integer values using the RECODE or AUTORECODE commands if HILOGLINEAR is used.

Although the process is straightforward to programme in SPSS syntax, in order to run GENLOG two preliminary conditions need to be satisfied to avoid zero cells taking part in the analysis, as they lead to parameters being infinite (Agresti, 1990; Hosmer and Lemeshow, 1989; Bishop et al., 1975). For this purpose, two ad hoc strategies can be implemented for eliminating the problems caused by zero cells that lead to practical problems for the program, causing it to have difficulty in converging:

1. First, the initial values (which are provided as a cell structure) are raised to a minimum value such as 0.5.

2. Second, the margins variable values (which are provided as a ‘weight’ to the cell values) are excluded when the value of the marginal cell equals zero. In the final estimates, these are given a fitted value of zero.

As described by Bishop et al. (1975: 101), ‘too many’ zero cells in the initial matrix can prevent convergence as a consequence of ‘persistence of zeros’. Although ‘too many’ is not defined, Norman (1999: 6) describes that ‘if a matrix contains evenly distributed zeros in more than 30 per cent of cells or are grouped closely together and comprise around 10 per cent of the table, convergence may not occur’. Since the occurrence of zero counts in census data is likely to exist, particularly in areas with small populations such Wards and the smallest census areas (EDs and OAs), IPF has been carried out in multiple separate files. This has involved a great deal of data preparation which was performed with SPSS with validation checks throughout the process for each separate data set.

For example, the final data set for mid2001 for Wards has 25,616,864 cases, one for each combination of ST Wards (8,797), age (91 categories), sex (2 categories) and ethnic group (16 categories). The final data set of mid2001 PART II: METHODOLOGY 114 Chapter 3: Notation, data and tools

for Wards was obtained after matching 15 separate data sets organised by Districts (with fifteen Districts covered and 1.7m records in each data set). This enabled GENLOG to run more efficiently, taking approximately forty minutes for each data set to reach a solution. To reduce the amount of time and memory accessed by SPSS, unnecessary output can be suppressed.

The calculation of marginal totals for the results, and their distance from the actual margins is an important step to validate the outcome after using IPF. The population estimated by IPF should be the same as known subtotals if the estimation has worked well. The following commands are an example of how to check the validity of the results for the overall total:

AGGREGATE /OUTFILE=*

MODE=ADDVARIABLES

OVERWRITE=YES

/PRESORTED

/BREAK=oa01_code eth01_16

/afteripfmarg margintotal=sum(c01oa01a7se margins).

COMPUTE check=afteripfmarg margintotal.

DESCRIPTIVES afteripfmarg margintotal check /stats=default sum.

The procedure is proven to converge when the marginal subtotals are consistent with each other. However, since small counts in census tables are subject to a small adjustment routine to ensure confidentiality of results, the tables used in IPF are not always precisely consistent. Generally, the effect of data adjustments on cell counts is ‘most severe in areas with small populations and/or for those census variables with a low frequency of occurrence, and/or distributed over a large number of categories’ (Cole, 1993: 221). PART II: METHODOLOGY 115 Chapter 3: Notation, data and tools

In this respect, in the 1991 Census a number of tables were subject to data modification. For example in the SAS census table S06, which provides detail of ethnic group for each ED in England and Wales by broad age (5 categories) and sex, each separate crosstabulation was modified independently. Similarly, in the 2001 Census, in the CAS Theme Table CT003, which provides detail of ethnic group for each OA in England and Wales by broad age (7 categories) and sex, each separate crosstabulation was also subject to data modification. As a result, occasionally an ethnic group has a nonzero value when it is crosstabulated by sex, where the same ethnic group has a zero value when it is crosstabulated by age. Since the table with fewer cells is likely to be subject to less modification (Rees et al., 2005), scaling can be used as a way to provide consistency between census tables before IPF is implemented (see Chapters 6 and 9).

The adjustment of small cell counts that were originally 1 and 2 by random rounding into 0 or 3 is likely to be more noticeable for small populations (ONS, 2006c). This adds approximation to all analysis, particularly for the smallest output geography, including those of this doctoral research, as discussed by Stillwell and DukeWilliams (2007).

Finally, it has to be noted that convergence of the data is not possible if there are minus numbers (Bishop et al., 1975). Therefore, all procedures have been constrained so that there are no negative populations when IPF is implemented. These procedures, which allow internal consistency, are discussed later in Chapters 4 to 9.

3.5.2: Applying Geographical Conversion Tables (GCTs)

As seen earlier in Section 2.7, GCTs constitute a generic solution to create harmonised geographies. The use of GCTs allows the transfer of population data of the source geography into the new target geography. For example, 1991 Census data by age, sex and ethnic group for wards as defined at 1991, can be converted to wards as defined differently in 2001 using a GCT. In this doctoral research the main purpose of using GCTs is to estimate a time series PART II: METHODOLOGY 116 Chapter 3: Notation, data and tools

on a consistent basis, although they are also used to merge data sets drawn from different sources.

GCTs rely on two key aspects: (1) the existence of reference codes to both the source geography and the target geography; and (2) an indication of the extent of overlap between the source geography and the target geography.

These two aspects are fundamental to compute the proportion of the source geography unit that lies in the target geography unit. If the geographies used link on a simple ‘bestfit’ basis, weights are all 1 and, therefore, the transfer of attributes from the source geography to the target geography only involves a simple or multiple allocation of information from the source geography to the target geography. The use of different weights is necessary when there are intersections between both geographies. Then a weight, which takes a value more than zero but less than or equal to one, shows the proportion of the source geography unit that lies in the target geography unit. The weighting criterion can be the population, the number of households or addresses, or another variable. In order to assess the data conversion process between pairs of geographies, Simpson (2002c) defined the ‘degree of hierarchy’ and the ‘degree of fit’. These measures quantify the amount of error associated with interpolation of source units to target units.

The ‘degree of hierarchy’ refers to the proportion of source units that are contained within a single target unit, and it is expressed as the percentage of source units with a weight equal to one. The higher the proportion, the lower the mismatch between source and target zones, and the higher the accuracy of resulting estimates. If all weights are one the conversion table is hierarchical, which means that the source units fully nest within the target units. For example, Census OAs are all contained within Census Districts.

PART II: METHODOLOGY 117 Chapter 3: Notation, data and tools

The ‘degree of hierarchy’ can be calculated as follows (Simpson, 2002c):

∑ wst = )1( *100 s,t ∑ 1( ) s

Where s is a source geography unit, which can only be allocated once (1) (for example a code for a 1991 Census ED), t is a target geography unit (for example a code for a 2001 Census OA), and wst is a weight showing the proportion of the source geography that overlaps the target geography.

The ‘degree of fit’ is used to evaluate similarity between the source and the target geography or, for example, to indicate how differently the GCTs may be estimating the 1991 data by the 2001 geography. This measure sums the largest weight for each source unit and expresses this as a proportion of the number of source units.

The ‘degree of fit’ can be calculated as follows (Simpson, 2002c):

∑ wst )(max *100 s ∑ )1( s

The transfer of data of the source geography into the new target geography is carried out by multiplying each record of source data by the appropriate weight indicated in the GCT. The aggregation of the weighted data values allocated to each target unit is used to derive the results for target units.

The calculation of data for source geography units (Ds) converted to data for target geography units (Dt) using the weights recorded in the GCT can be expressed as follows (Simpson, 2002c):

t = ∑ DwD sst s PART II: METHODOLOGY 118 Chapter 3: Notation, data and tools

According to Simpson (2002c: 74), ‘when data are converted, unless the table is hierarchical (all weights equal to 1), uncertainty is added in the conversion, such that the results for target units are estimates’. The estimation involved in the data conversion is expressed by the ‘degree of hierarchy’ and ‘degree of fit’.

This type of approach has been used in the UK to convert between different geographical systems and to harmonise time series data on a consistent geographical basis (Norman et al., 2003; Simpson 2002c; Wilson and Rees, 1998). For this purpose, look up table directories linking postcode to other geographical areas are generally used to inform GCTs, which are then used to transfer data from a source geography to a target geography. The method allows therefore a change in the zonal system for which the data preexist to a target geography for which the data are needed. The assumption is that the distribution of residential postcodes is a proxy for population distribution. Within this context, postcodes are generally taken to be points located using the UK National Grid Reference of their centroid.

Figure 3.1 illustrates a hypothetical pair of Wards in which the geography changed and for which postcodes are used to link the source with the target geography. In the source year, North and South Wards have a constituent set of postcodes, their point locations marked with black and white dots. In the target geography, East and West Wards have been created occupying the same areal extent as the previous Wards and each containing postcodes previously associated with North and South Wards.

The logic used in the GCT is to apportion the population data for North Ward using the proportion of postcodes falling in the intersection between North and West Wards (3/5) and between North and East Wards (2/5). In the same manner, the population of South Ward is apportioned using the proportion of postcodes in the South and West Ward (2/4) and South and East Ward (2/4).

PART II: METHODOLOGY 119 Chapter 3: Notation, data and tools

Figure 3.1. Postcodes used to link geographies and weight data conversion

Source geography Target geography

North Ward West Ward East Ward

South Ward

In practical terms, if the population of North and South Wards were 10,000 and 5,000 respectively, these can be apportioned to the alternative Wards as follows:

West Ward = part of North (10,000 * 3/5) + part of South (5,000 * 2/4)

East Ward = part of North (10,000 * 2/5) + part of South (5,000 * 2/4)

Total population West Ward = 8,500

Total population East Ward = 6,500

The following is a description of the method used to transfer population data from 1991 EDs to 2001 OAs. SPSS and ArcView were used to carry out this task which implies a conversion of data from fewer to more zones. The conversion weights were calculated using postcode counts in the intersections between the different geographical area definitions. The main sources of data for this GCT were postcode centroid locations obtained from the All Fields Postcode Directory (AFPD) and the latest, the National Statistics Postcode PART II: METHODOLOGY 120 Chapter 3: Notation, data and tools

Directory (NSPD), maintained by ONS and available from UKBORDERS.3 The link between each postcode in the AFPD and the ED was enhanced using the GIS pointinpolygon (PiP) technique. Previous research by Gatrell et al. (1991) found that adding 50m to both the easting and northing of the 100m resolution of the National Grid Reference (NGR)4 improved the linkages to EDs (Martin, 1996: 77). This enhancement was made under the expectation that more often than not, postcodes would be moved northeast into or retained within the correct ED. This procedure was not applied when using postmillennium postcode directories (i.e. NSPD), which have an improved NGR resolution. Dates of introduction and termination allow a set of 1991 valid, residential (‘small user’) postcodes to be extracted from recent postcode directories which have this improved grid reference resolution.

Figure 3.2 exemplifies this issue with an ED and OA and the first postcode in England and Wales (AL1 1AG) using the NSPD. The ED is highlighted in yellow, and the postcodes associated with that ED are represented in blue. The figure shows how AL1 1AG is not located within the polygon of the ED with which it is linked, which would result in a GCT with a proportion of the ED data being assigned to the wrong OA. Figure 3.3 shows by contrast how all the postcodes associated with an OA, represented in yellow, lie within that OA. This illustrates that there are some problems with the links to EDs, whereas the links to OAs are reliable.

In collaboration with Simpson and Sabater, as part of the ESRC’s Understanding Populations and Processes Programme (UPTAP), Norman undertook the conversion of the original small area Estimating with Confidence 1991 midyear population estimates (and the components used to derive these from 1991 Census data) to geographies compatible with the 2001 Census and midyear estimates.

3 The website link to the postcode directory download from UKBORDERS is only availabe to those with an Athens academic password at http://borders.edina.ac.uk/html/. 4 The NGR provides a unique reference system that can be applied to all Ordnance Survey (OS) maps, at all scales. An interactive guide to the National Grid is available at http://www.ordnancesurvey.co.uk/oswebsite/gi/nationalgrid/nghelp1.html PART II: METHODOLOGY 121 Chapter 3: Notation, data and tools

Figure 3.2: Postcodes linked with ED (KHF13)

AL1 1AG

Figure 3.3: Postcodes linked with OA (26UGGQ0005)

AL1 1AG

Source: Adapted from Norman et al. (2007). PART II: METHODOLOGY 122 Chapter 3: Notation, data and tools

Norman et al. (2007) describe and illustrate the method used to convert data between 1991 ED and 2001 OA geographies. The assumptions underlying this approach are that:

• The postcode points distribution (weighted by address counts in this case) is a proxy for population distribution.

• Although linking 1991valid postcodes to both EDs and OAs using PiP and the post2001 grid reference resolution risks that the links may be to the ‘wrong’ EDs the approach preserves the need for the sourcetarget intersections to have a subED/OA indicator of population distribution.

Norman et al. (2007) note, ‘it must be stressed that [the revised EwC estimates] for Output Areas are intended as building bricks for aggregation to larger areas’. Within this context, any conversion errors between EDs and OAs will be small when analyses are carried out using larger geographies.

Another relevant aspect for the creation of GCTs relates to the population distribution within postcodes. Generally people are not evenly distributed across postcodes, for example, there are more addresses and households per postcode in urban compared with rural areas as a result of an urbanrural gradient with fewer people in rural postcodes. It is for this reason that postcode counts are normally weighted by address counts (Simpson, 2002c) and by household counts (Norman et al., 2003). The logic of this approach has been applied to transfer data from 1991 to 2001 geographies.

Table 3.7 illustrates an extract for Aldersgate Ward in City of London of the GCT defined and constructed by Norman et al. (2007) to transfer population data from EDs to OAs. The GCT shows the addresses per ED source and OA target and the address count by EDOA intersection that uses a particular postcode (excluding small businesses/nonresidential addresses). This allows the computation of a weight to transfer data from EDs to OAs (i.e. weight 91 01) and vice versa (i.e. weight 0191). The aggregation of weights by source and target geography adds to 1 across units. For example the weight 9101 for 01AAFA01 (ED) indicates that 0.4680 of the source data are allocated to PART II: METHODOLOGY 123 Chapter 3: Notation, data and tools

00AAFA0002 (OA) and 0.5320 of the source data are allocated to 00AAFA0008.

Table 3.7: An extract of the GCT used to link 1991 EDs with 2001 OAs

ED code OA code Address count ED total OA total Weight 9101 Weight 0191 01AAFA01 00AAFA0002 117 250 121 0.46800 0.96694 01AAFA01 00AAFA0008 133 250 137 0.53200 0.97080 01AAFA02 00AAFA0001 117 117 117 1.00000 1.00000 01AAFA03 00AAFA0003 8 187 8 0.04278 1.00000 01AAFA03 00AAFA0004 179 187 180 0.95722 0.99444 01AAFA04 00AAFA0004 1 1 180 1.00000 0.00556 01AAFA05 00AAFA0005 242 242 242 1.00000 1.00000 01AAFA06 00AAFA0006 65 65 65 1.00000 1.00000 01AAFA07 00AAFA0002 4 52 121 0.07692 0.03306 01AAFA07 00AAFA0007 45 52 108 0.86538 0.41667 01AAFA07 00AAFA0008 3 52 137 0.05769 0.02190 01AAFA08 00AAFA0007 8 12 108 0.66667 0.07407 01AAFA08 00AAFS0001 4 12 285 0.33333 0.01404 01AAFA09 00AAFA0007 54 54 108 1.00000 0.50000 01AAFA10 00AAFA0007 1 1 108 1.00000 0.00926

Other observations can be made on what constitutes a boundary change. For example, locations where a digital boundary is in a different place may not be a boundary change as far as data collection and dissemination are concerned but due to different legal definitions (to do with a wrongly recorded water course, for example) or different digitising standards. However, this would not affect the data conversion because the weights, which are constructed from the number of residential addresses in that postcode, are presumably closely correlated to the variable being converted (i.e. population data). Additionally, the target units to which a source unit is allocated are always adjacent to one another, thus minimising potential error of misallocation.

Occasionally, a postcode point may fall in different source and target polygons when no change has actually occurred and the GCT would apportion data to the wrong target. This may happen for example as a result of EDs for housing that has been demolished and so does not appear in a 2001 postcode. Likewise there are 2001 OAs which do not have any 1991 ED attached PART II: METHODOLOGY 124 Chapter 3: Notation, data and tools

because they are new housing. In the construction of the GCT, these are included but given zero population.

Data conversion with no error is only possible if source data are precisely coded to dwelling units (or to other points) so that aggregation can be carried out hierarchically to any target geography. Hence, synthetic estimation would not be involved as all weights would equal one. The georeference of individual or householdlevel microdata appears as the ideal solution to this problem (Harris et al., 2002a). In the UK, this is becoming more feasible with Ordnance Survey (2007) ADDRESSPOINT.5 This is a data set created by matching information from Ordnance Survey that uniquely defines and locates residential, business and public postal addresses. Consequently, this database with microdata information can be used as the buildingbrick for the aggregation of data into any arbitrary unit. Although this approach can potentially enhance the conversion of data, it is nonetheless subject to confidentiality thresholds to avoid compromising data anonymity. Additionally, it can be very difficult to distinguish residential from business properties in ADDRESSPOINT (Thomasson, 2000) and it is the distribution of the residential population which is of interest in this doctoral research.

Although it is impossible to get an exact GCT, these are used as approximate building blocks that are suitable for aggregating to larger geographies. However, categorising and quantifying the approximation that is involved in the data conversion from one set of geographical areas to another is important.

Table 3.8 gives a list of the seven GCTs used in this thesis to harmonise data over time and space, with information on the ‘degree of hierarchy’ (DH) and ‘degree of fit’ (DF).

5 The ADDRESS-POINT product provides locations of all addresses identified from the intersection of Royal Mail’s Postcode Address File, with a spatial resolution of 0.1m. The website link is available from Ordnance Survey at http://www.ordnancesurvey.co.uk/oswebsite/products/addresspoint/ PART II: METHODOLOGY 125 Chapter 3: Notation, data and tools

Table 3.8: List of GCTs used to harmonise data over time and space

Reference Source Target Degree of Degree of geography geography hierarchy (DH) fit (DF) GCT01 1991 EDs 2001 OAs 10.9% 56.3% GCT02 1991 SAS Wards 2001 CAS Wards 53.8% 88.4% GCT03 1991 SAS Wards 1991 LBS Wards 100% 100% GCT04 1991 SAS Wards 2001 Districts 96.8% 99.8% GCT05 1991 Districs 2001 Districs 65.5% 99.2% GCT06 2001 CAS Wards 2001 ST Wards 100% 100% GCT07 2001 OAs 2004 electoral Wards 92.8% 98.4%

NB: GCT07 only refers to geography units in the District of Birmingham.

• GCT01, allows the conversion from 1991 EDs (113,465 units) to 2001 OAs (175,434 units) in England and Wales (defined and constructed by Norman et al., 2007). This GCT has been used to transfer population attributes from the smallest 1991 Census geographies to the smallest 2001 Census geographies. DH is 10.9 per cent = 100 * (12,469 / 113,465). DF is 56.3 per cent = 100 * (63,867 / 113,465). The subsequent aggregation of 2001 OAs as the building brick geography, has allowed the derivation of 2001 Wards and Districts too.

• GCT02, allows the conversion from 1991 SAS Wards (9,527 units) to 2001 CAS Wards (8,850 units) in England and Wales (defined and constructed by Norman, 2007a). This GCT has been implemented to convert SOCPOP values in 1991 Wards to their appropriate 2001 Wards. DH is 53.8 per cent = 100 * (5,129 / 9,527). DF is 88.4 per cent = 100 * (8,424 / 9,527).

• GCT03, allows the conversion from 1991 SAS Wards (9,527 units) to 1991 LBS Wards (9,365 units) in England and Wales (defined and constructed by Simpson, 2007a). This GCT is used as a lookup table to match EDs from census table S06 to census table L06. For the conversion ED data from the SAS has been aggregated to the Wards they comprise. In most cases, the correspondence between SAS and LBS Wards is 1:1, although due to more stringent confidentiality restrictions in SAS, more than one SAS Ward is further aggregated to a single LBS Ward. Since the correspondence is identical except where PART II: METHODOLOGY 126 Chapter 3: Notation, data and tools

some of the SAS Wards have been amalgamated to form LBS Wards (in this case, the source units are wholly contained within single target units) the DH and DF is 100 per cent.

• GCT04, allows the conversion from 1991 SAS Wards (9,527 units) to 2001 Districts (376 units) in England and Wales (defined and constructed by Simpson, 2007b). This GCT has been derived from GCT01 to convert OPCS student transfers by age and sex from 1991 to 2001 Districts, separately for additions and removals. DH is 96.8 per cent = 100 * (9,223 / 9,527). DF is 99.8 per cent = 100 * (9,512 / 9,527).

• GCT05, allows the conversion from 1991 Districts (403 units) to 2001 Districts (376 units) in England and Wales (defined and constructed by Simpson, 2007c). This GCT has been derived from GCT01 to help transferring the 1991 student population from vacation to termtime address. DH is 65.5 per cent = 100 * (264 / 403). DF is 99.2 per cent = 100 * (400 / 403).

• GCT06, allows the conversion from 2001 CAS Wards (8,850 units) to 2001 ST Wards (8,800 units) in England and Wales (defined and constructed by Hayes, 2006). This GCT is used as a lookup table to transfer the latest mid2001 population estimates from CAS Wards to ST Wards. Although in most cases the correspondence between CAS and ST Wards is 1:1, more than one CAS Ward is merged to a single ST Ward to avoid data disclosure. Because the correspondence is identical except where some of the CAS Wards have been amalgamated to form ST Wards, the DH and DF is 100 per cent.

• GCT07, allows the conversion from 2001 OAs (3,127 units) to 2004 electoral Wards (40 units) in Birmingham (defined and constructed by Norman, 2007b). This GCT has been used to transfer data from the smallest 2001 Census geographies to the current electoral Wards in PART II: METHODOLOGY 127 Chapter 3: Notation, data and tools

the District of Birmingham. DH is 92.8 per cent = 100 * (2,903 / 3,127). DF is 98.4 per cent = 100 * (3,076 / 3,127).

Assuming that the degree of hierarchy and degree of fit give an accurate indication of the extent to which the data conversion does not allocate whole units, it is clear that the smaller the source unit relative to the target unit, the higher the degrees of hierarchy and fit. For example, the conversion from 1991 SAS Wards to 2001 Districts, or 2001 OAs to 2004 electoral Wards give the best fit, whilst the ED to OA conversion has the poorest fit. Even conversions for geographies that are approximately equal can be show a low degree of fit as demonstrated by the conversion from 1991 SAS Wards to 2001 CAS Wards, or 1991 Districts to 2001 Districts. The measures of fit are properties of the entire GCT. In some cases, target units may be the aggregation only of whole source units. For example, the conversion from 1991 SAS Wards to 1991 LBS Wards, or 2001 CAS Wards to 2001 ST Wards.

Although there is no general level of error that should be expected, this will largely depend on the construction of the conversion table, the geographies involved, the weighting criterion and its correlation with the data.

The calculation of the degree of fit has shown the proportion of data that is not subject to estimation and, therefore, it is an important measure of reliability of each value output from data conversion for that target unit. For example, if 99 per cent of a source unit is allocated in one target unit and 1 per cent in another, the degree of fit is higher than if a source unit is shared equally between two target units (50 per cent in each). Therefore, when GCTs are used, unless the table is hierarchical (i.e. all weights equal to 1) uncertainty is added to the conversion.

As seen earlier, depending on the geographies involved, the degree of fit can differ substantially. For example, the GCT used to convert data from EDs to OAs shows a poor fit, partly because source units are not wholly contained within single target units. Since the degree of fit is a measure of reliability of each value output from data conversion, it is assumed that the OA results are PART II: METHODOLOGY 128 Chapter 3: Notation, data and tools

subject to the greatest amount of approximation. Therefore, the OA results are not to be used for comparison over time but to allow versatile aggregation into other areal units.

Simpson (2002c) recommends that the GCT weighting criterion should be correlated with the data being converted. Within this context, the amount of approximation depends on how well the data within the source units are correlated to the weights (which are based on the number of residential addresses). For 1991, Figure 3.4 shows a scatterplot of the number of residential addresses per Ward against the SAS Ward populations, a relationship with a correlation of 0.833. The results show a close correlation of the weighting criterion to the variable being converted, thus representing that the estimation of data will be generally unbiased.

Figure 3.4: Relationship between address counts and 1991 Ward SAS populations

PART II: METHODOLOGY 129 Chapter 3: Notation, data and tools

3.6: Conclusions

The main research methods and data sources that are extensively used throughout the methodology have been reviewed in this chapter. The aspects relating to the specification of adjustments to create a consistent population time series have been clarified. The general notation and a summary of data sources that are used for the creation of population time series have also been presented. In addition, the chapter has described the use of statistical (IPF) and geographical tools (GCTs) as a way to produce consistent midyear estimates over time and space. In the next chapter, the methods used to create mid2001 population estimates for each District in England and Wales by single year of age, sex and ethnic group are described. PART II: METHODOLOGY 130

Chapter 4: Mid-2001 population estimates for Districts in England and Wales

4.1: Introduction

This chapter describes the methodology used for the creation of mid2001 population estimates for Districts in England and Wales by ethnic group and with detail of age and sex. The stages involved for the creation of such estimates are explained in Section 4.2. Section 4.3 provides background information on the mid2001 population estimates for Districts in England and Wales without an ethnic group dimension published in September 2004 by ONS, and the mid2001 population estimates by ethnic group for Districts in England published in August 2006 by ONS as experimental statistics. Section 4.4 details the data sources used to create the desired population estimates and Section 4.5 explains the methods used to derive these estimates in two separate stages. Section 4.6 gives a validation of the results and, finally, a summary table of the issues, strategies and methods used to deal with the four problems are provided in Section 4.7.

4.2: Objective and overview

The objective is to create mid2001 population estimates by single year of age, sex and ethnic group using the 2001 Census geography for each District in England and Wales.

These estimates take into account timing between Census day and midyear and extra nonresponse not included in the published census outputs as described in Sections 2.3.3 and 2.4.2 respectively. PART II: METHODOLOGY 131 Chapter 4: Mid2001 population estimates for Districts in England and Wales

The creation of these mid2001 population estimates has been implemented in two stages:

1. Distribute to each ethnic group the timing adjustment to the published census counts. For Districts in England, this adjustment is taken directly from ONS as experimental statistics published in August 2006, and contains information on natural change and net migration (Large and Ghosh, 2006). For Districts in Wales, the mid2001 population estimates by age and sex including timing and published by ONS in November 2002 are accepted.

2. Distribute to each ethnic group the extra nonresponse not included in the ONC. The difference between the mid2001 population estimates published in November 2002 and the mid2001 population estimates published in September 2004 by ONS refers to extra nonresponse not included in census output. For England and Wales, ONS imputation rates have been applied to allocate this extra nonresponse.

The second stage constitutes an alternative approach to allocate extra non response to that made by ONS for Districts in England (Large and Ghosh, 2006) as experimental statistics. A comparison is undertaken to examine the differences in Section 4.6 when validating the results.

Figure 4.1 illustrates the transition with two stages used to create mid2001 population estimates by single year of age, sex and ethnic group for Districts in England and Wales separately.

PART II: METHODOLOGY 132 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.1: Transition to create full mid-2001 population estimates for Districts in England and Wales

England Wales

2001 Census for Districts (Com. Table C0533)

Add timing by single year of age, sex and Stage 1 ethnic group

District mid-2001 District mid-2001 (Nov02) (Nov02)

Add extra non- Add extra nonresponse to mid-2001 Stage 2 response to mid-2001

District mid-2001 District mid-2001 (Sep04) (Sep04) -final estimate- -final estimate-

4.3: Background

In light of the latest mid2001 population estimates by single year of age and sex for Districts in England and Wales published in September 2004 by ONS, previous mid2001 population estimates published in November 2002 are revised so that a consistent series can be achieved.

