Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 1 Proposal Part B

Proposal Full Title: Toolbox for Improving the Comparability of Cross-National Survey Data with Applications to SHARE

Proposal Acronym COMPARE

Date of Preparation 12 April 2005

Type of Instrument Specific Targeted Research Project

Research Area 8.2.2. Promotion and support for comparative research, methodologies and data generation

List of Participants Participant no. Participant organisation name Participant org. short name 1 (co-ordinator) Tilburg University, CentER, Tilburg, The Netherlands UTILB 2 University of Mannheim, Mannheim Research Institute MEA for the Economics of Aging, Mannheim 3 University of Linz, Dept. of Economics, Linz, Austria JKULINZ 4 University of Liège, CREPP, Liège, Belgium ULG 5 University of Antwerp, CSP, Antwerp, Belgium UNIANT 6 CERGE-EI, Prague, Czech Republic CERGE-EI 7 University of Southern Denmark, Institute of Public SDU Health, Odense, Denmark 8 IRDES, Paris, France IRDES 9 Panteion University, Athens, Greece UPANTE 10 University of Padua, Dept. of Economics, Padua, Italy UNIPADUA 11 Warsaw University, Dept. of Economics, Warsaw, WNE-UW Poland 12 CEMFI, Madrid, Spain CEMFI 13 University of Uppsala, Dept. of Economics, Uppsala, UNIUPPS Sweden 14 University of Lausanne, Institute of Health Economics UNIL and Management, Lausanne, Switzerland

Co-ordinating person

Professor Arthur van Soest CentER, Tilburg University, The Netherlands Email: [email protected] Fax: +31-13-4663280

1 In the event of inconsistency between information given in Part A and that given in Part B, the Part A version will prevail

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Contents

Proposal Summary ...... 3 B.1 Scientific and technological objectives of the project and state of the art ...... 4 B.2 Relevance to the objectives of Priority 7...... 13 B.3 Potential impact ...... 15 B.3.1 Contributions to standards: ...... 18 B.4 The consortium and project resources...... 19 B.4.1 Sub-contracting...... 34 B.4.2 Other countries ...... 34 B.5 Project management ...... 35 B.6 Detailed Implementation plan ...... 37 B.7 Other issues...... 50 B.7.1 Ethical issues ...... 50 B.7.2 Gender issues...... 51 B.7.3 Policy issues ...... 51 STREP Project Effort Form ...... 53 Deliverables list...... 54 Workpackage list...... 55 Workpackage description WP1...... 56 Workpackage description WP2...... 57 Workpackage description WP3...... 58 Workpackage description WP4...... 59 Workpackage description WP5-18...... 60 List of references...... 61

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Proposal Summary Page

Proposal full title: Toolbox for Improving the Comparability of Cross-National Survey Data with Applications to SHARE

Proposal acronym: COMPARE

Research Area: 8.2.2. Promotion and support for comparative research, methodologies and data generation

Research Topic: Comparative Survey Data

Proposal abstract (2000 characters max.)

In a diverse continent like Europe, much can be learned from cross-national research using surveys among households and individuals. Often, however, such comparisons suffer from differences across countries and socio-economic groups in the way people answer survey questions, particularly self-evaluations of, e.g., health or quality of work. This proposal aims at solving this problem by developing widely applicable tools for comparative survey research among European citizens, called anchoring vignettes. Anchoring vignettes are short descriptions of, e.g., the health or job characteristics of hypothetical persons. Respondents are asked to evaluate the hypothetical persons on the same scale on which they assess their own health or job. Respondents are thus providing an anchor, which fixes their own health assessment to a predetermined health status or job characteristic. These anchors can then be used to make subjective assessments comparable across countries and socio-economic groups. The project will develop anchors that can be used in a broad range of domains (such as health; work disability; quality of life, employment and health care; satisfaction with political institutions) and that can be applied to typical EU sponsored cross-national surveys (such as the ECHP, ESS, SHARE and SILC). Specifically, anchors will be constructed for SHARE, the Survey of Health, Ageing and Retirement in Europe, which currently covers some 22,000 respondents of age 50 and older in 11 EU countries. We use SHARE as a testing ground since it addresses crucial domains of European public policy, such as health care, socio-economic status, employment and retirement. The vignettes will be used to construct improved indicators of health, well-being, job satisfaction, etc., helping Europe to create opportunities for more accurate and richer analyses of the consequences of ageing and the effects of socio-economic and health care policies at the national and European level.

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B.1 Scientific and technological objectives of the project and state of the art Describe in detail the proposed project’s S&T objectives. The objectives should be those achievable within the project, not through subsequent development, and should be stated in a measurable and verifiable form. The progress of the project work will be measured against these goals in later reviews and assessments. Describe the state-of-the-art in the area concerned and how the proposed project will enhance the state-of-the-art in that area. (Recommended length –5-10 pages)

The overarching aim of this project is to develop and implement a new methodological approach that has the potential to substantially enhance the power of cross-national research for policy evaluation and behavioural analyses in Europe. B.1.1 will motivate the importance of this project, B.1.2 presents the basic idea of our methodology and research objectives, and B.1.3 describes the concrete application. B.1.1 Background and significance (a) The value of cross-national research The case for cross-national research has been made forcefully by the European Council in Lisbon when it established the Lisbon agenda of common employment targets, and by the OECD in its many cross-national analyses of social policies. The essential argument is that the variety of circumstances and policies is in general much larger across countries than within a single country so that policy makers and researchers can learn from what has happened and what has been tried elsewhere. Cross-national comparisons are particularly useful for the European Union with its open method of co-ordination – they are actually a crucial foundation of the Union’s policy instruments. Cross-national research is particularly fruitful for evaluation of public policy. The impact of economic and social policies can only be understood if we observe one policy in contrast to other policies (the “counterfactual”). For example, most European countries have only one health care system that has undergone only minor changes since good micro data have become available. As a consequence, it is not possible to evaluate a country’s health care system vis-à-vis alternative systems using only national data from that country. International variation in health care systems helps enormously in this respect, making it possible to compare a variety of systems. Of course other, related, differences across countries have to be accounted for, making a case for a studying a larger group of countries, some of which are similar in some respects and others in other respects. A formal argument for the usefulness of such a comparison is provided in National Academy of Sciences (2001). Similar arguments apply to labour market and pension policies. While several recent reforms have been implemented in these areas in many European countries, the international variation is still much larger than the variation within each country, particularly since long-lasting transition rules make these social systems inert. A third example is the fact that population ageing varies across countries. Hence, countries with relatively prolonged baby booms (such as France and the United Kingdom) will experience the ageing of their populations later than other countries and may therefore be in a position to evaluate the successes and failures of policies adopted in countries which already have experienced the demographic transition to higher proportions of older age groups in their population (such as Germany and Italy). There are striking variations in pension policy and health care provision across European countries. For instance, the share of retirement income provided by public pensions varies from more than 90% in the large Continental European countries to less than 50% in the

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Netherlands and Switzerland, where retirement income is largely provided privately by the second and third pillar (Börsch-Supan and Miegel, 2001). The extent to which pension systems contain incentives to retire at specific ages varies greatly across the major industrial countries (Gruber and Wise, 1999). The percentage of GDP spent on health care varies also considerably across the industrialised countries: in the European Union it ranges from 5.9% in Luxembourg to 10.4% in Germany, compared to 12.9% in the United States (OECD, 2002). Take up rates of disability insurance vary dramatically across EU member states, without discernible differences in corresponding healthcare spending (Aarts, Burkhauser, and de Jong, 1996). The work by Gruber and Wise (1999, 2004, 2005) on retirement and the work by Börsch- Supan (2001, 2003) on savings and pensions are examples of studies that interpret the variation in institutions across countries as “natural experiments,” identifying the effects of institutions on socio-economic outcomes, such as the prevalence of early retirement and the fraction of people on disability benefits. The work by the Gruber and Wise group has provided significant inputs for policy recommendations for reforms of pension systems (OECD, 2000; European Commission, 2000). (b) Challenges to, and pitfalls of, cross-national research While the potential benefits of comparative international research are increasingly clear, conducting such research in practice poses a number of challenges, such as the development of designs that can be readily adapted to different social and cultural settings, the harmonisation of concepts and measures that provide an acceptable level of cross-national comparability, and the co-ordination of data collection and analysis across countries. Recently, some surveys have been designed that by design focus on developing common measures, in particular Eurostat’s Survey of Income and Living Conditions (SILC), the EU- sponsored European Social Survey (ESS) and the EU-sponsored Survey of Health, Ageing and Retirement in Europe (SHARE), financed by the 5th framework programme. For many issues in studies of health, psychology, and economics, however, methods for obtaining common measurements are not well understood. The difficulties are relatively small for measuring easily quantifiable items such as the retirement age, household income, or savings. Other quantitative objective measures are often hard or impossible to obtain. Physical measurements of health, for example, are expensive and often require the assistance of a nurse at the in-person interviews. Moreover, such physical measurements often only provide information on a specific feature of a given health domain. Hence, the common solution is to apply self-reported measures of general health, work related health, or health in a broad domain such as mobility, pain, depression, or sleep. While these measures provide inexpensive and convenient ways to collect information on health aspects of a population or on health differences between populations, they rely on a subjective assessment of health (“how do you rate your health on a scale from very good, good, fair, bad to very bad”).

Comparison of such subjective measurements across countries (or socio-economic groups in one country) raises the issue whether people in different countries (or socio-economic groups) use the same benchmarks or scales on which they evaluate themselves. The answer appears quite clearly to be negative. A striking example is the following subjective evaluation of general health, using the Eurobarometer scale, displayed in Table B.1.1. The same question with the same response categories leads to an astounding variation in the distribution of health, with the fraction reporting that their health is “very good” ranging from only 3.5

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 6 percent in Portugal to 41.8 percent in Denmark. It seems quite unlikely that this difference reflects a genuine difference in general health between European countries; it seems more likely that a large part of the differences is due to the fact that people in different countries use different norms for what should be called “very good,” “good,” etc. This phenomenon that different groups of people use systematically different norms for assigning a label like “good” or “very good” to their own self-assessment, is what in psychometrics is called differential item functioning (DIF), defined as the inter-personal and inter-cultural variation in interpreting and using the response categories for the same question (Holland and Wainer, 1993). It substantially impedes the usage of cross-national data to make valid international comparisons in crucial areas such as health care and policy analysis. Additional information is needed to distinguish the effects of language, cultural and social norms from genuine health differences that may result from, for example, the effects of public health care policy. TABLE B.1.1: DIFFERENTIAL ITEM FUNCTIONING IN SELF-RATED HEALTH

“Over the last 12 months, would you say your health on the whole has been ....”

Very good Good Fair Bad very bad Belgium 18.83 44.30 26.26 8.75 1.86 Netherlands 18.94 40.20 30.23 7.64 2.99 Luxemburg 9.84 41.53 37.16 8.20 3.28 Austria 17.93 34.51 36.14 9.78 1.63 Germany (West) 10.12 35.66 41.20 10.84 2.17 Germany (East) 7.09 36.84 42.56 10.76 2.75 France 11.08 40.06 34.94 10.23 3.69 Italy 10.44 33.74 44.66 9.22 1.94 Spain 8.01 38.67 35.08 15.47 2.76 Portugal 3.52 17.34 37.44 30.65 11.06 Greece 16.20 35.48 20.31 25.45 2.57 Ireland 28.57 32.92 29.19 7.76 1.55 Northern Ireland 21.57 30.39 31.37 11.76 4.90 Great Britain 25.94 24.94 34.01 11.08 4.03 Denmark 41.78 27.15 24.02 4.70 2.35 Finland 10.47 25.13 48.95 11.78 3.66 Sweden 28.92 27.21 28.43 12.25 3.19 Source: Eurobarometer 44.3 (1996), Question 113. Respondents aged 50 and over.

Analogous examples can be provided for other subjective measurements such as well-being or satisfaction with the social and political environment. (c) S&T objectives The objective of this proposal is therefore to develop and apply tools that can be used to identify the differences in response scales induced by differences in language, culture and social norms, and to correct for such response scale differences, so that a comparison of distributions of the true phenomena of interest (such as general health, work related health, satisfaction with the political system or society, etc.) across countries can be obtained.

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Specifically, we will design new and improve existing tools for comparative survey research among European citizens, and we will implement these tools in the cross-national Survey of Health, Ageing and Retirement in Europe (SHARE) - a recently started comparative European survey of individuals aged 50 and over in 11 EU countries. SHARE is ideally suited for this application because it is a multi-disciplinary survey addressing a broad range of important domains of European public policy, such as health care, employment and social exclusion, which are likely to benefit considerably from cross-national analysis. Policies in these domains, however, frequently target indicators suffering from differential item functioning due to cultural differences and social norms. The tools are anchoring vignettes: short descriptions of for example, a health problem, a health care system with certain features, a job with given characteristics determining the quality of employment, etc. (see, e.g., King, Murray, Salomon, and Tandon, 2004, and Banks, Kapteyn, Smith and van Soest, 2004). The respondents are asked to assess the described features of the health, quality of health care, quality of employment, etc., on the same scale as used for the evaluations of their own health, quality of health care, etc. If different respondents evaluate the same hypothetical person (or situation) differently, this is evidence of response scale differences (i.e., differential item functioning). The response scale differences can be expressed more precisely using statistical models, making it possible to create indicators of health, quality of work, health care, or life, etc., that are better comparable across countries or socio-economic groups, since response scale differences are corrected for.

B.1.2 State of the art and methodological approach Progress in developing internationally comparable indicators is being made in several fields. One strand of research, continuing a large-scale cross-national effort, creates instruments that are comparable across countries, cultures, and language groups in their wording and design. Such instruments have been produced for depression (Prince et al., 1999) and are under development in physical functioning, i.e., how to handle (instrumental) activities of daily living (Robine et al., 2001), to name two prominent examples. The case for cross-national harmonisation of instruments has been made forcefully by the US National Academy of Science (2001), and it is underlying the design of EU-wide surveys such as ESS, SHARE and SILC. A second strand of research is represented by the large-scale research programme sponsored by the US National Institute on Aging which aims at understanding and correcting for differential item functioning through anchoring vignettes (King et al., 2004). Vignettes have extensively been used for domains of political efficacy, general health and work disability (King et al., 2004, Salomon, Tandon and Murray, 2004, Banks et al., 2004, Kapteyn, Smith and van Soest, 2004). Some work has been done on vignettes for quality of health care but this still seems to be in a preliminary stage. Anchoring vignettes on quality of employment, well-being (quality of life), poverty or social exclusion, do, to the best of our knowledge, not yet exist, but it would be natural to use the same framework to design such vignettes and model their evaluations jointly with self-assessments, to adjust for differential item functioning. This proposal will combine both approaches. First, it makes use of the strictly cross-national design methodology applied in SHARE. For instance, SHARE employs the depression measures developed by Prince et al. (1999) and it will include the physical health measures developed by Robine et al. (2001) once they are finalised. Second, this proposal will improve and implement the anchoring vignettes methodology for a broad range of domains.

