C E E CENTRE FOR THE ECONOMICS OF EDUCATION
ANNUAL REPORT 2000-2001
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ANNUAL REVIEW 2000-2001
INTRODUCTION 3
OBJECTIVES 5
RESEARCH PROGRAMME 5
· METHODOLOGICAL DEVELOPMENTS 7 · THE PRODUCTION OF EDUCATION AND SKILLS 10 · THE SUPPLY OF EDUCATION AND SKILLS 14 · THE DEMAND FOR EDUCATION AND SKILLS 17 · THE RETURNS TO EDUCATION AND SKILLS 20
ANNEXES
Annex A Staff List 22 Annex B Publications 23 Annex C Discussion Paper Series 28 Annex D Centre Seminars 30 Annex E Forthcoming Events – Seminars and Conferences 31
REFERENCES 33
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INTRODUCTION
This report covers the first year of the Centre for the Economics of Education (CEE). The Centre was set up in March 2000 and is funded by the Department for Education and Employment (DfEE) and consists of researchers affiliated with the Centre for Economic Performance (CEP) at the London School of Economics, the Institute for Fiscal Studies (IFS) and the Institute of Education (IoE). The formation of the Centre represents a major advance in the analysis of the economics of education as it brings together both economists and educationalists in a structured environment. This union provides the capability and capacity to undertake rigorous academic research on the economics of education: something that has, at least in recent years, suffered from being undertaken in a very piecemeal manner. In addition to core DfEE funding, individual researchers from the Centre have obtained additional funding from the DfEE to produce several comprehensive reports relating to resource allocation and pupil attainment and the returns to education and qualifications, both on a microeconomic and macroeconomic level, and CEE members are involved in evaluations of the Education Maintenance Allowance (EMA), Excellence in Cities (EiC) and the New Deal. Additional related research has been undertaken by CEE researchers for other government departments and funding organisations, including the Home Office, the Department of Social Security, the Economic and Social Research Council, Qualifications and Curriculum Authority and at European level, CEDEFOP (European Centre for the Development of Vocational Training).
The Centre is directed by Professor Stephen Machin (University College London and the Centre for Economic Performance, LSE) and has a research programme, which is subdivided into five strands, each with a dedicated strand leader overseeing all work undertaken in that area. The Centre has pulled together a set of leading researchers (see Annex A of the Appendix for a staff list) who work on the economics of education (a list of recent external publications is provided in Annex B of the Appendix). The specific strands of research and the research leaders are as follows:
Methodological Developments: Strand Leader: Professor Costas Meghir, University College London and Institute for Fiscal Studies
The Production of Education and Skills: Strand Leader: Professor Peter Dolton, University of Newcastle and Institute of Education
The Supply of Education and Skills: Strand Leader: Dr. Anna Vignoles, Centre for Economic Performance
3 The Demand for Education and Skills: Strand Leader: Professor Alison Wolf, Institute of Education
The Returns to Education and Skills: Strand Leader: Dr Lorraine Dearden, Institute for Fiscal Studies In the first year of the Centre, substantial progress has been made and/or proposed in all strands. Some of the research work has taken the form of preparatory work for the longer- term research aims of the Centre; however, the major difficulty in much of our work has been associated with the lack of suitable data and thus this report places emphasis on our efforts to build a methodological infrastructure for the analysis of the available data rather than on actual results that have been achieved to date. Nonetheless, there have been several areas where substantial progress has been made and some of the research has progressed far enough to be circulated for wider comment through a discussion paper series (see Annex C of the Appendix). It is one of the aims of the Centre that the work undertaken by its researchers should have as wide a circulation as possible amongst academics, policymakers and practitioners alike. This has been achieved through the creation of the discussion paper series and additional collaboration with the DfEE specifically for the dissemination of the research work. With this aim in mind, there has also been the creation of a dedicated Centre website which allows all material produced to be freely accessible in electronic format. In addition to the research and conference participation by CEE members, there has been an active and well-attended seminar series that was set up at the inception of the CEE, as well as several special events and conference papers aimed at highlighting the creation of the Centre and disseminating its research more widely. These are more fully detailed later on in this report (Annex D of the Appendix reports on the seminars already held). The Centre has produced a sufficiently large body of work with the result that a well publicised discussion paper series has been initiated and three international conferences over the next two years relating to educational choice, school effectiveness and the returns to education are currently being organised (See Annex E of the Appendix).
Building up our knowledge base on the cost effectiveness of various educational interventions and investments and making these research findings more accessible to policy- makers and practitioners remains one of the key objectives of the Centre. To this end, the Centre will not just disseminate its findings in top quality academic journals, although this is an important means of maintaining rigorous research standards. Rather, the Centre has created a clear dissemination strategy. The strategy is focused on both presenting and interpreting evidence to interested parties, such as policy-makers and practitioners, the Higher Education Funding Council for England (HEFCE) and the Qualification and Curriculum Authority (QCA). We have held various seminars and conference events (see Annex C below) and have used the Centre for Economic Performance’s highly successful Public Affairs Unit to promote our findings. In these efforts, we seek to ensure that our research work reaches our intended audience.
An integral part of the CEE’s work plan is to bring on and develop junior researchers and doctoral students (aided by additional funding from the DfEE). The core funding received from the DfEE has been vital to this intended aim so that we have been able to maintain a set of trained researchers (for periods longer than on a grant by grant basis). This continuity should enhance the human capital of such researchers and raise the quality of future research work produced by the Centre.
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The Centre has benefited from being multi-disciplinary in its approach. Additionally, collaboration with the Centre on the Wider Benefits of Learning (the other DfEE research Centre established at the same time as the CEE) has been essential to the overall success of the research agenda of the DfEE. For instance, any evaluation of the costs and benefits of ‘life-long learning’ needs to involve both Centres in order to a) more effectively identify and evaluate the effects of life long learning and b) to avoid duplication and unnecessary data costs. This collaboration has been crucial for the success of both Centres and will ensure that the DfEE continues to have a fully integrated programme of research to inform policy- making.
We believe that the Centre is core to the long-term academic research agenda on the economics of education in the United Kingdom and that our work is already starting to achieve the original aims of the policymakers that funded the Centre as well as the researchers that contribute to the work.
We now look at the Centre’s core objectives and how we have researched these, project by project, before turning to our plans for the coming year.
OBJECTIVES: THE RESEARCH PROGRAMME
Participation in different forms of post-secondary education, policies to improve the quality of schooling, pre-school education, improving responsiveness to the labour market among young people, evaluating skill needs and accurately estimating the wage returns to education are issues (amongst others) that have been the focus of systematic analysis by the Centre’s researchers. Despite the fact that there already exists a substantial amount of evidence on the benefits of certain educational interventions and investments, there remains a pressing need to assess educational interventions/investments in terms of their ‘value for money’, taking into account both the costs and benefits. For example, while we know a great deal about the impact of higher education on pupils’ subsequent earnings, we have only recently presented robust estimates of the economic returns to qualifications gained in further education (Skills Task Force Research Paper 27 and CEE Discussion Paper 4). The opportunity of bringing together economists and educationalists is being used to apply modern econometric techniques and new methodologies to the field of education policy yielding strong results, which we can build upon in the future.
STRANDS
We initially proposed that the new Centre, drawing on the extensive expertise of researchers from all three of the partner institutions, would undertake a wide range of projects. In conceptualising the organisation of the Centre, and in identifying immediate research priorities, we commenced with an overall picture of the subject area. From an economic perspective, education systems are seen primarily as systems of production, but ones in which both the key considerations of policy are critical – namely efficiency and equity. Within this general perspective, several major themes or sets of questions emerged.
The first concerns the efficiency with which the system carries out its current operations, i.e. The Production of Education and Skills (Strand 2). Given a prior definition of the skills and educational outcomes that the society desires, how efficient is the internal organisation of the system?