The revision between November 2002 and September 2004 to the mid2001 population estimates is due to estimates of extra nonresponse, not included in the imputed nonresponse contained in the census outputs. Section 2.4.2 described the three projects to produce an extra nonresponse and to derive final mid2001 population estimates for Districts, which included the PART II: METHODOLOGY 133 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Longitudinal Study adjustment, the Local Authorities Studies adjustment and the Manchester and Westminster Matching Studies (ONS, 2004b; 2004c).

How should this extra population be allocated to ethnic groups? ONS have made their own allocation (Large and Ghosh, 2006) and this project has created an alternative approach.

The method used by ONS (Large and Ghosh, 2006) assumes that the ethnic composition of this adjustment is the same as the ethnic composition existing in the census in each District by age and sex. Therefore, the method assumes that the extra nonresponse is the same for each ethnic group and is allocated by taking into account the characteristics of the population as a whole.

An alternative approach used in this project is based on the implementation of ONS imputation rates. As seen earlier in Section 2.4.2, people identified as not counted in 2001 were imputed to produce an adjusted total on which the final Census results were based. This strategy based on the ONC process, produced imputation rates by key variables, including sex and ethnic group for each District in England and Wales (ONS, 2001a). This information is assumed to apply for the allocation of extra nonresponse.

Figure 4.2 displays the results of ONS imputation rates by sex and ethnic group for England and Wales. This figure clearly illustrates how nonresponse in the 2001 Census was more prevalent among males than females and that nonresponse was considerably higher among ethnic groups other than White. Another aspect of nonresponse is that it did not occur uniformly across all areas, with some Districts with higher nonresponse than others. For example, Figure 4.3 and Figure 4.4 display the ONS imputation rates in the metropolitan Districts of Manchester and Birmingham respectively. As expected, these two figures exemplify how the patterns of census non response were particularly high in urban Districts, where characteristics known to be related to census nonresponse are more likely to be found such as higher proportions of ethnic minority groups, unemployment and multiple occupied dwellings (Simpson and Middleton, 1997). PART II: METHODOLOGY 134 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.2: ONS imputation rates by sex and ethnic group in England and Wales

Figure 4.3: ONS imputation rates by sex and ethnic group in Manchester District

Source: http://www.statistics.gov.uk/census2001/imputation_rates_by_variable.asp PART II: METHODOLOGY 135 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.4: ONS imputation rates by sex and ethnic group in Birmingham District

Figure 4.5: ONS imputation rates by sex and ethnic group in East Dorset District

Source: http://www.statistics.gov.uk/census2001/imputation_rates_by_variable.asp PART II: METHODOLOGY 136 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.5 shows contrarily how rural areas such as the District of East Dorset have a very different picture of nonresponse, with much lower imputation rates by ethnic group and sex.

Taking this information into account, one could argue that the patterns of census nonresponse found by ONS by sex and ethnic group in each District in England and Wales could also apply to those extra missed. Within this context, a method has been devised to allocate the extra nonresponse between ethnic groups using the ONS imputation rates. The assumptions underlying this approach are that:

• Some groups are more likely to be missed than others, for example ethnic minority groups.

• The characteristics of extra nonresponse not included in the census output are likely to be similar to nonresponse identified through the ONC process.

In addition to nonresponse, the timing adjustment with ageing is taken into account as described in Section 2.3.3. For this purpose, the timing adjustment by single year of age, sex and ethnic group from ONS as experimental statistics is accepted (Large and Ghosh, 2006). This adjustment was applied using a special Census commissioned table by ethnic group with the same detail of age and sex for each District in England. The timing adjustment from ONS contains information separately for births, deaths and migration between Census day and midyear for Districts in England. The main characteristics of this adjustment are as follows:

• Fertility rates were applied before allowing for mortality and migration. These were applied to the mean of the starting population and the agedon population for each single year of age. In this approach, some relevant aspects are: (1) the differences in ethnic group agefertility profiles by District were not modelled; (2) the allocation of births by ethnic group of mother to ethnic group of infant was based on extrapolation from patterns recorded in the Census. PART II: METHODOLOGY 137 Chapter 4: Mid2001 population estimates for Districts in England and Wales

• Mortality rates were applied to the population before taking into account migration. These were the same for each ethnic group within a particular agesexDistrict group.

• Internal migration was calculated by taking into account: (1) the propensity to migrate by ethnic group; (2) the effect of different agesex structures within District populations; (3) differences in migration levels and patterns from each District; and (4) differences in the propensity of a particular ethnic group to migrate to a specific District.

• Crossborder migration covered migration between England and the rest of the UK. The propensity to migrate to Scotland and Wales was assumed to be equal for each ethnic group. For Northern Ireland, it was assumed that the ethnic composition of migration was similar to the estimated composition of the inflow, thus the White Irish group was expected to be higher than the rest of ethnic groups. The ethnic composition of separate flows from Scotland, Wales and Northern Ireland were assumed to be the same as those recorded in the 2001 Census.

• International migration was modeled by taking into consideration the International Passenger Survey (IPS) and the 2001 Census. The latter was used to translate country of birth data of new migrants to ethnicity. In addition, flows of asylum seekers were estimated using Home Office data on the nationality of the applicants and dependants. The flows to Ireland were assumed to have a similar ethnic composition as flows from Ireland.

These methods are discussed in detail by Large and Ghosh (2006). This is clearly a major work by ONS which constitutes an important input to this project, one that is difficult to supersede within the scope of this doctoral research. PART II: METHODOLOGY 138 Chapter 4: Mid2001 population estimates for Districts in England and Wales

For Districts in Wales, the timing adjustment by single year of age and sex included by ONS in the mid2001 population estimates published in November 2002 is accepted (ONS, 2002a).

4.4: Data sources

The following data sets have been used to derive mid2001 population estimates for each District in England and Wales by single year of age, sex and ethnic group.

1. C01,d01E,a91,s,e 2001 Census by single year of age, sex and ethnic group for Districts in England, from ONS Commissioned Census table C0533.

2. C01,d01W,a91,s,e 2001 Census by single year of age, sex and ethnic group for Districts in Wales, estimated from the 22 age categories of Census table ST101 by demographic smoothing and constrained to the allgroups total (Simpson, 2005).

3. T01,d01E,a91,s,e 2001 timing adjustment from Census day to midyear by single year of age, sex and ethnic group for Districts in England, from ONS experimental statistics (as published in August 2006).

I 4. P 01,d01E,a91,s,e Mid2001 population estimates by single year of age, sex and ethnic group for Districts in England, from ONS experimental statistics unit (as published in November 2002).

I 5. P 01,d01W,a91,s,● Mid2001 population estimates by single year of age and sex for Districts in Wales, from ONS (as published in November 2002). PART II: METHODOLOGY 139 Chapter 4: Mid2001 population estimates for Districts in England and Wales

6. P01,d01E,a91,s,e Mid2001 population estimates by single year of age, sex and ethnic group for Districts in England, from ONS experimental statistics unit (as published in August 2006).

7. P01,d01,a91,s,● Mid2001 population estimates by single year of age and sex, without an ethnic group dimension for Districts in England and Wales, from ONS (as published in September 2004).

8. R01,d01,●,s,e Imputation rates for Districts in England and Wales, from ONS. Available at: http://www.statistics.gov.uk/census2001/imputation_rates_ by_variable.asp

4.5: Method

Stage 1. The timing adjustment is added to the published census counts with detail of single year of age, sex and ethnic group for each District in England.

In this stage, mid2001 population estimates by single year of age, sex and ethnic group for each District in England, consistent with (i.e. adding up to) the population estimates published by ONS in November 2002, are created. For this purpose, data published by ONS experimental statistics in August 2006 for Districts in England are employed.

The method uses census output derived from a commissioned table (C0533) and information on timing from ONS experimental statistics containing the demographic change (births, deaths and migration) between Census day (29th April) and midyear (30th June).

First, the census output is aged on to midyear. This procedure is implemented separately for those aged 0, 189 and 90 and over. Where the expression lag is used this refers to the previous age. PART II: METHODOLOGY 140 Chapter 4: Mid2001 population estimates for Districts in England and Wales

For those aged 0:

A01,d01E,a91,s,e = (1(62/365)) * C01,d01E,a91,s,e

For those aged 189:

A01,d01E,a91,s,e = (62/365) * lag(C01,d01E,a91,s,e) + (1(62/365)) * C01,d01E,a91,s,e

For those aged 90:

A01,d01E,a91,s,e = (62/365)* lag(C01,d01E,a91,s,e) + C01,d01E,a91,s,e

Second, the demographic change between Census day and midyear is applied to the aged census population. The output is consistent with the mid 2001 population estimate before extra nonresponse (i.e. as published by ONS in November 2002).

I P 01,d01E,a91,s,e = A01,d01E,a91,s,e + T01,d01E,a91,s,e

Since the adjustment of timing is not available for Wales from ONS experimental statistics, the mid2001 population estimates by single year of age and sex as published by ONS in November 2002 are accepted. This assumes the same timing adjustment for each ethnic group, proportionally for each agesexDistrict category.

Stage 2. Extra nonresponse is added to mid2001 population estimates by single year of age, sex and ethnic group for each District in England and Wales.

In this stage, mid2001 population estimates by single year of age, sex and ethnic group for each District in England and Wales, consistent with the population estimates published by ONS in September 2004, are created.

The method uses differential ethnic group nonresponse rates to allocate a total nonresponse to each ethnic group. The difference between the initial midyear population estimates (November 2002) and the latest mid2001 PART II: METHODOLOGY 141 Chapter 4: Mid2001 population estimates for Districts in England and Wales

population estimates (September 2004) without an ethnic group dimension is either very small or is dominated by nonresponse. The objective is to distribute the difference to ethnic groups. For this purpose, the nonresponse rate differences estimated by ONS within census output are maintained within each agesex group.

First, the difference between the revised population estimate at midyear, and the previous population estimate at midyear aggregated across ethnic groups, is computed. This gives the total extra nonresponse by single year of age and sex for each District in England and Wales.

I N01,d01,a91,s,● = P01,d01,a91,s,● – P 01,d01,a91,s,●

Second, an initial value for nonresponse at each age group is computed, using the allage ethnicspecific nonresponse rate for every age group, and the previous population estimate at midyear with an ethnic group dimension. This gives the correct distribution between ethnic groups but not the correct level.

I I N 01,d01,a91,s,e = P 01,d01,a91,s,e * R01,d01,●,s,e

From these initial values the distribution of nonresponse by ethnic group is computed, adding to 1 within each agesexDistrict category.

I I N 01,d01,a91,s,e / N 01,d01,a91,s,●

Finally, the ethnic group distribution of nonresponse to each estimate of total nonresponse is applied. The result is added to the mid2001 population estimates by single year of age, sex and ethnic group consistent with that published by ONS in November 2002.

I I I P01,d01,a91,s,e = P 01,d01,a91,s,e + (N01,d01,a91,s,● * (N 01,d01,a91,s,e / N 01,d01,a91,s,●))

Occasionally, the difference between the initial mid2001 population estimates (November 2002) and final mid2001 population estimates (September 2004) without an ethnic group dimension gives negative values. As a consequence, PART II: METHODOLOGY 142 Chapter 4: Mid2001 population estimates for Districts in England and Wales

the method outlined above to allocate extra nonresponse is not valid in some cases as the resulting population can be negative.

I IF (P 01,d01,a91,s,e < N01,d01,a91,s,●) P01,d01,a91,s,e < 0

On the basis that ONS decided to apply a measure of rounding to all cells to either zero or a multiple of 3 in all census tables produced for England and Wales, this issue is likely to appear particularly for small populations (ONS, 2006c). The recoding of small cell counts is likely to add approximation to all analysis as discussed by Stillwell and DukeWilliams (2007).

For these cases, a different approach is used to accommodate the difference to ethnic groups. The method consists of spreading the minus entries to each ethnic group in proportion to their existing population and not giving weight to nonresponse.

I I I P01,d01,a91,s,e = P 01,d01,a91,s,e + (N01,d01,a91,s,● * (P 01,d01,a91,s,e / P 01,d01,a91,s,●))

The implementation of this procedure allows us to deal with the positive and negative entries separately whilst making the adjustment for nonresponse consistent with the latest mid2001 population estimates. However, neither of the approaches can share out the adjustment when there is no population according to the initial mid2001 population estimates, which is also assumed to take place as a result of rounding cells to zero. Nonetheless, there is only one case of the latter issue. It is located in the District of the Isles of Scilly and refers to two females aged 89. Since the Isles of Scilly are predominantly White British, the solution adopted is to add the adjustment to the British group.

I I IF (P 01,d01,a91,s,● = 0 and N01,d01,a91,s,● > 0) P 01,d01,a91,s,e = N01,d01,a91,s,●

4.6: Validation

This section provides a variety of checks to ensure that the results are consistent with the latest mid2001 population estimates published by ONS. PART II: METHODOLOGY 143 Chapter 4: Mid2001 population estimates for Districts in England and Wales

This validation process is also used in later chapters referring to areas smaller than Districts to ensure that all results are fully consistent with one another.

The data set resulting from the procedures described above has 1,094,912 cases, one for each combination of:

• 2001 Districts in England (354) and Wales (22) = 376

• Age (90 single years and 90 and over) = 91

• Sex (Male and Female) = 2

• 2001 Ethnic groups as recorded in the census = 16

Table 4.1 shows the adjustments of timing and extra nonresponse included to the 2001 Census by ethnic group in England. For simplicity ethnic groups are not disaggregated by age and sex. The table indicates how the timing transfer adjustment overall adds nearly 41,000 people to the initial census population due to births and positive net migration between Census day and midyear. The majority of groups experience a gain in population during this period with the exception of the White Irish group with a population loss as a result of emigration (more detailed information about timing for each component of change is given in Chapter 10). Extra nonresponse represents the largest adjustment adding about 269,000 people to initial mid2001 population estimates published in November 2002 in England. The results display mid2001 population estimates: (1) using extra nonresponse as published by ONS experimental statistics (Large and Ghosh, 2006); and (2) using ONS imputation rates to allocate the extra nonresponse (as shown in Stage 2). Both estimates of extra nonresponse sum to the same total, and it is consistent with the final population for England as published in September 2004 by ONS. However, clear differences are found when compared by each ethnic group total. Because ONS imputation rates are differential by ethnic group, the differences show a much higher allocation of extra nonresponse to ethnic groups other than White, as opposed to the scaling method used by ONS experimental statistics. PART II: METHODOLOGY 144 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Table 4.1: 2001 Census and adjustments by ethnic group in England

Ethnic group Census 16 categories 2001 as Timing Mid2001 Extra non Mid2001 Extra non Mid2001 published transfer Nov02 response Sep04 response Sep04 (1) (1) (2) (2) 1 White British 42,747,136 1,103 42,748,239 180,156 42,928,395 152,306 42,900,546 2 White Irish 624,081 2,006 622,075 6,771 628,846 5,565 627,640 3 Other White 1,308,134 11,429 1,319,563 22,641 1,342,204 20,991 1,340,554 4 Mixed W/Caribbean 231,323 1,380 232,703 1,685 234,388 1,690 234,394 5 Mixed W/African 76,538 786 77,324 951 78,275 888 78,212 6 Mixed W/Asian 183,870 1,589 185,459 1,754 187,213 1,447 186,906 7 Other Mixed 151,427 1,303 152,730 1,603 154,333 1,453 154,183 8 Indian 1,028,724 4,205 1,032,929 11,950 1,044,879 17,999 1,050,928 9 Pakistani 706,740 4,255 710,995 8,320 719,315 15,178 726,174 10 Bangladeshi 275,414 1,543 276,956 4,209 281,165 7,003 283,960 11 Other Asian 237,920 1,801 239,721 3,977 243,698 3,410 243,131 12 Black Caribbean 561,389 599 561,988 7,598 569,586 12,236 574,224 13 Black African 475,710 5,748 481,458 9,430 490,887 17,428 498,886 14 Other Black 95,552 430 95,981 1,315 97,296 1,386 97,367 15 Chinese 220,765 2,973 223,738 3,192 226,930 5,936 229,674 16 Other 214,783 3,736 218,519 3,816 222,334 4,449 222,967 Total 49,139,505 40,873 49,180,378 269,368 49,449,746 269,368 49,449,746

NB: (1) Estimates taken directly from ONS experimental statistics; (2) estimates using ONS imputation rates.

Table 4.2 shows a comparison for the metropolitan Districts of Manchester and Birmingham. Similarly, the same pattern of allocation can be observed, with a greater allocation of extra nonresponse to the White British and White Irish groups when using the scaling method from ONS experimental statistics. These results give evidence of the effect of using the local proportion of the population as a whole, which differs substantially from using ONS imputation rates.

PART II: METHODOLOGY Chapter 4: Mid2001 population estimates for Districts in England and Wales

Table 4.2: 2001 Census and adjustments by ethnic group in two metropolitan Districts

Manchester Birmingham

Ethnic group Census Census 16 categories 2001 as Timing Mid2001 Extra non Mid2001 Extra non Mid2001 2001 as Timing Mid2001 Extra non Mid2001 Extra non Mid2001 published transfer Nov02 response Sep04 response Sep04 published transfer Nov02 response Sep04 response Sep04 (1) (1) (2) (2) (1) (1) (2) (2) 1 White British 292,498 1,292 291,206 23,641 314,848 21,237 312,443 641,345 1,536 639,809 5,795 645,604 3,591 643,400 2 Whire Irish 14,826 164 14,662 1,165 15,827 798 15,460 31,467 190 31,277 183 31,459 113 31,390 3 Other White 10,689 11 10,678 994 11,672 1,361 12,039 14,594 81 14,675 214 14,889 237 14,913 4 Mixed W/Caribbean 5,306 19 5,287 350 5,636 409 5,696 15,644 5 15,649 101 15,749 139 15,788 5 Mixed W/African 2,407 18 2,389 173 2,563 231 2,620 1,443 2 1,445 13 1,459 18 1,463 6 Mixed W/Asian 2,455 5 2,450 187 2,637 241 2,691 6,316 22 6,338 54 6,392 57 6,394 7 Other Mixed 2,499 14 2,485 185 2,670 258 2,743 4,545 6 4,551 40 4,591 58 4,609 8 Indian 5,815 33 5,848 501 6,350 661 6,509 55,749 110 55,639 606 56,245 879 56,517 9 Pakistani 23,112 40 23,072 1,747 24,819 2,009 25,081 104,018 60 103,958 1,179 105,137 2,230 106,188 10 Bangladeshi 3,644 6 3,638 271 3,909 441 4,078 20,836 2 20,834 228 21,062 423 21,257 11 Other Asian 3,313 9 3,322 271 3,593 314 3,636 10,088 5 10,093 126 10,219 186 10,279 12 Black Caribbean 9,043 65 8,978 666 9,645 1,101 10,080 47,832 185 47,647 428 48,075 795 48,442 13 Black African 6,658 69 6,727 544 7,272 1,017 7,744 6,205 135 6,340 90 6,430 203 6,542 14 Other Black 2,034 12 2,022 147 2,170 209 2,232 5,801 15 5,786 53 5,839 79 5,865 15 Chinese 5,132 5 5,137 459 5,595 859 5,996 5,110 43 5,153 77 5,230 120 5,273 16 Other 3,381 35 3,416 294 3,710 451 3,867 6,112 54 6,166 96 6,262 155 6,321 Total 392,812 1,493 391,319 31,596 422,915 31,596 422,915 977,105 1,746 975,359 9,283 984,642 9,283 984,642

NB: (1) Estimates taken directly from ONS experimental statistics; (2) estimates using ONS imputation rates. PART II: METHODOLOGY 146 Chapter 4: Mid2001 population estimates for Districts in England and Wales

The following figures are used to further illustrate the two different methods of allocation of extra nonresponse in the metropolitan Districts of Manchester and Birmingham as described above.

Figure 4.6: 2001 percentage adjustment due to extra non-response using ONS experimental statistics by age, sex and ethnic group in Manchester District

Figure 4.6 and Figure 4.7 display the method used by ONS experimental statistics to allocate extra nonresponse. The results show no differences between ethnic groups, thus corroborates the fact that the scaling method used by ONS experimental statistics only takes the characteristics of the population as a whole. As expected, the allocation of extra nonresponse is mainly concentrated among young male adults, principally because they were the groups estimated to have been missed by the Census. The largest PART II: METHODOLOGY 147 Chapter 4: Mid2001 population estimates for Districts in England and Wales

adjustments are found among males in their late twenties and early thirties, with increases over the initial mid2001 population estimates of about 15 and 8 per cent in the metropolitan Districts of Manchester and Birmingham respectively.

Figure 4.7: 2001 percentage adjustment due to extra non-response using ONS experimental statistics by age, sex and ethnic group in Birmingham District

Figure 4.8 and Figure 4.9 display the results after using the ONS imputation rates as an alternative approach. The output confirms that extra nonresponse is allocated taking into consideration differential nonresponse between ethnic groups. As predicted the allocation of extra nonresponse is focused on young male adults, where the largest differences between ethnic groups occur. PART II: METHODOLOGY 148 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.8 give evidence of the large adjustments of extra nonresponse in Manchester as a result of the Local Authorities Studies adjustment and Matching Studies (ONS, 2004b; 2004c). As expected, the largest adjustments are also found among young males, although females also receive a significant share of the adjustment in this District. The differences between ethnic groups are large, particularly for young groups. The lowest adjustments correspond to the White Irish and White British groups, whereas the largest adjustments are found among ethnic minority groups such as the Chinese and the Black Caribbean groups, with increases over the initial mid2001 population estimates of more than 30 per cent for those in their late twenties and early thirties.

Figure 4.8: 2001 percentage adjustment due to extra non-response using ONS imputation rates by age, sex and ethnic group in Manchester District

PART II: METHODOLOGY 149 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.9 shows the equivalent adjustment of extra nonresponse in the District of Birmingham. The results corroborate earlier observations, with even clearer differences in the allocation of extra nonresponse between ethnic groups. In this District, the largest percentage adjustments are also found among young male adults, with the largest adjustments among the Black African, Pakistani, Bangladeshi and Black Caribbean, with increases over the initial mid2001 population estimates of more than 15 per cent.

Figure 4.9: 2001 percentage adjustment due to extra non-response using ONS imputation rates by age, sex and ethnic group in Birmingham District

Table 4.3 shows the adjustment of extra nonresponse by ethnic group in Wales to the initial mid2001 population estimates without an ethnic group dimension published by ONS in November 2002. The table indicates how this PART II: METHODOLOGY 150 Chapter 4: Mid2001 population estimates for Districts in England and Wales

adjustment adds about 7,000 people to the initial mid2001 population estimates. Since information about timing by ethnic group has not been published for Wales, the table shows only the allocation of extra nonresponse using ONS imputation rates as described in Stage 2.

Table 4.3: 2001 Census and adjustments by ethnic group in Wales

Ethnic group Census 16 categories 2001 as Mid2001 Extra non Mid2001 published Nov02 response Sep04 (2) (2) 1 White British 2,786,562 n/a 6,112 2,792,843 2 Whire Irish 17,700 n/a 58 17,770 3 Other White 37,208 n/a 90 37,295 4 Mixed W/Caribbean 6,021 n/a 36 6,050 5 Mixed W/African 2,414 n/a 19 2,430 6 Mixed W/Asian 5,002 n/a 19 5,016 7 Other Mixed 4,234 n/a 18 4,249 8 Indian 8,270 n/a 156 8,423 9 Pakistani 8,238 n/a 180 8,412 10 Bangladeshi 5,422 n/a 113 5,528 11 Other Asian 3,437 n/a 26 3,460 12 Black Caribbean 2,599 n/a 27 2,626 13 Black African 3,719 n/a 64 3,781 14 Other Black 766 n/a 7 773 15 Chinese 6,311 n/a 104 6,416 16 Other 5,118 n/a 49 5,163 Total 2,903,023 2,903,156 7,076 2,910,232

NB: (2) Estimates using ONS imputation rates. Not available (n/a) is used where there exists a lack of data from ONS.

Table 4.4 shows the adjustments of ageing and timing included to the 2001 Census by age and sex for allgroups in England. Although detail of single year of age has been derived, for simplicity age is aggregated into fiveyear age groups. The effect of ageing between Census and midyear sums to 0 across all ages, however, some age groups are more affected than others. For example, it reduces the 0 year olds (some become age 1) and adds to the older groups. It is also noticeable the effect on different cohorts, for example for those aged 5054 (which refer to postwar cohorts) as well as younger groups on their forties and thirties (which mark the start and end of the baby PART II: METHODOLOGY 151 Chapter 4: Mid2001 population estimates for Districts in England and Wales

boom of the 1960s). Overall the timing adjustment has a positive impact over the initial census population, adding about 41,000 people.

Table 4.5 shows the adjustment of extra nonresponse included in the mid 2001 population estimates published by ONS in November 2002 by age and sex for allgroups in England. The largest adjustments due to extra non response as expected are found among males, particularly for those aged 25 34, whose population increase is substantial. As shown in the table, the distribution of extra nonresponse using both methods is consistent by age and sex, thus giving the same results when aggregated for allgroups.

Finally, Figure 4.10 shows those Districts with greatest adjustments between the 2001 Census as published and the mid2001 population estimates published in September 2004. As expected, the two Districts which receive the largest adjustments are Manchester and Westminster as a result of extra nonresponse included through the Matching Studies (ONS, 2004c). Other Districts which appear to have significant adjustments correspond to dense urban areas generally strongly influenced by recent migration, high unemployment rates and poor housing.