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Anchoring vignettes have successfully been developed and used to make subjective health ratings comparable across countries (cf., e.g., King et al., 2004, and Salomon et al., 2004). The basic idea of this adjustment is sketched in Figure B.1.2:

FIGURE B.1.2: COMPARING SELF-REPORTED HEALTH ACROSS TWO COUNTRIES IN CASE OF DIFFERENTIAL ITEM FUNCTIONING

*

Country A

Poor Fair Good Very good Excellent

* Country B

Poor Fair Good Very good Excellent

Figure B.1.2 presents the distribution of health (in a specific domain, such as mobility) in two countries. There are two differences between countries A and B. First, the density of the true underlying health variable in country A is to the left of that in country B, implying that on average, people in country A are less healthy than in country B. Second, the people in the two countries also attach different labels of a typical five-point scale (poor-fair-good-very good- excellent) to a given point of the health density. This is what we call differential item functioning. In the example in the figure, people with health indicated by the modal point of the density (*) would report “very good” health in country A, but only “good” in country B. Hence, people in country A are less healthy, but much more optimistic than people in country B. Due to the differential degrees of optimism, the frequency distribution of the self-reports in the two countries would suggest that people in country A are healthier than those in country B – the opposite of the actual health distribution. Correcting for the differences in the scales that people use is essential to compare the actual health distributions in the two countries. Vignettes can be used to do the correction. They have successfully been included in the World Health Survey (WHS), as a key component of the Global Burden of Disease project. A vignette question describes the health of a hypothetical person and then asks the respondent to

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 9 evaluate the health of that person on the same five-point scale. The following example illustrates a vignette for the domain of mobility, one of eight health domains in the WHS: Margaret feels chest pain and gets breathless after walking distances of up to 200 metres, but is able to do so without assistance. Bending and lifting objects such as groceries also causes chest pain. Overall in the last 30 days, how much of a problem did Margaret have with moving around? None, Mild, Moderate, Severe, or Extreme? The crucial point is that these vignette descriptions are the same in all countries, so that the vignette persons represent the same health conditions. Applied to the example of figure B.1.2, respondents will be asked to evaluate the health of a person whose health is given by the dashed line. In country A, this will be evaluated as “very good.” In country B, the evaluation would be “fair.” Since the actual health description of the vignette person is the same in the two countries, the difference in the country evaluations must be due to differential item functioning. Vignette evaluations thus help to identify the differences between the scales in the two countries. Using the scales in one of the two countries as the benchmark, evaluations in the other country can be adjusted by evaluating them on the benchmark scale. The corrected evaluations can then be compared to that in the benchmark country – they are now on the same scale. In the example in the figure, this will lead to the correct conclusion that people in country B are healthier than those in country A, on average. Will these corrections work in practice? We have three convincing examples that vignettes perform as they are designed. First, King et al. (2004) have applied the vignette methodology to political efficacy. Their results strongly support the ability of the vignettes to correct for differential item functioning. In their comparative study of political efficacy of Chinese and Mexican citizens, they find that without correction the Chinese seem to have more political influence than the Mexicans. The conclusion reverses if the correction is applied. Another application of King et al. (2004) is vignettes on visual acuity. According to self- reports, the Chinese would have better vision that the Slovakians. Corrections using vignettes reverses this conclusion, bringing it in line with an objective measure of visual acuity which shows that Slovakians have better vision than Chinese citizens.2 Third, Banks et al. (2004) have developed and used anchoring vignettes to analyse cross country differences in self-reported work disability, an important determinant of labour force status, determining whether people are on disability benefits, on early retirement, or still actively participating in paid work. They applied these anchoring vignettes for work disability, together with some of the World Health Survey (WHS) vignettes for domains of general health, in an experimental module, funded by the US National Institute of Aging that was given to modest size samples of SHARE 2004 in nine of the eleven SHARE countries. This pre-test is currently under evaluation. Preliminary analyses show a similar performance (high response rates, plausible variation with other covariates) as in the WHS. Most significantly, the experimental SHARE pre-test also contained more objective measures such as walking speed and grip strength, which can be used to validate the vignette corrections.

While the discussion focused on countries, the same methodology also applies to socio- economic groups within a given country. For example, it may be the case that men and women, respondents with high and low education level, or working and non-working

2 More applications to health are discussed in Sadana et al. (2002).

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 10 respondents use different response scales in evaluating their health, well-being, etc. Vignettes will be used to identify such differences and correct the indicators for them. This will lead to better insights in the differences between socio-economic groups in health, well-being, quality of work, etc. B.1.3 Application to SHARE (a) Innovation This STREP project will adapt the health and work disability vignettes of the WHS and Banks et al. to the entire range of SHARE countries plus two accession countries. Moreover, we will enhance the state of the art by extending the vignette approach to a broader set of domains. We select these domains by choosing items that are typically used in European Community- sponsored cross-national surveys, such as the ECHP, SILC, ESS and SHARE. Specifically, we will develop and field vignettes for the following domains: • Several domains of health (mobility, pain, sleep, breathing, emotional health, cognition); • The extent to which health limits the amount or kind of work people can do; • Political efficacy and satisfaction with the national political system; • The quality of health care; • Quality of employment; satisfaction with work; • Well-being and quality of life; • Poverty and social exclusion. The development of this new set of vignettes is an important innovation as it relates to the fundamental objectives of the European Union: the project addresses the domains and indicators that are the main targets of Union policies. They therefore support the open method of co-ordination in providing researchers as well as policy makers with much improved and more reliable indicators of the European Union’s policy objectives.

(b) SHARE as testing ground The Survey of Health, Ageing and Retirement in Europe (SHARE) collects interdisciplinary data on European citizens over the age of 50. Data include health variables, psychological variables, economic variables and variables on social and family networks and social support. SHARE is designed after the US Health and Retirement Study (HRS) and the English Longitudinal Study on Ageing (ELSA).3 Comparability with these surveys is one of the core targets. In the autumn of 2004, SHARE was conducted in Austria, Belgium, Denmark, France, Germany, Greece, Italy, the Netherlands, Switzerland, Sweden, Spain, covering approximately 15,000 households and 22,000 respondents. A survey modelled after SHARE will soon also be held among the 50+ population of Israel. SHARE is ideally suited for this application. First, it is a multi-disciplinary survey addressing a broad range of important domains of European public policy, such as health care, employment and retirement, social exclusion, which are likely to benefit considerably from cross-national analysis. Second, the policies in these domains frequently do not target indicators that can be measured objectively (such as GDP growth or reduction of economic poverty), but indicators based upon subjective assessments that are likely to suffer from

3 See http://www.ifs.org.uk/elsa/

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 11 differential item functioning (such as the citizens’ self-rated health status, their satisfaction with the health care and the political system, etc.). Third, the policy problems related to these domains are urgent but controversial and therefore benefit from a fact-based discussion to improve governance in our emerging knowledge-based society. In eight of the SHARE countries, a pre-test with vignettes on emotional, physical, and work related health was held in 2004 among approximately 350 households (about 475 respondents) per country. This project will apply a vignette questionnaire as an addition to the full core questionnaire developed in SHARE to about 600 households (900 respondents) in all SHARE countries plus two accession countries, the Czech Republic and Poland. Where possible in the original SHARE countries, we will administer the vignettes to the same respondents who have already received the vignette questions in the 2004 vignette pre-test. Our approach is designed to achieve two goals. First, the full sample size of about 900 respondents per country is sufficiently large to establish “conversion factors” along the lines described in B.1.2 for a large set of European countries and a broad range of domains, ranging from health to the satisfaction with health care and national policies to poverty and social exclusion. These conversion factors will be applicable to other cross-national surveys as well (ECHP, SILC, ESS, etc.). They will improve comparability of the indicators for these domains across countries and socio-economic groups within a country. Second, administering this vignette questionnaire wherever possible to the former respondents will create panel data on vignette evaluations and self-reports, making it possible to look at changes and transitions at the individual level and to study shifts in response scales jointly with changes in self-reported health conditions or work limitations. Panel data on vignettes will make it possible to both control for individual specific effects in the response scales and for random variation over time in the individual response scales, and to better distinguish reported from genuine changes. Moreover, the timing of the events often makes it possible to analyse the causal nature of relationships between variables where cross-section data can only reveal correlations without further assumptions. For example, cross-section data show a positive correlation between health and socio-economic status (for example measured by wealth). Panel data can be used to disentangle causal effects from wealth to health and from health to wealth. (c) Contribution of the project The project makes contributions to science and technology in at least four respects: First, it will develop new vignettes for several domains: quality of life, employment, and poverty and social exclusion and will adjust vignettes for other domains (quality of health care, general and work related health, political efficacy) to the context of Europe. These newly developed vignettes are of great value in themselves because they can be used in other surveys as well. The vignettes developed in this project will be made freely available to the research community at large. They are easy to administer to respondents, and typically respondents like to answer the vignette questions. Second, the project will use the vignettes to obtain distributions of indicators for important dimensions of the quality of life of European citizens across countries adjusted for response scale differences. These adjusted indicators can be used for better international comparisons and better analysis of the interrelations between these dimensions. While they are constructed from SHARE data, these indicators and their distribution, as well as their relation to the original answers and the corresponding “conversion factors”, can be used on any data set with

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 12 the same question. They can, for instance, be applied to the Eurobarometer’s self-reported health scale that was depicted in the introductory example in Table B.1.1. In addition, the project also creates a data set in 13 countries that has the full range of SHARE variables and therefore a great research potential in itself. Specifically and as a third contribution, the project adds a longitudinal dimension to the vignettes. The core questions form SHARE 2004 will again be included in this Vignettes survey wave, in order to provide the necessary covariates for the vignette analysis. We will attempt to re-interview as many respondents as possible who were part of the SHARE 2004 vignette sub-sample. Specifically, for the eight countries that participated in the vignette pre-test of SHARE 2004, we will select all respondents from those who already participated in the vignette pre-test, giving about 475 respondents per country. This creates a longitudinal data set for vignettes on six domains of general health and on work related health problems along with the covariates that go along with it in the core SHARE data. These panel data can be used to analyse relations between changes and to investigate causal mechanisms between the variables of interest, substantially increasing the value of SHARE for public policy. Fourth, the project adds data from two accession countries, Poland and the Czech Republic. This greatly enhances the value of the SHARE vignette sample as a survey because it will cover the economic, social, and cultural variation in the new European Union to an almost full extent. The vignette and core data will be made available to the research community at large, free of charge and as soon as possible, following the successful SHARE 2004 model. Further contributions are therefore the analytical possibilities created by this new cross- national add-on to the original SHARE data, which has both an enlarged cross-national dimension (Czech Republic and Poland) and a limited time dimension (re-interviews). Such further contributions will be measurable and verifiable by the number of publications resulting from these new data.

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B.2 Relevance to the objectives of Priority 7 Describe the manner in which the proposed project’s goals address the scientific, technical, wider societal and policy objectives of Priority 7 as stated in this call. (Recommended length – 2 pages)

The overall objective of Priority 7 – improving governance in our knowledge-based society – is directly addressed by this project. Fact-based discussions on governance in these times of far-reaching welfare state reforms require data. Since populations are diverse and policy interactions in modern welfare states complex, aggregate data on employment and health most frequently paint too coarse a picture to draw valid and robust policy conclusion. Micro data is required which captures the heterogeneity of modern populations. Moreover, fact-based discussions on welfare policy issues often cannot only rely on indicators that can be measured objectively (such as GDP growth or reduction of the percentage of households below an official poverty line), but require indicators that are likely to suffer from differential item functioning (such as the citizens’ self-rated health status, their satisfaction with the health care and political system, social exclusion, etc.). This research will enable a fact-based discussion also tailored towards these “softer” indicators. In addition, knowledge generation in economics and social sciences is increasingly based on modern empirical methods. Also these methods require micro data. Europe, however, is far behind the US in providing an infrastructure of micro data conducive to such knowledge generation and fact-based discussions on how to govern and reform pension, health care and labour market institutions under the pressures of population ageing. In the US, the Health and Retirement Study (HRS) is the infrastructure for research on health and employment, supporting cross-fertilization among economics, the social sciences and public health. Europe lacks this infrastructure, although it has significantly more severe labour market, pension and health care financing problems than the US, and a much more pronounced population ageing process, which will worsen these problems in the future. The value of a micro data infrastructure for policy research in Europe is therefore much large than the value of the HRS is for the United States. This project will provide a crucial addition to existing data, thereby creating a knowledge base suitable for policy research in Europe, and especially suited to improve governance of our welfare systems. More specifically, this project is ideally suited to address the objectives of research area 8.2.2, the promotion and support for comparative research, methodologies and data generation through the development and diffusion of a new methodology, which makes self-reported and subjective variables (such as self-rated health, well-being, satisfaction with the political and social environment, etc.), which are typically contained in large scale data-sets of a wide European user community, comparable and thus applicable for comparative research. The proposed project addresses several specific points mentioned in the description of research area 8.2.2 head on. They are highlighted in italics in the sequel of this section. The methodology is generic because it can be applied to a large set of very different domains and related disciplines (public health, economics, sociology, political science, psychology). We will actually supply “anchors” (see B.3 and B.6) for a broad range of variables commonly used in different fields and disciplines. The projects overarching aims are highly relevant to the overall objectives of priority 7, citizens and governance in a knowledge based society, since it supports a better understanding of the way how the different governance and welfare systems in Europe affect the well-being of European citizens. The impact of public policy – as realised in governance and welfare systems – can only be understood if we observe one policy in contrast to other policies. Hence, one needs internationally comparative data to exploit the rich variety in policies, institutions and other factors across European countries to learn about their effects and their

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 14 effectiveness. Moreover, many of the policies that one might want to consider and which address future public policy challenges, have already been implemented in some form in at least one of the European countries. The variation in institutions across European countries therefore creates a unique laboratory in which to study the effects of institutions on societal processes. For this to work, data must be comparable across countries (e.g. the measurement of work disability). From a European policy perspective, matters of economic and social policy are increasingly Community matters, due to the higher mobility of people and capital precipitating common policies such as the pension directive. Furthermore, the gradually increasing importance of indicators to assess and guide Union policy requires a reliable and comparable database to create such indicators. This project makes a fundamental contribution to this goal since it makes the many indicators that rest on self-reported and subjectively assessed variables comparable across countries. More specifically, this proposal uses as one testing ground (and only one – the conversion factors can be generally used, see B.3) the SHARE data which has a particularly wide applicability for social sciences and humanities research due to its broad range of variables and potential applications in public health, economics, and social sciences.