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Three other themes relate to the wider environment in which a given education system operates. The Supply of Education and Skills (Strand 3) investigates questions such as ‘How far does the environment external to the education system tend to promote (or mitigate against) educational ‘productivity’?’ and ‘How does the system of incentives in the wider society impact young people and adults, and affect skill supply?’
The strand relating to The Demand for Education and Skills (Strand 4) raises questions such as, ‘What indications can we find of over-supply and under-supply?’ and ‘How far can we identify substantive skills and clusters of skills that are highly productive and desired?’
The Returns to Education and Skills (Strand 5) looks at the system’s efficiency from a wider perspective. Rather than appraising the production of given outcomes, it looks at how those outcomes are actually rewarded over time and how far the current structure of educational spending reflects such rates of return data.
In addressing all of these questions, there is a need for better and innovative methodologies, using analytical tools from both the education and economics fields. Underpinning the Centre’s research, therefore, is a programme of work entitled Methodological Developments (Strand 1).
We now turn to a detailed discussion of the work in these strands.
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METHODOLOGICAL DEVELOPMENTS STRAND LEADER: PROFESSOR COSTAS MEGHIR
An important role that the Centre plays is to provide advice and guidance about which educational interventions or investments provide good value for their costs, i.e. to come up with recommendations on the cost effectiveness of different educational programmes and interventions. The evaluation objective is to analyse whether any observed response in the data is really due to the effects of the education programme or due to other factors. In order to identify the true causal impact of a particular education programme, it is essential to ensure that these other factors are appropriately controlled for; otherwise, incorrect policy conclusions will be drawn. This involves careful empirical modelling.
Estimating the Returns to Educational Investments
Education is not randomly determined. This fact must be taken into account to prevent biased estimates of the returns to educational investments. Recent literature regarding the returns to education has used a number of different techniques and has devoted substantial efforts to devising strategies to correct for these potential biases. These include proxy or matching methods, instrumental variable techniques and/or fixed effect methods (using twin or sibling data).
Members of the Centre have developed appropriate methodological techniques to estimate the true causal impact of education on earnings (Skills Task Force Research Paper 27 and CEE Discussion Paper 4). Each of the existing methodologies has a number of drawbacks, either because of the nature of the available data, and/or the appropriateness of the methodology being used. There is potential for substantial methodological development in this area using both better data and better methodological approaches. For example, the new propensity score matching techniques have not been used extensively in this area because until recently they were limited to binomial outcomes (e.g. training or no training). More recent methodological developments have now been developed which allow for multiple outcomes. These could potentially be used to overcome possible biases arising in the existing matching literature from differences in support (i.e. in the distribution of characteristics of those undertaking different qualifications, which has been shown to bias OLS estimates of the returns to qualifications). See Blundell (2001) for a review of this material.
Professor Richard Blundell gave a presentation on the latest developments in estimating the returns to education including the use of propensity score matching techniques at the Royal Statistical Society in February 2001.
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Evaluation Methodology
Researchers within the CEE have conducted rigorous evaluations of a number of different government policies, including education policies. These include an evaluation of the New Deal programme (Blundell and Van Reenen), the Working Family Tax Credit (Blundell and Meghir) and the evaluation of an income support scheme for secondary students in Australia (Dearden). Members of the team are also currently involved in the quantitative evaluation of the new Education Maintenance Allowance (EMA) for the DfEE (Dearden and Meghir), Excellence in Cities (Machin, Meghir and Conlon) as well as further work on the New Deal (Blundell, Meghir and Van Reenen).
Evaluation methods generally involve finding a suitable control group, which allows one to directly assess the impact of the program by comparing the outcomes of those in the treatment group with similar individuals in the control group. The most robust results are obtained if this control group is chosen using random assignment. If this is not possible, three related alternative approaches are possible: Matching, Differences-in-Differences and Instrumental Variables.
Matching requires having good and detailed data. This can often be quite difficult but in the case of the EMA evaluation, the recently developed propensity score matching techniques has been made use of in an attempt to choose appropriate control areas. To our knowledge, this has not been done before. This ensures, as near as is possible in the absence of randomisation, that the distribution of the observed characteristics in both the control and treatment groups is as similar as possible (the existence of ‘common support’). This turns out to be crucial in ensuring that unbiased policy impact estimates are obtained (see Heckman, Ichimura and Todd (1997)).
An alternative to matching is the second approach, difference-in-differences. This relies on finding a naturally occurring non-experimental control group. Once again this can be problematic, as it requires the control group to satisfy strong assumptions so as to mimic the control group from an experimental design. In Bell, Blundell and Van Reenen (1999), this idea has been developed to allow for differential trends across control and treatment group in the New Deal evaluation. The difference in differences technique has been combined with the propensity score matching technique in the evaluation of the EMA. Finally, if there is a good instrument for the policy variable, then an instrumental variables method may be used. This requires finding an instrument correlated with the policy change but not with any unobservable determinants of the outcome. The difference-in-differences approach to evaluation is related to the instrumental variables concept; both can be used together to improve robustness. Moreover, the ideas behind the matching method can be used in conjunction with both of these techniques (Blundell and Costa-Dias (1999)). Our aim remains to develop a robust and flexible approach to evaluation using these methods and combinations of them, where appropriate.
Multilevel Modelling
Much of the proposed empirical research involves studying systems that have inherently complex structures, including hierarchies and multiple methods of classification. For example, in the area of studying the ‘effectiveness’ of schools, the use of hierarchical data (multilevel) models is now well established as the standard approach to the modelling of
8 institutional differences. In relating school effects to local labour market conditions and locality effects, the data structures become even more complex with parallel hierarchies and cross classifications, for example, of neighbourhoods by schools. Modelling such complex structures is now possible using developments in fitting such statistical models (Goldstein (1995)).
Much of the Centre’s work has involved the integration of data from several sources. These data are often available at different levels of aggregation but also linked such as through area identifications. Work at the Institute of Education on modelling together disparate sources of data has been carried out in the context of ‘meta-analysis’ models with a recent ESRC grant. Modelling together disparate sources has also been the subject of a continuing co-operation with the Office of National Statistics on the merging of survey and Census data. This forms the basis of further exploration of efficient ways of combining different data sources.
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THE PRODUCTION OF EDUCATION AND SKILLS STRAND LEADER: PROFESSOR PETER DOLTON
The Impact of School Inputs on Educational Outcomes
How can we improve the effectiveness of our schools? This question reaches the core of the United Kingdom’s long-term education policy and is a primary focus of the research programme on the economics of education. Our work on these issues has commenced with a comprehensive review of the evidence from the United Kingdom and the United States on the relationship between school resources and student outcomes and has utilised existing high quality reviews of the US evidence wherever possible. This has revealed the primary questions that still need to be addressed. School effectiveness/school improvement literature has grown extensively, and has attempted to explain how and why pupils in some schools achieve greater educational and labour market outcomes than pupils in other, apparently quite similar, schools. The ‘school effect’ is also known to vary over time and for different types of students. There has been a substantial amount of research, both by education experts and economists, which has attempted to identify the key factors that determine school performance (e.g. Burtless (1996), Reynolds et al. (1996)). The results from this literature are quite mixed, depending on the factors being investigated, in terms of the student/school outcomes of interest and the methodology used. On balance, research in the United Kingdom suggests that student outcomes are not necessarily systematically related to the level of educational resources provided. However, this is clearly a research area that merits further attention.
Following our review, the next step has been work on a report commissioned by the Value for Money Unit on ‘An Examination of Different Approaches to Obtaining the Information to Measure the Relationship Between School Resources and Student Outcomes’. Three research approaches have been examined in the report:
1. observational studies using existing, archived data sets, that would estimate relationships between pupil outcomes, resources at school level and control variables; 2. longitudinal studies using data from a specially commissioned survey of a sample of primary or secondary schools in order to estimate relationships between pupil outcomes, resource allocation to and within schools, and control variables; 3. social experiments to examine the impact of resources allocated to specific policy interventions on pupil attainment.
