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Datazone level Namibian Index of Multiple Deprivation 2001

Empowered lives.

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This Report is an independent publication commissioned by the United Nations Development Programme at the request of the Government of Republic of Namibia. The analysis and policy recommendations contained in this report however, do not necessarily reflect the views of the Government of the Republic of Namibia or the United Nations Development Programme or its Executive Board.

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This report is the result of collaborative work between the Government of the Republic of Namibia (GRN), the United Nations Development programme (UNDp) and the centre for the analysis of South african Social policy at the Oxford Institute of Social policy at the University of Oxford.

n November 2009, the Khomas Regional when the 2011 Census becomes available and Council requested UNDP to assist in designing is subsequently used for carrying out a similar an objective criterion or set of criteria, devoid analysis. of political and other considerations, which the Council could use in allocating development This report presents, using tables, charts and resources. Subsequent discussions led to an digital maps, a profile of multiple deprivation in agreement that other stakeholders, especially the Karas region at data zone level, which is a relatively Central Bureau of Statistics needed to be involved new statistical geography developed for purposes and that the criterion or set of criteria needed to of measuring deprivation at a small area level. Igo beyond income poverty considerations. It was This technique of profiling deprivation at datazone also agreed that rather than focus on Khomas level, each with approximately 1000 people region alone, the criterion or set of criteria needed only, enables the identification and targeting of to be applicable to, or cover the entire country. pockets of deprivation within Karas region for Specifically, it was agreed that a composite index possible use in panning for and implementation of of multiple deprivation, the Namibia Index of development interventions. The aim of the exercise Multiple Deprivation (NIMD), be constructed at was to produce a profile of relative deprivation both national and regional levels. Since the scope across Karas region in order for the most deprived and depth of analysis needed for the development areas to be identified and clearly delineated. In of the NIMD required very detailed and reliable this way, it would be possible for regional and data and information, it was agreed that the 2001 constituency level policy and decision makers, census data, though ‘outdated’, be used as the as well development practitioners, to consider a source of information for preparing the NIMD. particular domain of deprivation, or to refer to inter alia Accordingly, the NIMD being presented in this the overarching NIMD for each constituency or report reflects the situation in Karas region at the datazone, in , allocating and applying 2001 time-point only. UNDP and the GRN recognize development resources and interventions. The that the report does not speak to possible changes NIMD can also be used as a platform for effecting in relative deprivation that may have occurred in a paradigm shift in development planning towards the Karas region since 2001. Nevertheless the 2001 increased focus on and targeting of deprived areas NIMD could serve as a benchmark against which and sectors; as well as interrogating the causes change over the last decade could be measured of inequality in access to basic services within

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 1 the region. The NIMD at datazone level should be Policy at the Oxford Institute of Social Policy at viewed as adding to the existing body of information the University of Oxford, under the leadership and and knowledge, including local knowledge systems, guidance a national steering committee chaired about poverty and deprivation in Karas region and by Mr Sylvester Mbangu, Director of the Central the large family of existing planning and resource Bureau of Statistics, with the participation of allocation tools and methodologies already in use representatives of the thirteen Regional Councils. at the regional and constituency levels. In addition to providing the funds for carrying out the project, UNDP provided overall oversight This project was undertaken by Professor Michael and technical backstopping to the project through Noble, Dr Gemma Wright, Ms Joanna Davies, Dr Ojijo Odhiambo, Senior Economist and Johannes Helen Barnes and Dr Phakama Ntshongwana of Ashipala, National Economist. David Avenell is the Centre for the Analysis of South African Social thanked for his assistance with producing the datazones.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 2 Table Of cONTeNTS

Section 1: Introduction 5

1.1 Background 5 1.2 Defining poverty and deprivation 6 1.3 The concept of multiple deprivation 6 Section 2: Datazones 7

Section 3: Methodology 8

3.2 An introduction to the domains and indicators 8 Domains 8 Indicators 8 3.3 Material Deprivation Domain 9 Purpose of the domain 9 Background 9 Indicators 10 Combining the indicators 10 3.4 Employment Deprivation Domain 10 Purpose of the domain 10 Background 10 Indicator 11 Combining the indicators 11 3.5 Health Deprivation Domain 11 Purpose of the domain 11 Background 11 Indicator 12 3.6 Education Deprivation Domain 12 Purpose of the domain 12 Background 12 Indicators 12 Combining the indicators 13 3.7 Living Environment Deprivation Domain 13 Purpose of the domain 13 Background 13 Indicators 14 Combining the indicators 14

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 3 3.8 Constructing the domain indices 15 3.3 Standardising and transforming the domain indices 15 3.4 Weights for the domain indices when combining into an overall Index of Multiple Deprivation 16 Section 4: Datazone level Namibian Index of Multiple Deprivation 2001: Kavango Region 17

4.1 Multiple Deprivation 17 4.2 Domains of deprivation 23 Section 5: conclusion and Some policy Recommendations 41

annex 1: Indicators included in the NIMD 2001 43

Material Deprivation Domain 43 Employment Deprivation Domain 43 Health Deprivation Domain 43 Education Deprivation Domain 43 Living Environment Deprivation Domain 43 appendix 2: Domain and overall NIMD scores and ranks 44

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 4 SecTION 1: INTRODUcTION

This report presents the datazone level Namibian Index of Multiple Deprivation 2001 (NIMD 2001) for Karas region. The NIMD is a composite index reflecting five dimensions of deprivation: income and material deprivation; employment deprivation; education deprivation; health deprivation; and living environment deprivation.