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B.3 Potential impact Describe the strategic impact of the proposed project, for example in reinforcing competitiveness or on solving societal problems. Describe the innovation-related activities. Describe the exploitation and/or dissemination plans which are foreseen to ensure use of the project results. Describe the added-value in carrying out the work at a European level. Indicate what account is taken of other national or international research activities. (Recommended length – 3 pages)

This project contributes directly to EU-policies. Responding to the March 2000 Special European Council in Lisbon, the following communication by the European Commission to the Council and the European Parliament states (p. 61): “Finally, the Commission will examine the possibility of establishing, in co-operation with Member States, a European Longitudinal Ageing Survey. This would provide essential data necessary for the design of effective policies in fields such as health care and social protection systems which cater for the changing needs of an ageing population. The utility of longitudinal ageing survey has already been demonstrated by the Health and Retirement Survey in the US and the English Longitudinal Study of Ageing (ELSA). There would be significant benefits in organising a longitudinal ageing survey at European level, both in terms of cost saving and ensuring that data is of high quality and comparable across countries. Moreover, it would mark an important step in promoting the process of open co- ordination advocated by the Lisbon European Council on the basis of comparable data and indicators.” To underscore the importance of this EU policy, it is noteworthy that the call for comparable data has found resonance at almost all recent G-7/G-8 summits. The final communiqué of the Denver Summit, for example, states: “Our governments will work together, within the OECD and with other international organisations, to promote active ageing through information exchanges and cross-national research. We encourage collaborative biomedical and behavioural research to improve active life expectancy and reduce disability, and have directed our officials to identify gaps in our knowledge and explore developing comparable data in our nations to improve our capacity to address the challenges of population ageing into the 21st Century.” It is exactly this commitment that we try to support with this research project. Implementing a methodology that renders a large set of typical cross-nationally measured variables comparable provides a particularly large added value to the European Community. There are two crucial reasons why comparable data on a European level is more than the sum of its national parts. First, matters of economic and social policy are increasingly Community matters, due to the increasing personal and capital mobility, precipitating common policies and common regulations such as the pension directive. Moreover, the gradually increasing importance of indicators to assess and guide Community policy requires a reliable and comparable data base to create such indicators. Second, the large diversity in institutional histories, policies and cultural norms in Europe, and the significant variation in the health and financial circumstances of individuals in different European countries that history has created, represents a unique living laboratory in which the various determinants of the current economic, health and socio-psychological state can much easier be identified than in the much more homogeneous environment of a single country. The strategic value of this project for all cross-national data sets in Europe (such as the Eurobarometer, the European Community Household Panel (ECHP), the European Social Survey (ESS), etc.) is increased by its application to the SHARE data. The Survey of Health, Ageing and Retirement in Europe provides the opportunity to both science and society to exploit this living European laboratory for a pressing policy challenge, namely the adaptation

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 16 of the European welfare regimes to population ageing. Since the ageing process affects all of us in a broad range of domains, many of them difficult to measure, such as health, life- satisfaction and well-being, this project provides the basis for major scientific breakthroughs. The insights gained from analysing and comparing the diversity of experiences in the SHARE data using this projects’ methodology will help both a supranational body like the EU and the separate countries to more effectively prepare for the continuing changes in age demographics in the future. The baseline wave of SHARE has already provided a wealth of findings, which provides important information for scientists and public policy makers. We select the following examples: • Within countries there is a strong relation between health (and health behaviour) and socio-economic status. For instance, individuals with a low education are 70% more likely to be physically inactive, and 50% more likely to be obese than individuals with a higher education. • There is a clear north-south gradient in various health measures (both subjective self- assessed and physical measures) and income: the elderly in the north are better off financially and are in better health. However, this does not translate into corresponding mortality differences. • Prevalence of current depression rises with age in most SHARE countries and is higher among women than among men. Particularly the southern European countries show a large gender gap with huge depression prevalence rates among elderly women. Past and current depression is significantly larger among unmarried respondents than among married respondents. • There is a clear negative association between depression and income or wealth in the northern countries, but such an association is completely absent in the south of Europe. • Cognitive ability is strongly associated with education – the higher educated are more cognitively able than the lower educated. Cross-country differences between cognitive impairment rates seem quite well in line with cross-country differences in education level. • Differences in out-of-pocket medical expenditures illustrate the cross-country differences in health care systems. In Germany, Sweden, Denmark and Greece, more than 80% of SHARE households had at least some out-of-pocket expenditure in the past 12 months. In France, Spain, and the Netherlands, the percentages are only 37%, 41% and 42%, respectively. • All countries reveal a positive relation between well-being and education level and income. • In the Nordic countries, almost 20% of the age group 65-74 does volunteer work, and in the Netherlands this is even more than 25%. In Spain and Greece less than 4% report to do volunteer work in all age groups. In all countries, volunteer work is much more common among higher than among lower educated. • Retirement ages and exit routes into retirement vary a great deal across countries. For example, the prevalence of disability insurance in the early retirement window varies from about 16% in Denmark to about 3% in Greece. There are no discernible cross- country differences in demographic composition or health status that can explain this large variation. • In all countries wealth inequality is larger than income inequality, which is larger than consumption inequality. But huge differences in inequality appear between the more egalitarian Northern countries, and the rest of European countries participating in SHARE.

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This enumeration shows the broad multidisciplinary nature and large potential of the SHARE data. This project will increase the potential for further insights from SHARE dramatically since it improves the cross-national comparability of key measures used in the above examples. Since the anchors and conversion factors will be applicable to other cross-national data sets in Europe also, the project’s impact on cross-national European research is likely to be large.

Innovation-related activities have been detailed in B.1.3. They include • The improvement of existing anchoring vignettes, • The adaptation of existing anchoring vignettes to the European context, and • The development of new anchoring vignettes in domains not yet covered (e.g., satisfaction with the political and social environment; well-being and quality of work), • Application of anchoring vignettes to a unique broad set of European countries, including small samples of repeated observations in eight original SHARE countries. • The construction of “conversion factors” applicable to a large set of EU-sponsored cross- national data, such as ECHP, SILC, ESS and SHARE, and similar data sets such as the Eurobarometer.

Dissemination activities: For the dissemination of our results, we follow the model already employed in the SHARE project. We will release all research findings in early result publications and make them accessible for a large audience via an Internet platform, conferences aimed at a scientific and a public policy audience, plus newsletters and other print publications. Our aim is to provide the scientific community with reliable conversion factors and anchors for a wide range of self- reported and subjectively assessed variables (see B.3.1). Following our commitment to contribute through SHARE to the urgently needed knowledge base for ageing research in Europe, we have released a public use data file to the scientific community already five months after the data collection was completed. We will follow this strategy also for the vignette data collected under this proposed project. It is central to the philosophy of the entire SHARE project to share the data collected as soon as technically possible with the entire scientific and public policy communities, the only restriction to data access being data confidentiality according to Community and national laws. Thus the new data will be made available to the research community at large as soon as possible, in user- friendly format and with extensive documentation. As with SHARE 2004, full details of the data content, access arrangements, and codebooks will be put on the existing SHARE website (www.share-project.org). Similarly, all articles, books and papers based on the collected data, whether substantive or methodological, are documented and catalogued. For example, an extensive volume with first results from SHARE 2004, published in April 2005, is downloadable in PDF format from the SHARE website. We will continue to follow this strategy for the vignette data generated under the present proposal. Publicly available and well-documented data invites substantive data analyses by academia and policy research institutes. The website will include detailed documentation of the development process and how to apply the conversion factors to external general-purpose data sets. We will organise a final project conference at the end of the project. This conference will be open to the scientific community at large, and we will tailor parts specifically for EU policymakers in order to disseminate the results of this study to the public policy community. Along the same lines, we will not only write scientific papers but also continue the tradition of many members of the team to publish articles in newspapers and magazines making our work

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 18 accessible to a broad audience. This will also serve as an informal channel to reach the target group of the research.

B.3.1 Contributions to standards Describe contributions to national or international standards which may be made by the project, if any. (Recommended length– 1 page)

This project will create “anchors” that standardize the answers to typical self-reported measures that are contained in most cross-national surveys collected and used by the European Union. A typical example is the question on self-reported health (on a scale from very good to very bad) displayed in Table B.1.1 above. It is used in the Eurobarometer, has been used in the European Community Household Panel (ECHP), the European Social Survey (ESS) and SHARE. The “anchors” or conversion factors will provide a translation of the answers given in one country to the scale used in another country, relating the normal self- reported health in one country to the normal self-reported health in another country, as well as relating the range of self-reports in one country to another country. The construction of these “anchors” is described in B.6 in greater detail. The conversion factors for each domain (health, well-being, political satisfaction etc.) will be available to the entire research community. They will provide a standard of comparison, make cross-national comparisons of the many self-reported and subjective measures in typical EU-surveys meaningful and thus stimulate comparative research. The conversion factors will be specific for socio-economic groups distinguished by, for example, education level, gender, age, marital status, and employment status. The same conversion factors can therefore also be used to adjust differences in self-reported health, satisfaction with life, etc. between socio-economic groups for differential item functioning between these groups. This will improve comparisons across socio-economic groups within and between countries and will create opportunities for richer studies of gender differences, education and age differences, etc. in the distribution of health, well-being, satisfaction with employment, etc.

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B.4 The consortium and project resources Describe the role of the participants and the specific skills of each of them. Show how the participants are suited and committed to the tasks assigned to them; show the complementarity between participants. Describe how the opportunity of involving SMEs has been addressed. Describe the resources, human and material, that will be deployed for the implementation of the project. Include a STREP Project Effort Form, as shown below, covering the full duration of the project. Demonstrate how the project will mobilise the critical mass of resources (personnel, equipment, finance…) necessary for success; and show that the overall financial plan for the project is adequate. (Recommended length –1-2 pages per participant)

B.4.a Participants

The consortium has 14 participants:

1. CentER at Tilburg University, represented by Arthur van Soest. CentER, the Center for Economic Research, will co-ordinate the project, lead the development and implementation of the vignettes, and supervise the data collection in the Netherlands. CentER is an internationally oriented research institute of the Faculty of Economics and Business Administration of Tilburg University with a lot of experience in internationally collaborative projects and data collection. Arthur van Soest has co-ordinated the development of health and work disability related vignettes in an NIA-sponsored project and is therefore ideally suited to lead this comparative project (Workpackage WP1) and to lead the development of further vignettes (WP2) and their evaluation (WP4). He also was Dutch country team leader in the baseline wave of SHARE and will use his experience to also lead the Dutch country team in this project (WP10).

2. MEA at Mannheim University, represented by Axel Börsch-Supan. MEA, the Mannheim Research Institute for the Economics of Aging is an Institute of the Department of Economics at the University of Mannheim. It has been founded in 2001 and has rapidly developed into one of the world-renowned centres of excellence for the economics of ageing. The director of MEA, Axel Börsch-Supan, has co-ordinated the data collection in the baseline wave of SHARE 2002-2004, and has co-ordinated the AMANDA evaluation project based on the SHARE data 2003-2005. He is therefore ideally suited to co-ordinate the data collection required for this project (WP3) and to link it with the overall SHARE project. He also was German country team leader in the baseline survey of SHARE and will use his experience to also lead the German country team in this project (WP12).

3.-14. Individual Country Teams. The country teams will translate the vignettes developed in Workpackage 2 and supervise data collection by survey agencies to be subcontracted (see B.4.1). Almost all institutions and their representatives have also been country team leaders in the baseline wave of SHARE and will use their experience to lead the country teams in this project (WP5-WP18).

The participants are described in greater detail below (B.4.d). They are well suited and committed to the tasks assigned to them, as was documented in the highly successful SHARE and AMANDA projects funded by the European Commission’s 5th framework programme. They have worked together now for more than three years and have developed a high degree of cooperation and complementarity. Arthur van Soest and Axel Börsch-Supan have participated in many internationally comparative projects on subjects (such as retirement behaviour, savings behaviour, and the economics of ageing), and methodological subjects (such as econometrics, data collection and response analysis). The design experience of Arthur van Soest complements well with the data collection experiences of Axel Börsch- Supan.

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B.4.b Small and Medium Enterprises (SME)

All data collection and the programming of the questionnaire will be performed by small and medium enterprises (SME). Data collection is a highly specialised task that will be subcontracted to SMEs in each country. In addition, CentERdata, a small service provider for IT-based survey techniques, will be subcontracted for programming and implementation tasks, see B.4.1.

B.4.c Human and Financial Resources

Participants in the proposal use the added-cost model (AC). The project duration is 24 months. Team leaders are paid fully by the respective universities and need no additional support. Co- ordinator (WP1, 2 and 4) and survey manager (WP3) will dedicate 30% of their time (each 7.2 person months), while all other team leaders will dedicate 20% of their time to the project (11 country team leaders at 20% of 24 months totals 52.8 person months).4 In addition, the co-ordinating institution will contribute another 33.3 fte. for assisting the co- ordinator in general co-ordination tasks (8 person months). Total dedicated time sums up to 75.2 person months. Each team will have a full-time equivalent researcher for those project periods in which their work is fully required, in other periods half-time. The country team researchers will help in developing and translating the vignettes; in co-ordinating the data collection with the survey agency; and in evaluating the responses. In addition, one researcher will support the development of the vignettes, their analysis, and the construction of conversion factors, and one researcher the co-ordination of the data collection across countries. Personnel effort is detailed in the time line, see B.6.1. Total researcher time is 11 person months for all participants except CentER (17 person months) and MEA (16 person months), totalling 154 person months.5 Additional human resources (total of 358 person months) will be mobilised by subcon- tracting data collection and programming as described in B.4.1. This corresponds to 27 person months of interviewer and fieldwork time in each of the 13 countries, plus 7 person months for programming and similar IT-tasks. Personnel resources correspond in proportion to those actually used in the SHARE project 2002-2004. Total human resources are 587.2 person months. Total personnel costs for researchers are 637,462 Euro, based on the person months detailed above and the salary of a researcher according to the European Commission’s Marie-Curie programme. Each team is assigned 8,000 Euro in travel and subsistence. This will cover four meetings (design, after pilot; after pre-test; after main survey) to be held in central locations. For the final conference open to the scientific community at large, with parts tailored specifically for EU policymakers in order to disseminate the results of this study to the public policy community, we budget 40,000 Euro. Travel and subsistence thus total 144,000 Euro, excluding overhead. Overhead to personnel, travel and subsistence (20%) amounts to 156,292 Euro. The largest budget item is the cost of data collection. In order to obtain a reliable sample and based on the preliminary experiences of the NIA-sponsored vignette project, each country will need a sample of 600 households. Based on the SHARE baseline survey, we assume that a

4 The two team leaders in Belgium contribute 10% each. 5 For the two Belgium teams (French speaking and Dutch speaking), the effort is 5.5 months each.