The Report considers the main theoretical and methodological issues. It assesses each approach in terms of the validity of evidence obtained regarding the relationship between school resources and student outcomes.
The report concludes that the three approaches are not alternatives. Instead the research programme should consist of a related set of projects drawn from each approach. Survey
10 studies and social experiments need to utilise existing datasets as much as possible. The Common Pupil Data Base (CPDB), due to be available from 2003, will reduce quite considerably the costs of collecting pupil level data from schools. Until the CPDB is available, studies can use the QCA matched pupil data sets for pupil progress between the different key stage tests. On the resourcing side, the Annual Schools Census data (Form 7) - provided in the LEASIS dataset - gives a range of input measures on staffing, qualifications of teachers, and key stage class size. The Audit Commission’s School Financial Comparison’s dataset contains a range of expenditures on different types of resources for 5000 schools, as well as revenue data. The OFSTED dataset for 1000 schools contains a wide selection of variables on the quality of management and teaching, which can be used for additional testing of factors relating to school effectiveness.
The report recommends that studies utilizing archived datasets should commence as soon as possible. A study combining the YCS dataset, which contains a rich set of variables on student performance and background characteristics, with resource inputs from LEASIS, has already been approved and has commenced.
The report also recommends that a survey study should be commissioned. Only a survey can include important student level background variables and variables on school and classroom processes that a study utilising only archived data would necessarily omit. However, causal effects can most reliably be estimated using social experiments. The increased use by the DFEE of social experimentation in piloting policy initiatives would further improve policy evaluation; it would provide valid estimates of the effects of specific expenditures on specific resources.
In addition to using this data to evaluate the determinants of school effectiveness, we are currently utilising the National Child Development Study to explore this issue. This would build on earlier work by the research partnership that used the NCDS data to look at an array of schooling issues, including the impact of school quality on outcomes.
There have been important changes in the education system that make it important to consider outcomes for younger cohorts. We now have the opportunity to analyse these issues in two distinct ways. First, a new wave of the NCDS has just become available, allowing us to consider the impact of school quality later in life on employment in much greater detail. This will put us in a very strong position to check the age effect found in some US studies on both employment and wages. Secondly, the 1970 British Cohort Survey contains a host of school input information – which is in the process of being coded by the collectors of the data. We will continue to devote resources to code up this information and to link the data with information from the censuses and CIPFA LEA school data. This will allow us to examine whether there have been important changes for these two different cohorts, and in particular the extent to which outcomes have become more or less sensitive to inputs. Combining the results from the 1958 and the 1970 cohorts, and using data from the new 1999 surveys of both these cohorts, should give us robust conclusions on the effect of school inputs on educational attainment and labour market outcomes. This work is clearly important; issues such as lowering student–teacher ratios continue to be high on the policy agenda.
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The Impact of Teachers and Teaching on Educational Outcomes
The relationship between the quality of teaching and the outcomes of pupil and school achievement is difficult to address and obviously requires robust data. No such data exists – hence our main contribution in this area will be to write an international survey of the evidence on performance related pay (PRP) and merit pay for teachers.
This survey examines the international literature on teacher pay and performance in the context of the recent teacher pay and management reforms and of the position of the teacher labour market in the UK. The report summarises the economic theory and application of performance related pay (PRP) to public sector occupations in general and as applied to teaching specifically. It sets the context by describing the present UK market for teachers and includes a commentary on teachers pay over the 1954-2000 period. The econometric methodology for the evaluation of the policy changes relating to the introduction of performance pay is reviewed prior to describing the UK and international evidence relating to the introduction of performance pay.
The Labour Market for Teachers: Teachers’ Salaries, Recruitment and Retention
Recruiting and retaining able and well-trained teachers is central to the provision of high quality state education. Research on teachers should provide a context over time relating to the fluctuations of market demand and supply and detailed evidence on the shortage of teachers in key subject areas and models of teacher recruitment and retention.
The time series pattern of the relationship between teacher salaries, teacher trade union density and concentration, and the supply and demand for teachers can be studied using annual data, over the period 1956-1998 which will extend existing work (see Dolton and Robson, (1996)). The pattern of potential recruitment to teaching can best be examined using the annual HESA surveys of graduate destinations. Using the last two years of this data from 1997 and 1998 we are modelling the decision of graduates to enter teaching, rather than an alternative career. This analysis will permit the recruitment problems in specific subjects to be explicitly studied. Further investigation of teacher shortages in specific subjects might be undertaken by modelling the effect of so-called ‘golden hand-shakes’.
The most recent data to examine the retention and exit from the teaching profession are the HEFCE cohort data and the data from the Database of Teacher Records (DTR). Using the cohort data we can control for the opportunity wage on offer in alternative careers and explicitly allow for the possibility of competing risks associated with exit from teaching to alternative jobs or exit from the labour force for personal and family reasons. These issues are important due to the high proportion of women in the profession. This work will then be compared to similar estimations from earlier cohorts of graduates. (See Dolton (1990), Dolton and Makepeace (1994), and Dolton and van der Klaauw (1999)).
Using the DTR we can more generally model the retention of teachers by subject and geography over the last few years. We can also distinguish the effects of retention policies on mid career professionals and model the differences between male and female teachers.
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FORWARD LOOK
As noted previously, substantial amounts of the work that has been undertaken in Strand 2 has occurred obtaining and converting data into a useable format, which is time consuming. Resulting from the work that has been undertaken, in the coming year we expect to embark on modelling several of the issues that have previously been mentioned particularly producing estimates of the determinants of staying-on using YCS data which incorporates LEASIS school data. Several papers will also be submitted to the CEE discussion paper series on Teacher Pay and Performance which will provide a comprehensive summary of the state of the literature in this area; on the link between educational inputs, as measured by school characteristics; on outputs as measured by pupil performance and labour market outcomes using the YCS cohort data; on teacher recruitment and retention which will focus on relative pay supply elasticity for both recruitment and retention.
Finally, members of the partnership (with the assistance of the ESRC) are holding an international conference on performance related pay for teachers.
CONFERENCE ON TEACHERS’ PAY AND INCENTIVES (UNDER THE AUSPICES OF THE CENTRE FOR ECONOMIC PERFORMANCE)
Date: 25th September 2001 Speakers Professor Edward Lazear, Stanford University Professor Victor Lavy, The Hebrew University, Israel Professor Peter Dolton, CEP, University of Newcastle
Performance Related Pay is currently being introduced for teachers in the UK, amid much controversy and opposition from both teachers and unions alike. Key topics to be researched in this area are whether a successful PRP scheme can realistically be devised for teachers, given the problems in identifying individual teacher contributions to pupil performance, and indeed in measuring pupil performance itself. Secondly, what is the impact of PRP schemes that have been implemented in this country and abroad, in terms of teacher behaviour and pupil outcomes?
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THE SUPPLY OF EDUCATION AND SKILLS STRAND LEADER: DR. ANNA VIGNOLES
The Centre considers the supply of education and skills to be a central issue in the economics of education. To date, the work that the Centre has undertaken has remained underdeveloped due to the initially reduced priority that has been placed on it in discussions with the Department for Education and Employment. However, the Centre is commencing research in this area in the immediate future. An outline of some of the issues on the research agenda is presented in the following section.
The Determinants of Staying On
Over the last few years, the rapid rise in the rate of post-16 education participation of the late 1980s and early 1990s appears to have slowed. This is contrary to government targets. It may reflect either a flattening of the long-term trend or simply the cyclical response to an increased availability of jobs for relatively unskilled young people in a buoyant economy. At present, we are not in a position to discriminate between these hypotheses since an important time series investigation into “staying-on” (Pissarides (1982)) is very dated and could not be reliably extrapolated into the 1990’s (for other time series work see Whitfield and Wilson (1991) and McIntosh (1998)).