PART II: METHODOLOGY Chapter 4: Mid2001 population estimates for Districts in England and Wales

Table 4.4: 2001 Census and adjustments of ageing and timing by age and sex for all-groups in England

Age groups

18 categories Census 2001 Ageing Census 2001 Timing Mid2001 as published with ageing adjustment Nov02

Males Females Total Males Females Total Males Females Total Males Females Total Males Females Total 1 04 1,497,982 1,428,115 2,926,097 53,306 50,808 104,114 1,444,676 1,377,307 2,821,983 49,623 47,535 97,159 1,494,300 1,424,842 2,919,142

2 59 1,599,899 1,522,730 3,122,629 3,493 3,370 6,863 1,596,406 1,519,360 3,115,766 240 274 34 1,596,646 1,519,086 3,115,732

3 1014 1,653,106 1,576,038 3,229,144 2,154 1,948 4,103 1,655,260 1,577,986 3,233,247 254 194 59 1,655,514 1,577,792 3,233,306

4 1519 1,550,710 1,481,854 3,032,564 4,470 2,750 7,221 1,555,180 1,484,604 3,039,785 81 1,620 1,539 1,555,261 1,482,984 3,038,245

5 2024 1,468,757 1,483,787 2,952,544 2,209 42 2,252 1,470,966 1,483,829 2,954,796 2,914 1,303 4,218 1,473,880 1,485,133 2,959,013

6 2529 1,603,735 1,665,082 3,268,817 12,364 13,519 25,884 1,591,371 1,651,563 3,242,933 4,940 4,178 9,118 1,596,311 1,655,741 3,252,051

7 3034 1,857,012 1,928,564 3,785,576 5,267 4,823 10,090 1,851,745 1,923,741 3,775,486 2,923 1,652 4,575 1,854,668 1,925,393 3,780,061

8 3539 1,916,012 1,965,330 3,881,342 2,603 3,404 6,008 1,918,616 1,968,734 3,887,350 847 577 1,424 1,919,463 1,969,311 3,888,774

9 4044 1,719,352 1,741,564 3,460,916 7,541 8,231 15,773 1,726,893 1,749,795 3,476,689 576 569 1,144 1,727,469 1,750,364 3,477,833

10 4549 1,541,930 1,569,737 3,111,667 3,944 3,585 7,529 1,545,874 1,573,321 3,119,195 373 65 438 1,545,501 1,573,256 3,118,757

11 5054 1,677,340 1,705,264 3,382,604 11,911 11,601 23,511 1,665,429 1,693,663 3,359,092 941 593 1,534 1,664,488 1,693,070 3,357,558

12 5559 1,379,622 1,406,030 2,785,652 22,586 22,189 44,775 1,402,208 1,428,219 2,830,427 1,775 1,211 2,986 1,400,433 1,427,008 2,827,441

13 6064 1,174,506 1,217,263 2,391,769 1,902 1,368 3,270 1,176,408 1,218,631 2,395,039 2,448 1,441 3,889 1,173,960 1,217,189 2,391,150

14 6569 1,034,795 1,119,270 2,154,065 5,147 2,939 8,086 1,039,942 1,122,209 2,162,151 3,488 2,105 5,593 1,036,454 1,120,104 2,156,558

15 7074 886,711 1,061,979 1,948,690 6,122 3,103 9,225 892,832 1,065,082 1,957,915 5,210 3,806 9,016 887,623 1,061,276 1,948,899

16 7579 687,312 957,908 1,645,220 6,482 2,490 8,971 693,794 960,398 1,654,192 6,935 6,006 12,941 686,859 954,392 1,641,251

17 8084 408,926 697,106 1,106,032 11,494 13,427 24,921 420,420 710,533 1,130,952 6,521 7,341 13,862 413,899 703,191 1,117,091

18 85+ 265,067 689,111 954,178 9,685 18,645 28,330 274,752 707,756 982,508 8,001 16,991 24,992 266,751 690,765 957,516

Total 23,922,773 25,216,731 49,139,505 0 0 0 23,922,773 25,216,731 49,139,505 26,707 14,166 40,873 23,949,481 25,230,897 49,180,378

PART II: METHODOLOGY Chapter 4: Mid2001 population estimates for Districts in England and Wales

Table 4.5: Adjustment of extra non-response to mid-2001 (Nov-02) by age and sex for all-groups in England

Age groups

18 categories Extra Mid2001 Extra Mid2001

nonresponse Sep04 nonresponse Sep04 Males Females Total Males Females Total Males Females Total Males Females Total 1 04 2,421 2,276(1) 4,697 1,496,721 1,427,118(1) 2,923,839 2,421 2,276(2) 4,697 1,496,721 1,427,118 2,923,839(2)

2 59 2,349 2,707 5,056 1,598,995 1,521,793 3,120,788 2,349 2,707 5,056 1,598,995 1,521,793 3,120,788

3 1014 2,816 1,939 4,755 1,658,330 1,579,731 3,238,061 2,816 1,939 4,755 1,658,330 1,579,731 3,238,061

4 1519 3,205 3,550 6,755 1,558,466 1,486,534 3,045,000 3,205 3,550 6,755 1,558,466 1,486,534 3,045,000

5 2024 20,448 7,123 27,571 1,494,328 1,492,256 2,986,584 20,448 7,123 27,571 1,494,328 1,492,256 2,986,584

6 2529 64,024 4,392 68,417 1,660,335 1,660,133 3,320,468 64,024 4,392 68,417 1,660,335 1,660,133 3,320,468

7 3034 65,065 5,436 70,501 1,919,733 1,930,829 3,850,562 65,065 5,436 70,501 1,919,733 1,930,829 3,850,562

8 3539 26,081 4,117 30,198 1,945,544 1,973,428 3,918,972 26,081 4,117 30,198 1,945,544 1,973,428 3,918,972

9 4044 7,493 2,587 10,080 1,734,962 1,752,951 3,487,913 7,493 2,587 10,080 1,734,962 1,752,951 3,487,913

10 4549 7,233 2,977 10,210 1,552,734 1,576,233 3,128,967 7,233 2,977 10,210 1,552,734 1,576,233 3,128,967

11 5054 3,670 3,595 7,265 1,668,158 1,696,665 3,364,823 3,670 3,595 7,265 1,668,158 1,696,665 3,364,823

12 5559 2,871 2,472 5,343 1,403,304 1,429,480 2,832,784 2,871 2,472 5,343 1,403,304 1,429,480 2,832,784

13 6064 2,349 1,961 4,309 1,176,309 1,219,150 2,395,459 2,349 1,961 4,309 1,176,309 1,219,150 2,395,459

14 6569 1,906 1,632 3,538 1,038,360 1,121,736 2,160,096 1,906 1,632 3,538 1,038,360 1,121,736 2,160,096

15 7074 1,895 2,110 4,005 889,518 1,063,386 1,952,904 1,895 2,110 4,005 889,518 1,063,386 1,952,904

16 7579 1,282 2,194 3,476 688,141 956,586 1,644,727 1,282 2,194 3,476 688,141 956,586 1,644,727

17 8084 717 1,149 1,865 414,616 704,340 1,118,956 717 1,149 1,865 414,616 704,340 1,118,956

18 85+ 282 1,045 1,327 267,033 691,810 958,843 282 1,045 1,327 267,033 691,810 958,843 TotalNB: (1) Estimates216,106 taken 53,262 directly 269,368 from 24,165,587 ONS experimental 25,284,159 49,449,746 statistics; 216,106 (2) estimates 53,262 269,368 using 24,165,587 ONS imputation 25,284,159 49,449,746 rates. PART II: METHODOLOGY 154 Chapter 4: Mid2001 population estimates for Districts in England and Wales

Figure 4.10: Districts with greatest adjustments between census and mid-year in England and Wales

4.7: Conclusions and summary

This section has focused on the estimation of mid2001 population estimates by single year of age, sex and ethnic group for each 2001 District in England and Wales. For the creation of these mid2001 population estimates, whilst the timing adjustment from ONS experimental statistics has been accepted an alternative approach to allocate the extra nonresponse not included in census output has been implemented. The method makes use of the ONS imputation rates, thus assuming that the same information applies for the allocation of extra nonresponse. The results highlight substantial differences with the allocation of extra nonresponse made by ONS experimental statistics (Large and Ghosh, 2006), which takes into account the characteristics of the population as a whole.

Evidence from the ONS imputation rates suggests that nonresponse is differential between ethnic groups and varies between areas. This evidence is PART II: METHODOLOGY 155 Chapter 4: Mid2001 population estimates for Districts in England and Wales

supported by previous research on census nonresponse in the UK and other countries (Simpson and Middleton, 1997). Therefore, it is assumed that the method implemented in this project based on imputation rates produces plausible results. However, acceptability requires more than plausibility. When judging the acceptability of these estimates one should keep in mind that these are also experimental statistics. Since full consistency with the latest ONS midyear estimates by ethnic group prevails to ensure an integrated quality assurance for census users, the alternative allocation of extra non response should be seen as a way to test the usability of ONS imputation rates. Further evaluation of these estimates is given in Chapter 5 to create the equivalent estimates for Wards.

Table 4.6 gives a summary of the issues, strategies and methods used to solve the four problems reviewed in Chapter 2. These are presented in the order that they are dealt with in the estimation process.

PART II: METHODOLOGY Chapter 4: Mid2001 population estimates for Districts in England and Wales

Table 4.6: Summary to create full mid-2001 population estimates for Districts in England and Wales

Issues Strategies Methods / assumptions Ethnic group categories Not needed. Target categories are those None used in 2001 (16 categories). For Districts in England, ONS Commissioned Census table C0533 has single years of Age group categories Target categories are those used in 2001 age. For Wales, the 22 age categories of Census table ST101 are spread to single years (91 categories). of age to 89 and 90+, by demographic smoothing and then constrained to the single years of age published for the allgroups total.

Population definition Student transfer Not applicable. Students already at term None time address in 2001.

Timing Move from Census day to midyear (30th For Districts in England we have used components of change between Census day and June). midyear estimated by ONS for their experimental population estimates by single year of age, sex and with an ethnic group dimension. The ONS estimates of natural change, migration within England, migration with the rest of UK, international migration and ageing, are applied to the 2001 Census as a starting population.

For Wales, 2001 midyear estimates by single year of age and sex, without an ethnic group dimension, consistent with those released by ONS in September 2002, are used. This assumes the same timing adjustment for each ethnic group, proportionally for each agesexDistrict category.

Nonresponse Extra nonresponse is incorporated in ONS The difference between the initial midyear population estimates (November 2002) and District population estimates (September the latest midyear estimates (September 2004) from ONS is dominated by extra non 2004). response. This difference is taken from the ONS District population estimates.

The ONS method for England used in their experimental statistics assumes that ethnic group composition of nonresponse is the same as the population ethnic group composition for age and sex groups within each District.

For Wales, we have used ONS imputation rates to allocate this extra nonresponse, thus assuming differential nonresponse by age, sex and ethnic group.

Boundary harmonisation Not needed. Target geographies are those None used in 2001 Census output (376 Districts).

PART II: METHODOLOGY 157

Chapter 5: Mid-2001 population estimates for Wards in England and Wales

5.1: Introduction

This chapter describes the methodology used for the creation of mid2001 population estimates for Wards in England and Wales by ethnic group and with detail of age and sex. These estimates follow previous work undertaken in Chapter 4 with the equivalent District estimates. In this chapter, a method of disaggregating the District estimates to Wards is implemented. For this purpose, two sets of Districts estimates are used: (1) the District estimates consistent with that published by ONS experimental statistics in August 2006; and (2) the District estimates previously created in Chapter 4 consistent with that published by ONS in September 2004.

Section 5.2 explains the main stages involved for the creation of such estimates. Section 5.3 provides background information on the mid2001 population estimates for Wards in England and Wales without an ethnic group dimension published in April 2005 by ONS. Section 5.4 gives an account of the data sources used to derive the target population estimates and Section 5.5 explains the methods used to derive these estimates in three stages. Section 5.6 provides a validation of the results. Finally, a summary table of the issues, strategies and methods used to deal with the four problems are provided in Section 5.7.

5.2: Objective and overview

The objective is to create mid2001 population estimates by single year of age, sex and ethnic group for each ST Ward in England and Wales.

PART II: METHODOLOGY 158 Chapter 5: Mid2001 population estimates for Wards in England and Wales

These estimates take into account the mid2001 population estimates for Districts which include the timing transfer between Census day and midyear and extra nonresponse not included in the census output as described in Chapter 4.

The production of these mid2001 population estimates has been implemented in three stages:

1. Transfer mid2001 population estimates for Wards by fiveyear age group and sex published by ONS from CAS to ST Wards in England and Wales using an appropriate GCT.

2. Disaggregate timing and extra nonresponse as a single adjustment to allgroups by single year of age and sex in each ST Ward in England and Wales.

3. Disaggregate timing and extra nonresponse as a single adjustment to ethnic groups by single year of age and sex in each ST Ward in England and Wales.

Figure 5.1 shows the transition with three stages used to create full mid2001 population estimates by single year of age, sex and ethnic group for ST wards in England and Wales. The transition has been applied using the two versions of District baseline estimates:

• Version 1. Mid2001 population estimates for Districts in England with timing and extra nonresponse allocated using the characteristics of the population as a whole. The resulting Ward estimates are consistent by age, sex and ethnic group with that published by ONS experimental statistics in August 2006.

• Version 2. Mid2001 population estimates for Districts in England and Wales with timing and extra nonresponse allocated using ONS imputation rates. As a result, the Ward estimates are consistent by age and sex with that published by ONS in September 2004, but not with ONS estimates by ethnic group.

PART II: METHODOLOGY Chapter 5: Mid2001 population estimates for Wards in England and Wales

Figure 5.1: Transition to create full mid-2001 population estimates for ST Wards in England and Wales

Ward mid-2001 District mid-2001 by 2001 Census (from ONS) single year of age for ST Wards (from Chapter 4) (table ST001)

Transfer Disaggregate timing Stage 1 Ward mid-2001 from Stage 2 and extra non- District mid-2001 by 2001 Census CAS to ST wards response to single ethnic group for ST Wards year of age (from Chapter 4) (table ST101)

Disaggregate timing Stage 3 and extra nonresponse to ethnic groups

Ward mid-2001 -final estimate-

PART II: METHODOLOGY 160 Chapter 5: Mid2001 population estimates for Wards in England and Wales

5.3: Background

In response to the increasing demand for small area statistics, and as part of the production of postcensal population estimates for geographical areas smaller than Districts in England and Wales, in April 2005 ONS published mid 2001 Ward estimates. These mid2001 population estimates incorporate a timing transfer and extra nonresponse to reflect the mid2001 population estimates for Districts published in September 2004 and, therefore, differ to the initial mid2001 population estimates for Wards published by ONS (ONS, 2006a).

The approach used by ONS to derive a timing adjustment for these estimates is based on a cohort component methodology. Population counts from the 2001 Census for OAs with detail of single year of age and sex were aged forward from Census day to midyear. The excess of births over deaths (natural change) was also included. For this purpose, births occurring from 1st May to 30th June were added (100,900 babies) and deaths during the same period were subtracted (84,100 persons). Although ONS did not make an adjustment for either internal or international migration from Census day to midyear, an adjustment for this component was incorporated through the constraining to the District estimates, which included this component of change. This assumes that population change due to migration between Census day and midyear in all Wards within a District is proportional to its population size.

The approach used by ONS to incorporate extra nonresponse to the published Census Ward estimates takes into account the Longitudinal Study adjustment and the Local Authorities Studies adjustment (ONS, 2004b), thus reflecting the adjustments included in equivalent estimates for Districts. In addition an adjustment was made for missing Census forms, adding 5,100 people in 20 Wards. For this purpose, the Ward mid2001 population estimates are constrained to the revised mid2001 population estimates for Districts published by ONS in September 2004.

PART II: METHODOLOGY 161 Chapter 5: Mid2001 population estimates for Wards in England and Wales

These estimates of the resident population as at mid2001 have been produced for publication as experimental statistics by fiveyear age group and sex for CAS Wards in England and Wales. The CAS Ward estimates reflect Ward boundaries as at May 2003. Due to boundary changes from April 2003 in Carmarthenshire, Ceredigion and Pembrokeshire (Wales), the Ward estimates for these Districts are not consistent with the published District mid year estimates, as these reflect the District boundaries as at mid2001. In addition, due to the small populations of the City of London and Isles of Scilly, mid2001 population estimates were not produced for the individual Wards of these local authorities, thus only District figures are given for these areas (ONS, 2006a).

Although the mid2001 population estimates for CAS Wards represent a step forward in the provision of small area estimates by ONS, these mid2001 population estimates have no ethnic breakdown and are limited in their age sex detail. As a consequence, analysis of population change with an ethnic group dimension is restricted under the current production of small area estimates from ONS. To overcome this problem a method has been devised to allocate timing and extra nonresponse to single year of age and between ethnic groups using Iterative Proportional Fitting (IPF).

5.4: Data sources

The following data sets have been used to derive mid2001 population estimates for each ST Ward in England and Wales by single year of age, sex and ethnic group.

1. P01,CASw01,a18,s,● Mid2001 population estimates by fiveyear age group (18 categories) and sex for CAS Wards in England and Wales, from ONS (as published in September 2004).

2. P01,d01,a91,s,● Mid2001 population estimates by single year of age and sex for Districts in England and Wales, from ONS (as published in September 2004)..

PART II: METHODOLOGY 162 Chapter 5: Mid2001 population estimates for Wards in England and Wales

3. P01,d01,a91,s,e Mid2001 population estimates by single year of age, sex and ethnic group for Districts in England and Wales, previously calculated in Chapter 4. It applies to both version 1 and 2.

4. C01,STw01,a22,s,e Census table ST101 by fiveyear age group (22 categories), sex and ethnic group for ST Wards in England and Wales, from CASWEB.

5. C01,STw01,a91,s,● Census table ST001 by single year of age and sex for ST Wards in England and Wales, from CASWEB.

6. GCT06 GCT to transfer data from 2001 CAS Wards to 2001 ST Wards in England and Wales (Hayes, 2006).

5.5: Method

Stage 1. Transfer mid2001 population estimates for Wards published by ONS from CAS to ST Wards in England and Wales using GCT06.

In this stage, mid2001 population estimates by fiveyear age group and sex as published in September 2004 are transferred from CAS Wards to ST Wards. In most cases, the correspondence between CAS Wards and ST Wards is 1:1, although due to confidentiality restrictions that are more stringent for the detailed ST tables, more than one CAS Ward is sometimes further aggregated to a single ST Ward. For this purpose, an appropriate GCT is used (Hayes, 2006).

After matching the GCT06, with one record for each CAS Ward, and its corresponding ST Ward, and the mid2001 population estimates for Wards from ONS, each value in the CAS Wards is aggregated to their appropriate ST Ward.

P01,STw01,a18,s,● = sum (over CAS Wards in ST Wards) P01,CASw01,a18,s,●

PART II: METHODOLOGY 163 Chapter 5: Mid2001 population estimates for Wards in England and Wales

As seen earlier, the mid2001 estimates for CAS Wards reflect Ward boundaries as at May 2003. These include final boundary changes in a number of Wards for which census data were released with draft boundaries (legally in existence on 31st December 2002).6 Since the mid2001 population estimates have adopted these changes, the adjustment reflects the impact of boundary change rather than timing and extra nonresponse.

Stage 2. Disaggregate timing and extra nonresponse to allgroups by single year of age and sex in each ST Ward in England and Wales.

In this stage, information on timing and extra nonresponse by fiveyear age group from Stage 1 is disaggregated to allgroups by single year of age. Since census values exist with this degree of detail, these are used as initial values in IPF to maintain agreement with both the District single year of age already estimated, and the Ward fiveyear age groups published by ONS.

To run IPF in SPSS, a margins variable is computed using the margin values from Wards and the margin values from Districts.

Margins = P01,STw01,a18,s,● * P01,d01,a91,s,● / P91,d01,a18,s,●

The denominator is derived from the District values. It is calculated using the age disaggregated data, which are summed as an aid to computing the margins variable.

The following information is used to run IPF in SPSS:

Initial values: C01,STw01,a91,s,● from census table ST001

Margin: P01,STw01,a18,s,● from Stage 1

Margin: P01,d01,a91,s,● from Chapter 4

Result: P01,STw01,a91,s,●

6 Information about these boundary changes is available from the ONS website at http://www.statistics.gov.uk/census2001/unprocess_forms.asp

PART II: METHODOLOGY 164 Chapter 5: Mid2001 population estimates for Wards in England and Wales

Within this procedure, IPF operates across Wards and single year of age within each District by fiveyear age group and sex. It assumes that within those categories, the ageWard interaction is as in the census output.

Stage 3. Disaggregate timing and extra nonresponse to ethnic groups by single year of age and sex to each ST Ward in England and Wales.

In this stage, information on both timing and extra nonresponse is disaggregated to ethnic groups by single year of age and sex. Since census values with an ethnic breakdown exist by fiveyear age group and sex, these are used as initial values in IPF to maintain agreement with both the District single year of age by ethnic group and the Wards single year of age, but without an ethnic group dimension, previously estimated in Stage 2.

To run IPF, a margins variable is computed using the margin values from Districts and the margin values from Wards.

Margins = P01,d01,a91,s,e * P01,STw01,a91s,● / P91,d01,a91,s,●

The denominator is derived from the District values. It is calculated using the ethnic group disaggregated data, which are summed as an aid to computing the margins variable.

The following information is used to run IPF in SPSS:

Initial values: C01,STw01,a22,s,e from census table ST101

Margin: P01,d01,a91,s,e from Chapter 4

Margin: P01,STw01,a91s,● from Stage 2

Result: P01,STw01,a91,s,e

Within this procedure, IPF operates across ethnic groups and Wards within each District by single year of age and sex. It assumes that within those

PART II: METHODOLOGY 165 Chapter 5: Mid2001 population estimates for Wards in England and Wales

categories, the Wardethnic group interaction is as in the census output for Wards.

5.6: Validation

Two data sets have been derived from the procedures described above. Each data set has 25,616,864 cases, one for each combination of:

• 2001 ST Wards in England and Wales = 8,7977

• Age (90 single years and 90 and over) = 91

• Sex (Male and Female) = 2

• 2001 Ethnic groups as recorded in the census = 16

Figure 5.2 and Figure 5.3 show the total difference between the mid2001 population estimates obtained after implementing IPF and the known sub totals from ONS as published in September 2004 in England and Wales for each ST Ward. As expected, the overall difference between the marginal totals and the known subtotals is always near zero, thus indicating how close they are to one another. For this calculation the marginal totals for each 2001 ST Ward by single year of age, sex and ethnic group have been aggregated across each 2001 ST Ward.

7 Since mid-2001 population estimates were not produced by ONS for the individual Wards of the City of London and Isles of Scilly, only District figures are given for these areas. There are a total of 5 ST Wards affected: Aldersgate (00AAFA), Cripplegate (00AAFQ), Farringdon Without (00AAFT), Portsoken (00AAFX) and St. Mary’s (15UHFD).

PART II: METHODOLOGY 166 Chapter 5: Mid2001 population estimates for Wards in England and Wales

Figure 5.2: Total difference between the mid-2001 population estimates obtained after IPF (version 1) and the known sub-totals in England and Wales by Wards

The results are similar for version 1 (with extra nonresponse included from baseline District estimates as published by ONS experimental statistics unit) and version 2 (with extra nonresponse included from baseline District estimates using ONS imputation rates).

PART II: METHODOLOGY 167 Chapter 5: Mid2001 population estimates for Wards in England and Wales

Figure 5.3: Total difference between the mid-2001 population estimates obtained after IPF (version 2) and the known sub-totals in England and Wales by Wards

Table 5.1 shows the final mid2001 population estimates obtained from ST Wards by ethnic group as recorded in the 2001 Census in England and Wales. For simplicity ethnic groups are not disaggregated by age and sex. The table is equivalent to the outputs derived from the District data set and, therefore, it illustrates consistency with the final population for Districts in England and Wales as published in September 2004 by ONS.

The observed absolute differences between ethnic groups are again due to the fact that the allocation of extra nonresponse from ONS experimental statistics unit (Large and Ghosh, 2006) is not differential by ethnic group, and only takes the characteristics of the population as a whole. Therefore, whereas version 1 reflects an allocation of extra nonresponse according to the existing population composition, version 2 takes into consideration information of ONS imputation rates, which results in greater increases among ethnic minority groups, especially among the South Asian and Black groups.

PART II: METHODOLOGY 168 Chapter 5: Mid2001 population estimates for Wards in England and Wales

Table 5.1: Mid-2001 population estimates by ethnic group in England and Wales (derived from the Ward data set)

Ethnic group Mid2001 Mid2001 Difference 16 categories Sep04 Sep04 (1) (2) (2) (1)

1 White British 45,721,238 45,693,388 27,850 2 Whire Irish 646,618 645,411 1,206 3 Other White 1,379,499 1,377,849 1,650 4 Mixed W/Caribbean 240,438 240,443 5 5 Mixed W/African 80,705 80,643 63 6 Mixed W/Asian 192,229 191,922 307 7 Other Mixed 158,582 158,432 150 8 Indian 1,053,302 1,059,350 6,049 9 Pakistani 727,726 734,585 6,859 10 Bangladeshi 286,693 289,488 2,795 11 Other Asian 247,157 246,591 567 12 Black Caribbean 572,212 576,850 4,638 13 Black African 494,668 502,667 7,999 14 Other Black 98,068 98,140 72 15 Chinese 233,346 236,090 2,744 16 Other 227,497 228,130 633 Total 52,359,979 52,359,979 0

NB: (1) Version 1. Mid2001 population estimates for Wards consistent with the District baseline estimates by ethnic group published by ONS experimental statistics in 2006. (2) Version 2. Mid2001 population estimates for Wards consistent with the District baseline estimates by ethnic group produced in Chapter 4 (using ONS imputation rates).

Table 5.2 shows the mid2001 population estimates obtained from ST Wards by age and sex for allgroups consistent with that published in September 2004 in England and Wales. These include the adjustments of timing and extra nonresponse to the initial census counts. Although detail of single year of age has also been derived for Wards, for simplicity age is aggregated into fiveyear age groups.

PART II: METHODOLOGY 169 Chapter 5: Mid2001 population estimates for Wards in England and Wales

Table 5.2: Mid-2001 population estimates by age and sex for all-groups in England and Wales (derived from the Ward data set)

Age groups Mid2001 Mid2001

18 categories Sep04 Sep04

(1) (2)

Males Females Total Males Females Total 1 04 1,582,445 1,508,558 3,091,003 1,582,445 1,508,558 3,091,003

2 59 1,693,702 1,612,265 3,305,967 1,693,702 1,612,265 3,305,967

3 1014 1,759,516 1,674,885 3,434,401 1,759,516 1,674,885 3,434,401

4 1519 1,652,119 1,578,418 3,230,537 1,652,119 1,578,418 3,230,537

5 2024 1,579,211 1,577,685 3,156,896 1,579,211 1,577,685 3,156,896

6 2529 1,741,892 1,744,662 3,486,554 1,741,892 1,744,662 3,486,554

7 3034 2,016,085 2,033,424 4,049,509 2,016,085 2,033,424 4,049,509

8 3539 2,049,687 2,081,985 4,131,672 2,049,687 2,081,985 4,131,672

9 4044 1,831,198 1,853,349 3,684,547 1,831,198 1,853,349 3,684,547

10 4549 1,643,894 1,670,133 3,314,027 1,643,894 1,670,133 3,314,027

11 5054 1,770,895 1,801,328 3,572,223 1,770,895 1,801,328 3,572,223

12 5559 1,491,994 1,520,020 3,012,014 1,491,994 1,520,020 3,012,014

13 6064 1,251,730 1,297,331 2,549,061 1,251,730 1,297,331 2,549,061

14 6569 1,104,859 1,194,005 2,298,864 1,104,859 1,194,005 2,298,864

15 7074 946,760 1,131,760 2,078,520 946,760 1,131,760 2,078,520

16 7579 734,052 1,020,415 1,754,467 734,052 1,020,415 1,754,467

17 8084 441,267 750,954 1,192,221 441,267 750,954 1,192,221

18 85+ 282,952 734,543 1,017,495 282,952 734,543 1,017,495

Total 25,574,258 26,785,720 52,359,979 25,574,258 26,785,720 52,359,979

As expected, the table shows how the final mid2001 population estimates for allgroups is consistent by age and sex using the baseline mid2001

PART II: METHODOLOGY 170 Chapter 5: Mid2001 population estimates for Wards in England and Wales

population estimates for Districts with (1) extra nonresponse as published by ONS experimental statistics unit (Large and Ghosh, 2006); and (2) using ONS imputation rates to allocate the extra nonresponse.

Figure 5.4 shows a selection of Wards with the greatest adjustments between census and midyear in England and Wales. As expected the Wards receiving the major adjustment to census figures correspond to small areas located in inner cities such as Central in Manchester, West End in Westminster and Ashley in the City of Bristol. This is in line with the adjustments of extra non response after the Local Authorities Studies adjustment and the Manchester and Westminster Matching Studies (ONS, 2004b; 2004c).