The NIMD and the component domains of provide a more detailed analysis of deprivation deprivation were produced at datazone level using which would enable Khomas Regional Council, and data from the 2001 Population Census. Datazones other regional councils across Namibia, to rank are small areas containing approximately the same their areas in order of deprivation, and also to set number of people (average 1,000). The datazone them in the context of all other areas in Namibia. level NIMD therefore provides a fine-grained The datazone level index presented in this report picture of deprivation and enables pockets of draws from the previous constituency index, and deprivation to be identified in Karas region. covers, in detail, the entire country including Karas The report is structured as follows: The background region. In constructing the NIMD at datazone level information and the conceptual framework which however, it became necessary to make some small underpins the model of multiple deprivation is changes to some of the domains and indicators described in this introductory section. In Section 2 the rationale for and process of constructing datazones are described. Section 3 introduces the domains and indicators that were included The NIMD and the in the NIMD and summarises the methodological approach that was used in constructing the NIMD. component domains of In Section 4 datazone level results for Karas region deprivation were produced are presented, while conclusions and some general policy recommendations are presented in Section 5. at datazone level using data 1.1 background from the 2001 Population Census. As will be elaborated Initially a NIMD was created at constituency level for the Khomas Region, but applicable to other in Section 2, datazones regions of the country as well, using data from the 2001 Population Census at constituency level after are small areas containing a two-day consultative process on the domains and approximately the same indicators with members of the Central Bureau of Statistics, civil servants from the Council and staff number of people members of UNDP. The objective of this phase of the project was to construct measures of multiple (average 1,000) deprivation at constituency level in order to

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 5 initially used in the constituency level study. These that there exists separate dimensions of deprivation changes are explained in detail in Section 3 of this which can be recognised and measured, and report. As such, the constituency level index has are experienced by individuals living in an area. also been revised to give a comparable measure. Multiple deprivation is therefore conceptualised as The initial results of the work at the datazone level a weighted combination of distinct dimensions or were presented to, and validated by, representatives domains of deprivation. An area level score for each of all the 13 Regional Councils at a workshop held domain is produced and these are then combined in Ondangwa in November 2011. to form an overall Index of Multiple Deprivation. 1.2 Defining poverty and deprivation relative Although the area itself is not deprived, it can nonetheless be characterised as deprived to Townsend (1979) sets out the case for defining other areas, in a particular dimension of deprivation, ‘Individuals, families and groups can be said to be in poverty in terms of relative deprivation as follows: on the basis of the proportion of people in the area poverty if they lack the resources to obtain the types experiencing the type of deprivation in question. of diet, participate in the activities and have the living In other words, the experiences of the people in an conditions and amenities which are customary or at area give the area its deprivation characteristics. It least widely encouraged or approved in the societies is important to emphasize that the area itself is not to which they belong’ deprived, though the presence of a concentration (Townsend, 1979, p31). of people experiencing deprivation in an area may give rise to a compounding deprivation effect, Though ‘poverty’ and ‘deprivation’ have often but this is still measured by reference to those been used interchangeably, many have argued individuals. Having attributed the aggregate of that a clear distinction should be made between individual experience of deprivation to the area them (see for example the discussion in Nolan and however, it is possible to say that an area is deprived Whelan, 1996). Based on this line of thought, it can in that particular dimension. And having measured be argued that the condition of poverty means not specific dimensions of deprivation, these can be having enough financial resources to meet a need, understood as domains of multiple deprivation. In whereas deprivation refers to an unmet need, his article ‘Deprivation’ Townsend also lays down which is caused by a lack of resources of all kinds, the foundation for articulating multiple deprivation not just financial. as an aggregation of several types of deprivation 1.3 The concept of multiple (Townsend, 1987). Townsend’s formulation of deprivation multiple deprivation is the starting point for the model of small area deprivation which is presented in this report. The starting point for the NIMD is a conceptual model of multiple deprivation. The model of multiple deprivation is underpinned by the idea

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 6 SecTION 2: DaTazONeS

Datazones are a new statistical geography for Namibia created especially for this version of the NIMD 2001. This section provides a non-technical overview of the process of creating the datazones and summarises their characteristics.

Internal homogeneity

The methodology adopted is based on a similar : It is important that process undertaken in South Africa (Avenell et al., datazones comprise EAs of similar characteristics. 2009) which in turn was adapted from techniques This helps to ensure that the datazone geography developed in the United Kingdom (see, for example, created is ‘meaningful’ in that, for example, in Martin et al., 2001). Datazones were built up urban areas housing of a similar type are grouped from Census Enumeration Areas (EAs) to create a together within one datazone and that those living standard uniform geography across Karas region in EAs within a single datazone share similar socio- based on the existing EA geography which nest economic characteristics. In order to achieve this within the six constituency boundaries. Though all EAs were analysed using a technique known a datazone may be created from a single EA, it is as cluster analysis. This technique groups EAs usually created by merging one or more contiguous across the country and the region into a small EAs which share common characteristics in number of ‘families’ based on a variety of relevant accordance with a set of pre-defined rules. The characteristics. The datazones were checked actual creation of datazones was undertaken using and validated by obtaining aerial photography a variety of geographical programming techniques underlays for the mapping software and visually (see Avenell et al., 2009). A set of rules governing inspecting boundary positions. the merging process was drawn up to ensure that the datazones had, as close as was possible, the following characteristics: Population size Though a datazone : Datazones are designed to have may be created from a a similar resident population size - this allows comparability across the region. The target single EA, it is usually population size was 1,000 with a minimum of 500 and maximum of 1,500. A total 68 datazones were created by merging created for the Karas region. Population density one or more contiguous : Datazones should comprise EAs of similar population density. This is important EAs which to ensure that urban areas become distinct from share common rural areas. The datazone algorithm incorporated thresholds to ensure that, wherever possible, urban characteristics in areas became tightly bounded. accordance with a set of pre-defined rules. Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 7 SecTION 3: MeThODOlOGy

3.1 an introduction to the domains

and indicators that the same person can be captured in more than one domain. So, for example, if someone Domains was unemployed, had no qualifications and had no access to basic material goods they would be The NIMD was produced using the 2001 Namibian captured in the Employment Deprivation, Education Population Census which was supplied by the Deprivation and Material Deprivation domains. Namibian Central Bureau of Statistics for the The indicators were chosen following an extensive purposes of this project. Whilst the intention consultation process with representatives of the Central Bureau of Statistics, Khomas Regional should always to be concept-led rather than ‘data- 2 driven’, the project team was restricted to selecting Council and UNDP . indicators from the range of questions included within the 2001 Census. The NIMD was produced at datazone level (and also at constituency level on The NIMD was a comparable basis). There are 68 datazones and produced using the six constituencies in Karas region. 2001 Namibian The NIMD contains five domains of deprivation: • Population Census 1 • Material Deprivation which was • Employment Deprivation • Health Deprivation supplied by the • Education Deprivation Namibian Central Living Environment Deprivation Bureau of Statistics Each domain is presented as a separate domain index reflecting a particular aspect of deprivation. for the purposes Each domain seeks to measure only one dimension of this project of deprivation, avoiding overlaps between the Indicators domains and providing a direct measure of the deprivation in question. Individuals can however, Each domain index contains a number of indicators. experience more than one type of deprivation There are 11 indicators in total in the NIMD. The at any given time and it is therefore conceivable aim for each domain was to include a parsimonious