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 21 household interview costs about 142.50 Euro on average, varying by country from 115 to 195 Euro. With 13 countries involved, this sums up to 1,245,500 Euro for data collection. Finally, programming and related IT-tasks are subcontracted to CentERdata. The subcontract volume is computed in proportion to the length of the vignettes questionnaire, again using the SHARE baseline survey costs as a base, and implies costs of 48,500 Euro. The total budget is 2,183,254 Euro including overhead on personnel, travel and subsistence is detailed and itemised in Table B.4.c:

TABLE B.4.c: BUDGET ELEMENTS BY PARTICIPANT

Partner Marie- Person Curie Survey months Personnel Travel&SubOverhead Total Subcontract Grand total CentER 1 UTILB 0.94 175.0 17 74,573 48,000 24,515 147,088 153,500 300,588 MEA 2 MEA 1.00 135.0 16 74,667 8,000 16,533 99,200 81,000 180,200 Austria 3 JKULINZ 1.00 155.0 11 51,333 8,000 11,867 71,200 93,000 164,200 Belgium_F 4 ULG 0.94 155.0 5.5 24,226 4,000 5,645 33,871 46,500 80,371 Belgium_D 5 UNIANT 0.94 155.0 5.5 24,226 4,000 5,645 33,871 46,500 80,371 Czech Republic 6 CERGE-EI 0.71 115.0 11 36,667 8,000 8,933 53,600 69,000 122,600 Denmark 7 SDU 0.97 175.0 11 49,584 8,000 11,517 69,101 105,000 174,101 France 8 IRDES 0.82 145.0 11 41,905 8,000 9,981 59,886 87,000 146,886 Greece 9 UPANTE 0.71 115.0 11 36,667 8,000 8,933 53,600 69,000 122,600 Italy 10 UNIPADUA 0.86 145.0 11 44,325 8,000 10,465 62,790 87,000 149,790 Poland 11 WNE-UW 0.71 115.0 11 36,667 8,000 8,933 53,600 69,000 122,600 Spain 12 CEMFI 0.76 175.0 11 39,202 8,000 9,440 56,642 105,000 161,642 Sweden 13 UNIUPPS 1.02 195.0 11 52,601 8,000 12,120 72,721 117,000 189,721 Switzerland 14 UNIL 0.99 195.0 11 50,820 8,000 11,764 70,584 117,000 187,584 Total 142.5 154 637,462 144,000 156,292 937,754 1,245,500 2,183,254

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B.4.d Detailed Description of Participants

1. CentER at Tilburg University, represented by Arthur van Soest

CentER will be the co-ordinating institution. CentER is the research institute of the Faculty of Economics and Business Administration of Tilburg University. It is an internationally oriented research institute, covering all fields in economics and business administration. It was established in 1998. Since 1992, it is also the faculty’s graduate school, providing research Master’s and PhD programmes in economics, business, and management, with about 18 PhD students enrolling in the PhD programmes each year. CentER offers a variety of research facilities, such as excellent computer facilities, competent supporting staff, a state-of-the-art economics laboratory for conducting experiments, and access to databases. CentER cooperates with CentERdata, a survey research institute, situated at the campus of Tilburg University, hosting its own large-scale household Internet panel that is representative for the Dutch population. Researchers have the opportunity to field questions in this panel at non-commercial costs. CentER has a lively visitor’s programme with about 60 international visitors per year, and organises about 7 research seminars per week. CentER’s research output in economics was ranked 18th in the world and 1st in Europe in the most recent ranking published by the Journal of European Economic Association (December 2003). The Royal Dutch Academy of the Arts and Sciences (KNAW) has re-accredited CentER as a research school in 2002, qualifying CentER as ”belonging to the European Top.” CentER is the co-ordinator of the ENTER Marie Curie Training Site and has been a participant in numerous EU and other international projects in different areas. The most relevant are ”Savings and Consumption” for which CentER was the co-ordinator, its successor ”Economics of Ageing in Europe” (AGE), ”A Survey of Health, Ageing, and Retirement in Europe” (SHARE), and ”Advanced Multidisciplinary Analysis of New Data of Ageing” (AMANDA). Many researchers at CentER also participate in CAR, CentER Applied Research, or Netspar, the Network for Studies on Pensions, Ageing and Retirement. CentER Applied Research provides a link between the university and the public and private sector, focusing on commissioned research projects at a scientific level. Netspar is a new network hosted by Tilburg University and CentER, with participants from several Dutch universities and partners in the private and public sector (pension funds, insurance companies, ministries, etc.), bringing together academic researchers from different fields, disciplines, backgrounds and institutions to stimulate research on pensions, ageing, retirement, etc. Arthur van Soest (Professor of Econometrics at CentER and senior economist at RAND, Santa Monica) will be responsible for the overall co-ordination of the project and lead the working group on vignette design. He will also lead the Dutch country team. His research focuses on micro-econometrics, discrete choice models, panel data, labour economics, labour supply, minimum wages, wage differentials, consumer behaviour, savings and portfolio choice, and income expectations. His recent work focuses on the economics of ageing. Current projects investigate analyzing preferences for and restrictions on gradual and partial retirement, studying expectations of in social security and pension income after retirement and of well-being in retirement, an international comparison of work disability, an analysis of portfolio adjustment around retirement, and testing for causal mechanisms from health to socio-economic status and vice versa. Most of these projects are funded by the US National Institute of Aging or the Michigan Retirement Research Centre. A list of recent publications can be found below. He supervised 12 PhD theses. He also co-ordinated the work of the Tilburg participation in the European Commissions 5th Framework programme’s RTN project

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AGE, and the RTD projects SHARE and AMANDA. For the baseline wave of SHARE, he was responsible for data validation and data base management and developed the vignette questionnaire. Other members of the research team are Frederic Vermeulen, assistant-professor at CentER specialised in applied micro who worked on collective models of labour supply and retirement behaviour of couples, Jan Nelissen, senior economist at CentER Applied Research and an expert in the economics of social security, and Gijsbert van Lomwel, also affiliated with CentER Applied Research and an expert in the economics of health care. Recent publications of Arthur van Soest are: • J. Banks, A. Kapteyn, J.P. Smith, and A. van Soest (2004), International Comparisons of Work Disability, CentER Discussion paper 2004-36. • R. Alessie, S. Hochguertel and A. van Soest (2004): Ownership of stocks and mutual funds: a panel data analysis, Review of Economics and Statistics, 86(3), 783-796. • C. Dustmann and A. van Soest (2004): An analysis of speaking fluency of immigrants using ordered response models with classification errors, Journal of Economic and Business Statistics, 22(3), 312-321. • X. Gong, A. van Soest and E. Villagomez (2004): Mobility in the urban labor market: a panel data analysis for Mexico, Economic Development and Cultural Change, 53(1), 1-36. • C. Dustmann, N. Rajah and A. van Soest (2003): Class size, education, and wages, Economic Journal, 113 (485). • X. Gong and A. van Soest (2002): Family structure and female labour supply in Mexico City, Journal of Human Resources, 37 (1), 163-191. • C. Dustmann and A. van Soest (2002): Language and the earnings of immigrants, Industrial and Labor Relations Review, 55(3), 473-492. • A. Van Soest, A., M. Das and X. Gong (2002): A structural labour supply model with flexible preferences, Journal of Econometrics, 107, 354-374. • S. Hochguertel and A. van Soest (2001), The relation between financial and housing wealth: evidence from Dutch households, Journal of Urban Economics, 49, 374-403. • M. Das, J. Dominitz and A. van Soest (1999): Comparing predictions and outcomes: Theory and application to income changes, Journal of the American Statistical Association, 94, 75-85.

2. MEA at the University of Mannheim, represented by Axel Börsch-Supan

The Mannheim Research Institute for the Economics of Aging is an Institute of the Department of Economics at the University of Mannheim. It has been founded in 2001 and has rapidly developed into one of the world-renowned centres of excellence for the economics of ageing. Its general aim is to anticipate and monitor the micro and macroeconomic aspects of population aging. The activities of the MEA are divided into four broad areas of research: • Social policy implications of aging, especially for pension systems and health care provision

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• Savings behaviour of households, especially in old age • Macroeconomic implications of an aging society, especially on growth and productivity • Public health and statistical analysis of data on health, ageing and retirement MEA currently employs a staff of 18 scientists, some 25 research-assistants, 3 part-time administrative staff. MEA has its own PC-based network with several servers, including facilities to handle very large data sets and confidential data. The institute has a library, a conference room, and all necessary technical support facilities. MEA publishes a quarterly newsletter and its own discussion paper series. MEA is the co-ordinating institution of the RTD-projects SHARE and AMANDA under the European Commission’s 5th framework programme and is a participant in the RTN-project AGE.

Axel Boersch-Supan will co-ordinate the data collection in the project. He will also lead the German country team. He has co-ordinated the SHARE and AMANDA projects under the 5th framework programme. He was also responsible for data collection in Germany. Axel Börsch- Supan is Director of the Mannheim Research Institute for the Economics of Aging (MEA) and Professor for Macroeconomics and Public Policy at the University of Mannheim, Germany. He received his Ph.D. in economics from the Massachusetts Institute of Technology in 1984. From 1984-89 he was assistant professor of public policy at Harvard’s John F. Kennedy School of Government before he returned to Germany in 1989. Börsch-Supan is chairman of the Council of Advisors to the German Economics Ministry and chaired the pension reform unit of the German Social Security Reform Commission. He is speaker of the special research group on behavioural economics (SFB504) at the University of Mannheim, co-ordinator of the SHARE and AMANDA 5th framework programme projects, research associate at the National Bureau of Economic Research (NBER) in Cambridge, Mass., and member of the German Berlin-Brandenburg Academy of Sciences. He has written and edited more than a dozen books. His journal articles focus on saving and retirement behaviour, pension reform and population ageing and have been published e.g. in the American Economic Review, the Journal of Public Economics, the Journal of Econometrics, and in Economic Policy. Some recent publications are: • Börsch-Supan, A. et al. (eds.), 2005, Health, Ageing and Retirement in Europe: First Results of SHARE, in press. • Börsch-Supan, A. und B. Berkel, 2004, Pension Reform in Germany: The Impact on Retirement Decisions. Finanzarchiv, Vol 60, No. 3, 393-421. • Börsch-Supan, A., R. Euwals und A. Eymann, 2004, Who determines household savings for old age? Evidence from Dutch panel data, Journal of Economic Psychology, Vol. 25, 195-211. • Börsch-Supan, A., 2003, Labor Market Effects of Population Aging, Review of Labour Economics and Industrial Relations, Vol. 17, 5-44. • Börsch-Supan, A. (ed.), 2003, Life-Cycle Savings and Public Policy, Academic Press, NY. • Börsch-Supan, A. und L. Essig, 2003, Stockholding in Germany, In: Luigi Guiso, Michael Haliassos and Tullio Jappelli (eds.), Stockholding in Europe, Palgrave MacMillan. • Boeri, T., A. Börsch-Supan, and G. Tabellini, 2002, Would you like to Reform the Pension System? The Opinions of European Citizens, American Economic Review, Vol. 92, 396- 401.

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• Börsch-Supan, A., Heiss, F. A. Ludwig, and J. Winter, 2003, Pension Reform, Capital Markets, and the Rate of Return, German Economic Review, Vol. 4, 151-181. • Börsch-Supan, A., 2001, International Comparison of Household Savings Behaviour: A Study of Life-Cycle Savings in Seven Countries, Research in Economics, Vol. 55, 1-14. • Börsch-Supan, A. und A. Reil-Held, 2001, How much is Transfer and how much Insurance in a Pay-As-You-Go System? Scandinavian Journal of Economics, Vol. 103, 505-524.

Description of country teams

The remaining participants represent the country teams in the countries other than the Netherlands and Germany. Almost all country teams will be identical to the country teams in SHARE 2004 and leverage their experiences for this project; exceptions are Denmark, where a new country team has been formed, led by Kaare Christensen (a well-known epidemiologist with a large experience in data collection amongst the elderly and extremely well suited for this task), and the two accession countries, which are new participants in the SHARE-related data collection. The Belgium team is for practical reasons divided into language regions; resources are split accordingly. Both teams work closely together as they have done in the successful 2004 SHARE baseline project.

3. Country Team Austria: University of Linz, represented by Rudolf Winter-Ebmer

The Department of Economics at the Johannes Kepler University of Linz has 20 members. It is a well establish research-oriented department with a young faculty. Independent studies evaluating publication records of economics departments throughout Austria, Germany and Switzerland show that the Department of Economics at JKU Linz has accumulated an impressive standing and degree of international recognition. The main research focus is on labour economics, public economics and problems of pension reform as well environmental economics. In these areas, members of the Department have published in the leading field journals and have contributed to the public discussion about these issues in Austria and abroad. Department members are active in international and national consulting – to the World Bank, the EU commission as well as the Austrian government; they are on the board or heading the major economic research institutions in Austria. The Department publishes its own discussion paper series. In recent years it got research funding from the EU, the Austrian Science Funds and the Austrian Central Bank. Members of the Department were involved in recent EU funded research concerning Eastern Enlargement of the Union, education policies and they have administered the first SHARE survey for Austria. Rudolf Winter-Ebmer is Professor of Economics at the University of Linz and Research Professor at the Institute for Advanced Studies in Vienna. He is a specialist in empirical labour economics and has worked on issues of ageing, wage determination, unemployment and education. He holds a PhD in economics from the University of Linz, has taught at Vienna, Innsbruck and Zurich. He is a Research Fellow of the London-based Centre for Economic Policy Research (CEPR) and at the Institute for the Future of Labour (IZA) in Bonn. He has published widely in journals like the American Economic Review, Journal of Labor Economics, the Journal of Human Resources and European Economic Review. He has

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 26 been heading EU-projects on education and ageing in the recent years. Some of his recent publications are: • Rudolf Winter-Ebmer (2003): “Benefit Duration and Unemployment Entry: Quasi Experimental Evidence for Austria”, European Economic Review, Vol. 47, 259-273. • Andrea Ichino, Rudolf Winter-Ebmer (2003), "The long-run Educational Cost of World War 2: An Example of Local Average Treatment Effect Estimation", Journal of Labor Economics, Vol. 22, 57-88. • Doris Weichselbaumer, Rudolf Winter-Ebmer (2005), "A meta-analysis of the international gender wage gap", Journal of Economic Surveys, forthcoming. • Brunello, G., C. Lucifora and R. Winter-Ebmer (2004), The wage expectations of European Business and Economics students, Journal of Human Resources, 39, 1116- 1142.