Figure 5.4: A selection of Wards with greatest adjustments between census and mid-year in England and Wales

Additionally, in some Wards the population adjustment appears to be negative, which is principally as a result of boundary changes after the 2001 Census. Although the 2001 Census counts were produced for Wards legally in existence on 31st December 2002, some Wards were produced with draft

PART II: METHODOLOGY 171 Chapter 5: Mid2001 population estimates for Wards in England and Wales

boundaries to use for the census output, for example, Stony Stratford in Milton Keynes and Severn, Drybridge and Cadicot Castle in Monmouthshire. Following a number of boundary changes between the draft and the final boundary, a number of OAs have been reassigned, for example, from Stoney Stratford Ward (00MGNW) to Wolverton Ward (00MGNZ). Whilst the mid 2001 population estimates have adopted these boundary changes, corrected Standard Tables have not been produced for the Wards affected to avoid risk of disclosure by differencing.

5.7: Conclusions and summary

This section has focused on the estimation of mid2001 population estimates by single year of age, sex and ethnic group for each 2001 ST Ward in England and Wales. For the creation of these estimates two versions of District baseline estimates with an ethnic group dimension have been used. As explained earlier, the first version corresponds to the mid2001 population estimates for Districts in England published by ONS experimental statistics in 2006 (Large and Ghosh, 2006). The second version refers to the mid2001 population estimates for Districts in England and Wales previously created in Chapter 4 using ONS imputation rates to allocate the extra nonresponse.

After implementing the same methods to these two versions, the results highlight that both versions are consistent by age and sex with the latest mid 2001 population estimates published by ONS in September 2004. However, significant differences are found in the final population figures between ethnic groups. As expected the population figures for ethnic groups other than White are higher when the District estimates created in Chapter 4, with differential nonresponse between ethnic groups, are used.

The methods used to disaggregate timing and extra nonresponse to single year of age in Stage 1 and to ethnic groups in Stage 2 give plausible results for both sets of estimates. As mentioned in Chapter 4, consistency with the latest ONS midyear estimates by ethnic group is favoured to provide an

PART II: METHODOLOGY 172 Chapter 5: Mid2001 population estimates for Wards in England and Wales

integrated quality assurance for census users. Therefore, the use of District baseline estimates containing an alternative allocation of extra nonresponse should be seen as a way to test the transferability of information from ONS imputation rates from Districts to smaller areas.

Chapter 6 extends the estimation of small areas by making equivalent estimates for OAs. For this purpose, only the Ward estimates consistent with that published by ONS as experimental statistics in August 2006 are used.

Table 5.3 gives a summary of the issues, strategies and methods used to tackle the four problems reviewed in Chapter 2. These are presented in the order that they are dealt with in the estimation process.

PART II: METHODOLOGY Chapter 5: Mid2001 population estimates for Wards in England and Wales

Table 5.3: Summary to create full mid-2001 population estimates for ST Wards in England and Wales

Issues Strategies Methods / assumptions Boundary harmonisation ONS estimates for 2001 CAS Wards are A GCT with one record for each CAS Ward and its correspondent ST Ward is used to transfer aggregated to ST Wards. the mid2001 population estimates for Wards from ONS, so each value in the CAS Ward is aggregated to their appropriate ST Ward (defined and constructed by Hayes, 2006).

The CAS Ward estimates reflect Ward Due to boundary changes from April 2003 in Carmarthenshire, Ceredigion and Pembrokeshire boundaries as at May 2003. These include (Wales), the Ward estimates for these Districts are not consistent with the published District final boundary changes in a number of midyear estimates, as these reflect the District boundaries as at mid2001. Estimates have not Wards for which census data were released been created for Wards within the City of London and the Isles of Scilly, thus in line with the with draft boundaries. ONS Ward population estimates (September 2004) due to the small numbers in these areas (ONS, 2006a).

Ethnic group categories Not needed. Target categories are those None used in 2001 (16 categories). Age group categories Single year of age (91 categories) is IPF is used to derive single year of age. First, Ward data for allgroups with 5year agesex created from 5year age groups. structure from ONS are made consistent with District data for allgroups by single year of age and sex from ONS, the interaction (singleyear by Wards) coming from the Census table

ST001. Second, Ward data for allgroups by single year of age and sex (derived from previous step) are made consistent with District data by single year of age, sex and ethnic group from ONS experimental statistics, the interaction (Ward by ethnic group) coming from the Census table ST101.

Population definition Student transfer Not applicable. Students already at term None. time address in 2001.

Timing Move from Census day to midyear (30th As above under ‘Age group categories’. June). Timing already incorporated in ONS Ward population estimates (September 2004).

Nonresponse Extra nonresponse already incorporated in As above under ‘Age group categories’. ONS Ward population estimates is spread to ethnic groups with differential as measured by imputation in the Census.

PART II: METHODOLOGY 174

Chapter 6: Mid-2001 population estimates for Output Areas in England and Wales

6.1: Introduction

This chapter describes the methodology used for the creation of mid2001 population estimates for OAs in England and Wales by ethnic group and with detail of age and sex. These estimates follow the method of disaggregating District to Ward estimates in Chapter 5, so that a method of disaggregating Ward estimates to OAs is implemented. For this purpose, only the Ward estimates consistent with that published by ONS as experimental statistics in August 2006 are used.

Section 6.2 describes the main stages involved for the creation of these estimates. Section 6.3 gives background information on the 2001 Census counts for OAs with an ethnic group dimension and the existing mid2001 population estimates for Super Output Areas (SOAs) without ethnic group. The data sources to create the target mid2001 population estimates for OA are detailed in Section 6.4. The methods used to create such estimates in four stages are described in Section 6.5. A validation of the results is given in Section 6.6 and, finally, a summary table of the issues, strategies and methods used to deal with the four problems are provided in Section 6.7.

6.2: Objective and overview

The objective is to create mid2001 population estimates by single year of age, sex and ethnic group for each OA included in the 2001 Census geography of England and Wales.

PART II: METHODOLOGY 175 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

These estimates take into account OA census information by age, sex and ethnic group and the mid2001 population estimates for Wards previously created in Chapter 5 to include the timing transfer between Census day and midyear and extra nonresponse not included in the census output.

The creation of these mid2001 population estimates has been implemented in four stages:

1. Derive a more detailed census table from table CT003. This consists of constructing a threedimensional census table from the two dimensional tables (ethnic group data crosstabulated separately by age and sex) in CT003 for each OA in England and Wales.

2. Disaggregate the mid2001 population estimates for Wards to each OA in England and Wales using the threedimensional census table created from CT003.

3. Disaggregate timing and extra nonresponse as a single adjustment to allgroups by single year of age and sex in each OA in England and Wales.

4. Disaggregate timing and extra nonresponse as a single adjustment to ethnic groups by single year of age and sex in each OA in England and Wales.

Figure 6.1 shows the transition with four stages used to create full mid2001 population estimates by single year of age, sex and ethnic group for each OA in England and Wales. This transition has been applied using only version 1 of the mid2001 population estimates for Wards. This means that the resulting OA estimates are consistent, for England, with the baseline District estimates by age, sex and ethnic group published by ONS as experimental statistics in August 2006 (Large and Ghosh, 2006). For Wales, the OA estimates are consistent with the baseline District estimates by age and sex published by ONS in September 2004.

PART II: METHODOLOGY Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

Figure 6.1: Transition to create full mid-2001 population estimates for Output Areas in England and Wales

2001 Census Ward mid-2001 by Ward mid-2001 by 2001 Census for OAs ethnic group single year of age for ST Wards (table CT003) (from Chapter 5) (from Chapter 5) (table ST001)

Derive a three- Disaggregate Disaggregate timing Stage 1 dimensional census Stage 2 Ward mid-2001 to Stage 3 and extra non- table from CT003 OAs by 5-year age, response to single sex and ethnic group year of age

2001 Census Disaggregate timing and extra non- for ST Wards Stage 4 (table ST101) response to ethnic groups

OA mid-2001

-final estimate-

PART II: METHODOLOGY 177 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

6.3: Background

As part of the production of small area statistics in England and Wales, in October 2006 ONS published mid2001 population estimates for Lower Layer Super Output Area (LSOA) and Middle Layer Super Output Area (MSOA), thus reflecting the new geographic hierarchy of SOAs. This set of estimates for different types of OA also incorporate the adjustments made to the mid 2001 population estimates for Districts published in September 2004 with extra nonresponse (ONS, 2006b).

These mid2001 population estimates have been produced for publication as experimental statistics by broad age group and sex for LSOAs and fiveyear age groups and sex for MSOAs. For consistency, the mid2001 population estimates for LSOA by age and sex have been constrained to the mid2001 population estimates for MSOA, which in turn are constrained to the final mid 2001 population estimates for Districts by age and sex for England and Wales as published in September 2004.

However, these mid2001 population estimates from ONS experimental statistics for LSOA and MSOA have no ethnic breakdown and are limited in their agesex detail. As a result, current small area estimates produced by ONS are not sufficient to carry out analysis of population change for small areas with an ethnic group dimension. To solve this problem a method has been devised to disaggregate timing and extra nonresponse to single year of age and between ethnic groups at OA level. This approach makes use of Iterative Proportional Fitting (IPF) and it is in line with that used in Chapter 5 to create mid2001 population estimates for Wards. The resulting mid2001 population estimates for OAs are consistent with those published by ONS by age and sex as experimental statistics for SOAs.

The approach taken to produce mid2001 for OAs by age, sex and ethnic group has been considered appropriate to ensure consistency between geographies. A different approach, using ONS quality indicators could have also been undertaken. These provide information on the proportion of people

PART II: METHODOLOGY 178 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

imputed in the 2001 Census output in Districts and smaller areas (including OAs), and it is expressed as a four point scale: (1) Less than 5 per cent; (2) 5 per cent and less than 10 per cent; (3) 10 per cent and less than 20 per cent; and (4) 20 per cent and over.8

However, the resources required to design and program the allocation of extra nonresponse using the ONS quality indicators, and simultaneously to be consistent with SOA, Ward and District totals, are more than the arguable gain in accuracy of the results.

6.4: Data sources

The following data sets have been used to derive mid2001 population estimates for each OA in England and Wales by single year of age, sex and ethnic group.

1. P01,STw01,a91,s,e Mid2001 population estimates, single year of age, sex and ethnic group for ST Wards in England and Wales, previously calculated in Chapter 5.

2. C01,STw01,a91,s,● Census table ST001 by single year of age and sex for ST Wards in England and Wales, from CASWEB.

3. C01,STw01,a22,s,e Census table ST101 by fiveyear age group (22 categories), sex and ethnic group for ST Wards in England and Wales, from CASWEB. Further aggregation of ages 5 7, 89, and of 15, 1617 and 1819 has been implemented to carry out the different tasks with 18 categories.

4. C01,oa01,a7,●,e Census table CT003 by broad age (7 categories) and ethnic group for OAs in England and Wales, from CASWEB.

8 Information about the ONS quality indicators is available from the ONS website at http://www.statistics.gov.uk/census2001/quality_indicators.asp

PART II: METHODOLOGY 179 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

5. C01,oa01, ●,s,e Census table CT003 by sex and ethnic group for OAs in England and Wales, from CASWEB.

6.5: Method

Stage 1. Derive a threedimensional census table from the twodimensional tables in CT003 for each OA in England and Wales.

The CAS census table CT003 is a Theme Table which provides detail of ethnic group for each OA. This table is twodimensional, with information on ethnic group for each OA in England and Wales but separately by broad age (7 groups) and then by sex. In this stage, a threedimensional census table containing crosstabulated data by age, sex and ethnic group is derived from the twodimensional tables in CT003.

The approach to derive this new table is based initially on scaling those values of the census table CT003 by broad age (7 categories) and ethnic group to the values of the census table CT003 by sex and ethnic group. This step is undertaken because some census tables have more reliable totals than others, which is related to the number of small cells in the table (Rees et al., 2005). From this perspective, it is assumed that the twodimensional table by sex and ethnic group is less subject to data modification because fewer cells are involved.

IF sum over age (C01,oa01,a7,●,e ) > 0 and sum over sex (C01,oa01,●,s,e) > 0,

R C 01,oa01,a7,●,e = C01,oa01,a7,●,e * sum over sex (C01,oa01,●,s,e ) / sum over age

(C01,oa01,a7,●,e)

IF sum over age (C01,oa01,a7,●,e ) = 0 and sum over sex (C01,oa01,●,s,e ) = 0,

R C 01,oa01,a7,●,e = 0

IF sum over age (C01,oa01,a7,●,e) > 0 and sum over sex (C01,oa01,●,s,e) = 0,

PART II: METHODOLOGY 180 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

R C 01,oa01,a7,●,e = 0

Due to the fact that the sum over the sex margin can also be zero, the resulting variable will always be zero to maintain consistency. If the sum over the sex margin is greater than zero and the sum over the age margin equals to zero, the positive values are spread equally to each age category with the following operation.

IF sum over age (C01,oa01,a7,●,e ) = 0 and sum over sex (C01,oa01,●,s,e) > 0,

R C 01,oa01,a7,●,e = C01,oa01,●,s,e / 7

After scaling the census table CT003 with an ethnic group dimension by broad age (7 categories) to its equivalent by sex, IPF is used to derive an amended census table CT003 by age (7 categories), sex and ethnic group. Since, census values for Wards from census table ST101 exist with this degree of detail; these are used as initial values in IPF to maintain agreement with both the OAs with broad age group information and the OAs with sex information.

To run IPF, a margins variable is computed using the revised margin values by broad age and ethnic group and the margin values by sex and ethnic group.

R Margins = C 01,oa01,a7,●,e * C01,oa01,●,s,e / C01,oa01,●,●,e

The denominator is derived from the margin values by sex and ethnic group, and it is the sum over sex as an aid to computing the margins variable.

Before IPF is run, an appropriate GCT containing the correspondence between CAS Wards and ST Wards is necessary. For this purpose, GCT06 is used (Hayes, 2006), to match OAs from census table CT003 and Wards from census table ST101.

PART II: METHODOLOGY 181 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

The following information is used to run IPF in SPSS:

Initial values: C01,STw01,a7,s,e from census table ST101

Margin: C01,oa01,a7,●,e from census table CT003

Margin: C01,oa01, ●,s,e from census table CT003

Result: C01,oa01, a7,s,e

Within this procedure, IPF operates across broad age groups (7 categories) and sex within each OA by ethnic group. It assumes that within those categories, the agesex interaction is as in the census output for the Ward containing the OA.

Stage 2. Disaggregate the mid2001 population estimates for Wards to each OA in England and Wales using the threedimensional census table previously created.

In this stage, the mid2001 population estimates for Wards by single year of age, sex and ethnic group are disaggregated to each OA in England and Wales. For this purpose, information by ethnic group is used from the census tabulation by broad age (7 categories) and sex previously derived. The Ward estimates were previously created in Chapter 5 (with extra nonresponse not differential by ethnic group – version 1), and have been aggregated to five year age groups to carry out this task.

The sharing method to OAs assumes that the agesexethnic group timing and extra nonresponse included in the Ward estimates applies to all OAs in that Ward. This is implemented as follows:

P01,oa01,a18,s,e = P01,STw01,a18,s,e * (C01,oa01, a7,s,e / C01,oa(w)01, a7,s,e)

Since the above procedure is not valid when cells in the census tabulation for OAs have no population, our approach to this is to share the mid2001

PART II: METHODOLOGY 182 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

population estimates for Wards equally to OAs. For this purpose, the number of OAs in each Ward is calculated.

IF C01,oa(w)01, a7,s,e = 0, then P01,oa01,a18,s,e = P01,w01,a18,s,e / oa(w)_N

C01,oa(w)01, a7,s,e is derived by summing C01,oa01, a7,s,e within each Ward, to ensure that one hundred per cent of each Ward value is distributed to OAs.

Finally, P01,oa01,a18,s,● is computed, which is derived by aggregating

P01,oa01,a18,s,e across ethnic groups within each OA, fiveyear age groups and sex.

Stage 3. Disaggregate timing and extra nonresponse to allgroups by single year of age and sex in each OA in England and Wales.

In this stage, information on timing and extra nonresponse without an ethnic group dimension is disaggregated to allgroups by single year of age and sex in each OA in England and Wales. Since census values for Wards exist with this degree of detail, these are used as initial values in IPF to maintain agreement with both the OA fiveyear age groups from Stage 2, and the Ward single year of age previously created in Chapter 5.

To run IPF in SPSS, a margins variable is computed using the margin values from Wards and the margin values from OAs.

Margins = P01,STw01,a91,s,● * P01,oa01,a18,s,● / P01,STw01,a91,s,●

The denominator is derived from the OA values, and it is the sum over single year of age as an aid to computing the margins variable.

PART II: METHODOLOGY 183 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

The following information is used to run IPF in SPSS:

Initial values: C01,STw01,a91,s,● from census table ST001

Margin 1: P01,STw01,a91,s,● from Chapter 5

Margin 2: P01,oa01,a18,s,● from Stage 2

Result: P01,oa01,a91,s,●

Within this procedure, IPF operates across OAs and single year of age within each Ward by fiveyear age group and sex. It assumes that within those categories, the single year of ageOA interaction is as in the census output.

Stage 4. Disaggregate timing and extra nonresponse to ethnic groups by single year of age and sex in each OA in England and Wales.

In this stage, information on both timing and extra nonresponse is disaggregated to ethnic groups by single year of age and sex in each OA in England and Wales. Since census values with an ethnic breakdown exist for Wards by fiveyear age group and sex, these are used as initial values in IPF. The aim is to use the initial values to maintain agreement with both the OA single year of age without ethnic group from Stage 3, and the OA fiveyear age groups with an ethnic group dimension from Stage 2.

To run IPF, a margins variable is computed using the margin values from OAs by fiveyear age group and single year of age previously estimated.

Margins = P01,oa01,a18,s,e * P01,oa01,a91,s,● / P01,oa01,a18,s,●

The denominator is derived from the margin values from OAs by single year of age, and it is the sum over fiveyear age groups as an aid to computing the margins variable.

PART II: METHODOLOGY 184 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

The following information is used to run IPF in SPSS:

Initial values: C01,STw01,a18,s,e from census table ST101

Margin: P01,oa01,a18,s,e from Stage 2

Margin: P01,oa01,a91,s,● from Stage 3

Result: P01,oa01,a91,s,e

Within this procedure, IPF operates across single year of age and ethnic group within each OA by fiveyear age group and sex. It assumes that within those categories, the ageethnic group interaction is as in the census output.

6.6: Validation

The data set resulting from the procedures described above has 510,863,808 cases, one for each combination of:

• 2001 Output Areas = 175,434

• Age (90 single years and 90 and over) = 91

• Sex (Male and Female) = 2

• 2001 Ethnic groups = 16

Figure 6.2 shows the overall differences between the mid2001 population estimates obtained after implementing IPF and the known subtotals from ONS as published in September 2004 in England and Wales for each ST Ward. As expected, the overall difference between the marginal totals and the known subtotals is always near zero, thus indicating how close they are to one another. For this calculation the marginal totals for each OA by single year of age, sex and ethnic group have been aggregated across each 2001 ST Ward.

PART II: METHODOLOGY 185 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

Figure 6.2: Total difference between the mid-2001 population estimates obtained after IPF and the known sub-totals in England and Wales by Wards (derived from the OA data set)

Table 6.1 shows the final mid2001 population estimates obtained from OAs by ethnic group as recorded in the 2001 Census in England and Wales. For simplicity ethnic groups are not disaggregated by age and sex. The results obtained are as in the equivalent Ward data set and, therefore, it illustrates consistency with the baseline District estimates for England by age, sex and ethnic group published by ONS in August 2006. For Wales, the results are also consistent with the District estimates by age and sex published by ONS in September 2004.

PART II: METHODOLOGY 186 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

Table 6.1: Mid-2001 population estimates by ethnic group in England and Wales (derived from the OA data set)

Ethnic group Mid2001 16 categories Sep04

1 White British 45,721,238 2 Whire Irish 646,618 3 Other White 1,379,499 4 Mixed W/Caribbean 240,438 5 Mixed W/African 80,705 6 Mixed W/Asian 192,229 7 Other Mixed 158,582 8 Indian 1,053,302 9 Pakistani 727,726 10 Bangladeshi 286,693 11 Other Asian 247,157 12 Black Caribbean 572,212 13 Black African 494,668 14 Other Black 98,068 15 Chinese 233,346 16 Other 227,497 Total 52,359,979

Figure 6.2 displays the mid2001 population estimates derived from OAs by age and sex for allgroups in England and Wales. Although detail of single year of age has also been derived for OAs, for simplicity age is aggregated into fiveyear age groups. Similarly, the results illustrate consistency with the mid2001 population estimates by age and sex published in September 2004.

PART II: METHODOLOGY 187 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

Table 6.2: Mid-2001 population estimates by age and sex for all-groups in England and Wales (derived from the OA data set)

Age groups Mid2001

18 categories Sep04

Males Females Total 1 04 1,582,445 1,508,558 3,091,003

2 59 1,693,702 1,612,265 3,305,967

3 1014 1,759,516 1,674,885 3,434,401

4 1519 1,652,119 1,578,418 3,230,537

5 2024 1,579,211 1,577,685 3,156,896

6 2529 1,741,892 1,744,662 3,486,554

7 3034 2,016,085 2,033,424 4,049,509

8 3539 2,049,687 2,081,985 4,131,672

9 4044 1,831,198 1,853,349 3,684,547

10 4549 1,643,894 1,670,133 3,314,027

11 5054 1,770,895 1,801,328 3,572,223

12 5559 1,491,994 1,520,020 3,012,014

13 6064 1,251,730 1,297,331 2,549,061

14 6569 1,104,859 1,194,005 2,298,864

15 7074 946,760 1,131,760 2,078,520

16 7579 734,052 1,020,415 1,754,467

17 8084 441,267 750,954 1,192,221

18 85+ 282,952 734,543 1,017,495

Total 25,574,258 26,785,720 52,359,979

6.7: Conclusions and summary

This section has focused on the estimation of mid2001 population estimates by single year of age, sex and ethnic group for each 2001 OA in England and Wales. These estimates have been produced using information with an ethnic

PART II: METHODOLOGY 188 Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

group dimension from the Ward estimates previously created in Chapter 5, which in turn are consistent with the equivalent baseline District estimates.

Although borrowing strength from their ‘parent’ Wards has proven to be successful to obtain consistency, the OA estimates are not expected to be accurate at that level, principally because the method of disaggregating Ward data to OAs assumes that the agesexethnic group timing and extra non response included in the Ward estimates applies to all OAs in that Ward.

As noted earlier, an approach to reflect differential nonresponse for each OA could be applied by taking into consideration ONS quality indicators, which contain information about the proportion of people imputed in the 2001 Census output for each OA in England and Wales. Nonetheless, the practical implementation of such a method, whilst maintaining consistency with the Ward and District totals, was considered unnecessary for the application of the OA estimates to build higherlevel geographies such as Wards. The usefulness of the OA results by single year of age, sex and ethnic group is demonstrated in Chapter 11 for building up to current Ward boundaries in the District of Birmingham.

Table 6.3 gives a summary of the issues, strategies and methods used to deal with the four problems reviewed in Chapter 2. These are presented in the order that they are dealt with in the estimation process.

Chapter 7 describes the methods used for the creation of mid1991 population estimates by single year of age and sex for OAs, Wards and Districts using the 2001 Census geography.

PART II: METHODOLOGY Chapter 6: Mid2001 population estimates for Output Areas in England and Wales

Table 6.3: Summary to create full mid-2001 population estimates for Output Areas in England and Wales

Issues Strategies Methods / assumptions Ethnic group categories Not needed. Target categories are those None used in 2001 (16 categories). Age group categories Single year of age (91 categories) is The disaggregation from Wards to OAs assumes that the agesexethnic group timing and extra created from 5year age groups. These are nonresponse from the Ward estimates applies to all OAs in that Ward. obtained after applying a threedimensional census table from CT003 to the Ward IPF is used to derive single year of age. First, OA data for allgroups with 5year agesex estimates by 5year age, sex and ethnic structure are made consistent with the Ward data for allgroups by single year of age and sex group. (from Chapter 5), the interaction (singleyear by Wards) coming from the Census table ST001. Second, OA data for allgroups by single year of age and sex (derived from previous step) are

made consistent with the initial disaggregated OA data with detail of ethnic group by 5year agesex structure, the interaction (ageethnic group) coming from the Census table ST101.

Population definition Student transfer Not applicable. Students already at term None time address in 2001.

Timing Move from Census day to midyear (30th As above under ‘Age group categories’. June). Timing already incorporated in Ward population estimates (September 2004) is spread to OAs.

Nonresponse Extra nonresponse already incorporated in As above under ‘Age group categories’. Ward population estimates is spread to OAs.

Boundary harmonisation Not needed. Target geographies are those None used in 2001 (175,434 OAs).

PART II: METHODOLOGY 190

Chapter 7: Mid-1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

7.1: Introduction

This chapter describes the methodology used for the creation of mid1991 population estimates for OAs, Wards and Districts using the 2001 Census geography in England and Wales with detail of age and sex. These are consistent with the latest mid1991 population estimates published by ONS post2001 Census (Duncan et al., 2002; ONS, 2002b).

The main stages involved in the creation of these estimates for OAs, Wards and Districts are described in Section 7.2. Background information on the previous mid1991 population estimates is given in Section 7.3. The data sources that are used to create the target mid1991 population estimates are detailed in Section 7.4. The methods used to create such estimates in eleven stages are described in Section 7.5. A validation of the results is given in Section 7.6 and, finally, a summary table of the issues, strategies and methods used to deal with the four problems are provided in Section 7.7.

7.2: Objective and overview

The objective is to create revised mid1991 population estimates by single year of age and sex using the 2001 Census geography for OAs, Wards and Districts in England and Wales in the light of the latest available data post 2001 Census.

PART II: METHODOLOGY 191 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

The main task consists of revising the nonresponse allowances included in the previous mid1991 population estimates by the EwC project so that mid 1991 population estimates for small areas are consistent and comparable with the time series of revised official subnational estimates. Previous mid1991 population estimates from the Estimating with Confidence (EwC) project (Simpson et al., 1997) are used (i.e. EWCPOP data).9

The creation of these mid1991 population estimates has been implemented in eleven stages:

1. Calculate a total nonresponse adjustment figure by age and sex for EDs in England and Wales, according to previous (EwC) estimates.

2. Constrain EwC populations and adjustments for EDs to their equivalents for Wards using the 1991 Census geography in England and Wales. These were not consistent in the EwC estimates.

3. Convert ED populations and adjustments to 2001 OAs in England and Wales.

4. Derive EwC mid1991 population estimates for 2001 Districts in England and Wales from the OA populations.

5. Aggregating these initial estimates and adjustments to 2001 Districts, compute the size of revision to undercount using mid1991 population estimates post2001 Census for 2001 Districts in England and Wales.

6. Revise the EwC size of undercount in England and Wales at District level and distribute it across each District’s OAs’.

7. Create mid1991 population estimates by fiveyear age group and sex for OAs in England and Wales after the undercount revision, without ‘hierarchy’ adjustment.

9 The revision of mid-1991 for sub-national areas has been implemented in conjunction with the Understanding Population Trends and Processes (UPTAP) project about the micro-geography of UK demographic change 1991-2001 (Norman, 2006; Norman et al., 2007).

PART II: METHODOLOGY 192 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

8. Apply residual ‘hierarchy’ adjustment to remove negative populations at OA level.

9. Derive mid1991 population estimates and adjustments by fiveyear age group and sex for 2001 CAS Wards in England and Wales after the undercount revision.

10. Disaggregate mid1991 population estimates for OAs in England and Wales after the undercount revision to single year of age.