1 2 This refers to material goods, that is, assets or possessions. During the consultation process a number of other domains were discussed. These included: access to recreation facilities, level of participation in community activities, crime, food security, provision of emergency services, and availability of affordable transport. Unfortunately data relating to these issues were not available within the Census. These issues could be incorporated into further iterations of the NIMD if appropriate administrative or geographical data becomes available. Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 8 (i.e. economical in number) collection of indicators that comprehensively captured the deprivation for In any event, the each domain, but within the constraints of the data available from the 2001 Census. When identifying 2001 Census did not indicators for the domains, it was important to have an income question ensure that they are direct measures of the domain of deprivation in question and specific to that and so an income poverty domain. indicator, if included,

In the construction of that index the indicators were would need to be modelled discussed at length during the consultation process from a different data source and every effort was made to ensure that they were appropriate for the Namibian context. The such as the Namibian domains need to allow different geographical areas to be distinguished from one another; therefore it Household Income and would be unhelpful to identify a deprivation which Expenditure Survey is experienced by most people in most areas as this would not enable the areas to be ranked relative to In the following sub-sections the domains and each other in terms of deprivation. indicators which make up the NIMD 2001 are described. 3.2 Material Deprivation Domain

With the exception purpose of the domain of changes to three This domain measures the proportion of the indicators in the newly population experiencing material deprivation constituted Living in an area by reference to the percentage of the population who are deprived of access to basic Environment material possessions. background Deprivation Domain,

the indicators are In other indices that have followed this model the same as those used (e.g. UK indices), an Income Deprivation Domain was created. However, there is an argument that in the previous such a domain is inappropriate within an Index of Multiple Deprivation, because - as explained above constituency level index.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 9 •

- deprivation can be regarded as the outcome of Number of people living in a household with no lack of income rather than the lack of income itself. access to a telephone/cell phone. combining the indicators To follow Townsend, within a multiple deprivation measure, only the deprivations resulting from a low income would be included so low income itself A simple proportion of people living in households would not be a component, but lack of material experiencing either one or both of the deprivations possessions would be included. In any event, the was calculated (i.e. the number of people living in 2001 Census did not have an income question and a household with no access to a television/radio so an income poverty indicator, if included, would and/or with no access to a telephone/cell phone need to be modelled from a different data source divided by the total population). 3.3 employment Deprivation such as the Namibian Household Income and Expenditure Survey. Such modelling work is being Domain undertaken separately for the Central Bureau of purpose of the domain Statistics (now Namibia Statistics Agency) by Lux Development and will provide a complementary small area measure of income poverty. For these This domain measures employment deprivation reasons, a material deprivation domain was conceptualised as involuntary exclusion of the produced. A lack of access to basic material goods working age population from the world of work can be understood as a proxy for low income. The by reference to the percentage of the working age 2001 Census included questions about access to population who are unemployed. background material goods (e.g. television, radio, newspaper, telephone and computer) which are internationally accepted and widely used as measures of variations The 2001 Census recorded employment status in in living standards. line with the International Labour Organisation (ILO) ‘labour force framework’ and the ‘priority ‘regardless of the amount of time Of the possible material goods that could be rules’ which give precedence to employment over devoted to it, which in extreme cases may be only one included as indicators, access to a television/radio all other activities hour’ and telephone/cell phone were selected as they represent important modes of communication (Hussmanns, 2007, p6). Therefore a person and a means of accessing information crucial to was considered to be employed if during the seven one’s life and livelihood. The quality of the services days prior to the Census night they worked for provided however, were not be taken into account. at least one hour for pay, profit or family gain. It Indicators follows that unemployment was defined as a • situation of a total lack of work. The definition of th Number of people living in a household with no unemployment adopted by the 13 International access to a television or a radio; or Conference of Labour Statistics (ICLS) stipulates

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 10 combining the indicators three criteria which must be simultaneously met for a person to be considered unemployed. According The domain was calculated as those identified as to this official definition, the unemployed are those unemployed and aged 15 to 59 inclusive divided by persons within the economically active population the number of people who are economically active (aged 15-65 inclusive) who during the reference in that age group. period (for the 2001 Census this is the seven days 3.4 health Deprivation Domain prior to Census night) were: 1. Without work, i.e. in a situation of total lack of purpose of the domain work; and 2. Currently available for work, i.e. not a student This domain identifies areas with relatively high or homemaker or otherwise unavailable for rates of people who die prematurely. The domain work; and measures premature mortality but not aspects of forthcoming 3. Seeking work, i.e. taking steps to seek behaviour or environment that may be predictive employment or self-employment. of health deprivation. background

Using the 2001 Census however, it was not possible to measure whether unemployed people were Although the consultation process raised the available for work and seeking work. Though importance of measuring people’s health status; other indices have also included people of and access to health facilities and healthcare, working age who cannot work because of illness these issues could not be measured using the 2001 or disability, as they are involuntarily excluded Census data. It was therefore not possible to include from the world of work and internationally are any measures of morbidity or access to health regarded as the ‘hidden unemployed’ (Beatty et services. Instead a form of standardised mortality al., 2000), the consultation group wanted to limit ratio known as Years of Potential Life Lost (YPLL) this domain to the economically active population was used. An internationally recognised measure and therefore disabled or long-term sick people of poor health, the YPLL measure is the level of were not included. The age band was modified to unexpected mortality weighted by the age of the 15-59 inclusive to reflect a concept of working age individual who has died (for details about how this relevant to Namibia. indicator was constructed see Blane and Drever, Indicator 1998). An area with a relatively high death rate in a • ceteris paribus young age group (including areas with high levels

Number of people aged 15-59 inclusive who of infant mortality) will therefore , are unemployed. have a higher overall YPLL score than an area with a similarly relatively high death rate for an older age group.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 11 3.5 education Deprivation Domain

The YPLL measure is purpose of the domain

related to life expectancy This domain measures deprivation in educational attainment for people aged 15 to 59 inclusive. in an area. Areas with low background life expectancy will have high YPLL scores Elsewhere in the Southern Africa Development Community (SADC) region it has been shown The YPLL indicator is a directly age and gender that the level of educational attainment in the standardised measure of premature death (i.e. working age adult population is closely linked 3 death under the age of 75) . The YPLL measure to an individual’s employment status and future is related to life expectancy in an area. Areas opportunities for those individuals and their with low life expectancy will have high YPLL dependants (Bhorat et al., 2004). scores. Equally high levels of infant mortality and perinatal mortality as well as high levels of serious The 2001 Census includes a record of the level illness such as HIV/AIDS and tuberculosis will all of education completed and a record of illiteracy. contribute to reduced life expectancy in an area These two questions provide the best available and therefore high YPLL scores. Thus, although measures of educational attainment and make up the YPLL is a mortality measure, it does, implicitly, the indicators for this domain. The consultation reflect the extent of serious ill-health in an area. process additionally raised the importance of And although it would have been possible to use affordable education and availability of tertiary infant mortality, under-five mortality, and life education opportunities, but again, these could not expectancy as indicators, YPLL in effect combines be adequately captured using the 2001 Census. Indicators all these issues into a single indicator and is • therefore a broader and more useful overview of health deprivation in an area. Number of 15-59 year olds inclusive with no Indicator schooling completed at secondary level or • • above; or Years of potential life lost Number of 15-59 year olds inclusive who are illiterate.