We intend to extend Pissarides’ analysis, both in time and by using data at the regional level. This will enable us to use a great deal more information to evaluate the factors influencing individuals’ decisions to stay on in full-time education, essentially because both patterns of staying–on and the business cycle are not that highly correlated across regions.
Factors Influencing Educational Choices
Young people beyond the age of 16 make year-by-year choices (if not month by month) on whether to continue in education or to start working. Understanding the nature of this choice is central to policies aimed at increasing the level of education undertaken by individuals. The work under this heading would involve estimating a Cameron and Heckman (1998) model of educational choice. The key issues are:
1. The extent to which these choices are affected by current labour market conditions and job opportunities. 2. The extent to which they depend on the quality of schooling currently available. 3. The extent to which expectations matter. 4. The extent to which financial difficulties (liquidity constraints) are an important factor.
We intend to use a number of data sources to deal with these issues. The first two data sets, the Youth Cohort Studies and the BHPS, actually survey the individuals as the transitions are taking place. The YCS first commenced in 1985 and the information available in the survey
14 explicitly allows us to model year to year educational and work transitions between the ages of 16 and 19 using contemporaneous information on the person’s circumstances (which is generally not available). Moreover, this data will allow us to identify how these transitions have changed over the late 1980s and early 1990s and if policy changes (such as changes in income support arrangements for 16 to 18 year olds in 1988 and HB changes in the early 1990s) have affected these transitions. We may also be able to use, subject to adequate sample size, the British Household Panel Survey (BHPS), which also allows us to observe transitions from education to work for children of sampled households. The advantage the BHPS has over the YCS is the availability of family income measures. The longitudinal aspect of this work and the link between children and parents will allow us to measure the impact of income and unanticipated (or anticipated) changes of income on educational participation. Hence the projects in this area will start by describing the transitions as a function of family background and economic circumstances.
We intend to look at this issue using both the NCDS and BCS70 panel data surveys. In NCDS/BCS70 we would include parental income at age 16 and early ability test scores to address whether it is children from poor households or low ability children that leave early. In regular cross sections we know the ages of other individuals in the household and when they left school and if they are still at school - and we observe household income. Thus we could estimate a model that allows for the censoring in the data; this is essential, as some children have not yet completed their schooling.
We then intend to interpret the evidence from these data sets using structural economic models and carry out policy simulations for different policy options. For example, the work would play a useful supporting role in the EMA evaluation, as the models will allow us to estimate the impact of additional income on education decisions. The work would also provide a contribution to the Bell curve debate.
Lifelong Learning
Lifelong learning is seen as the key to long-term economic success, both for the individual and for Britain as a whole (DfEE (1998)). This view reflects a belief that the demand for skills will continue to rise, partly as a result of continuing skill biased technological change (Machin and Van Reenen (1998), Machin, Harkness and McIntosh (2001)). It is certainly the case that many individuals do not take advantage of our education system first time round but want to/need to return to learning later in life. It is also well known that the least educated in society earn less, and are more likely to experience unemployment. Lifelong learning is one way that individuals can potentially improve their labour market prospects, and will arguably be of increasing importance because of the large reduction in the number of unskilled jobs available. Lifelong learning is also an important issue because it has implications for income inequality. For example, Layard et al. (1995) found that, although there has been an increase in job specific training among adults, much of this is provided by firms to workers who are already more educated. More recent work for the European Commission (summarised in Green, Wolf and Leney (1999)) confirms this to be a general pattern among European states. Thus firm provided adult learning/training might tend to reinforce inequalities arising from differences in initial education levels. This provides support for the view that the state should be involved in facilitating and funding lifelong learning, particularly for individuals who lack basic skills.
15 Yet there is remarkably little empirical evidence on the extent or effects of lifelong learning. There has been work on the returns to work related training (Blundell et al. (1999)) and on the returns to lifelong learning in the United States (Cohn and Addison (1997)). However, in the area of general adult education and training, even descriptive statistics for the United Kingdom are often lacking. This project will attempt to evaluate the labour market effects of lifelong learning, building on the investigation of the extent of adult learning described earlier and using the NCDS panel data in particular (where we now have data covering experience up to age 42). However, it is very likely that further data collection will be needed. We would wish to start by investigating the precise nature of available and planned data sources with the DfEE. Certainly the Centre, in partnership with the proposed Centre on the Wider Benefits of Learning, needs to ensure that work to evaluate the determinants and effects of lifelong learning is a top priority.
In policy terms, this project aims to evaluate whether lifelong learning is a good investment for individuals, and also to provide indications as to how policymakers can facilitate additional lifelong learning. The following specific questions are important. Does lifelong learning improve students’ productivity levels, increase their chances of getting and keeping a job (i.e. avoiding redundancy/unemployment) and raise their earnings? In particular, what types of lifelong learning have the biggest impact on the labour market success of mature students? For example, does vocationally orientated learning later in life have a higher economic return than more academic learning? If there is evidence that lifelong learning is a good investment, what are the key barriers that prevent individuals from returning to education? Clearly the risk of the investment may be one factor that prevents students from investing in lifelong learning. However, there may be other institutional barriers, such as the differential funding arrangements for full- and part-time study. Identifying such barriers is obviously of great importance to policymakers.
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THE DEMAND FOR EDUCATION AND SKILLS STRAND LEADER: PROFESSOR ALISON WOLF Rates of return analysis can provide both systematic and wide-ranging data on what types of education and skills are valued in the labour market but there are important limitations to its conclusions. It is very difficult to estimate genuine social (as opposed to individual) rates of return, especially to particular skills and knowledge because of the way in which employers use qualifications as general screening devices, and because of the interrelations between educational attainment and other factors (including innate ability). The other commonly used approach to identify the skills that are “needed” or in demand is the employer survey but this also suffers from major limitations (not least the disjunction between employer responses and measured employer behaviour). We will therefore be examining the economic demand for education and skills through a number of projects which complement rate of return analysis and employer surveys, but use quite different methodologies, and focus in greater depth on particular sectors of the economy.
What Business is Really Rewarding: An Investigation of Firms’ Selection and Testing Practices as Indicators of Market Demand
From the advent of publicly funded national education systems, governments have been trying to relate the nature and content of education to industrial requirements. As a growing body of detailed economic history and policy analysis makes clear, there has also been a consistent separation between what informants tell public policy-makers and the reality of industrial and commercial practice. Through much of this century, the FBI (later CBI), along with myriad witnesses to a whole procession of governmental commissions, emphasised the need for government to provide more formal technical education, more highly qualified technicians, and more industrially relevant degrees. Meanwhile United Kingdom employers have continued to concentrate their expenditures on initial training on familiar on-the-job routes. They have shown little inclination to hire, or greatly reward, large numbers of qualified technicians, or highly specialised graduates from “industrially-related” disciplines (see e.g. Sanderson 1999).
More recently, training activity by UK employers has greatly increased in volume (although the average length of training events has fallen). However, we continue to find a marked disparity between, on the one hand, industry’s “needs” and views (as articulated by employer organisations or through surveys and polls) and actual commercial practice in the areas of hiring, promotion and pay. Examples include surveys in which employers repeatedly fail to report any major requirements for mathematics skills, even though a very large wage premium is actually paid to those with higher level mathematics qualifications (SCAA (1996); Dolton and Vignoles (1999 and 2000)); or the repeated tendency of employer organisations, and senior industrialists from blue-chip companies to decry the value of traditional academic qualifications as compared to vocational courses and “key skills”, even
17 though employment and income evidence indicate that it is traditional academic qualifications which are being used in recruitment and rewarded in practice (see e.g. Desai (ed) (1999); Bynner et al. (1997)).
We are therefore examining alternative/additional sources of evidence on which skills employers genuinely value and reward, and in particular by looking at which skills they are actually willing to pay money to measure and detect. Over the last two decades there has been a huge increase in the use of psychometric testing, skill centres and other measurement- based selection and promotion procedures (Boyle (1993); Newell and Shackleton (1993); Jenkins (forthcoming)). These involve decisions by companies about what are important skills and capacities but are not already conveyed through a Curriculum Vitae or prior qualifications etc. Moreover, extensive testing by companies has now been widespread for long enough that it reflects extensive prior experience with its outcomes, which in turn feeds back into practice.