11. Derive mid1991 population estimates by single year of age and sex for 2001 ST Wards and Districts in England and Wales.

Figure 7.1 shows the transition with eleven stages used to create revised mid 1991 population estimates by single year of age and sex for each OA, ST Ward and District in England and Wales using the 2001 Census geography. The resulting OA estimates aggregated to Districts are consistent with the latest mid1991 population estimates by age and sex for Districts in England and Wales published by ONS post2001 Census (Duncan et al., 2002; ONS, 2002b).

PART II: METHODOLOGY 193 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Figure 7.1: Transition to create revised mid-1991 population estimates for Output Areas and above in England and Wales

EWCPOP data

Calculate a total non- Constrain EWCPOP Stage 1 response adjustment data from EDs to Stage 2 for EDs Wards

Convert ED populations and Stage 3 adjustments to OAs

Derive EwC Stage 4 mid-1991 for 2001 Compute undercount

Districts revision with mid- Stage 5 1991 post-2001

Revise EwC undercount size for Stage 6 Districts and OAs

Create mid-1991 for Stage 7 OAs after undercount Apply residual

revision ‘hierarchy’ Stage 8 adjustment

Derive mid-1991 and Stage 9 adjustments for 2001 CAS Wards

Create an initial Stage 10 single year of age

Derive mid-1991 for Stage 11 2001 ST Wards and Districts

PART II: METHODOLOGY 194 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

7.3: Background

After the 1991 Census, the EwC project produced and disseminated ED and electoral Ward mid1991 population estimates together with fiveyear age and sex detail and subgroupspecific adjustments to the published census output consistent with the OPCS mid1991 population estimates (OPCS, 1993). Four small areaspecific adjustments were applied to the 1991 Census counts relating to:

1. Allowances for undercount, as 1.2 million people were thought to have been missed during the taking of the 1991 Census (Heady et al., 1994), including armed forces;

2. Students to be counted at their termtime address;

3. Timing between Census day and the midyear (ageing, births, deaths and migration);

4. Data modification to maintain consistency of tables across the geographical hierarchy.

The EwC estimates became accepted as the ‘gold standard’ for 1991 mid year small area estimates (Penhale et al. 2000) and were widely used in local government and academic research including being the base population for the estimation of an annual time series of 1990s Ward level populations (Rees et al. 2004). Simpson et al. (1997) discuss these adjustments in detail.

However, the EwC estimates are not suitable directly for use to analyse population change between 1991 and 2001 for small areas after the publication by ONS of mid1991 population estimates post2001 Census by age and sex for Districts in England and Wales (Duncan et al., 2002; ONS, 2002b). There are two main reasons for this:

1. The latest mid1991 population estimates post2001 Census include revisions to estimated nonresponse in Districts, which imply that the

PART II: METHODOLOGY 195 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

same adjustment previously made by EwC for areas smaller than Districts in England and Wales should be revised.

2. The EwC estimates followed the 1991 Census geography for small areas. This implies inconsistency between the sum of the EDs in a Ward and the Ward totals due to suppression of EDs in small Wards for confidentiality reasons (Cole, 1993). The transfer of EwC estimates to the smallest census areas in the 2001 Census geography should provide consistency from OAs to higherlevel geographies as a result of the full association of areal units.

In order to revise the EwC estimates, a simple solution would be to apply an ‘evenspread’ to distribute the difference between the 1991 Census and the revised mid1991 population estimates for a District across constituent small areas pro rata to the original census count. However, this approach is inappropriate due to three main reasons:

• Nonresponse is concentrated in certain population subgroups (e.g. young adult men);

• Students and armed forces are locally concentrated;

• Response rates vary according to the difficulty of enumeration of each subDistrict area.

The EwC estimates distributed nonresponse information differentially with more allocated to areas where census enumeration was more difficult. For this reason, a defensible revision of small area populations must redistribute the revised nonresponse allowances, scaling the EwC adjustments on a small areaspecific basis using the proportion by which the District allowance changed.

PART II: METHODOLOGY 196 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

7.4: Data sources

The following data sets have been used to derive mid1991 population estimates for each OA, Ward and District in England and Wales using the 2001 Census geography by single year of age and sex.

1. EWCPOP91,ed91,a19,s

Mid1991 population estimates by fiveyear age group (19 categories) and sex for EDs in England and Wales, before revision, from EWCPOP.

2. EWCPOP91,SASw91,a19,s

Mid1991 population estimates by fiveyear age group (19 categories) and sex for Wards in England and Wales, before revision, from EWCPOP.

3. EWCPOP

C+N+T+S+M+F91,ed91,a18,s

1991 Census (C), nonresponse (N), timing (T), students (S), census modification (M) and armed forces (F) by five year age group (18 categories) and sex for EDs in England and Wales, before revision, from EWCPOP.

4. EWCPOP

C+N+T+S+M+F91,SASw91,a18,s

1991 Census (C), nonresponse (N), timing (T), students (S), census modification (M) and armed forces (F) by five year age group (18 categories) and sex for Wards in England and Wales, before revision, from EWCPOP.

PART II: METHODOLOGY 197 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

5. C91,oa01,a21,s Census table S02 by fiveyear age group (21 categories) and sex for EDs in England and Wales, from CASWEB. The table has been converted from 1991 EDs to 2001 OAs using GCT01 (Norman et al., 2007).

R 6. P 91,d01,a91,s Mid1991 revised population estimates by single year of age and sex for Districts in England and Wales, from ONS.

7. B9091,oa01,a(0),s Births from mid1990 to mid1991 for each OA in England and Wales, from ONS.

8. GCT01 GCT to transfer data from 1991 EDs to 2001 OAs in England and Wales (Norman et al., 2007).

7.5: Method

Stage 1. Calculate a total nonresponse adjustment figure by age and sex for EDs in England and Wales, according to previous (EwC) estimates.

In this stage, the total nonresponse adjustment as estimated by the EwC project, by fiveyear age group and sex for 1991 Enumeration Districts is computed. For this purpose, the average of nonresponse indicated by imputation and unemployment for ages up to 44, and the even spread non response for ages 45 and over from EwC is calculated, as defined by Simpson et al. (1997).

I N 91,ed91,a(<45),s = (NI91,ed91,a(<45),s + NU91,ed91,a(<45),s) / 2

I N 91,ed91,a(45+),s = NP91,ed91,a(45+),s

PART II: METHODOLOGY 198 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Stage 2. Constrain EwC populations and adjustments for EDs to their equivalents for Wards using the 1991 Census geography in England and Wales.

The total nonresponse and adjustments for timing, students, census modification and armed forces are made consistent with their SAS Ward total using 1991 geography definitions. This is carried out to maintain consistency of tables between EDs and Wards, as the EwC data for EDs did not exactly sum to Wards, but the Ward estimates were the more robust.

I I N91,ed91,a18,s = N 91,ed91,a18,s * (N91,SASw91,a18,s / N 91,ed(w)91,a18,s)

I I T91,ed91,a18,s = T 91,ed91,a18,s * (T91,SASw91,a18,s / T 91,ed(w)91,a18,s)

I I S91,ed91,a18,s = S 91,ed91,a18,s * (S91,SASw91,a18,s / S 91,ed(w)91,a18,s)

I I M91,ed91,a18,s = M 91,ed91,a18,s * (M91,SASw91,a18,s / M 91,ed(w)91,a18,s)

I I F91,ed91,a18,s = F 91,ed91,a18,s * (F91,SASw91,a18,s / F 91,ed(w)91,a18,s)

A P 91,ed91,a18,s = C91,ed91,a18,s + N91,ed91,a18,s + T91,ed91,a18,s + S91,ed91,a18,s +

M91,ed91,a18,s + F91,ed91,a18,s

Stage 3. Convert ED populations and adjustments to 2001 OAs in England and Wales.

The 1991 populations and adjustments for EDs in England and Wales by five year age group and sex are converted to OAs in England and Wales. For this purpose, GCT01 is used to transfer data from 1991 EDs to 2001 OAs (Norman et al., 2007).

The following calculation shows how each population by fiveyear age group and sex is multiplied by an appropriate weight indicated in the GCT. A final

PART II: METHODOLOGY 199 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

aggregation of the weighted data is allocated to each OA to produce the expected output for the smallest 2001 Census geographies.

I C 91,oa01,a18,s = C91,ed91,a18,s * Wt (GCT01)

I C91,oa01,a18,s = sum (across each OA) C 91,oa01,a18,s

I N 91,oa01,a18,s = N91,ed91,a18,s * Wt (GCT01)

I N91,oa01,a18,s = sum (across each OA) N 91,oa01,a18,s

I T 91,oa01,a18,s = T91,ed91,a18,s * Wt (GCT01)

I I T 91,oa01,a18,s = sum (across each OA) T 91,oa01,a18,s

I S 91,oa01,a18,s = S91,ed91,a18,s * Wt (GCT01)

I S91,oa01,a18,s = sum (across each OA) S 91,oa01,a18,s

I M 91,oa01,a18,s = M91,ed91,a18,s * Wt (GCT01)

I M91,oa01,a18,s = sum (across each OA) M 91,oa01,a18,s

I F 91,oa01,a18,s = F91,ed91,a18,s * Wt (GCT01)

I F91,oa01,a18,s = sum (across each OA) F 91,oa01,a18,s

Stage 4. Derive EwC mid1991 population estimates for 2001 Districts in England and Wales from the OA populations.

In this stage, EwC mid1991 population estimates for 2001 Districts are derived from the OA populations in Stage 3. For this purpose, the census counts and adjustments from Stage 3 are used.

I P 91,oa01,a18,s = C91,oa01,a18,s + N91,oa01,a18,s + T91,oa01,a18,s + S91,oa01,a18,s +

M91,oa01,a18,s + F91,oa01,a18,s

PART II: METHODOLOGY 200 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

The OA populations are aggregated to districts to provide EwC mid1991 population estimates by fiveyear age group and sex for Districts by the 2001 geography. These are used in the next stage to compute the total undercount using the mid1991 post2001 Census.

I I P 91,d01,a18,s = P 91,oa(d)01,a18,s

In addition, a variable referring to census undercount for each OA is computed. This variable is used in Stage 6, and it is derived by taking into account the initial nonresponse values and the armed forces adjustment.

U91,oa01,a18,s = N91,oa01,a18,s + F91,oa01,a18,s

Stage 5. Compute the size of revision to undercount using mid1991 population estimates post2001 Census for 2001 Districts in England and Wales.

The size of revision to undercount is calculated by subtracting the EwC mid 1991 population estimates from the mid1991 population estimates post2001 Census published by ONS, by fiveyear age group and sex. The EwC mid 1991 population estimates for 2001 Districts are obtained after aggregation of OAs by fiveyear age group and sex. The result is the undercount adjustment that is applied in the next stage to the EwC undercount.

A R I U 91,d01,a18,s = P 91,d01,a18,s P 91,d(oa)01,a18,s

Stage 6. Revise the EwC size of undercount in England and Wales at District level and distribute it across each District’s OAs’.

The adjustment of the EwC size of undercount is carried out in two steps. First, the EwC undercount for 2001 OAs obtained in Stage 4 is summed across each District and revised by the output of undercount adjustment calculated in Stage 5.

PART II: METHODOLOGY 201 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

U91,d01,a18,s = sum (across each District) U91,oa01,a18,s

R A U 91,d01,a18,s = U91,d01,a18,s + U 91,d01,a18,s

Second, the undercount revisions obtained in the previous step are distributed across each District’s OAs’ in proportion to the original undercount from EwC.

R R U 91,oa01,a18,s = U 91,d01,a18,s * (U91,oa01,a18,s / U91,d01,a18,s)

Stage 7. Create mid1991 population estimates by fiveyear age group and sex for OAs in England and Wales after the undercount revision, without ‘hierarchy’ adjustment.

In this stage, small areaspecific adjustments from Stage 4 and the undercount revision from Stage 6 are used to derive a revised set of mid1991 population estimates for OAs. The revised undercount is applied to the 1991 Census counts and the EwC adjustments for students, timing and modification within the 2001 geography remain unchanged from EwC.

R R P 91,oa01,a18,s = C91,oa01,a18,s + U 91,oa01,a18,s + S91,oa01,a18,s + T91,oa01,a18,s +

M91,oa01,a18,s

Since students are locally concentrated, it is assumed that the EwC adjustment for students transferred from EDs to OAs is more appropriate than proportionally scaling census counts to the revised mid1991 population estimates. Similarly, the EwC adjustment for timing is used, assuming the same demographic change (ageing, births, deaths and migration) between Census day (21st April) and midyear (30th June).

Stage 8. Apply residual ‘hierarchy’ adjustment to remove negative populations at OA level.

Some small negative populations are created by the above procedures as a result of (a) suppressed and special ED populations which led to mismatches

PART II: METHODOLOGY 202 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

between the sum of the EDs in a Ward and the Ward totals from EwC (Cole, 1993); and (b) the downward population revisions from ONS for a Districtage sex group which were greater than the total undercount for that group.

This is accounted for as residual ‘hierarchy’ adjustment which can be either positive or negative. First, for each agesex category any negative OA population is set to zero. Second, this adjustment upwards is balanced by a proportional reduction in all other OAs in the same District. This approach allows the maintenance of full consistency with the Districtagesex totals provided by ONS.

R RF IF P 91,oa01,a18,s < 0, P 91,oa01,a18,s = 0

Let H91,d01,a18,s be the sum of the positive OA populations in the District.

R RF R R IF P 91,oa01,a18,s > 0, P 91,oa01,a18,s = P 91,oa01,a18,s * (P 91,d01,a18,s / H91,d01,a18,s)

RF R H91,oa01,a18,s = P 91,oa01,a18,s P 91,oa01,a18,s

Stage 9. Derive mid1991 population estimates and adjustments by fiveyear age group and sex for 2001 CAS Wards in England and Wales after the undercount revision.

In this stage, OA data from Stages 7 and 8 are aggregated to Wards. This provides both revised mid1991 population estimates and adjustments by five year age group and sex for 2001 CAS Wards.

C91,CASw01,a18,s = sum (across each Ward) C91,oa01,a18,s

R R U 91,CASw01,a18,s = sum (across each Ward) U 91,oa01,a18,s

S91,CASw01,a18,s = sum (across each Ward) S91,oa01,a18,s

T91,CASw01,a18,s = sum (across each Ward) T91,oa01,a18,s

M91,CASw01,a18,s = sum (across each Ward) M91,oa01,a18,s

PART II: METHODOLOGY 203 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

H91,CASw01,a18,s = sum (across each Ward) H91,oa01,a18,s

RF R P 91,CASw01,a18,s = C91,CASw01,a18,s + U 91,CASw01,a18,s + S91,CASw01,a18,s +

T91,CASw01,a18,s + M91,CASw01,a18,s + H91,CASw01,a18,s

Stage 10. Disaggregate mid1991 population estimates for OAs in England and Wales after the undercount revision to single year of age.

In this stage, an initial single year of age OA population up to age 90 and over from the revised mid1991 population estimates for OAs by fiveyear age group and sex is initially created from the estimates created in Stage 8. For this purpose, various strategies are implemented according to age groups.

Since censuses have a tendency to undercount infants (Jeffries and Fulton, 2005), an approach is used for those less than one year old to alleviate this risk. Hence, information relating to the number of births from Vital Statistics in OAs from mid1990 to mid1991 is used.

RF RF P 91,oa01,a(0),s = (B9091,oa01,a(0),s + (P 91,oa01,a(04),s / 5)) / 2

Second, for ages 1, 2, 3 and 4, equal allocation is used to distribute the initial population from fiveyear age groups to single year of age. The population for initial age 0 is taken into account to derive the initial single year of age OA population.

RF RF RF P 91,oa01,a(1),s = (P 91,oa01,a(04),s P 91,oa01,a(0),s) / 4

RF RF RF P 91,oa01,a(2),s = (P 91,oa01,a(04),s P 91,oa01,a(0),s) / 4

RF RF RF P 91,oa01,a(3),s = (P 91,oa01,a(04),s P 91,oa01,a(0),s) / 4

RF RF RF P 91,oa01,a(4),s = (P 91,oa01,a(04),s P 91,oa01,a(0),s) / 4

Third, for ages 59 and 1014, equal allocation is also used to distribute the fiveyear age groups populations to single year of age. Repeatedly, each five

PART II: METHODOLOGY 204 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

year age group is divided by the number of ages within that category. Two examples are shown below for each group.

RF RF P 91,oa01,a(5),s = P 91,oa01,a(59),s / 5

RF RF P 91,oa01,a(10),s = P 91,oa01,a(1014),s / 5

Fourth, for ages 1519, the population proportions by age and sex indicated from the 1991 Census table S02 are taken into account, which are applied to the total population by fiveyear age group and sex.

RF RF P 91,oa01,a(15),s = P 91,oa01,a(1519),s * Wt C91,oa01,a(15),s

RF RF P 91,oa01,a(16),s = P 91,oa01,a(1519),s * Wt C91,oa01,a(16),s

RF RF P 91,oa01,a(17),s = P 91,oa01,a(1519),s * Wt C91,oa01,a(17),s

RF RF P 91,oa01,a(18),s = P 91,oa01,a(1519),s * Wt C91,oa01,a(18),s

RF RF P 91,oa01,a(19),s = P 91,oa01,a(1519),s * Wt C91,oa01,a(19),s

Where Wt C91,oa01,a(15),s + Wt C91,oa01,a(16),s + Wt C91,oa01,a(17),s + Wt C91,oa01,a(18),s

+ Wt C91,oa01,a(19),s = 1

Since the 1991 Census table S02 provides detail of age for 1617 and 1819 in the same categories, these have been previously divided by 2 before the calculation of proportions for these ages.

Fifth, for ages 2024 up to 8084, equal allocation is also used so that each fiveyear age group is divided by the number of ages within that category. Two examples are shown below for each group.

RF RF P 91,oa01,a(20),s = P 91,oa01,a(2024),s / 5

RF RF P 91,oa01,a(80),s = P 91,oa01,a(8084),s / 5

PART II: METHODOLOGY 205 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Finally, for ages 85 and over, an initial single year of age is calculated according to the population proportion indicated in the census table S02 for ages 8589 and 90 and over.

RF RF P 91,oa01,a(85),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(85),s

RF RF P 91,oa01,a(86),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(86),s

RF RF P 91,oa01,a(87),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(87),s

RF RF P 91,oa01,a(88),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(88),s

RF RF P 91,oa01,a(89),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(89),s

RF RF P 91,oa01,a(90+),s = P 91,oa01,a(85+),s * Wt C91,oa01,a(90+),s

Where Wt C91,oa01,a(85),s + Wt C91,oa01,a(86),s + Wt C91,oa01,a(87),s + Wt C91,oa01,a(88),s

+ Wt C91,oa01,a(89),s + Wt C91,oa01,a(90+),s = 1

A final single year of age for the revised mid1991 estimates for OA is implemented using IPF. Initial counts from Stage 10 are used as initial values in IPF to maintain agreement with both the OA fiveyear age groups previously estimated in Stage 9 and the District single year of age post2001 published by ONS.

To run IPF, a margins variable is computed using the margin values from OAs by fiveyear age group and the margin values from Districts by single year of age.

RF R RF Margins = P 91,oa01,a18,s * P 91,d01,a91,s / P 91,d01,a91,s

The denominator is derived from the margin values from OAs by fiveyear age group, and it is the sum over single year of age as an aid to computing the margins variable.

PART II: METHODOLOGY 206 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

The following information is used to run IPF in SPSS:

RF Initial values: P 91,oa01,a91,s from Stage 10

RF Margin: P 91,oa01,a18,s from Stage 8

R Margin: P 91,d01,a91,s from ONS mid1991 population estimates

Result: P91,oa01,a91,s

Within this procedure, IPF operates across single year of age and OA within each District by fiveyear age group and sex. It assumes that within those categories, the ageOA interaction is as in the previously created OA estimates by single year of age and sex from equal allocation.

Stage 11. Derive mid1991 population estimates by single year of age and sex for 2001 ST Wards and Districts in England and Wales.

Finally, mid1991 population estimates for ST Wards and Districts by single year of age and sex are derived from Stage 10. Since the aggregation of mid 1991 for OAs across each Ward results in 2001 CAS Wards, GCT06 is used, with one record for each CAS Ward and its corresponding ST Ward (Hayes, 2006). This allows the production of 2001 ST Ward estimates.

P91,CASw01,a91,s = sum (across each Ward) P91,oa01,a91,s

P91,STw01,a91,s = sum (over CAS Wards in ST Wards) P91,CASw01,a91,s

Mid2001 population estimates for 2001 Districts by single year of age and sex are derived from the previously created mid1991 population estimates for ST Wards by aggregation.

P91,d01,a91,s = sum (across each District) P91,STw01,a91,s

PART II: METHODOLOGY 207 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

7.6: Validation

The data set resulting from the procedures described above has 31,928,988 cases, one for each combination of:

• 2001 Output Areas = 175,434

• Age (90 single years and 90 and over) = 91

• Sex (Male and Female) = 2

Figure 7.2 shows the total difference between the revised mid1991 population estimates after implementing IPF and the known subtotals from ONS post2001 Census in England and Wales for each District.

Figure 7.2: Total difference between the mid-1991 population estimates obtained after IPF and the known sub-totals in England and Wales by Districts

PART II: METHODOLOGY 208 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

As expected, the overall difference between the marginal totals and the known subtotals is always near zero, thus indicating how close they are to one another. For this calculation the marginal totals for each OA by single year of age and sex have been aggregated across each 2001 District.

Table 7.1: EwC and revised 1991 undercount by age and sex in England and Wales

Age groups EwC Revised Undercount

18 categories undercount undercount adjustment

Males Females Total Males Females Total Males Females Total 1 04 60,233 45,230 105,463 40,593 45,230 85,823 19,640 0 19,640

2 59 52,496 37,761 90,257 35,473 37,761 73,234 17,023 0 17,023

3 1014 32,385 21,056 53,441 16,325 21,056 37,381 16,060 0 16,060

4 1519 52,465 22,616 75,081 34,621 22,616 57,237 17,844 0 17,844

5 2024 176,085 51,106 227,191 121,676 51,106 172,782 54,409 0 54,409

6 2529 202,365 65,606 267,971 110,520 65,606 176,126 91,845 0 91,845

7 3034 94,414 27,675 122,089 40,630 27,675 68,305 53,784 0 53,784

8 3539 38,796 8,072 46,868 18,755 8,072 26,827 20,041 0 20,041

9 4044 35,811 12,027 47,838 21,276 12,027 33,303 14,535 0 14,535

10 4549 4,185 1,104 5,289 4,185 1,104 5,289 0 0 0

11 5054 1,606 1,870 3,476 1,606 1,870 3,476 0 0 0

12 5559 3,297 459 3,756 3,297 459 3,756 0 0 0

13 6064 341 524 865 341 524 865 0 0 0

14 6569 82 2,986 2,904 82 2,986 2,904 0 0 0

15 7074 125 154 29 125 154 29 0 0 0

16 7579 406 2,957 3,363 406 2,957 3,363 0 0 0

17 8084 5,407 19,828 25,235 375 5,132 4,757 5,782 14,696 20,478

18 85+ 2,827 35,828 38,655 12 12,838 12,826 2,839 22,990 25,829 Total 762,644 349,531 1,112,175 448,842 311,845 760,687 313,802 37,686 351,488

NB: The undercount adjustment is computed as the difference between the revised and EwC undercount.

Table 7.1 displays the total differences between the EwC and revised undercount by fiveyear age group and sex in England and Wales. The table clearly shows how the revised adjustment of undercount has been subjected

PART II: METHODOLOGY 209 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

to a downward revision after the publication of revised mid1991 population estimates post2001 by ONS (Duncan et al., 2002; ONS, 2002b). The overall revisions reduce the EwC undercount by onethird of the originally estimated undercount. As expected, the major revisions are found among young males particularly for those aged 2034.

Table 7.2 shows the revised mid1991 population estimates obtained from OAs in England and Wales by age and sex. Although detail of single year of age has also been derived for OAs, for simplicity age is aggregated into five year age groups. The table includes the revised undercount and the unchanged adjustments for students, timing and modification used to derive the revised mid1991 population estimates. The results are consistent with that published by ONS for Districts in England and Wales by age and sex post2001 Census.

PART II: METHODOLOGY Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Table 7.2: Revised mid-1991 population estimates by age and sex in England and Wales

Age groups Census 1991 Revised Students Timing Modification Revised

18 categories as published undercount mid1991

Males Females Total Males Females Total Males Females Total Males Females Total Males Females Total Males Females Total 1 04 1,695,385 1,618,703 3,314,088 40,593 45,230 85,823 0 0 0 4,283 4,556 8,839 713 1,427 2,140 1,740,974 1,669,916 3,410,890

2 59 1,598,835 1,521,811 3,120,646 35,473 37,761 73,234 1,319 1,140 2,459 3,591 3,628 7,219 746 1,231 1,977 1,639,964 1,565,571 3,205,535

3 1014 1,531,626 1,454,331 2,985,957 16,325 21,056 37,381 5,003 4,315 9,318 4,217 3,830 8,047 393 1,186 1,579 1,557,564 1,484,718 3,042,282

4 1519 1,621,075 1,562,325 3,183,400 34,621 22,616 57,237 8,165 8,270 16,435 11,733 13,775 25,508 15,049 7,015 22,064 1,667,177 1,586,451 3,253,628

5 2024 1,814,489 1,866,827 3,681,316 121,676 51,106 172,782 8,221 7,860 16,081 3,590 5,227 8,817 30,043 20,016 50,059 1,970,839 1,940,582 3,911,421

6 2529 1,939,275 2,003,841 3,943,116 110,520 65,606 176,126 3,472 2,476 5,948 986 2,146 1,160 18,533 9,260 27,793 2,070,814 2,083,329 4,154,143

7 3034 1,789,948 1,818,029 3,607,977 40,630 27,675 68,305 1,289 713 2,002 6,177 8,928 15,105 10,748 3,983 14,731 1,848,792 1,859,328 3,708,120

8 3539 1,638,178 1,659,601 3,297,779 18,755 8,072 26,827 616 441 1,057 241 1,685 1,926 7,397 3,006 10,403 1,665,187 1,672,805 3,337,992

9 4044 1,818,251 1,835,186 3,653,437 21,276 12,027 33,303 297 128 425 6,472 5,558 12,030 5,917 2,761 8,678 1,839,269 1,844,544 3,683,813

10 4549 1,532,339 1,533,983 3,066,322 4,185 1,104 5,289 180 70 250 21,149 21,781 42,930 5,022 2,279 7,301 1,562,875 1,559,217 3,122,092

11 5054 1,356,829 1,357,428 2,714,257 1,606 1,870 3,476 0 0 0 6,224 5,546 11,770 4,041 1,559 5,600 1,356,252 1,355,311 2,711,563

12 5559 1,271,309 1,290,651 2,561,960 3,297 459 3,756 0 0 0 1,439 1,023 2,462 3,644 1,265 4,909 1,279,689 1,293,398 2,573,087

13 6064 1,232,527 1,321,199 2,553,726 341 524 865 0 0 0 1,473 3,162 4,635 3,122 1,857 4,979 1,233,835 1,319,370 2,553,205

14 6569 1,149,660 1,334,912 2,484,572 82 2,986 2,904 0 0 0 4,184 8,091 12,275 3,317 2,627 5,944 1,148,875 1,326,462 2,475,337

15 7074 867,352 1,140,739 2,008,091 125 154 29 0 0 0 8,362 8,344 16,706 2,663 3,640 6,303 878,502 1,152,569 2,031,071

16 7579 648,726 1,007,414 1,656,140 406 2,957 3,363 0 0 0 950 84 866 2,668 4,532 7,200 652,750 1,014,819 1,667,569

17 8084 371,863 733,087 1,104,950 375 5,132 4,757 0 0 0 2,507 2,020 4,527 2,644 5,555 8,199 376,639 745,794 1,122,433

18 85+ 186,550 565,472 752,022 12 12,838 12,826 0 0 0 2,686 5,656 8,342 2,116 8,546 10,662 191,340 592,512 783,852

Total 24,064,217 25,625,539 49,689,756 448,842 311,845 760,687 28,562 25,413 53,975 20,940 22,154 43,094 118,776 81,745 200,521 24,681,337 26,066,696 50,748,033

PART II: METHODOLOGY 211 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

7.7: Conclusions and summary

This section has focused on the estimation of mid1991 population estimates by single year and sex using the 2001 Census geography for OAs, Wards and Districts in England and Wales. These estimates have been produced using information by age and sex from EwC for EDs and SAS Wards and the latest mid1991 population estimates published by ONS for Districts post2001 Census.