3. Because the direct method of standardisation makes use of individual age/gender death rates it is often associated with small numbers. An empirical Bayes or ‘shrinkage’ technique is therefore used to smooth the individual age/gender death rates in order to reduce the impact of small number problems on the YPLL.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 12 combining the indicators

and therefore provides a more valid measure of A simple proportion of the working age population deprivation in terms of access to energy for lighting (aged 15 to 59 years old inclusive) who had not (Bhorat et al., 2004). This was the measure used in completed schooling at secondary level or who the previous constituency level index. However, at are illiterate was calculated (i.e. the number of datazone level, all individuals in a high proportion people with no schooling completed at secondary of datazones were found to lack electricity for level or above or who are illiterate divided by the lighting. These datazones would all be given population aged 15 to 59 inclusive). the same overall score for this domain, and so it 3.6 living environment Deprivation would not be possible to discriminate between Domain datazones in terms of their level of deprivation. For this reason the indicator was altered slightly purpose of the domain to include paraffin alongside electricity (and solar power) as the measure of access to energy for This domain measures both inadequacy in housing lighting. The inclusion of paraffin however, does conditions and a lack of basic services to the not imply any judgement about its suitability for home. lighting purposes, but is rather a means of enabling background datazones to be properly ranked on this domain.

The 2001 Census questionnaire provides indicators Access to clean drinking water and sanitation on households’ access to basic amenities. These facilities is essential for the good health of the aspects of the immediate environment in which population and thus an important indicator to people live impact on the quality of their life and include in this domain. An indicator of no access to provide good measures of deprivation in terms of access to services. Access to clean Measuring access to electricity as a basic amenity is drinking water and a useful indicator of living environment deprivation. Three Census indicators were considered: main sanitation facilities source of energy for cooking, lighting and heating. is essential for the Although cost, availability and effectiveness are factors in the consumption of all energy supplies, good health of the it has been argued that in certain instances, the population and thus choice of fuel for cooking may be influenced by cultural preference rather than availability alone, an important indicator whereas the use of electricity for lighting would to include in generally be the preferred choice, if available, this domain Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 13 piped water within the home or within 200 metres number of rooms excluding bathrooms, toilets, of the home was included. The threshold of 200 kitchens, stoops and verandas. Different versions metres was regarded by the consultation group as of the crowding indicator were considered. It was preferable to a threshold of 400 metres (the MDG felt that the most appropriate measure of crowding measure). Though in the previous (constituency) was to classify three or more people per room as a index people without flush toilets or ventilated pit deprivation. Setting the capacity cut-off at two or latrines were regarded as deprived, investigation of more people per room was considered. However, it this indicator at datazone level revealed that again, was felt that this lower capacity would capture too a high proportion of datazones scored 100 percent. many non-deprived people, for example relatively Therefore, as with the access to energy indicator, well-off couples sharing a one room urban an additional criterion was added: long drop pit apartment. Indicators latrines were included alongside flush toilets and ventilated pit latrines. Again, the inclusion of long • drop pit latrines does not imply adequacy, but Number of people living in a household without is included simply as a means of discriminating the use of electricity, paraffin or solar power for between datazones. • lighting; or Number of people living in a household without The quality of housing construction provides an access to a flush toilet or pit latrine (ventilated important indicator for the quality of day-to-day • or long drop); or life and vulnerability to shocks such as adverse Number of people living in a household without weather conditions (Bhorat et al., 2004; Programme piped water/borehole/borehole with covered of Action Chapter 2 World Summit for Social tank (but not open tank)/protected well inside Development Copenhagen 1995). There was much • their dwelling or yard or within 200 metres; or discussion during the consultation process about Number of people living in a household that is traditional dwellings and their adequacy. Though • a shack; or the 2001 Census contains fairly precise information Number of people living in a household with about materials used in the construction process, three or more people per room. combining the indicators there is no way of identifying whether the resultant buildings were of a high quality or not. It was therefore agreed that only shacks could be reliably A simple proportion of people living in households identified as constituting inadequate housing. experiencing one or more of the deprivations was calculated (i.e. the number of people living in a The crowding indicator is calculated by dividing household without electricity, paraffin or solar the number of people in the household by the power for lighting and/or without adequate toilet

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 14 facilities and/or without adequate water provision and/or living in a shack and/or in overcrowded As Censuses can be conditions divided by the total population). 3.7 constructing the domain indices regarded as a sample from a super-population, In all domains apart from the Health Deprivation Domain, the overall score is a simple proportion it is important to of the relevant population, and so can be easily consider and deal with interpreted. As Censuses can be regarded as a sample from a super-population, it is important large standard errors. to consider and deal with large standard errors. A A technique that takes technique that takes standard errors into account but still enables one to then combine the domains standard errors into into an overall index of multiple deprivation is called Bayesian shrinkage estimation. Specifically, account but still enables the scores for datazones can be unreliable when the one to then combine deprived population is small and so the shrinkage technique was applied to each of the domains. The the domains into an ‘shrunk’ estimate is the weighted average of the overall index of multiple original datazone level estimate and an appropriate larger spatial unit. The weight is based on the deprivation is called standard error of the original datazone estimate and the amount of variation within the constituency. Bayesian shrinkage For further details about this technique see Annex estimation 2 of the 2001 NIMD National Report available at http://www.undp.org.na/publications.aspx and combine domain indices which are each based on also Noble et al. (2006b). different metrics there needed to be some way to 3.8 Standardising and transforming standardise the scores before any combination the domain indices could take place. A form of standardisation and transformation is required that meets the following criteria. First it must ensure that each domain Having obtained a set of domain indices, these has a common distribution; second, it must not needed to be combined into an overall Namibia be scale dependent (i.e. conflate size with level of Index of Multiple Deprivation and in order to deprivation); third, it must have an appropriate