4. Country Team Belgium (French Speaking): University of Liège, represented by Sergio Perelman

CREPP, Centre of Research in Public and Population Economics as part of the University of Liège, is in charge of the SHARE project co-ordination in the Belgian French speaking community. CREPP main fields of specialisation are social security, particularly pension schemes and retirement behaviour, well-being among the elderly and intergenerational transfers. Several CREPP research projects are financed by the Belgian Science Policy Administration, particularly the baseline wave of SHARE (AGORA Program), the National Science Foundation (FNRS, FRFC Program), and the French Community (ARC Program). The Centre participates in the NBER International Social Security Project and to the European Financing Retirement (FINRET) network. In 2005 the CREPP staff is composed of 4 professors, 4 PhD students and 3 researchers. Sergio Perelman is Professor of Economics at the University of Liège and research associate at CREPP. His main fields of specialisation are social security, income distribution and labour participation among elderly people, and productivity analysis, technical efficiency and productivity growth. Over last years, Sergio Perelman participated actively in the International Social Security NBER project on "Retirement around the World" and also with the World Bank Institute program on Infrastructure Regulation. His recent publications include: • Dellis A., Desmet R., Jousten A. and S. Perelman, Micro-modeling of retirement in Belgium, in Gruber, J. and D. Wise (eds.), Micro Modelling of Retirement Incentives in the World, University of Chicago Press and NBER, 2004, 41-98. • Desmet R., Jousten A., Perelman S. and P. Pestieau, Microsimulation of social security reforms in Belgium, in Gruber, J. and D. Wise (eds.), Social Security Programs and Retirement Around the World: Fiscal Implications, University of Chicago Press and NBER (2005).

5. Country Team Belgium (Dutch Speaking): University of Antwerp, represented by Karel Van den Bosch

CSP, Centre for Social Policy, University of Antwerp, directs the Flemish part of Belgian SHARE project. Since its establishment in 1972 the Centre's principal objective has been to study the adequacy of social policies. Its research is mainly based on large-scale socio- economic surveys of households in Belgium and Flanders. On the basis of these surveys the

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CSP has monitored trends in the extent and distribution of income, welfare and poverty in Flanders and Belgium since 1976; in this field the CSP figures have in fact become the main reference point within Belgium. On the European level it co-ordinated the EUROPASS project, which was one of the first international comparative research projects on poverty and social security. Among other current international projects and networks, it is part of the EQUALSOC network, organised by Atkinson and Erikson. The CSP is the leading partner of a Flemish research consortium, funded by the Flemish government for the period 2005-2008 to study the social and economic impact of ageing in Flanders and Europe, with a focus on policy implications. In 2005 the CSP staff included 2 full professors, 2 lecturers, 2 post- doctoral researchers 4 PhD students, and 10 researchers. Karel Van den Bosch obtained his doctorate in the Social and Political Sciences in 1999. He now works as senior researcher at the Centre for Social Policy, University of Antwerp, Belgium. He teaches data-analysis at the University of Antwerp and also at the Catholic University of Brussels. His main research interests are poverty, income distribution, and the impact of the welfare state on these. Recent publications include: • Van den Bosch, K., Identifying the poor, using subjective and consensual measures, Aldershot: Ashgate, 2001, 445 p. • Cantillon Bea, Marx Ive, Van den Bosch Karel, "The puzzle of egalitarianism: relationship between employment, wage inequality, social expenditure and poverty" In: European journal of social security, 5:2(2003), pp. 108-127 • Van den Bosch, Karel, “Policy Impact”. Chapter IV-6 in: Rein, M., Moran, M. and Goodin, R. (eds.), Oxford Handbook of Public Policy, Oxford University Press (forthcoming)

6. Country Team Czech Republic: CERGE-EI, Prague, represented by Radim Bohacek

CERGE-EI is a joint workplace of the Center for Economic Research and Graduate Education of Charles University and the Economics Institute of the Academy of Sciences of the Czech Republic. CERGE-EI was founded in 1991 and its Ph.D. program in Economics is fully accredited in both the United States and the Czech Republic. Its main expertise is in social, economic and political transition in the Central and Eastern European countries and in the former Soviet Union region. The goals and interests of the institution are to stimulate and support academic and policy-oriented economic research; to disseminate this research and policy information to government, academic and business organisations; and to facilitate the transfer of modern western standards of economic instruction and scientific work to the Czech Republic and other countries of Central and Eastern Europe. CERGE-EI has grown to be recognised as a regional centre of educational excellence and has won numerous accolades from US governmental institutions, the European Commission, international grant authorities and research organisations: in 1992 and 1994, the European Community Secretariat of the ACE Programme designated the institution the only "Recognised Centre of Excellence in Ph.D. Studies in Economics" in Central and Eastern Europe, and in 1993 and 1994, CERGE- EI was recognised as a Center of Excellence in Economics Education and Research by the USAID. CERGE-EI employs 20 full-time faculty and has around 200 students from more than 20 transition countries. Radim Bohacek received his PhD in Economics at the University of Chicago in 1999 and holds MAs in Economics as well as Public Policy Studies and History from University of Chicago. He is Assistant Professor of Economics at CERGE-EI since 2000. His research focuses on general equilibrium models with heterogeneous agents, optimal fiscal and monetary government policies, and contract theory. He has published papers on “Optimal Tax

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Schedule” (with Michal Kejak, 2004), “Credit Markets and the Propagation of Monetary Policy Shocks” (with Hugo Rodriguez-Mendizabal, 2004), “The Efficiency-Equality Tradeoff in Social Insurance” (2003) and “Financial Constraints and Entrepreneurial Investment” (2003).

7. Country Team Denmark: University of Southern Denmark, Odense, represented by Kaare Christensen

The Institute of Public Health is located at the Medical Faculty of the University of Southern Denmark, Odense. The section of epidemiology comprises expertise in ageing research, clinical epidemiology, twin research, and medical demography. It has experience in establishing population-based clinical and demographic databases including bio-banking, with special emphasis on elderly twins, oldest-olds and centenarians. The focus of the research is determinants of ageing and longevity, age-related diseases, and quantitative biological variation. The main resources of the group are The Danish Twin Registry, the Twin Bio-bank, the 1905 Cohort and the Danish Centenarian Cohort, which include longitudinal studies of aging and mortality. Based on the work with these resources, the group has considerable experience in database management and participation in international population-based surveys, such as the GENOMEUTWIN study, the GEHA-study (Genetics of Healthy Aging) and the first SHARE study. Moreover the group has a long-standing interest in conducting large-scale surveys among older and oldest-old people, which at this point of time augments to more than 10,000 interviews. Kaare Christensen, MD, PhD, Dr MSci. is Professor of Epidemiology, Institute of Public Health, University of Southern Denmark and Senior Research Scientist (part-time employment) at the Terry Sanford Institute, Duke University, North Carolina, USA. He has been member of working groups and advisory panels appointed by US National Research Council, Washington DC, USA and the National Institute on Aging, Bethesda, USA. Kaare Christensen has conducted a long series of twin studies among the elderly in order to shed light on the relative contribution of genes and environment in ageing and longevity. He is engaged in interdisciplinary ageing research combining methods from epidemiology, genetics and demography. Selected publications include: • Vaupel JW, Carey J., Christensen K. It’s never too late. Science 2003; 301:1679-80. • Nybo H, Petersen HC, Gaist D, Jeune B, Andersen K, McGue M, Vaupel JW, Christensen K Predictors of mortality in 2,249 nonagenarians - the Danish 1905-Cohort Survey. Journal of the American Geriatrics Society 2003;51:1365-73. • Frederiksen H, McGue M, Jeune B, Gaist D, Nybo H, Skytthe A, Vaupel JW, Christensen K. Do children of long-lived parents age more successfully? Epidemiology 2002;13:334- 339. • Christensen K, Gaist D, Vaupel JW, McGue M. Genetic contribution to rate of change in functional abilities among Danish twins aged 75 years or more. Am J Epidemiol. 2002;155: 132-9.

8. Country Team France: IRDES, Paris, represented by Didier Blanchet

IRDES, Institut de Recherches et de Documentation en Economie de la Santé (formerly CREDES) is a non-profit association founded in 1985. Its mission is to provide a basis for the understanding of the future of the health care system. IRDES's multidisciplinary team monitors and analyses trends in the behaviour of consumers and health care professionals

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 29 from a medical, economic, geographic and sociological perspective. To this aim, IRDES conducts studies and research based primarily on data from its own surveys or those placed at its disposal, as well as on information collected from scientific literature, and from foreign systems. These activities cover a variety of issues regarding the supply and demand of care from a macro and micro-economic standpoint: trend analysis of morbidity and access to health care, studies of physicians' prescription practices, determinants of health care utilisation, evaluation of alternatives to hospitalisation. Didier Blanchet is head of the Department of Economic Studies at INSEE, the French National Statistical Institute. He holds diplomas from the Ecole Polytechnique, from ENSAE and a PhD in economics from the Institut d’Etudes Politiques de Paris. He has been a researcher at the National Institute of Demographic Studies from 1978 to 1993. Since 1993, he has occupied various positions within INSEE, including director of ENSAE and head of the Department of Employment and Labour Income Statistics. He is a member of the French Pensions Advisory Council. Main recent publications include: • Demographie et Economie, Report from the Conseil d’Analyse Economique, La Documentation Française (2002, with M. Aglietta et F. Héran). • France: the difficult path to consensual reforms, in Social Security Pension Reform in Europe, M. Feldstein et H. Siebert, Eds, NBER/The University of Chicago Press, (2002, with Fl. Legros). • Estimating models of retirement behaviour on French data, in Social Security Programs and Retirement Around the World, J. Gruber et D.A. Wise, Eds, NBER/The University of Chicago Press (2004, with R. Mahieu).

9. Country Team Greece: Regional Development Institute at Panteion University, Athens, represented by Antigone Lyberaki

The Regional Development Institute for university research was formally established in Athens (Greece), in 1975, and sprang from the Institute of Regional Development, which was founded by presidential decree the same year. It is a university research centre affiliated to the Department of Urban and Regional Development of Panteion University of Social and Political Sciences (Athens), which operates under the form of a private legal entity as an educational research centre. The main task of the Institute is the advancement of the research in all fields of the developmental process. This is achieved by linking urban, local and regional development issues with broader National and EU processes, and by promoting a regular exchange of ideas and experience on a worldwide basis. The Institute is also concerned with the advancement of theory and with addressing current development problems. Also of significant importance is the fact that the RDI, in collaboration with the Greek State and the EU, has contributed substantially to the formulation of research studies on Regional Development Planning and Policy Making. Antigone Lyberaki is Professor of Economics at Panteion University in Athens. She has a Ph.D. in Economics and an MPhil in Development Studies from IDS at Sussex University. She was a member of the EU Business Environment Simplification Task Force (BEST), which reported in 1997-98 and has acted as co-ordinator for three Greek National Action Plans for Employment between 2001 and 2003. She has also participated in the preparation of the National Action Plan for Social Inclusion 2003-2005. Her current research interests are migration, ageing societies and gender. Recent publications include: • “Inflow of migrants and outflow of FDI: Aspects of interdependence between Greece and the Balkans” (2003) with L.Labrianidis, P.Tinios & P. Hatziprokopiou), Journal of Ethnic and Migration Studies (JEMS),

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• “Innovation, Structural Change and Convergence: SME financing in Greece” (2005 forthcoming OUP with Giannitsis & Milonas), • “Changing labour markets and their implication for social protection” (forthcoming). She co-authored “Work and Cohesion” (2002 with P.Tinios) and “Flexible Work: new forms and quality of employment” (2004 with G.Dendrinos).

10. Country Team Italy: University of Padua, represented by Guglielmo Weber

The Economics Department of Università di Padova will be responsible for supervising the data collection process in Italy, and for revising the questionnaire sections on income and assets. The Economics Department now counts around 60 members whose teaching and research interests cover the whole spectrum of economics and management science. Of particular relevance to this proposal is the presence of research groups in applied econometrics, public and health economics as well as labour economics. The applied econometricians have a strong record in the analysis of consumer choice, covering saving, household portfolio choice, and consumer demand. All fields of economics are covered, including public and health economics, as well as econometrics and labour economics. The Department has been involved in SHARE from its inception: Prof. Guglielmo Weber has been country team leader, responsible for the data collection of the baseline wave of data in Italy, and (in the follow-up project, AMANDA) working group leader on assets and expectations, as well as in the AGE TRN-project. Guglielmo Weber (Ph.D. economics, LSE 1988) is a full professor of econometrics at the Statistics Faculty and head of the Economics Department. He previously worked at University College London and Università di Venezia. He is also an international research affiliate of the Institute for Fiscal Studies (London) and CEPR research fellow. His specialisation is the econometric analysis of consumer behaviour using survey data. He has worked on US, UK and Italian household survey data analysing demand patterns, saving and household portfolio decisions. He has also been involved in the analysis of recall errors in consumer survey data, within a working group set up by the Italian Central Statistical Office (ISTAT) in co- operation with the Bank of Italy. His publications include: • Weber, G., R. Blundell, P. Pashardes (1993), What Do We Learn On Consumer Demand Patterns From Micro data?, American Economic Review 83, 570-97. • G. Weber C. Meghir (1996), Intertemporal Non-Separability or Liquidity Constraints? A Disaggregate Analysis on US Panel Data, Econometrica 64, 1151-81. • Weber, G., O. P. Attanasio, J. Banks, C. Meghir (1999), Humps and Bumps in Lifetime Consumption, Journal of Business & Economic Statistics 17, 22-35. • Weber G., M. Browning, T. Crossley (2003) Asking Consumption Questions in General Purpose Surveys Economic Journal , 113, F540-F587

11. Country Team Poland: University of Warsaw, represented by Michal Myck

Though economics has always been taught at the Warsaw University (founded in 1816), it was not until 1953 when a separate Department of Economics (or translated literally from Polish: Department of Economic Sciences) was created. In its past among many distinguished professors, people such as Oskar Lange and Michal Kalecki were among its staff. Over the past fifty years the Department awarded over 350 PhD degrees and over 100 people received

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 31 the habilitation. The department plays an important role in the development of economic theory and policy in Poland. Members of its academic staff have played an active part in the design and operation of the process of Poland’s economic transformation. At the moment the Department has 100 members of permanent academic staff and provides courses for 1800 students from Poland and abroad. Teaching and research is organised in thirteen Chairs and covers a broad range of areas, from economic history to econometrics and from economic policy to information technology. Michał Myck received his Economics MPhil from Oxford and a Ph.D. in Economics from Warsaw University. He has been Senior Research Economist at the Institute for Fiscal Studies in London before he returned to Warsaw University. He is currently International Research Associate at the Institute for Fiscal Studies. His recent publications include: • “The Role of Employment Experience in Explaining the Gender Gap”, IFS Working Paper Series, WP04/16, 2004, with G. Paull. • “Taxes and Transfers”, Oxford Review of Economic Policy, vol.18 no. 2, 2002, pp. 187- 201, with T. Clark, A. Dilnot, and A. Goodman. • “The Returns to Academic and Vocational Qualifications in Britain”, Bulletin of Economic Research, vol.54, no.3, 2002, pp. 249-273, with L. Dearden L., S. McIntosh, and A. Vihnoles.