The method used to redistribute the revised undercount from Districts to OAs has proven to be a valid solution. As noted earlier, this approach is seen as being significantly more appropriate than distributing the difference between census and midyear estimates for a District across constituent small areas pro rata to the original census count. Since students are locally concentrated, the method has also adopted the student adjustment from EwC for each ED, and transferred to OAs. Again, this is assumed to be more appropriate than proportionally scaling census counts to the revised mid1991 population estimates. In addition, the method has taken the EwC adjustment for timing, thus assuming the same proportional demographic change between Census day and midyear for areas smaller than Districts as for the containing District. Within this context, the use of an appropriate GCT has been crucial to convert ED populations and adjustments to 2001 OAs in England and Wales.

Additionally an aspect of consistency between geographies not addressed in the original EwC project has been solved. Whilst the EwC ED estimates did not sum to their associated Wards, so there were discrepancies in the outputs, the revised estimates have removed this inconsistency so that the agesex outputs agree across the subdistrict geographical hierarchy.

Finally, to make the revised mid1991 population estimates by fiveyear age group more versatile, single year of age has been estimated using information from the District level single year of age distributions, except in two particular cases: (1) For those aged less than one year old, for which local counts of registered births in the year before the 1991 Census have been used; and (2)

PART II: METHODOLOGY 212 Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

for older teenagers and those aged 85 and over, for which 1991 Census age detail has been borrowed.

Table 7.3 gives a summary of the issues, strategies and methods used to deal with the four problems reviewed in Chapter 2. These are presented in the order that they are dealt with in the estimation process.

Chapter 8 describes the methods implemented to derive a student transfer from vacation to termtime address for each 2001 OA in England and Wales by fiveyear age, sex and ethnic group.

PART II: METHODOLOGY Chapter 7: Mid1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Table 7.3: Summary to create full mid-1991 population estimates for Output Areas and above in England and Wales (without ethnic group)

Issues Strategies Methods / assumptions

Population definition Student transfer Move students from vacation to term The EwC adjustment for students in each ED is used. Since students are locally concentrated, time address. it is assumed that this strategy is more appropriate than proportionally scaling census counts to the revised mid1991 population estimates.

Timing Move from Census day to midyear The EwC adjustment for timing is used. This assumes the same proportional demographic (30th June). change (ageing, births, deaths and migration) between Census day and midyear for areas smaller than Districts as for the containing District.

Boundary harmonisation Estimates for 1991 EDs are transferred A GCT is used to convert EwC data from the 1991 EDs to 2001 OAs. The EDOA GCT is to 2001 OAs, and summed 2001 CAS defined and constructed by Norman et al. (2007) using postcode lookup tables provided by and ST Wards and Districts. ONS and OS.

Nonresponse The difference between EwC mid1991 The ONS revision to 1991 nonresponse by 5year age groups and sex (mostly a reduction population and ONS revised mid1991 among men aged under 40) is distributed to each 2001 District’s OAs’ in proportion to the EwC incorporated 1991 non population (estimated by ONS for 2001 original undercount estimated by EwC. response estimated in 1994. Districts) constitutes the ONS revision ONS revised the estimate of to nonresponse. 1991 nonresponse in 2002. Ethnic group categories Not applied here. See Chapter 9. None

Single year of age (91 categories) is Age group categories Initially, five year agegroups are divided by five except ages 04, 1519 and 85+ where created from 5year age groups. different solutions are applied. For age 0, information on births form Vital Statistics is used. For ages within 1519 and 85+, census counts from SAS Table 02 are used.

Iterative Proportional Fitting (IPF) is used to derive single year of age. OA data with 5year age sex structure is made consistent with the District data for allgroups by single year of age and sex from ONS, the interaction (singleyear by OA) coming from equal allocation.

PART II: METHODOLOGY 214

Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

8.1: Introduction

This chapter describes the methodology used for the creation of a 1991 student transfer from vacation to termtime address for OAs, Wards and Districts using the 2001 Census geography in England and Wales by age, sex and ethnic group. These are consistent with the EwC adjustment of students by age and sex used in Chapter 7.

Section 8.2 describes the main stages involved in the creation of this student transfer for OAs, Wards and Districts. Section 8.3 gives background information on the previous data sets for 1991 by age and sex. Section 8.4 provides detail of the data sources used to derive the 1991 student transfer with an ethnic group dimension. Section 8.5 describes the methods used to create the student transfer in three stages. A validation of the results is given in Section 8.6.

8.2: Objective and overview

The objective is to create a 1991 transfer of students from vacation to term time address with an ethnic group dimension using the 2001 Census geography for OAs, Wards and Districts. This adjustment is used in Chapter 9 for the creation of revised mid1991 population estimates with an ethnic group dimension.

PART II: METHODOLOGY 215 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

The main task consists of using information from OPCS of the number of students whose vacation address was in a different District from their term time address, and transfer these students to their termtime address using the 2001 Census geography for Districts, Wards and OAs and with an ethnic group dimension. The creation of this student transfer has been implemented in three stages:

1. Convert OPCS student transfers from 1991 to 2001 Districts.

2. Share the 1991 student transfers to ethnic groups.

3. Share the 1991 District net student transfers of each ethnic group to 2001 CAS Wards and OAs.

Figure 8.1 shows the transition with three stages to create a student transfer by fiveyear age, sex and ethnic group for each OA, Ward and District in England and Wales using the 2001 Census geography.

Figure 8.1: Transition to create a 1991 student adjustment with ethnic group for Output Areas and above in England and Wales

1991 student adjustment from OPCS

Convert student transfer from 1991 to Stage 1

2001 Districts

Share 1991 student transfers to ethnic Stage 2 groups

Share 1991 District adjustment to 2001 Stage 3

Wards and OAs

PART II: METHODOLOGY 216 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

8.3: Background

The 1991 student transfer described in this chapter is based on the previous EwC research to derive a student adjustment without an ethnic group dimension (Simpson et al., 1997). In EwC research, indicators from the 1991 Census were used to allocate these flows to Wards and enumeration districts within each local authority district. There remains on EwC outputs the net adjustment for each Ward and ED, by age and sex.

Ideally, one wishes to share the flows of students into and out of each District to each 1991 ethnic group. However there are no data to directly help to identify the ethnic group composition of students studying in a different district from their census vacation address. Nonetheless, the 1991 Samples of Anonymised Records (SARs) has a variable showing whether a student was resident during termtime at the same address or a different address, the latter being divided into addresses in the same or different region, and not known.

Table 8.1 gives this information for students aged 2024 (as shown in Chapter 2). Although the data for ages 1824 are not shown, the figures are very similar. As expected, the results indicate that the great majority of students were resident during termtime at the same address as at vacation. It can also be noted that the ethnic composition of students whose termtime address was the same as the vacation address is not like that of other students, it is noticeably less White. In contrast, the ethnic composition of those studying away from their vacation address is more similar to the ethnic composition of the population as a whole, although with some exceptions such as the Black Caribbean and the Pakistani groups.

The differences between the ethnic composition of the population and that of students for these ages can be explained by two factors: (1) students of a particular ethnic group are more likely to live at home; and (2) some ethnic groups are better represented in higher education than others (Mitchell et al., 2002). Within this context, it seems that students for these ages tend to be White, Indian, or Chinese rather than Black Caribbean.

PART II: METHODOLOGY 217 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Table 8.1: Percentage distribution between ethnic groups of those aged 20-24

Source: 1991 SARs.

This would suggest that the removal of students from the 1991 population could assume an ethnic distribution of the population of the relevant age. However, the composition of students added to the District in which they study, which also includes overseas students, is unlikely to be the same as the composition of the receiving District. A way to solve this issue is by taking into account the 2001 ethnic composition of students. Although it is assumed that there has been an expansion of student numbers since 1991 (with the likely impact on the student composition), the 2001 Census is the only source of data that recognises the ethnic composition of students as different from the population. For this purpose, the addition and removal of students is given as follows:

• The ethnic composition of students removed from the District is given according to the ethnic group composition of residents of the same age.

PART II: METHODOLOGY 218 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

• The ethnic composition of students added to the District is given according to the ethnic group composition of residents of the same age (age 1017), or of students in termtime taken from the 2001 Census (ages 18 and over).

Although the solution is very approximate, it is considered that this approach is more plausible than other options such as taking the ethnic composition of students to be the same as the local population.

8.4: Data sources

The following data sets have been used to derive a student transfer for each OA, Ward and District in England and Wales using the 2001 Census geography by fiveyear age, sex and ethnic group.

1. Sa91,d91,a11,s,● OPCS addition of students whose termtime address was in the District, but not their vacation address. It has detail of fiveyear age groups 59 to 5054 with additional split at age 17/18.

2. Sr91,d91,a11,s,● OPCS removal of students whose vacation address was in the District, but not their termtime address. It has detail of fiveyear age groups 59 to 5054 with additional split at age 17/18.

3. Sa91,SASw91,●,●,● Indicator of students whose termtime address was in the SAS Ward, but different from their vacation address, as used in EwC.

4. Sr91,SASw91,●,●,● Indicator of students whose vacation address was in the SAS Ward, but different from their termtime address, as used in EwC.

5. S91,d01,a18,s,● Net transfer of students from vacation address to term time address for 2001 Census Districts, from Chapter 7.

PART II: METHODOLOGY 219 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

6. S91,CASw01,a18,s,● Ditto, for 2001 CAS Ward.

7. S91,oa01,a18,s,● Ditto, for 2001 OAs.

8. Cs01,d01,a(1624),s,e Census table ST108, students aged 1624 by ethnic group and sex.

9. Cs01,d01,a(1618),s,● Census table T02, fulltime students and schoolchildren aged 16, 17, 18 by sex.

10. C01,d01,a22,s,e Census table ST101, population aged 1617, 1819, 20 24 by ethnic group and sex.

11. GCT04 GCT to transfer data from 1991 SAS Wards to 2001 Districts in England and Wales (Simpson, 2007b).

12. GCT05 GCT to transfer data from 1991 Districts to 2001 Districts in England and Wales (Simpson, 2007c).

8.5: Method

Stage 1. Convert OPCS student transfers from 1991 to 2001 Districts.

In this stage, the OPCS student transfer by age and sex is converted from 1991 to 2001 Districts. Since students are focused in particular parts of a District, two appropriate GCTs are constructed from GCT01. GCT04 indicates the population proportion of each 1991 SAS Ward in each 2001 District (Simpson, 2007b). This allows the calculation of the student addition 1991 Ward indicator (as defined in Simpson et al., 1997) for each 2001 District. It is only different from the 1991 Ward value when the 1991 Ward crosses a 2001 District. The same procedure is applied to compute the student removal 1991 Ward indicator within each 2001 District.

SaSASw91d01 = Sa91SASw91 * Pr91d01

PART II: METHODOLOGY 220 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

SrSASw91d01 = Sr91SASw91 * Pr91d01

The result is the student addition Ward indicator for each intersection of 1991 District and 2001 District. GCT05 indicates the proportion of each 1991 District in each 2001 District (Simpson, 2007c). The same procedure applies to the student removal.

Sad91d01 = sum over 1991 District (SaSASw91d01)

Srd91d01 = sum over 1991 District (SrSASw91d01)

Finally, the proportions of student addition and removal for a 1991 District which lies in a 2001 District are computed. This facilitates the calculation of an initial transfer of the OPCS student adjustments from 1991 to 2001 Districts.

Sapd91d01 = Sad91d01 / Sad91

Srpd91d01 = Srd91d01 / Srd91

SaId01,a11,s = sum over 1991 District (Sad91,a11,s * Sapd91d01)

SrId01,a11,s = sum over 1991 District (Srd91,a11,s * Srpd91d01)

The difference between these initial values and the net transfer of students from EwC, transferred to 2001 Districts, is computed. As a result, the initial estimates of additions and removals of students from OPCS can be revised so that the net transfer is equal to that computed already, by adding half of the difference to the additions and subtracting half from the removals. For the two calculations the age category 1519 is split into two age groups, proportional to the flows in the initial values. This differs from the EWCPOP data set, where this category is not divided.

Sdiffd91,a10,s = (S91,d01,a10,s,● – [SaId01,a10,s,● – SrId01,a10,s,●])

SaIId01,a10,s = SaId01,a10,s,● + Sdiffd91,a10,s,● / 2

SrIId01,a10,s = SrId01,a10,s,● + Sdiffd91,a10,s,● / 2

PART II: METHODOLOGY 221 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Because some negative values result from the above calculations, a solution adds the opposite flow.

IF SaIId01,a11,s,● < 0 Sad01,a11,s,● = 0 and Srd01,a11,s,● = SrIId01,a11,s,● – SaIId01,a11,s,●

IF SrIId01,a11,s,● < 0 Srd01,a11,s,● = 0 and Sad01,a11,s,● = SaIId01,a11,s,● – SrIId01,a11,s,●

Otherwise Sad01,a11,s,● = SaIId01,a11,s,● and Srd01,a11,s,● = SrIId01,a11,s,●

Stage 2. Share the 1991 student transfers to ethnic groups.

In this stage, an ethnic group dimension is given to the 1991 student transfer separately for males and females for two groups: schoolchildren and older students. First, to compute the number of schoolchildren with an ethnic group dimension, census table T02 is used for schoolchildren, who are given the ethnic composition of the population aged 1617 from census table ST101. For the calculation, schoolchildren are considered to be all those aged 16, 17 and two thirds of those aged 18 (those with birthdays between Census day 29th April and the end of September will already have left school).

Cs01,d01,a(1618),s,e = (Cs01,d01,a16,s,● + Cs01,d01,a17,s,● + (2/3) Cs01,d01,a18,s,●)

* (Cs01,d01,a(1617),s,e / Cs01,d01,a(1617),s,●)

Second, to compute the number of students by ethnic group for the age group 1624 as a whole census table ST108 is used. Since this table includes schoolchildren, these are deducted from students aged 1624, to infer the ethnic composition of postschool students. This gives an estimate of students aged 1824 in fulltime postschool education, by ethnic group.

Cs01,d01,a(1824),s,e = Cs01,d01,a(1624),s,e Cs01,d01,a(1618),s,e

Following the previous calculation, the ethnic composition of students aged 1824 in fulltime postschool education is computed as a percentage of the total, separately for males and females.

PART II: METHODOLOGY 222 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Csp01,d01,a(1824),s,e = Cs01,d01,a(1824),s,e / Cs01,d01,a(1824),s,●

Finally, the ethnic composition of students aged 25 and over is computed directly from census table ST108. From the census table, the ethnic group distributions are used to add students aged 18 and over to their termtime District where different from vacation District. The District ethnic group distribution is used for removal of students. In the following calculation, the ethnic group proportion within each District by age and sex is labelled saep and srep for students added and removed respectively.

Sad01,a11,s,e = Sad01,a11,s * saep

Srd01,a11,s,e = Srd01,a11,s * srep

Stage 3. Share the 1991 net student transfers to ethnic groups for 2001 CAS Wards and OAs.

In this stage, the ethnic group distribution of additions and removals for each District by age and sex are applied to the positive and negative net transfers in each CAS Ward and OA. Since the total net transfers summed across Wards in a District are not exactly equal to the total already calculated for a District by age, sex and ethnic group, the difference is allocated equally to each Ward (i.e. if there are 20 Wards, each Ward receives one twentieth of the discrepancy). The same procedure is repeated for OAs within each Ward.

IF SCASw01,a18,s,● > 0 then SCASw01,a18,s,e = SCASw01,a18,s,● * pSad01,a11,s,e

IF SCASw01,a18,s,● < 0 then SCASw01,a18,s,e = SCASw01,a18,s,● * pSrd01,a11,s,e

IF Soa01,a18,s,● > 0 then Soa01,a18,s,e = Soa01,a18,s,● * pSaCASw01,a11,s,e

IF Soa01,a18,s,● < 0 then Soa01,a18,s,e = Soa01,a18,s,● * pSrCASw01,a11,s,e

PART II: METHODOLOGY 223 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

8.6: Validation

The data set resulting from the procedures described above has 63,156,240 cases, one for each combination of:

• 2001 Output Areas = 175,434

• Age (5year age groups up to 85 and over) = 18

• Sex (Male and Female) = 2

• 1991 Ethnic groups = 10

Table 8.2 shows the 1991 net student transfer to termtime address by ethnic group as estimated for England and Wales. For simplicity ethnic groups are not disaggregated by age and sex. As expected, the total number of 1991 students transferred from vacation to termtime address is consistent with the 1991 student transfer without ethnic group from EwC used in Chapter 7.

Table 8.2: 1991 net student transfer to term-time address by ethnic group in England and Wales

Ethnic group Student transfer 10 categories

1 White 2,142 2 Black Caribbean 386 3 Black African 7,517 4 Black Other 1,822 5 Indian 11,429 6 Pakistani 5,510 7 Bangladeshi 1,968 8 Chinese 10,293 9 Asian Other 2,816 10 Other Other 10,092 Total 53,975

PART II: METHODOLOGY 224 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

It represents a net impact of student transfers for the whole of England and Wales, presumably because of overseas students (including from Scotland and Northern Ireland) who are not counted as usually resident during vacation time but included in the population estimates as usually resident during term time. The table below exemplifies how the ethnic composition of students transferred to the address in which they study, which also includes overseas students, is predominantly nonWhite, with the Indian group and the Chinese groups experiencing the largest student transfers.

Table 8.3 shows the 1991 net student transfer to termtime address obtained from OAs by fiveyear age group and sex. The output table is equivalent to the 1991 net student transfer to termtime address used in Chapter 7 for the revision of mid1991 population estimates by age and sex without an ethnic group dimension. Similarly, it highlights that over half the students transferred to a termtime address from a different district vacation address are aged 15 24, and another fifth are aged 1014.

Table 8.4 shows the five Districts with the highest and lowest 1991 net student transfer. As expected, those Districts which receive the largest student transfers are Districts with large universities, with significant numbers of overseas students. On the contrary, those Districts which experience a loss of students are nonUniversity Districts which, in most cases, appear to experience the pull factor from neighbouring Districts with large universities in the region such as Manchester, Leeds, Sheffield and Liverpool.

PART II: METHODOLOGY 225 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Table 8.3: 1991 net student transfer to term-time address by age and sex in England and Wales

Age groups Students

18 categories

Males Females Total 1 04 0 0 0

2 59 1,319 1,140 2,459

3 1014 5,003 4,315 9,318

4 1519 8,165 8,270 16,435

5 2024 8,221 7,860 16,081

6 2529 3,472 2,476 5,948

7 3034 1,289 713 2,002

8 3539 616 441 1,057

9 4044 297 128 425

10 4549 180 70 250

11 5054 0 0 0

12 5559 0 0 0

13 6064 0 0 0

14 6569 0 0 0

15 7074 0 0 0

16 7579 0 0 0

17 8084 0 0 0

18 85+ 0 0 0

Total 28,562 25,413 53,975

PART II: METHODOLOGY 226 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Table 8.4: Districts with greatest 1991 student transfer in England and Wales

District name Student transfer

OXFORD 1 14,538

MANCHESTER 2 14,036

CAMBRIDGE Highest 3 11,022

LEEDS 4 8,633

SHEFFIELD 5 8,162

WIRRAL 1 2,642

STOCKPORT 2 2,162

MACCLESFIELD Lowest 3 2,161

SEFTON 4 1,989

SOLIHULL 5 1,824

The following figures display the 1991 net student transfer to termtime address by age, sex and ethnic group in two Wards near universities. For this purpose, Carfax in Oxford and Fallowfield in Manchester are used. Figure 8.2 shows the net student transfer for the White group for these two Wards separately. As expected, the adjustment illustrates how these two Wards experience a significant gain due to students moving to their termtime address. The largest net student transfers are found among those aged 20 24, with similar adjustments for males and females in Fallowfield (Manchester), and slightly higher for males than females in Carfax (Oxford).

Similarly, Figure 8.3 shows the net student transfer for the nonWhite groups in these two Wards. The results illustrate how the largest net student transfers are found among ethnic groups such as the Chinese and the Indian. Contrarily, the net student transfer for ethnic groups such as the Black Caribbean and the Bangladeshi is significantly smaller.

PART II: METHODOLOGY Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Figure 8.2: 1991 net student transfer to term-time address by age and sex for the White group in two Wards

Carfax (Oxford) Fallowfield (Manchester)

PART II: METHODOLOGY Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

Figure 8.3: 1991 net student transfer to term-time address by age and sex for the non-White groups in two Wards

Carfax (Oxford) Fallowfield (Manchester)

PART II: METHODOLOGY 229 Chapter 8: 1991 student transfer for Output Areas and above in England and Wales

8.7: Conclusions

The method used to create a 1991 transfer of students with an ethnic group dimension using the 2001 Census geography has been described in this chapter. The cascading down from District to smaller areas by age, sex and ethnic group has been reviewed, providing consistent results. However, it is not thoroughly defensible. For example, the ethnic composition of students removed is in all areas the District population composition, which may be different from the small area composition. The resources required to design and program the student transfers to reflect small area composition and simultaneously to be consistent with the District totals, are more than the arguable gain in accuracy of the results. There may however be areas where the transfers result in locally implausible results.

In the next chapter, the 1991 net student transfer by ethnic group for OAs is used for the creation of revised mid1991 population estimates by age, sex and ethnic group using the 2001 Census geography in England and Wales.

PART II: METHODOLOGY 230

Chapter 9: Mid-1991 population estimates for Output Areas and above in England and Wales

9.1: Introduction

This chapter describes the methodology used for the creation of mid1991 population estimates for OAs, Wards and Districts using the 2001 Census geography in England and Wales by age, sex and ethnic group. These estimates are consistent with the previously created mid1991 population estimates by age and sex described in Chapter 7 and, therefore, they are also consistent with the latest mid1991 population estimates published by ONS post2001 Census (Duncan et al., 2002; ONS, 2002b).

Section 9.2 describes the main stages involved in the creation of these estimates for OAs, Wards and Districts. Section 9.3 gives background information on the previous data sets for 1991 by age, sex and ethnic group. Section 9.4 gives detail of the data sources used to create the target mid 1991 population estimates. The methods used to create such estimates in seven stages are described in Section 9.5. A validation of the results is given in Section 9.6 and, finally, a summary table of the issues, strategies and methods used to deal with the four problems are provided in Section 9.7.

9.2: Objective and overview

The objective is to create mid1991 population estimates by single year of age, sex and ethnic group using the 2001 Census geography for OAs, Wards and Districts in England and Wales in the light of the latest available data post2001 Census. Previous mid1991 population estimates from the EwC project are used (i.e. SOCPOP data). PART II: METHODOLOGY 231 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

The main task consists of revising the initial nonresponse allowance included in the previous 1991 Census counts by the EwC project and including a timing adjustment subsumed to this revision so that mid1991 population estimates for small areas are created.

The resulting mid1991 population estimates for Districts and smaller areas by age, sex and ethnic group with a revision of nonresponse and timing, are fully consistent with the mid1991 population estimates by age and sex for Districts in England and Wales published by ONS post2001 Census (Duncan et al., 2002; ONS, 2002b). The approach to achieve consistency between the ethnic group population estimates and the official population estimates without ethnic group is based on the application of the previously created mid1991 population estimates by age and sex for OAs and above, as described in Chapter 7.

In addition, a student net adjustment with detail of age, sex and with an ethnic group dimension is included from Chapter 8. The implementation of this adjustment is undertaken at OA level, and it is consistent with the student net adjustment without ethnic group from EwC, which is used in Chapter 7 for the mid1991 population estimates for allgroups.

The creation of these mid1991 population estimates has been implemented in seven stages:

1. Derive a threedimensional census table from the two twodimensional tables of S06, with data crosstabulated by broad age, sex and ethnic group for each ED in England and Wales.

2. Disaggregate the 1991 SOCPOP estimates for Wards to each ED in England and Wales using the threedimensional table created from S06.

3. Convert SOCPOP ED estimates to OAs using the 2001 Census geography in England and Wales. PART II: METHODOLOGY 232 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

4. Scale the SOCPOP estimates to the allgroups estimate (without students) for each OA in England and Wales.

5. Add student adjustment with an ethnic group dimension to each OA in England and Wales.

6. Disaggregate mid1991 population estimates for OAs in England and Wales by fiveyear age, sex and ethnic group to single year of age.

7. Aggregate the OA estimates to derive mid1991 population estimates for ST Wards and Districts in England and Wales by single year of age, sex and ethnic group.

Figure 9.1 shows the transition with seven stages used to create mid1991 population estimates by single year of age, sex and ethnic group for each OA, ST Ward and District in England and Wales using the 2001 Census geography.

PART II: METHODOLOGY Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Figure 9.1: Transition to create full mid-1991 population estimates for Output Areas and above in England and Wales

1991 Census SOCPOP for EDs for 1991Wards (table S06) (from EwC)

Derive a three- Disaggregate Stage 1 dimensional census Stage 2 SOCPOP Wards to Stage 3 Convert SOCPOP table from S06 EDs by 5-year age, EDs to OAs sex and ethnic group

Add OA student Scale SOCPOP OAs OA revised mid-1991 Stage 5 adjustment by to all-groups estimate by 5-year age and sex ethnic group (without students) Stage 4 for all-groups (from Chapter 8) (from Chapter 7)

SOCPOP Disaggregate Aggregate OA mid- for 2001 Wards by OA mid-1991 by 1991 to derive ST single year of age and Stage 6 ethnic group to single Stage 7 Wards and Districts ethnic group year of age

PART II: METHODOLOGY 234 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

9.3: Background

As seen earlier in Chapter 7, after the 1991 Census the EwC project estimated nonresponse, timing and student adjustments to create a full population estimate (EWCPOP) for Wards and EDs, consistent with those of OPCS for Districts in England and Wales (OPCS, 1993).

In addition, the EwC project also produced 1991 Census counts with non response for each ethnic group for Wards. These estimates called SOCPOP included a differential nonresponse adjustment to the 1991 Census published by OPCS. However, neither timing nor a student population adjustment was included in the SOCPOP estimates by age, sex and ethnic group detail, which is important in many local areas. For example, deducting young people from many areas where they were only resident in vacation, and adding young people to fewer areas where students were resident in termtime.

As shown in Chapter 7, since the EwC estimates have been revised in the light of the latest available data post2001 Census, the SOCPOP estimates can follow a revision with an ethnic group dimension. A defensible revision of small area populations by ethnic group must redistribute the revised non response, imposing consistency with the revision to nonresponse for all groups. The four deficiencies taken into account in the revision of previous estimates are as follows:

1. Revised undercount;

2. Timing between Census day and midyear;

3. The counting of students at vacation address rather than termtime address;

4. Boundary changes between the two censuses.

PART II: METHODOLOGY 235 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

9.4: Data sources

The following data sets have been used to derive mid1991 population estimates for each OA, Ward and District in England and Wales using the 2001 Census geography by single year of age, sex and ethnic group.