Direct examination of testing for recruitment and promotion can provide access to a far more in-depth analysis of responses to skill needs than can be obtained from survey research. It also allows for a more broad-based sample of industrial and commercial behaviour than can be obtained from interviews with NTO/RDA personnel and the like. The latter inevitably over-represent large companies and those with motivated, publicly oriented Human Resource departments familiar with current policy language. Decisions that involve up-front expenditure by companies will, in contrast, reflect decisions and discussions phrased in the working vocabulary of the company and justified in relation to its central priorities. They will also be the product, in most cases, of many rather than single individuals.
Surprisingly little is known about current practice, other than at an anecdotal and general level. This is regrettable, given the obvious relevance of findings to the school curriculum and to elucidating relationships between different skills, and individual and company success. The project involves, in the first instance, a substantive effort to collect primary descriptive data. While companies are not generally (for obvious reasons) pro-active in sharing information about their individual practices, this is not a research area where we have experienced any major data collection problems (not least because of the obvious relevance of the outcomes to any participating company). Some of the initial findings relating to this research theme are available in CEE Discussion Paper 12.
FORWARD LOOK
Data collection on the research project on firms’ testing and recruitment practices will shortly be complete, with the exception of secondary analysis of validation data from a major testing company, where we may not have full access to the relevant data until the summer. We shall be making a report to the DfEE in the early summer, and expect to present key findings to a seminar in September involving interested policymakers and practitioners, including the Employment Service. We are also making a presentation to a Chartered Institute of Personnel and Development conference in June, with particular reference to those parts of the data that we are collecting in collaboration with CIPD. We envisage submitting a further paper to the CEE discussion paper series by the summer (in addition to the completed Discussion Paper 12 which draws on this work): another will follow in the autumn if and when the analysis of the validation data bears fruit.
18 A related source of evidence on demand for skills, which we believe is also under-utilised, is the detailed content of companies’ training programmes. Although we have time-series data on the volume and length of training, there is remarkably little information available on the content of company-supported training.
Some new information of relevance to this strand will be available in spring 2002 from a project just awarded to the Institute of Education and directed by Professor Wolf and Professor Hoyles (Professor of Mathematics Education and current chair of the UK Joint Mathematics Council). This will examine the demand for specific levels of mathematical skills in a sample of industries and sectors, and is funded by a consortium of all nine RDAs along with the Science, Technology and Mathematics Council (the NTO for this sector).
19
THE RETURNS TO EDUCATION AND SKILLS STRAND LEADER: DR LORRAINE DEARDEN The issues addressed by these projects are of crucial importance to students, parents and policy-makers alike. The purpose of this phase of the research programme is to adapt and develop rigorous methodologies to measure the economic return on investments in education. The methodological work informs other parts of the research programme that relate to the evaluation of the cost effectiveness of different types of educational interventions.
The Returns to Education
Whilst both the Institute of Fiscal Studies and the Centre for Economic Performance have carried out much work on the economic returns to some academic qualifications, particularly degrees, more work needs to be done, particularly on the returns to vocational qualifications and those obtained specifically in Further Education. The UK data sets we have made use of include the Labour Force Survey, the British Household Panel Survey, the General Household Survey, the National Child Development Study and the British Cohort Study (1970). With regard to the last two data sets, this new work will use information from the 1999 surveys of the NCDS and BCS70 cohorts, which would be used to update our earlier research using these data sets. This data has only recently become available but is not yet in usable format. The Centre has produced an extensive report estimating the returns to academic and vocational qualification in the UK (Skills Task Force Research Paper 27 and CEE Discussion Paper 4). The key findings are as follows:
• The additional returns associated with academic qualifications, taking no account of the time taken to acquire such qualifications, are typically higher than those associated with vocational qualifications at the same level. • When consideration is given to the time required to obtain the various qualifications, the returns per year of study for vocational qualifications move closer on average to those accruing to academic qualifications, although the extent of the variation in the former is higher. • Gender differences exist. With respect to academic qualifications, women tend to earn a higher return than men do, particularly to degrees. For vocational qualifications, men and women earn their highest returns with different types of qualifications. The vocational qualifications with the highest returns for men are HNC/HNDs, ONC/ONDs and higher level City and Guilds qualifications. For women, the vocational qualifications with the highest returns are teaching and nursing qualifications. • The estimated returns to qualifications using the NCDS data set are consistently smaller than results obtained using IALS or LFS data. Since the NCDS equations are the only specifications that control for ability at an early age, this suggests that estimates that do not control for ability may be upwardly biased. On the other hand, once we take into account ability bias and measurement error bias in the NCDS equations, the results are similar to those derived using the other two data sets, suggesting that estimates that only
20 control for employer characteristics, region and gender (as with the LFS) appear to be reasonable estimates of the true returns.
The Effects of Literacy and Numeracy on Wages and Employment – A National Study
Using longitudinal data from the 1970 British Cohort Study, we are investigating issues relating to the formation of basic skills, particularly the effects of early childhood experiences on later adult skill levels. We are also investigating the impact of current (adult) skill levels on various labour market outcomes, such as earnings, unemployment and occupation. This work builds on work already completed by the Centre for Economic Performance on this issue, and work currently being funded by the DfEE using the NCDS data. It also addresses issues relating to the effect of basic literacy and numeracy on lifetime chances, initially raised by Bynner and Parsons’ work with these data sets (Bynner and Parsons (1998)), (DfEE Research Report 192 and CEE Discussion Paper 3).
• Currently around 80% of UK adults have achieved Level 1 literacy skills, and 60% Level 1 in numeracy (British Skills Agency Standard). DfEE (1999) suggested a target of 90% and 70% respectively by 2010. • This report evaluates the impact of better literacy and numeracy skills on individuals’ economic outcomes, focusing particularly on the effect of increasing numeracy and literacy skills up to Level 1. • We found evidence of a large positive effect on earnings and employment rates from having better numeracy skills, specifically from achieving at least Level 1 skills, although there was also evidence of a large premium from acquiring just Entry Level numeracy skills. • Not taking into account other factors that influence earnings, individuals with Level 1 numeracy skills earn around 15-19% more than those with skills below this level. Even after allowing for an independent effect from the worker’s education/qualification level, and after controlling for family background, workers with Level 1 numeracy skills earn around 6-7% more than their less skilled peers. We also use NCDS data to control for initial ability in reading and mathematics at age 7, ability at 16 and education level, thus giving an approximate estimate of the effect of moving an adult up the numeracy distribution. The results still suggest that, for a given level of numeracy and literacy at 16, improving an adult’s numeracy skills to Level 1 will raise their earnings by 6%. • Individuals with Level 1 numeracy skills are around five percentage points more likely to be employed (not taking into account other factors). Even in the full model that conditions for a person’s education level, Level 1 numeracy skills are still associated with having a 2-3-percentage point higher probability of being in employment. • There was also evidence of a positive relationship between literacy and economic outcomes, although the results from the two data sets used in this chapter differ substantially. IALS data indicate that the effect of literacy skills on both earnings and employment is of a similar magnitude to the numeracy effect and may, in the case of the effect on employment rates, be larger than the numeracy effect. • With no controls, Level 1 literacy is associated with having 15% higher earnings (similar to the numeracy effect). Once other variables are added to the model the effect from Level 1 literacy is reduced to 1-3% in the NCDS but is still a sizeable 11% in IALS.