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 15 degree of cancellation built into it; and fourth, it must A form of standardisation facilitate the identification of the most deprived datazones. The exponential transformation of the and transformation is ranks best meets these criteria and was applied required that meets the in the NIMD 2001. For further details about this technique see Annex 3 of the 2001 NIMD National following criteria. First it Report available at http://www.undp.org.na/ publications.aspx and also Noble et al. (2006b). must ensure that each 3.9 Weights for the domain indices domain has a common when combining into an overall Index of Multiple Deprivation distribution; second, it must not be scale dependent (i.e. Domains are conceived as independent dimensions conflate size with level of of multiple deprivation, each with their own deprivation); third, it must additive impact on multiple deprivation. The strength of this impact, though, may vary between have an appropriate degree domains depending on their relative importance. of cancellation built into it; As a starting point, equal weights for the domains were recommended and this was supported by the and fourth, it must facilitate consultation group. Each domain was therefore assigned a weight of 1. The NIMD was therefore the identification of the most constructed by adding the standardised and deprived datazones. The transformed domain indices with equal weights. exponential transformation of the ranks best meets these criteria and was applied in the NIMD 2001. For further details see Annex 3 and Noble et al. (2006b)

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 16 SecTION 4: DaTazONe level NaMIbIaN INDex Of MUlTIple DepRIvaTION 2001: KaRaS ReGION

4.1 Multiple Deprivation

combined together). The lightest shading relates to the least deprived datazones. Maps 2 and 3 are In this section a profile of multiple deprivation in zoom-ins of Map 1, showing the datazones within Karas region, at both constituency and datazone the Keetmanshoop and Luderitz areas (as these levels, is presented. Using the data from the NIMD are small in physical size and therefore hard to it is possible to compare the 68 datazones and distinguish on Map 1). These maps provide an six constituencies within Karas. Map 1 shows easy to interpret picture of the pattern of multiple the datazones in Karas in relation to the overall deprivation in the Karas Region. NIMD (i.e. the five separate domains of deprivation

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 17

Map 1

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 18

Map 2

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 19 Map 3

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 20 20 Table 1 shows some of the data underlying these rank of 1 among the datazones in Karas. If ranked maps. The NIMD 2001 score, national rank (where alongside all datazones in Namibia, it ranks at 253. 1=most deprived and 1,871=least deprived) and Therefore none of the datazones in Karas are in the Karas rank (where 1=most deprived and 68=least most deprived 10 percent of datazones in Namibia deprived) for the 20 most deprived datazones in terms of multiple deprivation (the cut-off for in Karas are shown. Appendix 2 provides this the 10 percent most deprived is a rank of 187). information for all of the datazones in Karas. The least deprived datazone in Karas is located in The most deprived datazone in Karas is in Oranjemund which is ranked at 1,862 in Namibia

TableKarasburg 1: The constituency, 20 most deprived and is thereforedatazones given in the a Karasas Region a whole. NIMD rank – NIMD rank – Datazone constituency NIMD score national within Karas

297 Karasburg 252.0 253 1 305 Keetmanshoop Rural 241.2 327 2 291 Karasburg 219.9 494 3 329 Luderitz 218.8 503 4 292 Karasburg 212.2 562 5 293 Karasburg 208.3 593 6 331 Luderitz 207.4 601 7 299 Karasburg 203.6 624 8 317 Keetmanshoop Urban 201.5 646 9 295 Karasburg 200.5 653 10 279 Berseba 198.3 674 11 294 Karasburg 190.4 746 12 278 Berseba 190.3 747 13 276 Berseba 188.3 763 14 287 Karasburg 184.1 792 15 290 Karasburg 177.0 868 16 282 Berseba 174.9 887 17 281 Berseba 170.5 914 18 304 Keetmanshoop Rural 166.3 944 19 284 Berseba 160.3 997 20

The six constituencies in Karas vary in terms of the datazone in Namibia is ranked 1, and the least range of deprivation of their datazones. Chart 1 deprived datazone is ranked 1,871). Oranjemund shows the minimum, maximum and median rank of and Keetmanshoop Rural constituencies are datazones in each constituency, and the interquartile omitted from the chart because they comprise just national range for the overall NIMD. This is based on the five and seven datazones respectively, which is too ranks (i.e. where the most deprived few to calculate a meaningful interquartile range.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 21

Interpreting the Charts: For details on how to interpret the chart please see the ‘How to interpret interquartile range charts’ description in section 4.1 of the national report available at http://www.undp.org.na/publications.aspx Interpreting the Charts: For details on how to 4.1 of the national report available at http://www. interpret the chart please see the ‘How to interpret undp.org.na/publications.aspx interquartile range charts’ description in section

The vertical green line for each constituency shows the range of the ranks of the The vertical green line for each constituency ranks in Keetmanshoop Urban and Luderitz datazonesshows in thea constituency range of the ranks (including of the datazones the dots in whichare higher for (lesssome deprived) constituencies than in Berseba, like andGibeon and Rehobotha constituency West (including Urban ,the appear dots which at either for some end ofKarasburg the line). which Mariental both have median Rural, ranks Mariental situated Urban andconstituencies, Rehoboth like East Luderitz, Urban appear all at have either aend relatively towards wide the middle range of ofthe deprivation. distribution. If the box of the line). The datazones in Karasburg are ranked is relatively short this indicates that datazones inThe the greenwidest range. box for each constituency showsare theranked range in a narrowof the range, NIMD with ranks similar ofNIMD the middle 50 percent of datazones in the constituencyranks (the (and interquartile therefore similar range). levels The of multiple horizontal line withinThe greenthe box box for eacheach constituency constituency shows represents the deprivation). the rank All o f of the the median constituencies datazone have within a that constituency.range of the NIMD The ranks median of the rankmiddle in 50 Rehoboth percent broadlyWest Urban similar rangeis th fore highest the middle (least 50 percent. deprived) in the region,of datazones while inGibeon the constituency has the (the lowest interquartile (most deprived)If the box sitsmedian towards rank. the bottom If the of b theox chartis relatively it range). The horizontal line within the box for each short this indicates that datazones are ranked in atells narrow us that rang datazonese, with in similar the constituency NIMD areranks constituency represents the rank of the median concentrated in the most deprived part of the (and therefore similar levels of multiple deprivation). Rehoboth Rural, Rehoboth West Urban datazone within that constituency. The median national distribution of the NIMD. If the box sits and Gibeon, have a narrow range for the middle 50 percent. Mariental Rural, Mariental Urban and RehobothDatazone East level Urban Namibian on theIndex other of Multiple hand Deprivation have a much 2001 wider- Karas range Region for the middle 22 50 percent.