1. SOCPOP91,LBSw91,a18,s,e

1991 Census by fiveyear age (18 categories), sex and ethnic group for LBS Wards in England and Wales with an allowance for nonresponse (consistent with EWCPOP without timing or student adjustments).

2. SOCPOP91,LBSw91,a86,s,e

1991 Census by single year of age, sex and ethnic group for LBS Wards in England and Wales with an allowance for nonresponse (consistent with EWCPOP without timing or student adjustments), derived by demographic smoothing (Williamson, 2006).

3. P91,oa01,a91,s,● Mid1991 population estimates by single year of age and sex for OAs in England and Wales, previously calculated in Chapter 7.

4. S91,oa01,a18,s,● 1991 student transfer by fiveyear age group (18 categories) and sex for OAs in England and Wales, previously calculated in Chapter 8.

5. C91,ed91,a5,●,e 1991 Census table S06 by broad age (5 categories) and ethnic group for EDs in England and Wales, from CASWEB.

6. C91,ed91,●,s,e 1991 Census table S06 by sex and ethnic group for EDs in England and Wales, from CASWEB.

PART II: METHODOLOGY 236 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

7. C91,LBSw91,a20,s,e 1991 Census table L06 by fiveyear age (20 categories), sex and ethnic group for Wards in England and Wales, from CASWEB.

8. GCT01 GCT to transfer data from 1991 EDs to 2001 OAs in England and Wales (Norman et al., 2007).

9. GCT02 GCT to transfer data from 1991 SAS Wards to 2001 CAS Wards in England and Wales (Norman, 2007a).

10. GCT03 GCT to transfer data from 1991 SAS Wards to 1991 LBS Wards in England and Wales (Simpson, 2007a).

9.5: Method

Stage 1. Derive a threedimensional census table from the twodimensional tables of S06, with data crosstabulated by broad age, sex and ethnic group for each ED in England and Wales.

The SAS census table S06 provides detail of ethnic group for each ED. This table is twodimensional, with information on ethnic group for each ED in England and Wales but separately by broad age (5 groups) and then by sex. In this stage, a threedimensional census table with data crosstabulated by age, sex and ethnic group is derived from the twodimensional tables in S06. This section follows the same method of Section 6.5 for 2001 OAs.

The approach to derive this new table is based initially on scaling those values of the census table S06 by broad age (5 categories) and ethnic group to the values of the census table S06 by sex and ethnic group. This initial step is carried out because it is assumed that the twodimensional table with fewer cells (that by sex and ethnic group) is less subject to data modification (Rees et al., 2005).

IF sum over age (C91,ed91,a5,●,e ) > 0 and sum over sex (C91,ed91,●,s,e) > 0,

PART II: METHODOLOGY 237 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

R C 91,ed91,a5,●,e = C91,ed91,a5,●,e * sum over sex (C91,ed91,●,s,e ) / sum over age

(C91,ed91,a5,●,e)

IF sum over age (C91,ed91,a5,●,e ) = 0 and sum over sex (C91,ed91,●,s,e ) = 0,

R C 91,ed91,a5,●,e = 0

IF sum over age (C91,ed91,a5,●,e) > 0 and sum over sex (C91,ed91,●,s,e) = 0,

R C 91,ed91,a5,●,e = 0

Because the sum over the sex margin can also be zero, the resulting variable will always be zero to maintain consistency. If the sum over the sex margin is greater than zero and the sum over the age margin equals to zero, the positive values are spread equally to each age category with the following operation.

IF sum over age (C91,ed91,a5,●,e ) = 0 and sum over sex (C91,ed91,●,s,e) > 0,

R C 91,ed91,a5,●,e = sum over sex (C91,ed91,●,s,e) / 5

After scaling the census table S06 with an ethnic group dimension by broad age (5 categories) to its equivalent by sex, IPF is used to derive an amended census table S06 by age (5 categories), sex and ethnic group. Since census values for Wards from census table L06 exist with this degree of detail, these are used as initial values in IPF to maintain agreement with both the EDs with broad age group information and the EDs with sex information.

To run IPF, a margins variable is computed using the revised margin values by broad age and ethnic group and the margin values by sex and ethnic group.

R Margins = C 91,ed91,a5,●,e * C91,ed91,●,s,e / C91,ed91,●,●,e

The denominator is derived from the margin values by sex and ethnic group, and it is the sum over sex as an aid to computing the margins variable.

PART II: METHODOLOGY 238 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Before IPF is run, an appropriate GCT containing the correspondence between SAS Wards and LBS Wards is necessary. For this purpose, GCT03 is used (Simpson, 2007a), to match EDs from census table S06 and Wards from census table L06.

The following information is used to run IPF in SPSS:

Initial values: C91,LBSw91,a5,s,e from census table L06

R Margin: C 91,ed91,a5,●,e from census table S06

Margin: C91,ed91,●,s,e from census table S06

Result: C91,ed91,a5,s,e

Within this procedure, IPF operates across age (5 categories) and sex. It assumes that within each EDethnic group category, the agesex interaction is as in the census output for the Ward containing the ED.

Stage 2. Disaggregate the 1991 SOCPOP estimates for Wards to each ED in England and Wales using the threedimensional table created from S06.

The SOCPOP Ward estimates by fiveyear age, sex and ethnic group taken from the EwC project are shared out to EDs in this second stage. This is undertaken using the amended census tabulation with ethnic group by broad age (5 categories) and sex previously created in Stage 1. The sharing method to EDs assumes that the agesexethnic group nonresponse rate from SOCPOP for a Ward applies to all EDs in that Ward. This approximation is corrected in the scaling to population estimates without an ethnic group dimension but specific to each small area, when scaling to the mid1991 population estimates for allgroups estimate for each OA in Stage 4.

SOCPOP91,ed91,a18,s,e = SOCPOP91,LBSw91,a18,s,e * (C91,ed91,a5,s,e / C91,ed(w)91,a5,s,e)

Since the above procedure is not valid when cells in the census tabulation for EDs have no population, the solution used is to share the SOCPOP Ward

PART II: METHODOLOGY 239 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

estimates equally to EDs (i.e. if there are 10 EDs, each ED receives one tenth of the adjustment). For this purpose, the number of EDs in each Ward is calculated.

IF C91,ed(w)91,a5,s,e = 0, then SOCPOP91,ed91,a18,s,e = SOCPOP91,LBSw91,a18,s,e / ed(w)_N

C91,ed(w)91,a5,s,e is derived by summing C91,ed91,a5,s,e within each Ward, to ensure that one hundred per cent of each Ward SOCPOP value is distributed to EDs.

Stage 3. Convert SOCPOP ED estimates to OAs using the 2001 Census geography in England and Wales.

In this stage, the previous SOCPOP estimates by fiveyear age, sex and ethnic group for Wards in England and Wales are transferred to 2001 Census boundaries using an appropriate GCT. As seen earlier in Chapter 7, GCT01 is used to transfer 1991 ED populations to 2001 OAs successfully. Hence, each SOCPOP estimate by fiveyear age, sex and ethnic group is multiplied by an appropriate weight indicated in the GCT. The transfer of data ends with a final aggregation of the weighted data to each OA.

I SOCPOP 91,oa01,a18,s,e = SOCPOP91,ed91,a18,s,e * Wt (GCT01)

I SOCPOP91,oa01,a18,s,e = sum (across each OA) SOCPOP 91,oa01,a18,s,e

Stage 4. Scale the SOCPOP estimates to the allgroups estimate (without students) for each OA in England and Wales.

The SOCPOP estimates are scaled to the mid1991 population estimates for allgroups previously created and described in Chapter 7. The allgroups estimates have been aggregated to fiveyear age groups and sex for this calculation. The result is an adjusted 1991 midyear estimate by fiveyear age, sex and ethnic group which takes into account the undercount revision and

PART II: METHODOLOGY 240 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

timing derived from the revised mid1991 by fiveyear age group and sex for allgroups. This operation imposes consistency between the mid1991 population estimates for allgroups and the mid1991 population estimates by ethnic group.

The implementation of this procedure is done after deducting the student transfer, which is added separately in Stage 5 with an ethnic group dimension.

A P 91,oa01,a18,s,e = SOCPOP91,oa01,a18,s,e * (P91,oa01,a18,s,● – S91,oa01,a18,s,●) /

SOCPOP91,oa01,a18,s,●

A different approach is necessary when the SOCPOP estimate of an OA and its corresponding Ward have no population. This is mainly caused by the timing adjustment as the SOCPOP estimates refer to Census day and the revised mid1991 population estimates for allgroups already include this adjustment. In this case, the mid1991 population estimate without the student adjustment is distributed equally to ethnic groups (i.e. if the mid1991 population estimate indicates that there are 2 people and the SOCPOP estimate has no population, each ethnic group receives 0.2 of the discrepancy).

A P 91,oa01,a18,s,e = (P91,oa01,a18,s,● – S91,oa01,a18,s,●) / 10

Stage 5. Add student adjustment with an ethnic group dimension to each OA in England and Wales.

The 1991 net student transfer from vacation address to termtime address with an ethnic group dimension is added in this stage. This adjustment for students by fiveyear age, sex and ethnic group for OAs in England and Wales has been derived separately in Chapter 8. The adjustment is consistent with the equivalent adjustment without ethnic group from the EwC project previously used in Chapter 7.

I A P 91,oa01,a18,s,e = P 91,oa01,a18,s,e + S91,oa01,a18,s,e

PART II: METHODOLOGY 241 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Some small negative populations are created by adding the student adjustment. This is principally caused by the method used to derive an ethnic composition for students, which takes the District population composition to derive an ethnic group composition for students rather than the small area composition. Full detail of the method used to derive a student transfer with an ethnic group dimension is described in Chapter 8.

An approach is implemented to deal with this issue in two separate steps. In the first step, for each agesexethnic group category any negative OA population is set to zero. This adjustment upwards is balanced by a proportional reduction in other ethnic groups in the same OA.

I IRF IF P 91,oa01,a18,s,e < 0, P 91,oa01,a18,s,e = 0

Let H91,oa01,a18,s,● be the sum of the positive populations in the OA for all groups.

I IRF I I IF P 91,oa01,a18,s,e > 0, P 91,oa01,a18,s,e = P 91,oa01,a18,s,e * (P 91,oa01,a18,s,● /

H91,oa01,a18,s,●)

Since the first step may not be possible to carry out when the sum of populations in the OA for allgroups is negative, a second step may be necessary. In this case, the proportional reduction of the population is within the District.

IRF RF IF P 91,oa01,a18,s,e < 0, P 91,oa01,a18,s,e = 0

Let H91,d01,a18,s,● be the sum of the positive populations in the District for all groups.

IRF RF IRF IRF IF P 91,oa01,a18,s,e > 0, P 91,oa01,a18,s,e = P 91,oa01,a18,s,e * (P 91,d01,a18,s,● /

H91,d01,a18,s,●)

This approach allows the maintenance of full consistency with the student adjustment by age and sex for allgroups provided by EwC.

PART II: METHODOLOGY 242 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Stage 6. Disaggregate mid1991 population estimates for OAs in England and Wales by fiveyear age, sex and ethnic group to single year of age.

In this stage, a single year of age from the revised mid1991 population estimates with an ethnic group dimension is derived using IPF. SOCPOP values exist with this degree of detail (Williamson, 2006) and, therefore, they can be used in IPF as initial values. However, these SOCPOP values smoothed to single year of age refer to 1991 Wards. This means that an appropriate GCT is needed to convert data from 1991 to 2001 Wards. For this purpose GCT02 is used (Norman, 2007a).

SOCPOP91,w01,a86,s,e = SOCPOP91,LBSw91,a86,s,e * Wt (GCT02)

After the conversion, the SOCPOP values are used as initial values in IPF to maintain agreement with both the OA fiveyear age groups with ethnic group estimated in Stage 5, and the OA single year of age without ethnic group previously estimated in Chapter 7.

To run IPF, a margins variable is computed using the margin values from OAs by fiveyear age group and the margin values from OAs by single year of age.

RF Margins = P 91,oa01,a18,s,e * P91,oa01,a91,s,● / P91,oa01,a18,s,●

The denominator is derived from the margin values from OAs by single year of age, and it is the sum over fiveyear groups as an aid to computing the margins variable.

The following information is used to run IPF in SPSS:

Initial values: SOCPOP91,w01,a86,s,e from SOCPOP smoothed

RF Margin: P 91,oa01,a18,s,e from Stage 5

Margin: P91,oa01,a91,s,● from Chapter 7

Result: P91,oa01,a91,s,e

PART II: METHODOLOGY 243 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Stage 7. Aggregate the OA estimates to derive mid1991 population estimates for ST Wards and Districts in England and Wales by single year of age, sex and ethnic group.

Finally, mid1991 population estimates by single year of age, sex and ethnic group for 2001 ST Wards and Districts are derived from the previously estimated OAs in Stage 6. Since the aggregation of the mid1991 for OAs across each Ward results in 2001 CAS Wards, an appropriate GCT is used (GCT06) with one record for each CAS Ward and its corresponding ST Ward (Hayes, 2006), to produce the target estimates for ST Wards.

P91,CASw01,a91,s,e = sum (across each Ward) P91,oa01,a91,s,e

P91,STw01,a91,s,e = sum (over CAS Wards in ST Wards) P91,CASw01,a91,s,e

P91,d01,a91,s,e = sum (across each District ) P91,STw01,a91,s,e

9.6: Validation

The data set resulting from the procedures described above has 319,289,880 cases, one for each combination of:

• 2001 Output Areas = 175,434

• Age (90 single years and 90 and over) = 91

• Sex (Male and Female) = 2

• 1991 Ethnic groups = 10

PART II: METHODOLOGY 244 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Figure 9.2: Total difference between the mid-1991 population estimates obtained after IPF and the known sub-totals in England and Wales by Districts

Figure 9.2 shows the total difference between the revised mid1991 population estimates after implementing IPF and the known subtotals from ONS post2001 Census in England and Wales for each District. As expected, the overall difference between the marginal totals and the known subtotals is near zero, thus indicating how close they are to one another. For this calculation the marginal totals for each OA by single year of age, sex and ethnic group have been aggregated across each 2001 District.

Table 9.1 shows the revised mid1991 population estimates obtained from OAs by ethnic group as recorded in the 1991 Census in England and Wales. For simplicity ethnic groups are not disaggregated by age and sex. The results show how the total population across ethnic groups is consistent with the revised mid1991 population estimates from OAs without an ethnic group dimension created in Chapter 7.

PART II: METHODOLOGY 245 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Table 9.1: Revised mid-1991 population estimates by ethnic group in England and Wales

Ethnic group Revised mid1991 10 categories

1 White 47,429,019 2 Black Caribbean 569,621 3 Black African 255,336 4 Black Other 221,040 5 Indian 891,827 6 Pakistani 494,973 7 Bangladeshi 176,912 8 Chinese 173,184 9 Asian Other 211,199 10 Other Other 324,922 Total 50,748,033

Table 9.2 shows the revised mid1991 population estimates obtained from OAs in England and Wales by age and sex. Although detail of single year of age has also been derived for OAs, for simplicity age is aggregated into five year age groups. This table is equivalent to the revised midestimates by age and sex without an ethnic group dimension from Chapter 7. Both sets of mid 1991 population estimates are consistent with that published by ONS post 2001 Census by single year of age and sex for each 2001 District in England and Wales.

PART II: METHODOLOGY 246 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Table 9.2: Revised mid-1991 population estimates by age and sex in England and Wales

Age groups Revised mid1991

18 categories

Males Females Total 1 04 1,740,974 1,669,916 3,410,890

2 59 1,639,964 1,565,571 3,205,535

3 1014 1,557,564 1,484,718 3,042,282

4 1519 1,667,177 1,586,451 3,253,628

5 2024 1,970,839 1,940,582 3,911,421

6 2529 2,070,814 2,083,329 4,154,143

7 3034 1,848,792 1,859,328 3,708,120

8 3539 1,665,187 1,672,805 3,337,992

9 4044 1,839,269 1,844,544 3,683,813

10 4549 1,562,875 1,559,217 3,122,092

11 5054 1,356,252 1,355,311 2,711,563

12 5559 1,279,689 1,293,398 2,573,087

13 6064 1,233,835 1,319,370 2,553,205

14 6569 1,148,875 1,326,462 2,475,337

15 7074 878,502 1,152,569 2,031,071

16 7579 652,750 1,014,819 1,667,569

17 8084 376,639 745,794 1,122,433

18 85+ 191,340 592,512 783,852

Total 24,681,337 26,066,696 50,748,033

9.7: Conclusions and summary

This section has focused on the estimation of mid1991 population estimates by single year of age, sex and ethnic group using the 2001 Census geography for OAs, Wards and Districts in England and Wales. These estimates have

PART II: METHODOLOGY 247 Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

been produced using information by age and sex from the revised mid1991 for OAs previously created in Chapter 7.

The method of disaggregating information from the Ward SOCPOP estimates to EDs has initially allowed an allocation of nonresponse to EDs. This approach assumes the same level of agesexethnic group nonresponse in each of the Ward’s EDs. The use of GCT01 has made the transfer of SOCPOP data from EDs to OAs possible, thus facilitating the scaling to the OA mid1991 population estimates for allgroups. This method has imposed the different levels of nonresponse for each small area. It has also been used to include timing, which is subsumed to nonresponse within this approach.

Additionally, a net student transfer with an ethnic group dimension at OA level has been implemented. This is consistent with the allgroup student adjustment in each OA, and the ethnic group student adjustment in Wards and Districts. Finally, IPF has been used to derive single year of age from the mid1991 population estimates by fiveyear age group. The approach has taken into account SOCPOP data smoothed to single year of age, thus assuming that the ageethnic group interaction comes from this data set.

Although these methods have proven to be successful to obtain consistency, the OA estimates are not expected to be accurate at that level. The practical use of the OA results by single year of age, sex and ethnic group is nonetheless demonstrated in Chapter 11 for building up to current Ward boundaries in the District of Birmingham.

Table 9.3 gives a summary of the issues, strategies and methods used to deal with the four problems reviewed in Chapter 2. These are presented in the order that they are dealt with in the estimation process.

Chapter 10 provides a discussion about the degree of internal and external validity of the results for quality assurance purposes.

PART II: METHODOLOGY Chapter 9: Mid1991 population estimates for Output Areas and above in England and Wales

Table 9.3: Summary to create full mid-1991 population estimates for Output Areas and above in England and Wales

Issues Strategies Methods / assumptions Nonresponse Nonresponse adjustments are made Ward nonresponse specific to each 5year age group, sex, ethnic group (from the EwC data initially for EDs from the Ward set SOCPOP) is distributed to EDs assuming the same level of agesexethnic group non SOCPOP estimates (5year ages, sex response in each of the Ward’s EDs. The different levels of nonresponse for each locality is and ethnic group). imposed in the conversion to OAs by making them consistent with the allgroup nonresponse as estimated in Chapter 7 after deducting the student adjustment.

Boundary harmonisation Estimates for 1991 EDs are transferred GCT01 is used as in Chapter 7. to 2001 OAs.

Population definition Student transfer Move students from vacation to term For Districts, OPCS adjustments to add and to remove students from each 1991 District are time address. converted to 2001 District boundaries using suitable GCTs (Simpson, 2007b and 2007c). The ethnic group composition of students removed because studying elsewhere is assumed the same as the resident population. The ethnic group composition of students added because at vacation elsewhere is assumed to be that of the 2001 ethnic group distribution of students, separately for males and females and ages 1824 and 25+. These adjustments are distributed to Wards and OAs, rather crudely but maintaining consistency both with the allgroup student adjustment in each OA, and the ethnic group student adjustment in each higher level.

Timing Move from Census day to midyear The timing adjustment is subsumed into the adjustment for nonresponse (see above); it is (30th June). usually small relative to each of the other adjustments.

Ethnic group categories Not needed. Target categories are None those used in 1991 (10 categories). Age group categories Single year of age (91 categories) is IPF is used to derive single year of age. OA data with 5year agesex structure and by ethnic created from 5year age groups. group are made consistent with the OA data for allgroups by single year of age and sex (from Chapter 7), the interaction (singleyear by ethnic group) coming from SOCPOP data smoothed to single year of age.

249

PART III: ANALYSIS AND CONCLUSIONS

PART III: ANALYSIS AND CONCLUSIONS 250

Chapter 10: Quality assurance

10.1: Introduction

How can one give assurance about the quality of the results? This part of the thesis argues that although there is no measured truth against which the accuracy of the results can be measured, internal checks and posthoc validation can provide reassurance for users of the results.

Many of the assumptions made are plausible rather than certain, and subject to error. This error would be accompanying the errors of recording, processing and imputation involved in the census itself (ONS, 2003a). One should take a cautious approach to the results, bearing in mind that it is likely that the potential for error in any one estimate is greater for smaller populations, at least in percentage terms.

However, assurances can be given. Section 10.2 discusses the importance of plausible construction of the estimates to their validity, and the variety of checks which have been made to ensure that the results are internally consistent, and thus have a degree of internal validity. Section 10.3 presents results to allow users to judge whether the data sets and adjustments made to the census ‘make sense’ of what they expect. Further validity testing is given in Chapter 11, where a senior demographer in the largest local authority District in England provides his judgement of the results. This provides a degree of face validity or external validity.

PART III: ANALYSIS AND CONCLUSIONS 251 Chapter 10: Quality assurance

10.2: Internal validity

The methods used to create a consistent population time series from 1991 to 2001 have been reviewed earlier in previous chapters. Their plausibility provides some reassurance that the time series has been constructed in a valid way. Implausibility would lead to rejection of the results. The data are constructed by taking into account the following:

(a) The assumptions taken are equally or more plausible than other possible assumptions.

(b) Where other assumptions are equally or more plausible (but perhaps impossible to implement) the outcome would not have a misleading effect on users of the data.

In addition, each element of the methods explained earlier in Chapters 4 to 9 was subject to the following constraints to ensure internal consistency:

• There are no negative populations. Adjustments to census output may be negative, which applies in particular as a result of the net adjustments for transferring students from vacation to termtime address in 1991, and the impact of population change between each Census day and midyear. The impact of modification to census data outputs can also lead to negative values when different census tables are differenced to derive new variables. All procedures have been constrained so that there are no negative populations in the final data sets. What these procedures have in common is that they distribute the amount of differences among the items in proportion to their absolute populations. The use of this method is in line with the treatment of marginal totals with positive and negative entries (Siegel and Swanson, 2004).

• There is full consistency with the statistical agencies’ latest estimates of mid1991 and mid2001 populations published in 2004 without an ethnic group dimension, as well as with the mid2001 populations first published in 2006 with an ethnic group dimension. Many of the procedures adjust

PART III: ANALYSIS AND CONCLUSIONS 252 Chapter 10: Quality assurance

census data with an ethnic group dimension according to plausible principles in order to address one or other of the census’ four deficiencies as a population estimate. The population estimates created also ensure consistency with the government population estimates without an ethnic group dimension. For these processes, scaling is often used which, when in more than one dimension, is implemented with IPF.

• Wherever possible individual adjustments are estimated separately, retaining their own coherence. Each adjustment to the published census data sets is dealt with separately wherever possible and subject to constraints to maintain known patterns of age, locality, sex and ethnic group. For example, reductions in estimated nonresponse for 1991 are implemented by adjusting only the previous estimate of nonresponse within each agesexethnic group. Had the population as a whole been adjusted then the structure of nonresponse would have been changed allowing many large negative values for nonresponse. As another example, the conversion from 1991 to 2001 Census geographical boundaries has used the lowest geographical source unit possible (the 1991 Census ED) so that spatial difference in agesexethnic group are respected when constructing the 1991 population for 2001 boundaries. This also allows the quantification of the contribution of each adjustment to the final population estimates.

10.3: External validity

There is no external truth by which to judge the time series, but its analysis may provide some ‘face validity’ of the results if they agree with experts’ expectations. In this section, an analysis is given focusing on national totals by age, sex and ethnic group. Further analyses, by which to quality assure the results, are also undertaken for the District of Birmingham and smaller areas as a case study in the next chapter.

PART III: ANALYSIS AND CONCLUSIONS 253 Chapter 10: Quality assurance

The figures below illustrate the percentage adjustments to derive the mid 2001 and mid1991 population estimates and population change between 1991 and 2001, for allgroups and nonWhite groups, using data taken directly from census output and the full population estimates.

The adjustments to derive mid2001 population estimates are displayed after aggregating the results for all Districts to country totals by single year of age, sex and ethnic group as recorded in the 2001 Census (16 categories). The results for the mid2001 population estimates highlight the assumptions used by ONS for Districts of England which have been replicated. The adjustments to derive mid1991 population estimates are displayed after aggregating the results for all Districts to country totals by fiveyear age, sex and ethnic group as recorded in the 1991 Census (10 categories). Although single year of age has been produced for the mid1991 population estimates, this detail of age combined with ethnic group is not available from Census output and, therefore, the results are shown by fiveyear age group (18 categories). The adjustments used for the revision of the mid1991 population estimates without an ethnic group dimension are also shown.

Figure 10.1 displays the 2001 percentage adjustment due to timing as a result of the shift from Census day (29th April) to midyear (30th June), approximately 9 weeks or one sixth of a year. Overall the timing adjustment has a positive impact over the initial census population. The population increases are caused by births, for those aged 0, and migration, which adds population at young adult ages. The population decrease is caused by deaths, which reduces population at all ages but especially at old ages. The other element of timing, ageing, reduces the 0 years old and adds to the older groups, some ages being more affected than others. Generally, the effect of ageing dominates the single year of age adjustments (even though it sums to 0 across all ages), because the size of some neighbouring single age cohorts by ethnic group is quite different. It becomes particularly evident for those born after each World War and at the start and end of the Baby Boom of the 1960s.

PART III: ANALYSIS AND CONCLUSIONS 254 Chapter 10: Quality assurance

Figure 10.1: 2001 percentage adjustment due to timing by age, sex and ethnic group in England

Figure 10.2 displays the 2001 percentage adjustment caused by migration between England and the rest of the UK. The results show a slight increase in the population of England as a result of this type of internal migration. The adjustments are nonetheless less than one per cent in all cases. The largest percentage adjustments are found among young females within the Irish group, which is characterised by outmigration most likely to Northern Ireland.

PART III: ANALYSIS AND CONCLUSIONS 255 Chapter 10: Quality assurance

Figure 10.2: 2001 percentage adjustment due to migration between England and the rest of the UK by age, sex and ethnic group

Figure 10.3 displays the 2001 percentage adjustment as a result of international migration to England from outside the UK. The percentages reveal that international migration is an important contributor to the population growth during this nine week period. As expected, the largest adjustments are concentrated in young adults, with the major increases among males, with percentage adjustments of nearly five per cent. The Chinese group, the Black African group and the residual group (the Other) show the largest percentages of immigration, with significant increases. Other groups such as the Bangladeshi group, predominantly females, and the Black African group, predominantly males, form an important contribution to the immigration flow. As seen earlier with migration between England and the rest of the UK, a

PART III: ANALYSIS AND CONCLUSIONS 256 Chapter 10: Quality assurance

similar pattern of emigration is found for the Irish group, most likely of emigration to the Republic of Ireland.