21 APPENDIX A
CENTRE FOR THE ECONOMICS OF EDUCATION STAFF LIST
Professor Stephen Machin (UCL/CEP) Director Dr. Gavan Conlon (CEP) Centre Co-ordinator
Professor Costas Meghir (UCL/IFS) Leader Strand 1 Professor Peter Dolton (CEP/IoE/Newcastle University) Leader Strand 2 Dr. Anna Vignoles (CEP) Leader Strand 3 Professor Alison Wolf (IoE) Leader Strand 4 Dr. Lorraine Dearden (IFS) Leader Strand 5
Ms Joanne Blanden (CEP) Strand 3 Professor Richard Blundell (UCL/IFS) Strand 1 and 5 Dr Arnaud Chevalier (CEP) Strand 2 Mr Damon Clark (CEP) Strand 3 Dr. Leon Feinstein (CEP) Strand 2 Professor Harvey Goldstein (IoE) Strand 1 Ms. Kirstine Hansen (CEP) Strand 3 Dr. Jonathan Haskel (QMW/CEPR/IFS) Strand 5 Dr Andrew Jenkins (IoE) Strand 3 and 4 Dr. Rosalind Levacic (IoE) Strand 2 Dr. Steven McIntosh (CEP) Strands 2 and 3 Professor Stephen Nickell (CEP) Strands 1 and 3 Dr Howard Reed (IFS) Strand 4 Dr Hilary Steedman (CEP) Strand 3 Professor John Van Reenen (IFS) Strands 1 and 5 Professor Ian Walker (IFS) Strand 5 Professor Gareth Williams (IoE) Strand 5 Ms. Theodora Xenogiani (CEP) Strand 2 and 3 Dr Yu Zhu (Warwick) Strand 5
22 APPENDIX B
CENTRE FOR THE ECONOMICS OF EDUCATION: SELECTED PUBLICATIONS Professor Richard Blundell [1]“The Labour Market Impact of the Working Families' Tax Credit, Fiscal-Studies, 21(1), March 2000, pages 75-103. [2]“Comments on James Heckman's "Policies to Foster Human Capital", Research in Economics; 54(1), March 2000, pages 57-60. [3]“The Returns to Higher Education in Britain: Evidence from a British Cohort”, Economic Journal; 110(461), February 2000, pages F82-99. [4]“Latent Separability: Grouping Goods without Weak Separability”, (with Jean Marc Robin), Econometrica; 68(1), January 2000, pages 53-84.
Dr Arnaud Chevalier [5]“Graduate Over-Education in the UK”, CEE Discussion Paper No. 7, Nov. 2000. [6]“Financial transfers and educational achievement” CEE Discussion Paper No. 8, forthcoming, (with G. Lanot).
Dr. Gavan Conlon [7]“Initial Training Policies and Transferability of Skills in Britain and Spain”, January 2001, Institute Juan March Working Paper No. 162, with Cruz Castro, L. [8]“The Differential in the Rate of Return to Academic and Vocational Qualifications in the United Kingdom”, CEE Discussion Paper No. 11, forthcoming. [9]“One in Three: The Incidence and Outcomes of Lifelong Learners in the United Kingdom”, CEE Discussion Paper No. 13, forthcoming.
Dr. Lorraine Dearden [10]“The Effects of Families and Ability on Men's Education and Earnings in Britain” Labour- Economics; 6(4), November 1999, pages 551-567. [11]“The Returns to Academic and Vocational Qualifications in Britain” CEE Discussion Paper No. 4, November 2000, (with Michal Myck Steven McIntosh and Anna Vignoles). [12]“The Returns to Academic Vocational and Basic Skills in Britain”, June 2000, Research Report 192, Department of Education and Employment. [13]“The Effects of School Quality on Educational Attainment and Wages”, (2000) IFS Discussion Paper W00/22, (with C. Meghir and J. Ferri).
Professor Peter Dolton [14]“The Incidence and Effects of Overeducation in the U.K. Graduate Labour Market”, Economics of Education Review; 19(2), April 2000, pages 179-198, (with Anna Vignoles). [15]“The Return to Post Compulsory School Mathematics Study” Economica (with Anna Vignoles), forthcoming. [16]“The Long-Run Effects of Unemployment Monitoring and Work Search Programs: Experimental Evidence from the UK”, Journal of Labor Economics (with D. O’Neill). [17]“The Effective Use of Student Time: A Stochastic Frontier Production Function Case Study”, CEE Discussion Paper No. 10, forthcoming (with Oscar D. Marcenaro and Lucia Navarro).
23 [18]“Over-Education in the Graduate Labour Market: Some Evidence from Alumni Data”, CEE Discussion Paper No. 9, forthcoming (with Mary Silles). [19] “Overeducation: Problem or Not?” in Changing Relationships Between Higher Education and the State, (1999) M.Menkel and B.Little (eds), London 1999 (with A. Vignoles). [20] “The Pay-Off to Mathematics A-level” in The Maths We Need Now: Demands, Deficits and Remedies, A.Wolf and C.Tikly (eds) Institute of Education, London 2000 (with A. Vignoles). [21] “The Effects of School Quality on Pupil Outcomes: An Overview” in Education, Training and Employment in the Knowledge Based Economy, H.Meijke (ed), Macmillan 2000 (with A. Vignoles).
Professor Harvey Goldstein [22]“Multilevel Models for Repeated Binary Outcomes: Attitudes and Voting over the Electoral Cycle”, Journal of the Royal Statistical Society, Series A; 163(1), 2000, pages 49-62 (with Min Yang and Anthony Heath). [23] “An Analysis of International Comparisons of Adult Literacy” Assessment in Education, Vol 8 no 2 (July 2001), in press. (with Blum, A., & Guérin-Pace, F[m5].)
Dr. Jonathan Haskel [24]“Trade and Labor Approaches to Wage Inequality”, Review of International Economics, 8(3), August 2000, pages 397-408. [25]“A Bargaining Model of Farrell Inefficiency”, International Journal of Industrial Organization; 18(4), May 2000, pages 539-56 (with Sanchis Amparo) [26]“Unemployment in the OECD and Its Remedies: Discussion”, in Dennis J Snower and Guillermo de la Dehesa, eds. Unemployment Policy: Government Options for the Labour Market. Cambridge University Press, 1997, pages 534-541.
Dr. Andrew Jenkins [27]“Companies' Use of Psychometric Testing and the Changing Demand for Skills: A Review of the Literature”, CEE Discussion Paper No. 12, forthcoming.
Professor Rosalind Levacic [28]“The Relationship Between Resource Allocation and Pupil Attainment: A Review”, CEE Discussion Paper No. 2, September 2000, (with Anna Vignoles, James Walker, Stephen Machin and David Reynolds).
Professor Stephen Machin [29]“UK Economics and the Future Supply of Academic Economists”, Economic-Journal; 110(464), June 2000, pages F334-349. (with Andrew Oswald). [30]“Another Nail in the Coffin? Or Can the Trade Based Explanation of Changing Skill Structures Be Resurrected?” Scandinavian-Journal-of-Economics; 101(4), December 1999, pages 533-554 (with Thibaut Desjonqueres and John Van-Reenen). [31] ‘The Changing Distribution of Male Wages, 1966-92”, (2000), Review of Economic Studies (with A. Gosling and C. Meghir). [32]‘Poor Kids: Child Poverty in Britain, 1966-96', Fiscal Studies (1999) (with P. Gregg and S. Harkness). [33]The Effects of Minimum Wages on Employment: Theory and Evidence From Britain', Journal of Labor Economics, (1999) (with R. Dickens and A. Manning). [34]'The Causes and Consequences of Long-Term Unemployment in Europe', (1999) in O. Ashenfleter and D. Card (eds.) Handbook of Labor Economics, North Holland (with A. Manning). [35]'Childhood Disadvantage and Success or Failure in the Labour Market', (1999) in D. Blanchflower and R. Freeman (eds.) Youth Employment and Joblessness in Advanced Countries, National Bureau of Economic Research, Cambridge, MA (with P. Gregg). [28]“The Relationship Between Resource Allocation and Pupil Attainment: A Review”, CEE Discussion Paper No. 2, September 2000, (with Anna Vignoles, James Walker, Rosalind Levacic and David Reynolds).