12. Country Team Spain: CEMFI, Madrid, represented by Pedro Mira

CEMFI is a graduate school set up by Bank of Spain as a non-profit independent foundation in 1987. Its goals are the graduate teaching and research in all fields of Economics and Finance. The teaching activities at CEMFI include a two-year Master’s program, a Ph.D. group, and a Summer School. Currently, it has a full-time faculty of ten professors which includes an active group of researchers with specific empirical interests in consumption, savings, labour markets and population economics. Pedro Mira received a B.A. in Economics in 1988 from Universidad Complutense and a Ph.D. in Economics in 1995 from the University of Minnesota. He has been an Associate Professor of Economics at CEMFI since 2001. His research interests include Labour and Population Economics and the structural estimation of dynamic models of discrete choice. He is a member of the Editorial board of Investigaciones Economicas. He served as deputy country leader of the Spanish country team during the baseline wave of SHARE. Recent publications include: • Swapping the nested fixed point algorithm: A class of estimators for discrete Markov decision models (with V. Aguirregabiria), Econometrica 70 (2002) pp.1519-1543. • A Note on the Changing Relationship Between Fertility and Female Employment in Developed Countries (with N. Ahn), Journal of Population Economics (2002), 15:667- 682. • Job Bust, Baby Bust: Evidence from Spain, (with N. Ahn), Journal of Population Economics 14 (2001) pp. 505-521.

13. Country Team Sweden: University of Uppsala, represented by Anders Klevmarken

Uppsala University is one of the oldest universities in Northern Europe and includes all faculties. It has a strong research orientation and undergraduate and graduate teaching programs in all faculties. The Department of Economics is an active research institution with

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 32 both graduate and undergraduate programs. There are about 10 tenured full professors and about 25 additional department members with a PhD in teaching or research positions. Much of the research is oriented towards microeconomic issues and usually with an empirical policy focus. Department members have been instrumental in building up the Swedish Household Panel Survey (HUS) and the longitudinal register based micro data set LINDA. Labour economics is very strong, but there are also strong groups in public economics, micro econometrics, housing economics and macroeconomics. In terms of publications in leading international economic journals the Department of Economics at Uppsala University is one of the top four economics departments in the Nordic Countries. Anders Klevmarken holds a PhD in statistics from Stockholm University. He was professor of Econometrics at the Swedish Council for Humanities and Social sciences. He has also had research positions at Statistics Sweden and The Industrial Institute for Economic and Social Research (IUI), been department head at the National Social Insurance Board (RFV) and visiting professor/scholar to the University of Georgia and the University of Michigan. He was the president of the European Society for Population Economics and served as a member of the Swedish Council for Social Research. He is a member of the scientific council of Statistics Sweden and of the standing committee for the consumer price index. Klevmarken has twenty years of experience with data collection and survey research and initiated the Swedish household panel survey Household Market and Nonmarket Activities (HUS) Recent selected publications are: • On Ageing and Earnings, in Labour Markets in an Ageing Europe, ed. by P. Johnson and K.F. Zimmerman, Cambridge University Press, 1993. • Inequality and Mobility of Wealth in Sweden 1983/84-1992/93 (jointly with Lars Bager- Sjögren), Review of Income and Wealth; 44(4), December 1998, 473-495. • Did the Tax Cuts Increase Hours of Work? A Statistical Analysis of a Natural Experiment, Kyklos, Vol. 53, 3, 2000, 337-361.

14. Country Team Switzerland: University of Lausanne, represented by Alberto Holly

The Institute of Health Economics and Management (IEMS) is an interdisciplinary institute founded in 1998 by the Ecole des Hautes Etudes Commerciales (HEC) and the Faculty of Medicine, with the active support from the Hospital Administration of the Canton de Vaud. IEMS has been created in order to reinforce synergy between Health Economics and Management related disciplines - Economics, Management, Medicine, Public Health, Sociology/Anthropology, Demography and Law- and to promote advanced training and high quality research in Health Economics. The collaboration of IEMS and IUMSP (Institute of Social and Preventive Medicine) has lead to the development of a unique centre of competence on Health Care Economics at the University of Lausanne. Alberto Holly is professor of econometrics at the Faculty of Economics (HEC) and director of the Institute of Health Economics and Management (IEMS) at the University of Lausanne. He has held visiting professor positions at Harvard University, MIT, London School of Economics and Political Sciences. He is a Fellow of the Econometric Society (elected in 1985) and has been Co-Editor of the Econometric Society Monograph Series. He has published many studies about estimation and specification testing in non-linear econometric models. For the past ten years, his research activity has been devoted to health economics issues, notably with the application of econometric methods in this field. In particular, he has investigated how the demand for health services can be influenced by regulatory changes and financing constraints. He has published in some of the leading journals in economics and

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 33 econometrics, including Econometrica, Econometric Theory, European Economic Review, Journal of Econometrics. Recent publications are: • “Technological Change in Treatment of Myocardial Infarction in Switzerland, 1986-1993” (with F. Paccaud), in: Global Analysis of Technological Change in Health Care: Heart Attacks; M. McClellan and D.Kessler (eds). Health Policy and Management Series, University of Michigan Press (2003). • “Risk Adjustment in Switzerland”(with K.Beck, S.Spycher, L.Gardiol), Health Policy, 65, 2003, 63-74. • “Risk Adjustment and Risk Selection on the Sickness Fund Insurance Market” (with Van de Ven, K. Beck, F. Buchner, D. Chernichovsky, L. Gardiol, LM Lamers, E. Schokkaert, A. Shmueli, S. Spycher, C. Van de Voorde, RCJA van Vliet, J. Wasem, I. Zmora), Health Policy, 65, 2003, 75–98.

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B.4.1 Sub-contracting If any part of the work is foreseen to be sub-contracted by the participant responsible for it, describe the work involved and explain why a sub-contract approach has been chosen for it. (Recommended length –1 page)

In each participating country, we will sub-contract all survey fieldwork to specialised, highly renowned fieldwork organisations. Conducting personal interviews in the general population is a highly specialised task that can only be done by experienced organisations. We will in all possible and reasonable cases re-contract the same agencies that have already conducted the SHARE survey in 2004.

Each survey agency will conduct 600 household interviews (approx. 900 respondents) and deliver the data in computer-readable form. Specifically, the agencies will: • Draw a probability sample of the population to be interviewed, where possible from the sample interviewed in 2004. • Train interviewers in general interviewing techniques and study-specific material • Organise the fieldwork • Supervise interviewers • Collect and deliver the data in computer-readable form Human resource effort by the survey agencies amounts to about 3 full-time persons for the 9 month of full-time data collection in each country, totalling 351 person months.

In addition, programming of the vignettes will be performed by CentERdata, a survey development company specialising in high-tech survey organisation and access management, which has already programmed the original SHARE questionnaire as a CAPI (Computer- Aided Personal Interview) instrument. In addition, CentERdata will perform all other IT-tasks such as database and access management. The project requires about 7 full-time equivalent person months for programming, database and access management.

Both tasks (interview collection and CAPI programming) are highly specialised and professional tasks that are most efficiently carried out by specialised subcontractors, all small and medium enterprises (SMEs).

B.4.2 Other countries If one or more of the participants is based outside of the EU and Associated states, explain in terms of the project’s objectives why this/these participants have been included, describe the level of importance of their contribution to the project. (Recommended length –1 page)

The project has one formal participant based outside the EU which is Switzerland. Switzerland has been part of SHARE from the beginning, and is an important part of this research because of its different health and pension system. This adds substantially to the much-needed institutional variation across countries.

The project will assemble an advisory board (see B.5). This board will also include researchers from the United States who have experience in the substantive issues of this proposal (Arie Kapteyn, RAND Corporation; James Smith, RAND Corporation; Norbert Schwarz, University of Michigan; Daniel Kahneman, Princeton University) and in the related data collection (Michael Hurd, RAND Corporation; Robert Willis, University of Michigan; David Weir, University of Michigan).

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B.5 Project management Describe the organisation, management and decision making structures of the project. Describe the plan for the management of knowledge, of intellectual property and of other innovation-related activities arising in the project. (Recommended length –3 pages)

Management of this project continues the highly successful co-operation in the SHARE and AMANDA projects under the 5th framework programme. It relies to a very large extent on the same persons who have collected the SHARE baseline data, designed the SHARE questionnaire, and did the analyses of the SHARE data under the AMANDA project. The lessons drawn and the experiences collected from the original SHARE project and the synergies between questionnaire design, data collection and data analysis are a major advantage in carrying out this STREP. The management structure corresponds to the workpackages (WP) described in Section B.6, and is displayed in Figure B.5:

FIGURE B.5: STRUCTURE OF PROJECT AND PROJECT MANAGEMENT

Overall coordination (WP1) (Arthur van Soest, CentER, Tilburg University)

Vignette design (WP2, WP4) Survey management (WP3) (Arthur van Soest, CentER, (Axel Börsch-Supan, MEA, Tilburg) Mannheim)

Receives input from Austrian Country team (WP5) area specialists (former SHARE and Belgian Country team (WP6,7) AMANDA working ….. groups) Swedish Country team (WP17)

Swiss Country team (WP18)

The co-ordinator, Arthur van Soest, Professor of Economics at Tilburg University and research associate at CentER, bears the overall responsibility (WP1). Specifically, the co- ordinator is responsible for implementing the project and maintaining the same high methodological standards in all participating countries. He is accountable for the project’s finances and deliverables. Tilburg University will provide the institutional support and the computer facilities for the co-ordination tasks. Project management is then split according to the two main project tasks. The development and evaluation of the vignettes (WP2 and WP4) are also led by Arthur van Soest, the co- ordinator of the project. Vignette development will exploit the experiences from the SHARE and AMANDA working groups who designed the subject modules of SHARE and have evaluated the preliminary SHARE data under the AMANDA project. Since the teams formed in SHARE and AMANDA are very well connected, no formal arrangements are necessary.

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Data collection will be centrally co-ordinated (WP3) and locally executed (WP5-18). Since data collection requires contractual arrangements, the leaders of the country teams will be formal partners in the research consortium. The co-ordination of data collection is done by Axel Boersch-Supan, the co-ordinator of the SHARE project, professor of economics at the University of Mannheim and director of the Mannheim Research Institute for the Economics of Aging (MEA). He will ensure cross- national comparability, timely delivery of interim and final data sets is done, documentation and delivery to a publicly accessible database (scientific user file). He will sign the subcontracts to field agencies proposed by the country team leaders. Technical and logistical support for the survey organisation, database management and user access administration will be subcontracted to CentERdata, a survey development company specialising in high-tech survey organisation and access management. CentERdata has programmed the questionnaire and the sample management system used in the 2004 baseline survey. The country teams (mostly identical with the SHARE country teams) represent Austria, Belgium (Dutch and French Speaking), the Czech Republic, Denmark, France, Germany, Greece, Italy, the Netherlands, Poland, Spain, Sweden and Switzerland. The country team leaders propose the field agencies to be subcontracted, sign-off the country- and language-specific survey instruments before they go into the field, and are responsible for observing legal requirements such as safety and confidentiality regulations. They sign off the final counts of surveys conducted and are responsible for the survey quality. The country team leaders are responsible for the implementation of the project in all of its phases in the respective countries and are accountable for their share of the project’s finances. Communication will largely rely on modern information technology. In particular, we will post results, drafts of the new longitudinal questionnaire, timelines and deadlines, milestones and deliverables on the Internet, to facilitate information sharing and feedback. This open information policy also serves an open structure which allows external researchers to participate whenever useful, and it closely links our research with that of researchers interested in cross-national comparisons. In addition, we will arrange working meetings at crucial points during the development process (before first pilot of vignettes, after pilot, after pre-test, and after the main survey). We aim to benefit as much as possible from the experience of others, including researchers involved in the ongoing US Health and Retirement Study (HRS) and the English Longitudinal Study on Ageing (ELSA) to maintain comparability with the Anglo-Saxon countries. The principal investigators from the HRS and ELSA have been asked and have accepted to serve on an advisory board and to participate in the meetings of the project. They will also be sent material for comments and asked for advice on anything that may affect the quality of our work. They have access to the same information as the participants in the project. The project will assemble a formal advisory board with researchers who have experience in the cross-national analysis of self-response and subjective data (Arie Kapteyn, RAND Corporation; James Smith, RAND Corporation; Norbert Schwarz, University of Michigan; Daniel Kahneman, Nobel laureate, Princeton University) and in the related data collection (Michael Hurd, RAND Corporation; Robert Willis, University of Michigan; David Weir, University of Michigan). From the English Longitudinal Study on Aging, Richard Blundell, Michael Marmot, James Nazroo, and James Banks will provide input. Progress monitoring and reporting will mainly take place during the working meetings in formal presentations by each country team and working group leader, following the successful model of the baseline SHARE project. A consortium agreement has been filed in baseline SHARE; we will adapt it to this STREP maintaining its core contents.

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B.6 Detailed Implementation plan This section describes in detail the work planned to achieve the objectives for the full duration of the proposed project. The recommended/maximum length, excluding the forms specified below, is up to 15 pages. An introduction should explain the structure of this Implementation plan and how the plan will lead the participants to achieve the objectives. The plan should be broken down according to types of activities: Research, technological development and innovation related activities, demonstration activities and project management activities. It should identify significant risks, and contingency plans for these. The plan must for each type of activity be broken down into workpackages (WPs) which should follow the logical phases of the project, and include management of the project and assessment of progress and results. Essential elements of the plan are: a) Implementation plan introduction – explaining the structure of this plan and the overall methodology used to achieve the objectives. b) Work planning, showing the timing of the different WPs and their components (Gantt chart or similar) c) Graphical presentation of the components showing their interdependencies (Pert diagram or similar) d) Detailed work description broken down into workpackages: Workpackage list (use Workpackage list form below); Deliverables list (use Deliverables list form below); Description of each workpackage (use Workpackage description form below, one per workpackage): Note: The number of workpackages used must be appropriate to the complexity of the work and the overall value of the proposed project. Each workpackage should be a major sub-division of the proposed project and should also have a verifiable end-point (normally a deliverable or an important milestone in the overall project). The planning should be sufficiently detailed to justify the proposed effort and allow progress monitoring by the Commission – the day-to-day management of the project by the consortium may require a more detailed plan.