Figure 10.3: 2001 percentage adjustment due to international migration by age, sex and ethnic group in England

Figure 10.4 displays the 2001 percentage adjustment due to extra non response identified by ONS after the release of census results. This adjustment refers to the extra nonresponse allocated by ONS experimental statistics unit (Large and Ghosh, 2006). Although the results show differences between ethnic groups, this is entirely due to the concentration of each group in particular types of Districts with different levels of nonresponse (the White British population is found most often in Districts of lower nonresponse). As expected, this extra nonresponse is mainly concentrated among young male

PART III: ANALYSIS AND CONCLUSIONS 257 Chapter 10: Quality assurance

adults, with the largest adjustments among the Black African group, with an increase over the initial census population of more than 10 per cent for those on their twenties and early thirties.

Figure 10.4: 2001 percentage adjustment due to extra non-response as published by ONS experimental statistics by age, sex and ethnic group in England

Figure 10.5 also displays the 2001 percentage adjustment due to extra non response identified by ONS after the release of census results, although in this case the adjustment of extra nonresponse has been allocated using ONS imputation rates. The results show significant differences between ethnic groups, which is partly as a result of the concentration of ethnic groups in Districts with different levels of nonresponse, and partly due to the

PART III: ANALYSIS AND CONCLUSIONS 258 Chapter 10: Quality assurance

assumption that the extra nonresponse was differentially distributed between ethnic groups in the same way as the nonresponse already estimated by imputation within census outputs.

Figure 10.5: 2001 percentage adjustment due to extra non-response (using ONS imputation rates) by age, sex and ethnic group in England

As seen earlier in Chapter 4, although the total extra nonresponse is the same (about 270,000 people in England), the allocation of extra nonresponse is differential by ethnic group using the ONS imputation rates. As a result, the percentage adjustments are much higher, to the extent that these double the previous largest adjustments. For example, the Black African group experiences an increase of more than 20 per cent over the initial census population for those in their twenties and early thirties. The White British group

PART III: ANALYSIS AND CONCLUSIONS 259 Chapter 10: Quality assurance

is the lowest of all ethnic groups, thus in line with the evidence from ONS imputation rates used in the ONC (as shown in Chapter 4) that ethnic groups other than White are more likely to be missed by the census.

Figure 10.6: 2001 percentage adjustment due to extra non-response and timing by age, sex and ethnic group in Wales

Figure 10.6 displays the 2001 percentage adjustment due to extra non response and timing in Wales. Since information on the separate components of timing and extra nonresponse has not been undertaken for Districts in Wales, the adjustments reflect the single assumption that all adjustments should be distributed to ethnic groups in the same way as the nonresponse already estimated by imputation within census outputs. While this is plausible for the largest adjustments which are in young adult ages and due to non

PART III: ANALYSIS AND CONCLUSIONS 260 Chapter 10: Quality assurance

response, it is less defensible for other ages where the timing adjustment may be of similar size to or larger than extra nonresponse. This partly explains the more volatile nature of the adjustments.

Figure 10.7: 1991 percentage adjustment due to students, timing, modification and non-response by age and sex in England and Wales

Figure 10.7 displays the 1991 percentage adjustment due to students transferred from vacation to termtime address, timing, modification and non response in England and Wales. The major adjustment is due to non response, even though the revision to census nonresponse lowers the original census nonresponse. As expected, those mostly affected by the revision of nonresponse are primarily young male adults in their twenties and thirties. Additionally, the figure illustrates three more adjustments. The student

PART III: ANALYSIS AND CONCLUSIONS 261 Chapter 10: Quality assurance

adjustment, almost imperceptible for England and Wales as a whole; the adjustment for modification, which illustrates the discrepancies between 1991 Census subdistrict population counts and larger areas due to confidentiality measures applied to the small area data (Marsh, 1993); and timing, which shows a slight decrease for those in their teens and early twenties and a slight increase for those in their forties, most likely due to migration.

Figure 10.8: 1991 percentage adjustment due to student transfer by age, sex and ethnic group in England and Wales

Figure 10.8 displays the 1991 percentage adjustment due to the student transfer from vacation to termtime address with an ethnic group dimension in England and Wales. The results show the net impact of student transfers for England and Wales as a whole, highlighting the impact of students not

PART III: ANALYSIS AND CONCLUSIONS 262 Chapter 10: Quality assurance

counted as usually resident during vacation time but included in the population estimates as usually resident during termtime. As seen earlier in Chapter 8, these are overseas students (including from the rest of the UK) with significant differences between ethnic groups among males and females. For example, the Chinese group experiences the largest percentage adjustment, with an increase of the initial census population of about 40 per cent for males and females.

Figure 10.9: 1991 percentage adjustment due to revised non-response and timing by age, sex and ethnic group in England and Wales

Figure 10.9 displays the 1991 percentage adjustment due to the revised non response and timing in England and Wales. The results are fully consistent with the mid1991 population estimates by age and sex for Districts in England and Wales published by ONS post2001 Census (Duncan et al.,

PART III: ANALYSIS AND CONCLUSIONS 263 Chapter 10: Quality assurance

2002; ONS, 2002b). As expected, the figure shows larger adjustments among males than females overall and significant differences between ethnic groups, thus in line with the results obtained for the mid2001 population estimates. As shown in Chapter 9, this is predominantly because previous mid1991 population estimates with an allowance of nonresponse differential by ethnic group from the EwC project (i.e. SOCPOP data) were used. This assumes that the revised nonresponse is also differentially distributed between ethnic groups in the same way as the nonresponse already estimated by EwC. Hence, the lowest percentage adjustment is found among the White group, whereas the rest of ethnic groups experience important changes. The large corrections for ethnic minority groups such as the Black Other, the Black Caribbean, the Black African and the Bangladeshi, reveal the importance of including an adjustment of nonresponse differential by ethnic group. For example, the percentage adjustment for those aged between 15 and 34 is very significant, above all for ethnic groups other than White, with an increase of the initial census population of more than 25 per cent for males and more than 15 per cent for females. The timing adjustment (subsumed in the revision of nonresponse) also explains some of the variations between groups, for example, immigration would suggest larger increases for nonWhite groups.

The following maps provide a visual illustration of population change between 1991 and 2001 in Districts of England and Wales using a Universal Data Map (UDM) (i.e. cartogram) created by Danny Dorling and Helen Durham.10 The areas in these cartograms are Districts represented in proportion to the population size in 2001 maintaining the topology wherever is possible. The rationale for using this type of map is that those areas with large populations such as cities are displayed more clearly than with traditional maps, which tend to highlight patterns in sparsely populated areas (i.e. where few people live).

Figure 10.10 displays the percentage population change between 1991 and 2001 for all groups using the 2001 District geography in England and Wales.

10 Further information about the base map is available at the Social and Spatial Inequalities Research Group (University of Sheffield) website: http://www.sasi.group.shef.ac.uk/maps/index.htm

PART III: ANALYSIS AND CONCLUSIONS 264 Chapter 10: Quality assurance

Two maps are shown: (1) using census output from 1991 and 2001 as published; and (2) using full estimates for 1991 and 2001. The latter includes a revised nonresponse, timing and students transferred to their termtime address for the mid1991 population estimates and timing and extra non response for the mid2001 population estimates.

Figure 10.10: Percentage population change between 1991 and 2001 for all-groups for 2001 Districts in England and Wales

Census output Full estimates

2.8 3 1 1 1.3 1.3 1.3 1.3 3.1 3 2.4 2.4 0.4 0.4 0.4 0.4

2.8 2.1 2.1 0.1 1 1 1 1.3 2.5 2.5 2.7 2.4 2.4 0.7 2.4 2.4 2.4 0.4 1.3 1.3

0.5 0.5 9 9 1.7 1.7 1 5.2 5.2 5.2 2.5 2.5 0.3 0.3 9.4 9.4 2.3 2.3 2.4 4.2 4.2 4.2 1.3 1.3

2.6 2.6 2.7 1.6 5.2 5.2 3.8 3.8 3.8 3.8 2.2 2.2 2.3 1 4.2 4.2 3.1 3.1 3.1 3.1

3.1 3.1 0.7 4.3 1.6 3.4 2.1 2.1 3.8 3.8 2.6 2.6 2.1 3.7 1 3.9 9.2 9.2 3.1 3.1

1.9 1.9 4.3 4.3 1.5 1.5 4.7 4.7 1 1 4.9 4.9 1.5 1.5 3.7 3.7 1.1 1.1 4 4 1.9 1.9 2.6 2.6

1.8 3.4 3.4 3.4 4.1 4.1 6.7 8 8 8 6.3 6.3 6.3 3.8 4.9 4.9 2.4 8.3 8.3 8.3 5.8 5.8 7.5 9.2 9.2 9.2 6.2 6.2 6.2 6.7 2.6 2.6

4.3 4.3 4.3 1.8 1.9 1.9 0.3 4.4 4.4 4.4 1.3 1.3 1.3 1.3 5.2 5.2 5.2 10 4.6 4.6 2.4 2.4 2.5 2.5 2.5 2.4 3.4 3.4 2.8 4.3 4.8 4.8 5.2 5.2 5.2 5.2 9.3 9.3 9.3 10 4.1 4.1 4.1 4.1

0.5 0.5 1.4 1.4 3.7 3.7 0.3 0.3 3.6 3.6 2.7 2.7 1.3 1.3 1.3 1.3 1.3 1.3 2.3 2.3 4.6 2.4 0.2 0.2 1.8 1.8 4.2 4.2 2.8 2.8 3.9 3.9 1.8 1.8 5.2 5.2 5.2 5.2 5.2 5.2 0.1 0.1 4.1 4.1

3.4 2.5 1.8 1.8 1.4 1.4 0 0 0.8 0.8 0.8 0.2 1.2 1.2 0.4 0.4 1.3 1.3 1.3 1.3 1.3 1.3 6.6 6.6 6.9 6.9 5.1 5.1 2.2 0.7 1.3 1.3 0.5 0.5 1.1 1.1 0.6 0.6 0.6 0 1.6 1.6 2.4 2.4 5.2 5.2 5.2 5.2 5.2 5.2 7.5 7.5 7.6 7.6 4.1 4.1

3.4 3.4 2.5 2.5 1.8 1.8 1.4 1.4 0 0 1.3 1.3 1.2 1.2 0.4 0.4 0.4 0.4 0.4 0.4 2.6 0.3 0.3 0.3 1.6 1.6 6.9 6.9 5.1 5.1 2.2 2.2 0.7 0.7 1.3 1.3 0.5 0.5 1.1 1.1 2 2 1.6 1.6 2.4 2.4 2.4 2.4 2.4 2.4 4.2 1.4 1.4 1.4 0.6 0.6 7.6 7.6 4.1 4.1

3.4 3.4 7.1 7.1 1.4 1.4 0 0 1.3 1.3 2.3 2.3 0 0 0.3 0.3 0.4 0.4 2.6 2.6 0.3 0.3 0.3 0.3 1.6 1.6 6.9 6.9 5.1 5.1 2.2 2.2 2.8 2.8 0.5 0.5 1.1 1.1 2 2 2 2 0.4 0.4 0.5 0.5 2.4 2.4 4.2 4.2 1.4 1.4 1.4 1.4 0.6 0.6 7.6 7.6 4.1 4.1

3.4 3.4 7.1 7.1 1.4 6 6 6 2.3 2.3 2.3 2.3 0 0 0.3 0.3 2.6 2.6 2.6 2.6 1.3 1.3 2.3 2.3 1.6 1.6 6.9 0 2.2 2.2 2.8 2.8 0.5 3 3 3 2 2 1.5 1.5 0.4 0.4 0.5 0.5 4.2 4.2 4.2 4.2 2.5 2.5 1.3 1.3 0.6 0.6 7.6 0.3

7.1 7.1 7.1 7.1 6 6 2.3 2.3 1.4 1.4 2.3 2.3 2.3 2.3 2.6 2.6 1.3 1.3 1.3 1.3 1.3 1.3 2.3 2.3 2.3 2.3 0 0 1.9 1.9 2.8 2.8 2.8 2.8 3 3 2 2 0.5 0.5 1.5 1.5 1.5 1.5 4.2 4.2 2.5 2.5 2.5 2.5 2.5 2.5 1.3 1.3 1.3 1.3 0.3 0.3 1.1 1.1

5.8 5.8 5.8 5.8 7.1 7.1 2.6 2.6 2.6 2.6 2.3 2.3 1.4 1.4 0.9 0.9 0.9 0.9 1.3 1.3 1.3 1.3 2.1 2.1 2.1 2.1 2.1 2.1 3.8 3.8 3.8 3.8 1.9 1.9 5.5 5.5 5.5 5.5 2.8 2.8 1.8 1.8 1.8 1.8 2 2 0.5 0.5 0.5 0.5 0.6 0.6 2.5 2.5 2.5 2.5 1.6 1.6 1.6 1.6 1.6 1.6 1.4 1.4 1.4 1.4 1.1 1.1

5.8 5.8 5.8 5.8 5 5 3.5 3.5 3.5 3.5 2.3 2.3 1.4 1.4 4.6 4.6 1.3 1.3 2.9 2.9 2.4 3.1 3.1 2.9 2.9 2.9 1.2 1.2 3.8 3.8 11 11 5.5 5.5 5.5 5.5 4.8 4.8 4.4 4.4 4.4 4.4 2 2 0.5 0.5 5.1 5.1 1.6 1.6 2.3 2.3 3 3.3 3.3 3.6 3.6 3.6 1.4 1.4 1.4 1.4 12 12

0.5 0.5 7.2 7.2 7.2 7.2 0.4 0.4 0.4 0.4 2.2 2.2 3.9 3.9 3.2 3.2 0.7 0.7 2.4 2.4 5.8 5.8 4.8 4.8 7.4 7.4 0.5 0.5 4.1 4.1 3.4 3.4 13 11 11 2.1 7.4 7.4 0.9 0.9 6.9 6.9 6.9 6.9 0.9 0.9 0.9 0.9 3 3 4.1 4.1 3.7 3.7 0.6 0.6 3 3 6.2 6.2 8.2 8.2 8.4 8.4 3.7 3.7 4.3 4.3 3.9 3.9 13 12 12 0.7 8.7 8.7

4.6 4.6 0.7 0.7 6.6 6.6 1 1 1 1.2 1.2 1.2 6.1 6.1 3.2 3.2 12 12 3.5 3.5 3.5 3.5 3.6 3.6 4.8 4.8 0.5 0.5 0.5 0.5 1.9 1.9 3.4 13 7.2 7.2 2.1 2.1 2.6 2.6 5.1 5.1 2 2 7.4 7.4 2.5 2.5 2.5 1 1 1 7 7 3.7 3.7 14 14 1.3 1.3 1.3 1.3 4.2 4.2 8.2 8.2 3.7 3.7 3.7 3.7 4.4 4.4 3.9 13 8.1 8.1 0.7 0.7 3.6 3.6

4.6 4.6 8.9 7 6.2 6.2 3.2 3.2 4.2 4.2 3 3 3 3 2 2 0.1 0.1 8.9 13 13 5.5 5.6 4.8 14 14 14 14 4.6 4.6 18 18 3.1 3.1 2.7 6.3 6.3 10 10 1 4.2 4.2 5.1 5.1 12 8.1 7.7 7.7 0 0 2.8 2.8 2.2 2.2 2.2 2.2 0.8 0.8 0.5 0.5 9.1 13 13 8.5 6.1 9.7 15 15 14 14 4.7 4.7 18 18 19 19 1.3 7.1 7.1 11 11 0.2 5.3 5.3

4.1 4.1 12 12 3.6 3.6 4.2 4.2 4.2 4.2 3 3 2 2 2 2 5.8 5.8 7.4 7.4 6.2 12 12 0.3 7.6 7.6 7.6 2.1 2.1 2.1 7 7 7 21 21 11 4.2 4.2 1 1 1.7 1.7 4.8 4.8 14 14 1.6 1.6 2.8 2.8 2.8 2.8 2.2 2.2 0.8 0.8 0.8 0.8 6.3 6.3 7.4 7.4 6.9 13 13 0.2 8.9 8.9 8.9 2 2 2 7.4 7.4 7.4 21 21 12 4.9 4.9 0.2 0.2 6.6 6.6

1.9 1.9 1.6 1.6 12 12 3.6 3.6 0.9 0.9 2.7 2.7 2.7 2.7 2 2 2 2 1.2 1.2 5.6 5.6 3.1 3.1 7 7 9.1 9.1 9.1 9.4 9.4 9.4 4.2 4.2 5.4 5.4 5.5 11 11 11 6.6 6.6 6.6 10 10 10 3.4 3.4 3.3 3.3 14 14 1.6 1.6 0 0 2.4 2.4 2.4 2.4 0.8 0.8 0.8 0.8 1.8 1.8 7.8 7.8 3.4 3.4 7.4 7.4 10 10 10 11 11 11 4.3 4.3 6.1 6.1 6.3 11 11 11 8.9 8.9 8.9 11 11 11

3.3 3.3 4.6 4.6 1.6 1.6 0 0 2.4 2.4 0.8 0.8 0.8 0.8 2.2 2.2 1.8 1.8 7.8 7.8 17 17 7.4 7.4 6.3 6.3 2.1 2.1 2.1 4.3 5.7 5.7 11 11 5.5 5.5 3.2 3.2 3.2 13 1.6 1.6 4.1 4.1 3.6 3.6 0.9 0.9 2.7 2.7 2 2 2 2 0.4 0.4 1.5 1.5 5.6 5.6 19 19 7 7 4.9 4.9 2.3 2.3 2.3 4.2 4 4 10 10 5.1 5.1 2.4 2.4 2.4 13

3.3 3.3 3.3 3.3 5.8 4 1.9 1.9 0 0 0 2.4 0.8 0.8 0.8 0.8 2.2 2.2 3.7 3.7 14 12 17 17 4.3 4.3 5.8 6.9 7.2 7.2 6.2 6.2 6.2 6.2 6.2 6.2 7 7 5.2 5.2 12 2.8 2.8 2.8 1.2 4.1 1.6 1.6 1.6 1.6 5.4 3.8 1.3 1.3 0.9 0.9 0.9 2.7 2 2 2 2 0.4 0.4 3 3 15 12 19 19 3.5 3.5 5 7.3 7.3 7.3 6.6 6.6 6.6 6.6 6.6 6.6 6.7 6.7 4.6 4.6 11 2.5 2.5 2.5 0.5 4.2

20 20 4.5 4.5 4.5 4.5 9.5 9.5 3.7 3.7 0.8 0.8 0.8 0.8 0.3 0.3 0.3 0.3 2.2 2.2 8.2 8.2 12 12 14 14 4.3 5.8 7.2 7.2 7.3 7.3 7.3 7.3 3.3 3.3 3.3 3.3 3.1 3.1 12 12 0.1 0.1 1.2 1.2 4.1 4.1 14 14 3.5 3.5 3.5 3.5 9 9 3.2 3.2 2 2 2 2 0.4 0.4 0.4 0.4 0.4 0.4 6.8 6.8 6.3 6.3 13 13 3.5 5 7.3 7.3 6.9 6.9 6.9 6.9 2.8 2.8 2.8 2.8 3.1 3.1 11 11 0.2 0.2 0.5 0.5 4.2 4.2

1 1 3 3 3 3 6.2 6.2 6.2 6.2 9.5 9.5 4.7 4.7 14 14 6 6 11 11 0.9 0.9 5.9 5.9 6 6 14 14 2.7 2.7 7.2 7.2 17 17 17 17 7.6 7.6 12 12 3.3 3.3 9 9 9 9 2.2 2.2 0.5 0.5 2.3 2.3 2.3 2.3 5.6 5.6 5.6 5.6 9 9 3.2 3.2 12 12 5.6 5.6 11 11 0 0 5.8 5.8 5.2 5.2 13 13 3.5 3.5 7.3 7.3 12 12 12 12 4.4 4.4 12 12 2.8 2.8 9 9 9 9 2.7 2.7

1 3 5.5 5.5 3.1 3.1 6.4 6.4 2.9 2.9 6.2 6.2 4.2 4.2 8.3 8.3 8 8 6.8 6.8 8.9 8.9 5.2 23 23 23 0.7 0.7 2.7 2.7 11 11 11 11 7.6 7.6 12 12 15 15 15 15 7.1 7.1 7.1 7.1 2.2 2.2 0.5 2.3 5.7 5.7 3.7 3.7 6 6 1.6 1.6 5.6 5.6 3.8 3.8 6.2 6.2 8.2 8.2 2.8 2.8 7.4 7.4 3.3 5.1 5.1 5.1 0.2 0.2 3.5 3.5 12 12 12 12 4.4 4.4 12 12 15 15 15 15 6.5 6.5 6.5 6.5 2.7 2.7

0.2 0.2 0.3 0.3 0.2 0.2 0.4 0.4 2.9 2.9 12 12 12 1.3 1.3 1.3 1.3 1.3 12 12 5.5 5.5 5.2 5.2 7.4 7.4 2.7 2.7 4.8 4.8 7.9 7.9 11 11 14 4.5 4.5 38 22 22 22 15 4.1 4.1 4.1 1 2.2 2.2 2.7 2.7 1.3 1.3 0.6 0.6 0.1 0.1 1.6 1.6 11 11 11 0.5 0.5 0.5 0.5 0.5 11 11 5 5 3.3 3.3 6.9 6.9 2 2 4.8 4.8 8.3 8.3 12 12 13 9.9 9.9 37 21 21 21 15 3.1 3.1 3.1 0.3 2.7 2.7

0.2 0.2 0.2 0.2 0.3 0.3 0.2 0.2 7.1 7.1 7.1 7.1 1.3 1.3 1.3 1.3 6.7 6.7 5.5 5.5 5.8 5.8 5.8 11 11 11 1.6 1.6 4.8 4.8 7.9 12 14 14 9.4 9.4 12 12 12 12 4.1 4.1 1 1 1 1 2.7 2.7 2.7 2.7 1.3 1.3 0.6 0.6 4.4 4.4 4.4 4.4 0.5 0.5 0.5 0.5 3.7 3.7 5 5 4.1 4.1 4.1 7.3 7.3 7.3 2.9 2.9 4.8 4.8 8.3 10 13 13 7.2 7.2 13 13 13 13 3.1 3.1 0.3 0.3 0.3 0.3

2.7 2.7 2.7 2.7 0.3 0.3 7.1 7.1 7.1 7.1 6.3 6.3 6.3 6.3 6.7 6.7 6.7 6.7 6.8 6.8 8 8 14 14 8.9 8.9 4.8 4.8 7.9 7.9 12 12 3.1 3.1 9.4 9.4 9.4 12 1.6 1.6 1.6 1.6 3.6 3.6 6.1 6.1 9.4 2.7 3.2 3.2 3.2 3.2 1.3 1.3 4.4 4.4 4.4 4.4 5.4 5.4 5.4 5.4 3.7 3.7 5 5 2.8 2.8 6.5 6.5 14 14 5.1 5.1 4.8 4.8 8.3 8.3 10 10 3.7 3.7 7.2 7.2 7.2 13 0.9 0.9 0.9 0.9 2.7 2.7 6 6 4.5 0.5

0.2 0.2 0.2 0.2 1.7 1.7 11 8.3 8.3 8.8 8.8 8.8 9.6 9.6 9 9 5.5 5.5 14 14 1.7 1.7 2.5 2.5 5.5 5.5 5.5 10 3.1 3.1 3.1 3.1 7.2 7.2 7.2 7.2 1.6 1.6 8.4 8.4 2.1 6.1 9.4 9.4 2.7 2.7 0.6 0.6 0.6 0.6 1 1 9.9 7.6 7.6 6.8 6.8 6.8 9.4 9.4 8.2 8.2 5.2 5.2 12 12 1 1 2.3 2.3 5.9 5.9 4.6 9.5 3.7 3.7 3.7 3.7 5.9 5.9 5.9 5.9 0.9 0.9 7.3 7.3 1.5 6 4.5 4.5 0.5 0.5

3.4 3.4 9.4 9.4 6.6 6.6 19 6.5 10 10 11 11 1 1 1 1 6.1 6.1 5.5 5.5 5.5 5.5 10 10 12 12 12 12 7.2 7.2 5.5 5.5 4 4 2.1 2.1 5.2 5.2 1.3 1.3 3.1 3.1 7.7 7.7 5.9 5.9 16 6.6 8.6 8.6 9 9 0.1 0.1 0.1 0.1 3 3 5.9 5.9 4.6 4.6 9.5 9.5 12 12 12 12 5.9 5.9 6.1 6.1 3 3 1.5 1.5 3.6 3.6 0.2 0.2

6.3 13 8.7 8.5 8.5 8.5 8.2 8.2 4.7 4.1 6.5 9.2 5.7 5.7 10 10 3.2 5.6 5.6 5.6 3.5 3.5 6.6 6.6 0.1 0.1 6.4 6.4 6.4 6.4 5.5 5.5 5.5 5.5 5.7 4 4 4 11 11 6.1 12 8.1 6.8 6.8 6.8 7.3 7.3 2.7 3.3 6.6 8.5 5.4 5.4 5.8 5.8 3.8 5.2 5.2 5.2 3.8 3.8 7.9 7.9 0.4 0.4 6.7 6.7 6.7 6.7 6.1 6.1 6.1 6.1 5.5 3 3 3 11 11

12 12 8.7 8.7 14 14 4.2 4.7 4.1 4.1 10 10 5.7 5.7 9.6 9.6 7 7 5.2 5.2 2.6 2.6 1.7 1.7 7.5 7.5 6.8 6.8 4.6 4.6 0.4 0.4 5.7 5.7 5.3 5.3 11 11 6.6 6.6 6.1 6.1 2.9 2.7 3.3 3.3 7.2 7.2 5.4 5.4 9.1 9.1 0.7 0.7 4.6 4.6 0.5 0.5 1.4 1.4 7.1 7.1 6 6 2.5 2.5 0.1 0.1 5.5 5.5 3.2 3.2

6.3 11 11 9.1 1.1 1.1 5.8 8.7 8.1 8.1 8.1 8.1 10 10 1.7 1.7 8.9 8.9 7 7 8.8 8.8 8.8 12 12 12 14 14 3.4 3.4 8 8 10 10 4.7 4.7 5.7 10 10 9.1 4.1 4.1 4.9 6.6 4 4 4 4 7.2 7.2 0.3 0.3 8.6 8.6 0.7 0.7 8.1 8.1 8.1 11 11 11 14 14 2.8 2.8 7.1 7.1 6.5 6.5 3.3 3.3

5.7 6.3 4.3 4.3 1.1 1.1 1.1 5.8 2.5 2.5 1.5 1.5 1.5 2.8 8.4 8.4 8.4 8.4 8.4 8.4 5.5 5.5 5.1 5.7 2.9 2.9 4.1 4.1 4.1 4.9 2.4 2.4 0.5 0.5 0.5 2 3.9 3.9 3.9 3.9 3.9 3.9 4.6 4.6 4.8 6.4 6.7 6.7 6.5 5.8 5.6 5.6

Population Change: Decrease Increase, 010% Increase, >10%

The results show how measuring population change directly from census output would be misleading for various Districts because of the impact of adjustments described above. The introduction of a consistent time series clearly affects the interpretation of population change for allgroups. In some Districts, what is seen to be population growth during the decade according to

PART III: ANALYSIS AND CONCLUSIONS 265 Chapter 10: Quality assurance

the 1991 and 2001 Census output is actually a population decrease when using the full mid1991 and mid2001 population estimates.

Figure 10.11: Percentage population change between 1991 and 2001 for non-White groups for 2001 Districts in England and Wales