If this box sits towards the bottom of the chart it tells us that datazones in the constituency are concentrated in the most deprived part of the national distribution of the NIMD. If the box sits towards the top of the chart it tells us that the datazones in the

23 towards the top of the chart it tells us that the Karasburg (with 59 percent and 49percent of the datazones in the constituency are concentrated in population experiencing material deprivation, the least deprived part of the national distribution. respectively). The same two constituencies are also Datazones in Keetmanshoop Urban and Luderitz the two most deprived in terms of employment are concentrated towards the least deprived end of deprivation with Berseba being the most deprived the Karas distribution, while datazones in Berseba (with 39 percent of the relevant population being and Karasburg are concentrated in the middle of employment deprived). the distribution. In terms of education deprivation Keetmanshoop within Karas Further analysis shows that the datazones in the Rural is the most deprived constituency (with 76.3 most deprived 10% of datazones on percent of the relevant population being education the overall NIMD are located in three constituencies. deprived), followed by Berseba (75.6 percent) and These three constituencies and the number that are Karasburg (75 percent). These three constituencies in the most deprived 10% of datazones within Karas are also the three most deprived in terms of living are as follows: Karasburg (4 of 16), Keetmanshoop environment deprivation. The most deprived Rural (1 of 7) and Luderitz (1 of 14). constituency in Karas is Karasburg (with 83 4.2 Domains of deprivation percent of the total population experiencing living environment deprivation), followed by Berseba (82 Although it is not possible to calculate multiple percent) and Keetmanshoop Rural (76 percent). deprivation rates as such, each of the individual Oranjemund is the least deprived constituency on domains of deprivation can be presented at all four of the domains. constituency level, and for all domains except the Health Deprivation Domain the domain scores can The domain scores and ranks for each of the be compared. datazones in Karas are presented in Appendix 2. As in Table 2, four of the five domains are expressed as Table 2 provides the domain scores for each rates. Health deprivation is expressed as the years constituency in Karas, excluding health as the of potential life lost in that datazone. A datazone health score is not calculated as a rate. The other with a relatively high death rate in a young age four domains are in the form of simple deprivation group (including areas with high levels of infant rates. So for example, 36.6 percent of the population mortality) will have a higher score than an area in Luderitz constituency experienced material with a similarly relatively high death rate for an deprivation in 2001. The within Karas ranks are older age group, all else being equal. The measure shown as well as the domain scores, for each is related to life expectancy in an area, so datazones constituency in Karas (where 1=most deprived). with low life expectancy will have high scores on In terms of material deprivation, the two most this domain. deprived constituencies in Karas are Berseba and

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 23 2 1 3 5 4 6 rank iving l iving Karas) (within deprivation deprivation environment environment 81.7 82.8 76.4 48.2 65.0 24.3 iving l iving rate (%) rate deprivation deprivation environment environment 2 3 1 5 4 6 rank Karas) (within ducation e deprivation 75.6 75.0 76.3 63.8 67.1 43.7 ducation rate (%) rate e deprivation deprivation 1 2 5 3 4 6 rank Karas) (within deprivation mployment e mployment 39.0 31.1 24.1 30.6 27.6 14.9 rate (%) rate deprivation deprivation mployment e mployment 1 2 3 5 4 6 rank Karas) (within Material Material deprivation 58.8 48.7 41.9 18.2 36.6 17.2 rate (%) rate Material Material deprivation deprivation onstituency c Berseba Karasburg Keetmanshoop Rural Keetmanshoop Keetmanshoop Urban Keetmanshoop Luderitz Oranjemund Table 2: Domain scores and ranks for each constituency in the Karas Region in the Karas for each constituency and ranks 2: Domain scores Table

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 24 Table 3 shows the percentage of each constituency’s constituencies has datazones in the most deprived nationally datazones that are in the most deprived 10 percent 10 percent on the education domain. Luderitz of datazones for each domain. There also has one datazone in the most deprived 10 are four constituencies that feature in the most percent in terms of health deprivation. None of deprived 10 percent of datazones in Namibia on the constituencies have datazones in the most at least one of the domains: Berseba, Karasburg, deprived 10 percent for material, employment or Keetmanshoop Rural and Luderitz. Each of these living environment deprivation. Table 3: percentage of datazones in most deprived 10 percent of datazones in Namibia Number of Material employment health education living env. constituency datazones deprivation deprivation deprivation deprivation deprivation

Berseba 10 0.0 0.0 0.0 30.0 0.0 Karasburg 16 0.0 0.0 0.0 37.5 0.0 Keetmanshoop Rural 7 0.0 0.0 0.0 28.6 0.0 Keetmanshoop Urban 16 0.0 0.0 0.0 0.0 0.0 Luderitz 14 0.0 0.0 7.1 14.3 0.0 Oranjemund 5 0.0 0.0 0.0 0.0 0.0

Table 4 shows the percentage of each constituency’s from health. 40 percent of Berseba’s datazones within Karas datazones that are in the most deprived 10% are in the most deprived 10 percent in terms of of datazones for each domain. employment deprivation. Keetmanshoop Urban Karasburg is the only constituency that has at least only has datazones in the most deprived 10 percent one datazone in the most deprived 10 percent for in terms of health deprivation. Oranjemund does each domain. Berseba has datazones in the most not have any datazones in the most deprived 10 deprived 10 percent for all of the domains apart percent for any of the five domains. Table 4: percentage of datazones in most deprived 10 percent of datazones in the Karas Region Number of Material employment health education living env. constituency datazones deprivation deprivation deprivation deprivation deprivation

Berseba 10 20.0 40.0 0.0 20.0 10.0 Karasburg 16 18.8 6.3 18.8 18.8 25.0 Keetmanshoop Rural 7 0.0 14.3 14.3 14.3 0.0 Keetmanshoop Urban 16 0.0 0.0 6.3 0.0 0.0 Luderitz 14 7.1 0.0 7.1 0.0 7.1 Oranjemund 5 0.0 0.0 0.0 0.0 0.0