24 [36] “Crime and Economic Incentives” IFS Discussion Paper W00/17 (with C. Meghir).
Dr. Steven McIntosh [37]“Measuring and Assessing the Impact of Basic Skills on Labour Market Outcomes”, CEE Discussion Paper No. 3, November 2000, (with Anna Vignoles). [11]“The Returns to Academic and Vocational Qualifications in Britain” CEE Discussion Paper No. 4, November 2000, (with Lorraine Dearden, Michal Myck and Anna Vignoles).
Professor Costas Meghir [38]“Moment Conditions for Dynamic Panel Data Models with Multiplicative Individual Effects in the Conditional Variance”, Annales-d'Economie -et-de -Statistique , 0(55-56), Sept.-Dec. 1999, pages 317-330, (with Frank Windmeijer). [31] “The Changing Distribution of Male Wages, 1966-92”, (2000), Review of Economic Studies (with A. Gosling and S. Machin). [1]“The Labour Market Impact of the Working Families' Tax credit”, (2000) Fiscal Studies, vol 21 pp 75-104, (with Blundell, Duncan and McCrae) [36]“Crime and Economic Incentives”, IFS Discussion Paper W00/17 (with Stephen Machin). [39]“Wages Experience and Seniority”, January 2001, IFS working paper 01/01, January 2001 (with Christain Dustmann). [13]“The Effects of School Quality on Educational Attainment and Wages”, (2000) IFS Discussion Paper W00/22, (with L. Dearden and J. Ferri).
Professor Stephen Nickell [40]“The Netherlands and the United Kingdom: A European Unemployment Miracle? Economic Policy: A European Forum, 0(30), April 2000, pages 135-175 (with Jan van Ours).
Professor John Van Reenen [41]“How Effective Are Fiscal Incentives for R&D? A Review of the Evidence”, Research Policy, 29(4-5), April 2000, pages 449-469 (with Bronwyn Hall). [42]“The Returns to Education: A Review of the Macro-Economic Literature”, CEE Discussion Paper No. 7, December 2000, (with Barbara Sianesi). [30]“Another Nail in the Coffin? Or Can the Trade Based Explanation of Changing Skill Structures Be Resurrected?” Scandinavian-Journal-of-Economics; 101(4), December 1999, pages 533-554 (with Thibaut Desjonqueres and Stephen Machin).
Dr Anna Vignoles: [43]“An Audit of the Data Needs of the DfEE Centres for the Economics of Education and the Wider Benefits of Learning”, CEE Discussion Paper No. 1, November 2000, (with Tanvi Desai and Estela Montado). [28]“The Relationship Between Resource Allocation and Pupil Attainment: A Review”, CEE Discussion Paper No. 2, September 2000, (with Rosalind Levacic, James Walker, Stephen Machin and David Reynolds). [37]“Measuring and Assessing the Impact of Basic Skills on Labour Market Outcomes”, CEE Discussion Paper No. 3, November 2000, (with Steven McIntosh). [11]“The Returns to Academic and Vocational Qualifications in Britain” CEE Discussion Paper No. 4, November 2000, (with Lorraine Dearden, Steven McIntosh, Michal Myck). [44]“Basic Skills, Soft Skills and Labour Market Outcomes: Secondary Analysis of the NCDS”, January 2001, Research Report 250, Department of Education and Employment. [45]“Basic Skills, Soft Skills and Labour Market Outcomes: Secondary Analysis of the NCDS”, January 2001, Research Brief 250, Department of Education and Employment. [46]“The Incidence and Effects of Overeducation in the U.K. Graduate Labour Market”, Economics of Education Review; 19(2), April 2000, pages 179-198. [15]“The Return to Post Compulsory School Mathematics Study” Economica (with Peter Dolton), forthcoming.
25 [19] “Overeducation: Problem or Not?” in Changing Relationships Between Higher Education and the State, (1999) M.Menkel and B.Little (eds), London 1999 (with P. Dolton). [20] “The Pay-Off to Mathematics A-level” in The Maths We Need Now: Demands, Deficits and Remedies, A.Wolf and C.Tikly (eds) Institute of Education, London 2000 (with P. Dolton). [21] “The Effects of School Quality on Pupil Outcomes: An Overview” in Education, Training and Employment in the Knowledge Based Economy, H.Meijke (ed), Macmillan 2000 (with P. Dolton).
Professor Ian Walker [47]"The Returns to the Quantity and Quality of Education: Evidence for Men in England and Wales" Economica, 67, pages 19-35, 2000 (with C Harmon). [48]“The Returns to Education: A Review of Evidence, Issues and Deficiencies in the Literature”, CEE Discussion Paper No. 6, December 2000 (with Colm Harmon, Hessel Oosterbeek). [49]"Sheepskin Effects in Hours and Wages" Dartmouth Working Paper 12, Sept 2000 (with P Trostel).
Professor Alison Wolf [50] “Mathematics for Some or Mathematics for All? Curious UK Practices in International Context.” In C. Tikly and A. Wolf (eds) The Maths We Need Now: Demands, Deficits and Remedies, London: Institute of Education: 2000. Pages 104-137. [51] “A Comparative Perspective on Educational Standards”. In Goldstein, H. and Heath, A. Educational Standards. Proceedings of the British Academy 102. Oxford: Oxford University Press for The British Academy. 2000. Pages 9-38. [52] “Qualifications and Assessment” in Richard Aldrich (ed) A Century of Education, Routledge: 2001 forthcoming. [53] “Special issue of Assessment in Education: High stakes examinations and Higher Education”, vol. 8, no. 3, (with Stephen Bakker (eds.)) forthcoming.
26 APPENDIX C
CEE SEMINAR SERIES
28th January 2000 Professor Ian Walker, University of Warwick, "Gross and Net Returns to Education" joint with A. Chevalier
11th February 2000 Professor Rosalind Levacic, Centre for Education Policy & Management, Open University, "Allocating Resources to and Within Schools: How Can the CEE Contribute to Evidence Informed Policy and Practice?"
25th February 2000 Professor David Autor, MIT, "Why Do Temporary Help Firms Provide Free General Skills Training?"
10th March 2000 Professor Carol Propper, University of Bristol “GP Fundholders and Waiting Times”
22nd May 2000 The Great Education Debate “Schools: Does More Mean Less?” (In association with the Times Education Supplement) Professor Eric Hanushek, Princeton University Professor Caroline Hoxby, Harvard University
26th May 2000 Professor David Reynolds, Loughborough University "Contemporary Education Policies, the Green Paper and the Next Wave of Educational reform - an insider account"
9th June 2000 Professor Richard Berthoud "Parents and Employment: Will Working Families Tax Credit Make Much Difference?"
23rd June 2000 Professor Costas Meghir, UCL and IFS "Assessing the Returns to Schooling Using a Social Experiment
7th July 2000 Dr. Arnaud Chevalier CEE, “Overeducation in the British Graduate Labour Market
6th October 2000 Professor Ian Walker, University of Warwick, “School Leaving, Parental Background and Parental Incomes’
27 27th October 2000 Dr Jonathan Haskel, Queen Mary and Westfield, London, “Estimating Returns to Education Using UK Twin Data”
24th November 2000 Professor Harvey Goldstein, Institute of Education “Value Added Work Using National Data on GCSE and A-Level Scores/Types of School”
19th January 2001 David Armstrong, PCW Belfast. "Building Performance: an Empirical Assessment of the Relationship Between School Investment and Pupil Performance"
2nd February 2001 Professor Caroline Hoxby, Harvard University “Peer Effects in the Classroom”
16th February 2001 Dr Lex Borghans, Research Centre for Education and the Labour Market, Maastricht University. "Do We Need Computer Skills to Use a Computer? Evidence from the UK"
2nd March 2001 Dr Lorraine Dearden, Institute of Fiscal Studies. "The Impact of the Education Maintenance Allowance (EMA) on Post- Compulsory Education Participation"
16th March 2001 Professor David Mayston, University of York. “Modelling the Impact of Resources on Educational Outcomes"
4th May 2001 Dr Colm Harmon, University College Dublin “Migration Decision, Religious Background and the Returns to Schooling – Evidence from Northern Ireland”
1st June 2001 Dr. John Micklewright, UNICEF Innocenti Research Centre, Florence "In what OECD countries is learning achievement most unequal?"