B.6.1 Overview The project is implemented along three main activities. The first one is development of vignettes (Workpackage 2). This will be discussed in section B.6.2. The second one is the process of data collection in 13 countries (Workpackages 3 and 5-18). See Section B.6.3. Third, the data will be used to evaluate vignettes and self-assessments and to construct “conversion factors” to make indicators of health, quality of life, employment, health care, etc. better comparably across countries (Workpackage 4). This is the topic of section B.6.4. These three elements form the backbone of the project as depicted in Figure B.6.1 below:

FIGURE B.6.1: PROJECT FLOW

Overall coordination, external advice, dissemination WP1

Vignette Data Evaluation development collection Conversion rules WP2 WP3 WP4

Support from Executed by specialists country teams … WP5 WP18 The first step is the development of the vignettes (WP2). Most of the work will be done by CentER, co-ordinated by Arthur van Soest. He will get help from specialists in their fields,

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 38 mainly participants in the SHARE and AMANDA working groups who are still in close contact to this team and overlap to a large extent (see description of participants, B.4.d). They will produce a draft questionnaire that will be administered to the pilot respondents. Feedback from the pilot respondents and analysis of the pilot responses will improve the vignette questionnaire. This loop will be done twice (after the pilot follows an all-country pre-test), in each step improving the vignette questionnaire, before the final vignette questionnaire will be administered to the target sample. Data collection will be centrally co-ordinated by WP3, but executed locally by each country team (WP5-18). Once the main data has been collected, the final project step begins. Evaluation of the target sample (WP4) will produce conversion rules translating country- specific response behaviour into standardised response scales applicable not only to the SHARE data, but to other surveys (ECHP, ESS, SILC, Eurobarometer) as well. The project flow of Figure B.6.1 corresponds to the following project phase and time allocation, depicted as a time line in Figure B.6.2:

Phase 1: months 1-5 Evaluation of pre-test vignettes in the baseline wave of SHARE in 2004 on health and work disability. Evaluation of other existing vignettes. Development of new vignettes for other domains. Milestone 1: First draft of vignette questionnaire ready.

Small-scale pilots in two countries (most likely Germany and Italy) to validate the vignettes and select those that are most informative. Milestone 2: Vignettes validated in pilots.

This first phase requires input from the experts in the SHARE and AMANDA teams in all disciplines. The co-ordinator will organise brain-storm sessions to design new vignettes and evaluate the existing vignettes.

Phase 2: month 6 Finalising the selection of vignettes and wording of the vignette questions in all SHARE languages. About 50 vignettes will be selected on a variety of domains. About half of them will be put in the SHARE drop-off, the other half will be in the main instrument, the computer assisted personal interview (CAPI). Milestone 3: Selection of vignettes completed.

Phase 3: months 7-9 Translations and pre-test in all countries; evaluation of pre-test and final adjustment vignette questionnaire Milestone 4: Vignettes pre-tested and adjusted in all participating countries.

Phase 4: months 10-17 Fieldwork on main vignette sample in 13 countries. About 900 respondents in each country (600 households). Milestone 5: Mid term review when 50% of vignettes have been sampled. Milestone 6: Vignette fieldwork completed in all participating countries.

Phase 5: months 16-19 Construction of the database containing the vignette data and the data from the CORE interview for each of the 13 SHARE countries.

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Milestone 7: Vignette database completed.

Phase 6: months 20-23 Construction of cross-country comparable indicators. Analysis of the relations between these indicators, correcting for differential item functioning across countries and socio-economic groups. Milestone 8: Conversion factors computed and evaluated.

Phase 7: months 23-24 Final report and conference Milestone 9: Project finished with final report and conference.

Figure B.6.2 shows how these phases are connected to the personnel allocation presented in the section on “Human and Financial Resources” (B.4.c). “T” denotes personnel effort by the co-ordinating institution, CentER at Tilburg; “M” by MEA at Mannheim; and “CT” by each of the other country teams.

FIGURE B.6.2: TIME LINE AND PERSONNEL ALLOCATION

Project month 1 2 3 4 5 6 7 8 9101112131415161718192021222324Person Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec months Project phase 1 2 3 4 5 6 7

Milestones M1 M2 M3 M4 M5 M6 M7 M8 M9 Vignette Development T TTT T 31 Translation CT 0,5 13

Fieldwork Coordination M MMMMMMMM 51

Pilot CT CT 1,5 13 Pretest CT 113 Main Field Work CT CT CT CT CT CT CT CT 613

Evaluation CT CT CT CT 213 Development of Conversion Factors TTTT 21 Final Report T T 11 154 Tilburg (T) Mannheim (M) Country teams (CT) Total Person months development/evaluation 8,5 7,5 2,5 * 11 = 28 44 Note: Person months fieldwork 8,5 8,5 8,5 11 94 111 bold: full time working on project Total person months 17 16 11 11 121 154 italics : half time working on project

B.6.2 Vignette Development (WP2)

As explained in section B.1, vignettes will be used to construct internationally comparable indicators of several domains of general health, work related health, the quality of health care, satisfaction with the political system, satisfaction with work, social participation and social networks, and several aspects of social exclusion. This workpackage will evaluate the vignettes on health (including work related health) included in the baseline 2004 SHARE wave and adjust these vignettes where necessary before they are included in the SHARE vignette survey in 2006. It will develop new vignettes for the other domains given above, expanding the vignette methodology to new domains. It will test the new vignettes using small pilot samples in two countries. It will translate the vignettes into all SHARE languages and implement the vignettes in the additional samples for the SHARE vignette survey (see workpackages 3 and 4). Finally, it will use the data for some first analyses, using the vignettes to make cross-country comparisons corrected for differences in response behaviour (“differential item functioning”).

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Specifically, we will develop and field vignettes for the following domains: • Several domains of health (mobility, pain, sleep, breathing, emotional health, cognition); • The extent to which health limits the amount or kind of work people can do; • Political efficacy and satisfaction with the national political system; • The quality of health care; • Quality of employment; satisfaction with work; • Quality of life and well-being; • Poverty and social exclusion. In some cases, the vignettes have already been developed and used in several surveys, including part of the baseline wave of SHARE. This applies to the six health domains as well as work related health. Vignettes for political efficacy have been developed and used by King et al. (2004). Examples of vignettes on many aspects of the quality of the health care system are given on the anchoring vignettes web site of Gary King, http://gking.harvard.edu/vign/. Vignettes for the other domains will be developed specifically for the current project.

Vignettes for physical and mental health The additional sample in SHARE baseline had 18 vignettes on six domains of health, with the six corresponding self-reports. The domains were selected on the basis of their contribution to self-reported overall health: mobility, pain, emotional health, sleep, breathing and cognition. For these six, a self-report of health in that domain was asked on a five-point scale, and three vignettes were selected from the vignettes used in the World Health Survey. One of the tasks of this workpackage is to analyse these vignettes and, if necessary, adjust them for implementation in the SHARE vignette survey. In particular, it needs to be checked whether the vignettes indeed identify DIF across countries or across socio-economic groups. This is possible since we have three vignettes for each domain, implying the possibilities of consistency checks. Such checks may lead to adjustments of wordings of the vignette questions in one or more countries, most likely to correct for unintended differences in meaning due to translation. We will make as few adjustments as possible to retain the panel nature of the vignette evaluations, which can be used to distinguish genuine changes in health from reporting changes.

Vignettes for Work Limiting Disability Banks et al. (2004) apply these ideas to comparing self-reported work disability across countries. The self-reported work disability question is given by:

Do you have an impairment or health problem that limits the amount or kind of work you can do?

With possible answers:

None / mild / moderate / severe / extreme

The vignettes describe people with a work related health problem and respondents are asked to answer the same question but then about these (hypothetical) people. Banks et al. (2004) not only correct international comparisons corrected for DIF, but also correct comparisons of different socio-economic groups within a given country. For example, justification bias (Bound, 1991; Kerkhofs and Lindeboom, 1995; Kreider, 1999; Currie and Madrian, 1999) can be seen as a form of DIF, with people on disability programs or other non-workers giving systematically different evaluations of their own work limiting disabilities than people who

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 41 work. Comparing evaluations of vignette persons with disabilities in a certain domain (such as back pain, depression, or breathing problems, etc.) given by workers and non-workers will show whether workers and non-workers give systematically different evaluations that could reflect justification bias.

The SHARE vignette pre-test in 2004 included vignettes on work-limiting health problems in the domains of pain, depression, and cardio-vascular disease. These make it possible to analyse cross-country differences in work related health, corrected for DIF. The same work limitation vignette questions have also been administered to a sub-sample of the US Health and Retirement Study (HRS) 2004 and will most likely be included in one of the next waves of the English Longitudinal Study on Ageing (ELSA). One of the tasks of Workpackage 2 is to analyse the answers to these vignette questions, and adjust them for implementation in the SHARE vignette survey in 2006.

Vignettes for Well-being and Quality of Life One of the innovations of SHARE baseline wave is the inclusion of a newly developed measure of quality of life in early old age. This innovation is important because the majority of people living in the so-called third age are in good health and capable of participating in a variety of activities. It has been repeated again and again that adding life to years is as important as adding years to life. Thus, a measure is needed that identifies and quantifies those aspects of quality of life in early old age that are specific to a stage in the life course characterised by transition from work to retirement, by an increase of personal freedom and by new options of social participation. In several studies, quality of life was shown to improve health and to promote active ageing. Yet, the degree of this quality critically depends on people’s socio-economic circumstances above and beyond their health status. Poverty, deprivation and chronic social stress go along with poor quality of life, and, thus, reduce the chances of experiencing its beneficial effects (Marmot et al. 2003, Motel-Klingebiel et al. 2004). The starting point of the measurement of quality of life in SHARE is that quality of life should be assessed as the degree to which human needs are satisfied. In this stage of the life course the following domains of need seem to be particularly relevant: control, autonomy, self-realisation, and pleasure. Control is understood as the ability to actively intervene in one’s environment (Patrick et al. 1993). Autonomy is defined as the right of an individual to be free from the unwanted interference of others (Patrick et al. 1993). Self-realisation and pleasure aim to capture the active and reflexive processes of being human (Turner 1995). Following Doyal and Gough (1991), the approach chosen in SHARE treats these four domains as equal rather than hierarchically organised. These concepts were operationalised in a measurement approach termed CASP-19 (C=control, A=autonomy, S=self-realisation, P=pleasure; and 19 refers to the sum of 19 Likert-scaled items measuring these concepts on one-dimensional scales; see Hyde et al. 2003). For SHARE an abridged version of the CASP-19 was designed, removing the items with the lowest contribution to the index. Cross-country differences in the computed CASP-12 index show that quality of life scores are relatively low in Greece, Italy, and Spain and relatively high in Switzerland, the Netherlands and Denmark. Differences between countries are highly significant. There is clear evidence of a North-South gradient in quality of life across the European countries under study. Table B.6.1 shows the quality of life mean scores by education and equivalent household income. As can be seen, people with high education (upper secondary or tertiary according to the International Standard Classification ISCED-97) report a better quality of life in most countries compared to those with low education (primary or lower secondary). These

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 42 differences are statistically significant except for Switzerland. Furthermore, we observe a strong income gradient of quality of life. Differences between the three income groups are significant in all countries.

Table B.6.1 Well-being by Income and Education

CASP-12 (mean sum score) by Socio-Economic Status Country Education Equivalence Income Primary or Upper sec. or Lower tertile Middle Upper tertile lower sec. tertiary SE 38.10 39.37 37.51 38.80 39.89 DK 39.08 39.96 38.39 39.33 41.20 DE 35.34 38.21 35.68 37.86 39.48 NL 38.36 39.92 37.79 39.21 40.18 CH 40.07 40.89 39.83 40.59 40.93 AT 36.51 39.08 37.08 38.45 39.39 IT 33.43 36.16 33.64 34.33 34.78 ES 34.51 39.27 34.47 34.32 37.01 GR 32.15 35.76 32.37 33.02 34.99 Total 34.85 38.21 35.35 36.61 37.98

40 39 38 37 36 35 34 33 32 31 30 Yes No Yes No >2 <2 >2 <2Yes No ADL Self-Rated Chronic Number of Depression Limitation Health (less Diseases Symptoms (EURO-D) than good)

Fig. B.6.1 CASP-12 for different health indicators (all countries: means)

Figure B.6.1 shows for several health indicators a significant difference in quality of life: Better health is consistently associated with better quality of life. Importantly, this holds true for all SHARE countries included in the analysis. These findings are valuable for policy since they show how health policy affects non-health dimensions of well-being and hence help shape a successful and sustainable implementation of strategies for active ageing across Europe. It will be an important aim of this SHARE

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 43 vignette survey to follow the SHARE baseline cohort prospectively in time in order to test to which extent these associations are causal. While the findings discussed above reveal very interesting differences in Europe, the subjective ratings of well-being could very well suffer from the same comparability problems as subjective measures of health or assessments of work disability. This proposal aims at improving the comparability of measures of well-being across countries or socio-economic groups by developing vignettes for the most important dimensions of well-being. This works in the same way as for the health vignettes discussed above. For example, the first well-being question in SHARE baseline wave is:

Here is a statement that people have used to describe their lives or how they feel. We would like to know how often, if at all, you think this applies to you… 1. Often 2. Sometimes 3. Rarely 4. Never My age prevents me from doing the things I would like to.

It may be the case that in one culture, a certain limitation induced by old age is seen as a handicap for doing things someone would like to do, while in another country, people will consider it as a minor limitation, not affecting things someone can do in a serious enough way to report this. The differences across countries and socio-economic in the way respondents evaluate such questions can be identified using vignettes of people with certain age-related limitations, in the same way as for the health vignettes. On the basis of their contributions to the CASP-12 scale and pilot estimates whether they suffer from differential item functioning or not, we will select about four of the twelve domains. For each of these, we will formulate about three vignette questions, which will be fielded in the SHARE vignette sample in 2006. Some randomisation will be necessary, since the total number of vignettes administered to each respondent should not be too large. We expect to administer about six vignettes on well-being to each respondent.