The following maps present each of the five deprived datazones. It is intended that these maps domains at datazone level for Karas and for the should provide accessible profiles of the domains Keetmanshoop and Luderitz areas. As with Maps of deprivation in the Karas Region. 1, 2 and 3 the lightest shading relates to the least

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 25

Map 4

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 26

Map 5

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 27 Map 6

Datazone level Namibian Index of Multiple31 Deprivation 2001 - Karas Region 28

Map 7

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 29

Map 8

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 30 Map 9

Datazone level Namibian Index of Multiple34 Deprivation 2001 - Karas Region 31

Map 10

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 32

Map 11

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 33 Map 12

Datazone level Namibian Index of Multiple38 Deprivation 2001 - Karas Region 34

Map 13

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 35

Map 14

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 36 Map 15

Map 13

Datazone level Namibian Index of Multiple42 Deprivation 2001 - Karas Region 37

Map 16

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 38

Map 17

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 39 Map 18

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 45 40 SecTION 5: cONclUSIONS aND SOMe pOlIcy RecOMMeNDaTIONS

The analysis presented in this report has identified particular areas – both datazones and constituencies – where deprivation is high relative to other areas in Karas region. This analysis can support pro-poor policy formulation processes and programmatic interventions in many ways

By providing reliable and objective information on, and profiling the distribution of, multiple deprivation and the distribution of the individual By providing reliable domains of deprivation across the region, the and objective information analysis presented in this report can provide planners; policy and decision makers at the regional on, and profiling the level with the evidence base on which to plan and distribution of multiple make decisions regarding resource allocation and the geographic areas (constituencies and deprivation and the individual datazones) and sectors in which to prioritise public investments, government support and service domains of deprivation delivery. Specifically, the analysis can be useful in across the country, the NIMD the following ways: Temporal analysis of nature, scope and effects of can provide policy and poverty reduction programmes decision makers with the : By describing the geographical distribution and extent of individual evidence base on which to dimensions of deprivation and overall multiple deprivation at constituency and datazone levels, make decisions regarding this report provides a baseline map of deprivation resource allocation and the against which progress in poverty reduction in these areas can be measured over time, that is geographic areas and sectors between successive censuses (2001 and 2011 in which to prioritise public censuses). The NIMD is based on data relating to 2001 time- line and significant changes may have investments, government taken place since then. It will thus be necessary to support and service conduct further analyses using the 2011 Census data and information in order to shed light on the delivery relating to the extent to which changes have occurred in the region and possible reasons for any noted changes. various domains of deprivation Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 41 Interrogating the causes of inequality

: The report constituencies and datazones characterised by could be used by the regional authorities to initiate severe multiple deprivation could be targeted for the process of interrogating the causal factors of integrated development projects and programmes. such wide inter- and intra-constituency (datazone The most deprived areas vary by domain, and not all level) variations with respect to specific domains areas show a uniform degree of deprivation across and the overall combined and weighted index of the domains. This should be taken into account deprivation. when selecting a measure of deprivation to use Better planning and targeting of development as it is important to choose the most appropriate resources: measure for the particular policy purpose. Regional Councils have two distinct sources of development revenue – transfers It should be noted however, that the NIMD, as relative from central government and locally generated presented in this report, provides a profile of resources. The NIMD allows for better planning deprivation in Karas region and even for and targeting of such resources on the basis of the least deprived areas, such as Oranjemund relative deprivation to the datazone level. Priorities constituency, contain pockets of deprivation. They can then be identified at the constituency and are simply less deprived than other areas with datazone levels that could be addressed through higher levels of deprivation such as Karasburg integrated development approaches. Importantly, and Berseba constituencies. As such, spatially funds could be targeted to and ring-fenced for those targeted policy initiatives should be regarded as sectors/domains in which specific constituencies a complement to, rather than a substitution for, and datazones are particularly deprived or to mainstream pro-poor policies and strategies that the most deprived constituencies and datazones the Regional Council and National Government are within a constituency. It is also conceivable that already implementing in Karas region.

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 42 aNNex 1: INDIcaTORS INclUDeD IN The NIMD 2001

Material Deprivation Domain •

Number of 15-59 year olds (inclusive) who are Numerator illiterate • Denominator

Number of people living in a household with • no access to a television or a radio; or Population aged 15-59 (inclusive) living environment Deprivation Domain Number of people living in a household with no access to a telephone/cell phone Denominator Numerator •

Total population Number of people living in a household employment Deprivation Domain without the use of electricity, paraffin or solar • power for lighting; or Numerator Number of people living in a household • without access to a flush toilet or pit latrine Number of people aged 15-59 who are • (ventilated or long drop); or unemployed Number of people living in a household Denominator without piped water/borehole/borehole with covered tank (but not open tank)/protected Total economically active population aged 15-59 well inside their dwelling or yard or within inclusive • 200 metres; or health Deprivation Domain Number of people living in a household that is • a shack; or Numerator Number of people living in a household with • three or more people per room Denominator Years of potential life lost education Deprivation Domain

Total population Numerator •

Number of 15-59 year olds (inclusive) with no schooling completed at secondary level or above; or