15th June 2001 Dr Rosa Fernandez, SKOPE, University of Oxford "The Opportunity Cost of Education in the Presence of Unemployment: Application to University Enrolment in Spain"
29th June 2001 Professor Larry Kenny, University of Florida "Effect of Teacher Salary Incentives on Student Performance."
28 APPENDIX D
CEE DISCUSSION PAPER SERIES
Discussion Paper No. 1: “An Audit of the Data Needs of the DfEE Centres for the Economics of Education and the Wider Benefits of Learning” Anna Vignoles with assistance from Tanvi Desai and Estela Montado
Discussion Paper No. 2: “The Relationship Between Resource Allocation and Pupil Attainment: A Review” Anna Vignoles, Rosalind Levacic, James Walker, Stephen Machin and David Reynolds
Discussion Paper No. 3: “Measuring and Assessing the Impact of Basic Skills on Labour Market Outcomes” Steven McIntosh and Anna Vignoles
Discussion Paper No. 4: “The Returns to Academic and Vocational Qualifications in Britain” Lorraine Dearden, Steven McIntosh, Michal Myck and Anna Vignoles
Discussion Paper No. 5: “The Returns to Education: A Review of Evidence, Issues and Deficiencies in the Literature” Colm Harmon, Hessel Oosterbeek and Ian Walker
Discussion Paper No. 6: “The Returns to Education: A Review of the Macro-Economic Literature” Barbara Sianesi and John Van Reenen
29 Discussion Paper No. 7: “Graduate Over-Education in the UK” Arnaud Chevalier
Discussion Paper No. 8: “Financial Transfers and Educational Achievement” Arnaud Chevalier and Gauthier Lanot
Discussion Paper No. 9: "Over-Education in the Graduate Labour Market: Some Evidence from Alumni Data" Peter Dolton and Mary Silles
Discussion Paper No. 10: "The Effective Use of Student Time: A Stochastic Frontier Production Function Case Study" Peter Dolton, Oscar D. Marcenaro, Lucia Navarro
Discussion Paper No. 11: “The Differential in Earnings Premia between Academically and Vocationally Trained Males in the United Kingdom" Gavan Conlon
Discussion Paper No. 12: “Companies use of Psychometric Testing and the changing demand for skills: A Review of the Literature” Andrew Jenkins
Discussion Paper No. 13: “The Outcomes associated with the Late Attainment of Qualifications in the United Kingdom” Gavan Conlon
30 APPENDIX E
FORTHCOMING EVENTS - SEMINARS
EDUCATIONAL CHOICE
Speakers: Professor Bob Gregory, Australian National University, Canberra Professor Costas Meghir, University College London and IFS
A key strand of the UK government’s educational policy is to increase participation in education beyond the age of 16 where compulsory education ends. The participation decision is a rational choice made by individuals, and it is therefore of prime importance to identify the factors that influence such decisions. To the extent that some of the factors fall within the control of government, such as the minimum wage, social welfare payments, the quality of education provision and the availability of funding, this identification of factors affecting the choice at 16 should influence the policy debate on how to further increase the UK’s education participation rate.
RATES OF RETURN TO EDUCATION
Speakers: Professor David Card, University of California, Berkeley Professor Ian Walker, University of Warwick and IFS
One key determinant of individuals’ educational choices is the rate of return they can expect to earn on their investment in human capital, in terms of higher wages. Thus, it is vital that reliable estimates of the rates of return to possible educational choices and routes of qualification attainment are in the public domain and can inform this decision-making process. Although this topic has already attracted a large literature on both sides of the Atlantic, consensus has yet to be reached on issues such as individual heterogeneity, biases resulting from omitted ability measures, and the costs to individuals and society of undertaking specific qualifications (say). As a result, accurate private and social rates of return remain problematic to estimate.
SCHOOL EFFECTIVENESS
Speakers: Professor Richard Murnane, Harvard University Professor Harvey Goldstein, Institute of Education
Clearly some pupils perform better than others, in terms of their educational and labour market outcomes, but what are the factors that affect these differences? The key issue for public policy is, after controlling for individual pupil effects such as natural ability, how much can schools affect performance, and by what routes. Key factors to be studied include funding and resources, class size and teacher quality. While there is already a substantial literature in this area, many studies find the effects of schooling variables insignificant in determining pupil performance. Do we really believe that such variables do not affect pupil performance at all, or will better quality data enable us to identify significant relationships? This seminar will provide some of the answers, indicating cost effective ways to improve school effectiveness and revealing new techniques for unravelling the relationships involved
Organiser: Dr. Gavan Conlon
31
FORTHCOMING EVENTS – CONFERENCES
AMERICAN ECONOMIC ASSOCIATION, JANUARY 4,5,6, 2002, ATLANTA, GEORGIA
“REFORMING SCHOOLS”
CHAIR: ORLEY ASHENFELTER (PRINCETON UNIVERSITY)
Papers
Professor Costas Meghir (UCL and IFS), “The impact of the Education Maintenance Allowance on School Staying on Rates for 16 year olds in the United Kingdom”
Dr. Arnaud Chevalier (CEE), Prof. Peter Dolton (University of Newcastle and CEE) and Dr. Steve McInstosh (CEE), “Teacher Recruitment and Retention In the UK”
Professor Alan Krueger (Princeton University), “Evaluating the Reform of American Schools”
Professor Stephen Machin (UCL and CEE), “Changes in Educational Wage Differentials in the United Kingdom; Supply Changes and the Evolution of Wage Differentials by Sex and Subject of Study”
Discussants:
Professor Caroline Hoxby (Harvard University) Professor John Heywood (University of Wisconsin-Milwaukee) Professor Daron Acemoglu (MIT) Professor Eli Berman (Boston University)
Organiser: Dr. Arnaud Chevalier
32 REFERENCES
Acemoglu, D. and Pischke, S. (1999) "The Structure of Wages and Investment in General Training", Journal of Political Economy, 107, pp.539-572.
Ashenfelter, O. and Krueger, A. (1994) "Estimating the Returns to Schooling Using a New Sample of Twins", American Economic Review, 84, pp. 11157-1173.
Ashenfelter, O. and Rouse, C. (1999) "Schooling, Intelligence and Income in America: Cracks in the Bell Curve", NBER Working Paper 6902.
Ashton, D., B. Davies, A. Felstead and F. Green (1999) Work Skills In Britain. Oxford: SKOPE, Oxford and Warwick Universities.
Behrman, J., Rosenweig, M. and Taubman, P. (1994) "Endowments and the Allocation of Schooling in the Family and in the Marriage Market: The Twins Experiment", Journal of Political Economy, 102, 6, pp. 1131-1174.
Bell, B., Blundell, R. and Van Reenen, J. (1999) “Getting the Unemployed Back to Work: The Role of Targeted Wage Subsidies”, International Tax and Public Finance, 6, pp. 339- 360.
Blundell, R., Dearden, L. and Sianesi, B (2001) “Estimating the Returns to Education: Models, Methods and Results”, Centre for the Economics of Education Discussion Paper, forthcoming.
Blundell, R. and Costa Dias, M. (1999) "Evaluation Methods for Non-Experimental Data" forthcoming, Fiscal Studies.
Blundell, R., Duncan, A., McCrae, J. and Meghir C. (1999). “The Labour Market Impact of the Working Families Tax Credit,” forthcoming, Fiscal Studies.
Bound J., and Solon, G. (1998) "Double Trouble: Estimates of Returns to Education Based on Twins", NBER Working Paper 6721, September.
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