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 43 aNNex 2: DOMaIN aND OveRall NIMD ScOReS aND RaNKS 88.2 86.9 86.6 128.5 188.3 140.6 198.3 190.3 157.2 170.5 174.9 160.3 184.1 112.0 123.5 177.0 219.9 208.3 212.2 200.5 190.4 252.0 154.9 score NIMD 6 3 1 5 9 2 7 41 21 14 15 16 18 36 42 20 34 28 10 35 26 24 29 rank iving l iving deprivation deprivation environment environment 65.6 84.4 90.3 88.5 97.2 88.2 85.7 70.8 64.8 85.0 71.6 78.1 96.1 71.3 80.2 81.9 99.2 99.8 97.9 96.5 99.7 77.8 96.9 score iving l iving deprivation deprivation environment environment 6 3 8 4 7 5 41 24 34 11 21 23 35 44 42 40 14 43 36 28 15 29 10 rank ducation e deprivation 70.1 75.3 72.7 81.2 83.0 79.8 76.4 76.0 72.6 68.4 70.0 70.3 78.3 68.9 71.9 80.3 83.0 80.7 81.7 73.9 78.2 73.3 79.9 score ducation e deprivation deprivation 8 6 4 9 5 31 28 29 56 25 32 18 64 23 26 47 14 11 35 20 55 22 38 rank h ealth deprivation deprivation 69.4 11.3 71.8 351.0 373.0 754.9 361.8 405.2 348.4 475.4 416.8 395.3 121.7 563.3 620.7 333.3 823.0 427.5 422.6 208.9 644.0 910.5 1026.6 score h ealth deprivation deprivation 8 2 4 1 6 5 47 16 40 31 65 68 64 25 48 20 39 24 26 29 28 15 11 rank deprivation mployment e mployment 5.6 52.0 60.9 21.1 40.8 25.5 31.0 54.4 61.8 10.3 52.7 10.4 34.5 21.0 37.7 27.0 36.5 34.4 33.4 33.6 43.9 48.8 53.5 score deprivation deprivation mployment e mployment 8 7 1 4 9 3 2 6 48 36 18 20 45 13 33 16 15 27 35 40 10 42 56 rank Material Material deprivation 22.7 71.7 34.9 75.9 51.7 92.6 48.1 25.4 62.3 80.9 38.7 58.9 59.6 44.3 36.6 30.8 69.6 84.9 68.4 85.8 29.9 13.0 77.5 score Material Material deprivation deprivation onstituency Berseba Berseba Berseba c Berseba Berseba Berseba Berseba Berseba Berseba Berseba Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg Karasburg This table presents the scores and ranks for every datazone in Karas for the five domains and the overall NIMD. For all domains except health the all domains except For NIMD. domains and the overall the five for datazone in Karas every for and This ranks the table scores presents score is calculated as a rate. So for example, 22.7% of the population in datazone 275 in Berseba constituency experienced material deprivation in 2001. Health is expressed as the years of potential life lost (a measure of premature mortality) in that datazone, and a higher score indicates 1=most deprived). each datazone (where for shown are ranks The within Karas health deprivation. greater

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 44 54.9 76.6 93.3 99.9 78.8 65.2 98.5 16.1 23.8 89.5 28.3 36.1 33.8 81.9 87.6 62.9 73.4 62.8 203.6 156.2 146.4 166.3 241.2 110.5 124.8 127.0 148.9 101.4 110.0 201.5 130.2 8 60 11 30 45 25 17 22 31 40 62 54 46 39 55 50 65 27 37 38 43 63 56 64 53 58 44 33 49 51 47 30.5 96.1 96.7 76.8 61.6 80.5 87.3 83.5 76.1 67.5 25.2 48.6 61.4 68.7 48.3 58.0 15.0 78.6 70.4 70.4 63.6 24.3 40.4 20.8 48.7 36.2 62.0 74.2 59.1 56.1 61.0 1 2 59 32 13 46 33 18 22 16 56 48 20 17 49 27 66 37 30 26 19 63 53 61 60 62 50 45 52 51 54 56.0 87.9 72.8 79.3 66.9 72.8 77.3 83.5 76.2 78.1 62.1 65.7 76.4 77.7 65.2 74.1 33.8 71.2 73.1 74.4 77.0 45.3 64.4 51.8 54.8 49.5 65.1 67.2 64.9 65.1 63.8 3 7 2 33 30 19 16 36 49 37 46 39 13 48 50 24 12 52 65 42 59 57 17 58 65 41 44 15 43 27 40 0.0 0.0 83.4 52.6 67.3 58.4 334.3 358.0 474.8 509.4 291.1 115.9 211.5 154.8 202.4 565.5 117.5 114.3 406.9 799.6 606.1 176.8 500.8 182.5 170.7 534.6 176.8 379.3 186.7 1187.4 1225.4 7 3 41 18 51 53 56 10 59 61 32 27 14 38 46 17 62 19 23 13 12 52 34 55 58 50 42 49 37 44 36 24.4 52.5 40.2 17.6 14.7 13.8 54.5 49.9 12.3 11.0 28.9 33.7 44.1 27.4 22.7 40.7 10.5 37.9 37.4 46.6 48.0 16.6 28.5 14.0 12.8 19.1 24.2 19.2 27.5 23.6 27.7 47 58 37 21 25 24 28 31 41 34 52 68 55 60 53 32 67 38 49 22 59 61 30 44 29 66 11 63 57 50 51 2.3 7.0 2.8 8.2 5.7 3.9 5.5 23.3 10.9 34.5 48.0 44.8 45.2 44.3 41.8 30.7 38.6 16.5 13.4 15.9 41.2 32.8 19.1 47.0 43.9 26.3 44.0 67.2 11.4 16.9 16.9 Karasburg Karasburg Karasburg Keetmanshoop R. Keetmanshoop Keetmanshoop R. Keetmanshoop Keetmanshoop R. Keetmanshoop Keetmanshoop R. Keetmanshoop R. Keetmanshoop R. Keetmanshoop Keetmanshoop R. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop Keetmanshoop U. Keetmanshoop U. Keetmanshoop U. Keetmanshoop Luderitz Luderitz Luderitz Luderitz Luderitz

Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 45 71.3 48.8 20.9 74.1 84.4 13.7 10.9 35.4 15.1 218.8 157.7 207.4 125.9 131.7 4 32 13 52 59 61 48 23 19 66 68 12 57 67 1.2 6.2 74.5 90.4 98.1 52.2 31.6 30.0 60.1 82.7 85.4 10.3 94.4 39.1 9 12 31 55 58 64 47 39 38 68 67 25 57 65 79.7 73.1 79.9 63.2 58.2 41.3 66.5 70.7 70.9 28.2 31.1 74.5 59.5 35.3 1 10 21 34 45 65 51 53 62 60 65 54 61 63 0.0 0.0 77.3 19.9 42.0 74.1 25.4 18.0 642.9 423.7 334.1 165.8 100.9 1481.2 9 33 21 22 35 43 57 45 67 63 66 30 54 60 8.8 9.7 28.8 37.7 37.6 27.9 24.1 13.4 23.2 50.2 10.4 31.3 14.5 12.0 5 12 23 46 39 54 19 26 17 65 64 14 43 62 4.5 5.1 5.6 63.3 45.5 80.0 24.8 32.0 14.7 51.0 44.6 54.4 60.7 28.5 Luderitz Luderitz Luderitz Luderitz Luderitz Luderitz Luderitz Luderitz Luderitz Oranjemund Oranjemund Oranjemund Oranjemund Oranjemund

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Datazone level Namibian Index of Multiple Deprivation 2001 - Karas Region 48 Disclaimer

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For electronic copy and a list of any errors or omissions found as well as any updates subsequent to printing, please visit our website: http://www.undp.org.na/publications.aspx Datazone level Namibian Index of Multiple Deprivation 2001

Empowered lives.

Resilient nations.

Karas Region