Vignettes for Quality of Employment For the youngest age group in the SHARE 50+ population, active and successful ageing is very much related to labour force participation and satisfaction with work. Early retirement from regular employment provides a major challenge to social and health policy in European countries (Brugiavini 2001). As people over 60 years old will comprise up to one third of the population in several European countries in the next two decades, a shrinking number of economically active people will have to support a growing number of economically dependent elderly people. Currently, large variations in workforce participation rates are observed across European countries, e.g. in the age group 55-59. In recent years, this rate has fallen to below 20% in Belgium, Italy, France and the Netherlands, to about 35% in Germany and to 40% in Spain, whereas this percentage is much higher in countries like Switzerland, Norway, Japan and the United States. Therefore, a major policy challenge consists in increasing the number of regularly employed people at older age by influencing the determinants of early retirement. At least three types of determinants have been identified. First, financial incentives, often in combination with economic pressure from employers, pension schemes with extended eligibility and alternative income options need to be mentioned. National policies vary quite substantially with respect to these regulations. Secondly, poor health, chronic illness and disability are important determinants of early exit from the labour market. This holds particularly true for occupations where working conditions cannot be modified or adjusted to a reduced work ability of employees. Poor quality of work and employment is a third determinant of premature departure from working life. Today, this is not only the case for jobs with high ergonomic

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 44 exposure and high physical workload. Rather, stressful working conditions, e.g. high work pressure, monotonous jobs, poor incentives and elevated job instability influence employees' decision to depart from jobs as early as they can (Mein et al. 2000). Importantly, these stressful working conditions also contribute to poor health and to the development of chronic illness, i.e. to conditions that in turn influence early retirement (Ostry et al. 2003, Schnall et al. 2000). Thus, poor quality of employment exerts both direct and indirect effects on premature retirement. Given its importance, quality of work and employment seems to be a prominent target of policy interventions as its improvement may result in increased work ability and longer maintenance of regular employment. Although poor quality of work has been monitored across Europe in a previous panel survey (Paoli & Merllié 2001) no study has yet compared this topic in terms of two major theoretical concepts of health-related stressful employment, the demand-control model (Karasek et al. 1998), and the effort-reward imbalance model (Siegrist et al. 2004). The former model identifies stressful work by job task profiles characterised by high demand in combination with low control (low decision latitude), whereas the latter model claims that an imbalance between high efforts spent and low rewards received in turn (money, esteem, career prospects, job security) adversely affects health. Moreover, no comparative data so far exist on associations between stressful work and the health. In both instances, the SHARE investigation is the first one to explore these topics at the European level. To measure health-related stressful work, a short battery of items derived from the job content questionnaire measuring the demand-control model (Karasek et al. 1998) and from the questionnaire measuring the effort-reward imbalance model (Siegrist et al. 2004) was included in the SHARE baseline interview. Items were selected on the basis of factor loadings on respective original scales. The factor scores were used to define an index for “poor quality of work.” An international comparison for the age group 50-65 shows very poor quality of employment in Greece and in Italy. In Spain, Germany and Austria, overall quality of work is still rather poor, whereas it is fair in France, Denmark and Sweden. Two countries show high overall quality of work, Netherlands and Switzerland. This suggests that there is a north-south gradient in quality of work. Like for well-being, within country comparisons of the SHARE quality of work index across socio-economic groups and the relation with health also provide interesting insights with policy value. Quality of employment appears to be strongly associated with socio-economic status (educational degree) in almost all European countries: better quality of employment goes along with better education. Moreover, quality of employment appears to be strongly associated with well-being in all European countries: lower quality of employment goes along with higher prevalence of poor self-rated health and depression. It will be an important aim to re-interview as many respondents from the SHARE baseline wave as possible. Changes over time are one of the most useful instruments enabling us testing to which extent these associations are causal. While the findings discussed above reveal very interesting differences in Europe, the subjective ratings of quality of work could very well suffer from the same comparability problems as subjective measures of health etc. This proposal aims at improving the comparability of measures of quality of work across countries or socio-economic groups by developing vignettes for the most important dimensions of well-being. This works in the same way as for the health and well-being vignettes discussed above. As an example, one of the quality of work questions in the SHARE baseline wave is: I have an opportunity to develop new skills. Would you say you strongly agree, agree, disagree or strongly disagree? 1. Strongly agree 2. Agree 3. Disagree 4. Strongly disagree

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The differences across countries and socio-economic in the way respondents evaluate such questions can be identified using vignettes of people with certain specific jobs, in the same way as for the health vignettes. On the basis of their contributions to the quality of work scale and the expected amount of DIF (predicted from small pilots), we will select about four of the seven domains. For each of these, we will formulate about three vignette questions. Some randomisation will be necessary, since the total number of vignettes administered to each respondent should not be too large. We expect to give about six vignettes on quality of work to each working respondent. For those who do not work, we will consider asking similar questions on the last job they had. This is particularly important for respondents in the age group 50-65, since the fact that they no longer work could be due to lack of job satisfaction and quality of work in the past.

Vignettes for the Quality of Health Care The SHARE baseline wave has some questions on the use of health care and some objective indicators of the quality of health care, such as whether a physician performed certain health tests, revealing substantial differences in the SHARE countries. For example, the fraction of people with more than three visits to their general practitioner in the past 12 months varies from 28% in Sweden to 71% in France. There is, however, no evaluation of the respondents’ opinion on the quality of health care. In the new survey, we propose to compare the quality of health care systems by subjective questions, in the spirit of, for example, Schoen et al. (2004). They use a number of subjective and objective questions to compare the health care systems of five countries, the U.S., the U.K., Australia, New Zealand and Canada, and find that in almost any respect, the U.S. performs very poorly. Schoen et al. (2004) do not control for differential item functioning. We thus propose that respondents will be asked to assess several aspects of their health care systems, such as waiting time for a test or an operation, willingness to refer patients to (other) experts, cooperation of the insurance company, and communication with medical professionals. Examples of such vignettes have been developed by Chatterji et al., see http://gking.harvard.edu/vign/eg/. An example in the domain “choice of providers” is: Jim had stomach problems for several years. He has visited his doctor many times. His requests for a referral to a particularly well-known stomach specialist have been turned down because his doctor was sure that he was capable of treating the illness and assured Jim of this. Now, overall, how would you rate Jim’s experience of being able to choose to see the health care provider he went to? 1. Very good 2. Good 3. Moderate 4. Bad 5. Very bad We will select some of these vignettes for SHARE, pilot them in small scale samples in two SHARE countries, revise them if necessary, and implement them in the main vignette survey. We expect to ask about six of these vignettes to each respondent.

Vignettes for Political Efficacy Political efficacy refers to the “feeling that individual political action does have, or can have, an impact upon the political process, that is, that it is worthwhile to perform one’s civic duties” (Campbell et al., 1954). Measurement of political efficacy has a long history in political science, see, e.g., Niemi, Craig and Mattei (1991) or Morrell (2003). While these studies emphasize that measurement issues play a large role in within country comparisons, results of King et al. (2004) show that the challenge is even larger in cross-country comparisons, due to large differences in the response scales that respondents use in different

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 46 countries. King et al. (2004) show that vignettes can identify this form of differential item functioning (DIF), and their results accounting for DIF leads to completely different conclusions about the differences in political efficacy between countries. The vignettes in King et al. (2004) are placed in the context of a developing country, for example: Toshiro lacks clean drinking water. There is a group of local leaders who could do something about the problem, but they have said that industrial development is the most important policy right now instead of clean water. How much say does Toshiro have in getting the government to address issues that interest him? 1. Unlimited Say 2. A Lot of Say 3. Some Say 4. Little Say 5. No Say at All We propose to develop new vignettes for political efficacy that fit the context of the European Union. With small pilots in two SHARE countries, we will test the usefulness of these vignettes and select those that contribute most to measuring DIF across countries. The vignettes will then be translated and implemented in the instrument to be fielded in the pre- tests and the main vignette survey. We expect to ask about four vignettes on political efficacy to every respondent.

Vignettes for Poverty and Social Exclusion Social exclusion has many dimensions, one of which is economic poverty. While an objective measure of poverty consists in the form of household income or household consumption expenditure corrected for purchasing power differences, this may not be a complete measure of poverty if poverty also depends on factors such as access to cheap housing, access to cheap or free help from family, friends, or neighbours, etc. A rather general but subjective measure of economic poverty is obtained by the question: Thinking of your household's total monthly income, would you say that your household is able to make ends meet ... 1. With great difficulty 2. With some difficulty 3. Fairly easily 4. Easily This question may suffer from DIF across socio-economic groups and across countries. To correct for this, vignettes will be developed describing hypothetical people in given economic circumstances. To the best of our knowledge, such vignettes do not yet exist. Another dimension of social exclusion is lack of social contacts with family, friends, neighbours, etc. The SHARE baseline wave contains several objective questions on contacts. This is useful but will still give an incomplete picture of the quantity, intensity, and above all, the quality of social contacts. To get an overall picture, we will add a question on satisfaction with social contacts, with vignettes of hypothetical people whose social networks are described in some detail. As before, the vignettes will be used to correct for DIF. These vignettes still need to be developed and tested. The objective information on social contacts will help to validate the vignettes and select the optimal set of vignettes. We anticipate asking about six vignettes on social exclusion to each respondent: three on economic poverty and three on (lack of) social contacts. Of course, apart from economic poverty, health problems can also be an important source of social exclusion. Thus we will also be interested in the correlation between health measures and the social contacts measure. This is just one example of the interesting aspects of a multidisciplinary survey like SHARE.

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B.6.3 Data collection and the development process (WP3, WP5-18) The first stage of data collection is a small-scale pilot in two countries only (most likely Germany and Italy). We will test our instruments on a quota sample of 50 respondents, stratified by gender (25 men/25 women) and retirement status (25 pre-retirement, 25 post- retirement) in each country. With the typical number for this kind of pilot surveys (about five interviewers), the pilot will take about two to three weeks to be completed. The pilot is a critical step in the process of questionnaire design. Once the instrument has been translated in all participating countries' languages, it will become very burdensome to make major changes. The sample size of 100 (both countries) is large enough to conduct experiments on how to elicit reliable information in the various fields covered. The pilot will inform all research groups about potential problems and suggest improvements to the instrument. The research groups will then take necessary steps to redesign and finalise the instrument (WP2). The finalised instruments will be translated in all languages by professional survey translators. We benefit from our experience in SHARE 2004 (Harkness, 2005). The translated instruments will be pre-tested in all participating countries using a quota sample of 50 respondents in each country, again stratified by gender and retirement status. This all-country pre-test will serve as a dress rehearsal for the main vignette survey. Based on the pre-test experiences, we will revise and refine translation where necessary. The third stage of data collection is the main vignette survey in which we will administer the basic CAPI SHARE interview together with the full set of vignettes to 600 households (about 900 respondents) in each participating country. Wherever possible, we will re-interview previously sampled respondents. One of the overarching principles in the planned project is strict cross-national comparability. Due to institutional differences across countries, we did not and cannot always use the same sampling procedures. For example, in some countries we used registers both as a sampling frame and as a source of reliable background information, whereas in other countries no generally accepted sampling frame existed. Still, because of the common principle that all samples should be probability samples based upon sound statistical sampling procedures, SHARE 2004 as well as the project proposed here will generate comparable data sets in terms of statistical properties. The sampling procedures in all countries allow for the construction of sampling weights to correct for non-response and regionally stratified sampling. These sampling weights guarantee that all samples can be made representative for the over 50 population and their spouses in each country. Similar common principles apply to the fieldwork. For instance, in order to minimise non-response rates, we will apply several strategies from interview training through a careful documentation of interview and item non-response to monitoring of interviewer performance. We will also exploit the lessons of the SHARE baseline wave, and in particular will study the response behaviour in SHARE 2004 with respect to different interview modes, sequences of questions, and respondent incentives. The actual data collection work will be sub-contracted to specialised survey agencies in the participating countries. In most cases, this will be the same agency that already collected the SHARE baseline data in 2004. Exceptions are of course the two accession countries where we will select survey agencies following the same rules as were developed under SHARE 2004 (see WP3). In all countries, country team leaders (as part of WP5-18) will set up subcontracts with centrally specified (WP3) detailed specifications. These specifications will contain minute details of what is required, by when and in what form (sampling principles, non-response handling, etc.; for details see the respective workpackage). Potential subcontractors will also have to supply details (e.g. interviewer experience and training). Since it may in a later stage be necessary to post-stratify or weight the survey data to correct for non-response bias, a

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 48 small number of extra data items will be recorded by interviewers about every selected address (or other primary sampling unit), whether or not candidate respondents at such an address were successfully interviewed (e.g. area characteristics; type of accommodation). Data collection tasks (WP5-18) include the control and evaluation of data quality. WP3 will ensure that careful checks on response and data quality are made and recorded in a uniform way within every country so as to permit continuous monitoring and evaluation of the process. All these procedures have been successfully employed during the SHARE baseline wave data collection in 2004. Software and recording procedures can largely be re-used, making this project very cost effective since it does not have to bear all fixed costs of development. The collected data will become part of the existing SHARE database and thus available to all interested researchers, subject to national privacy legislation. They will be stored in a user- friendly format (with, for example, extensive variable descriptions and value labels) and documentation will be developed and made available on the website.

B.6.4 Evaluation and construction of conversion rules (WP4) SHARE can be used to construct indicators of several aspects of physical and mental health, of social participation and family and social networks, of transfers between generations, of consumption, income and wealth, of access and use of health care, of well-being and quality of life, of quality of employment, incentives for retirement and labour force participation, of economic poverty and social exclusion, etc. The micro-data in SHARE are extremely useful to analyse the relations between these indicators at the individual or household level, and to investigate whether institutional differences across countries affect these relations. The strengthening of SHARE in this proposal adds to this in two ways. First, the vignettes will be used to make the indicators better comparable across countries and across socio-economic groups, correcting for differences in response scales (DIF). Second, re-interviews of the same respondents who took part in the 2004 pre-test make it possible to look at changes in these indicators. Using the time difference makes it possible to study the relations between the indicators in a much richer way and to identify causal relationships (cf. Adams et al., 2003). In this section, we briefly explain how vignette models will be used to better compare the distribution of health, quality of employment, etc. across countries and socio-economic groups, how they will be used to analyse the relation between indicators for the various domains, and how they can be applied in a broader context, increasing the value of other European surveys. In order to do this, we first need to explain the essential features of the vignette models themselves, as discussed more extensively in King et al. (2004) and Banks et al. (2004). Essentially, the models are variants of ordered probit models to take account of the ordered categorical nature of the questions (e.g., self-reported health ranging from poor to excellent). See Figure B.1.2. The thresholds between the categories of the ordered probit models are allowed to vary with characteristics such as age, education, gender, and labour force status, as well as across countries. (In Figure B.1.2, the thresholds are the vertical lines, and they are different in the two countries.) This is what is meant by DIF: the thresholds between the categories determine the individual and country dependent response scales. What we are ultimately interested in is the underlying continuous variable, irrespective of the response scales, e.g. “genuine” work related health, the distribution of which is sketched by the bell shaped curves in Figure B.2.1. Let us call this variable y*. Vignettes provide additional information to estimate the distribution of y* and the way in which it varies with characteristics such as gender, age, education level, country, etc. as well as the individual specific thresholds. This crucial contribution of vignettes is that together

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 49 with self-assessments, they provide enough information to estimate both. The ordered probit with individual specific thresholds model would not be identified if we only had the self- assessments. The first application of this model is to compare the distribution work related health, purged for DIF, across countries. This is straightforward once the model is estimated. The equation for y* will contain country dummies and interactions of country dummies with other variables such as gender and education level. The estimated coefficients will give insight in cross- country differences, how these vary with education or gender, etc. Moreover, the model can easily be used to generate counterfactuals, like: how many people in the Netherlands would report a work related health problem which is moderate or worse, if the Dutch respondents would use the response scales actually used by the French? Comparing this with the fraction of French respondents reporting a moderate or worse work related health problem gives a comparison of work related health in the Netherlands and France using the same response scales in both countries, and thus provides better insight in cross-country differences in work related health than the self-reports in the data themselves. The second application concerns the analysis of the relation between two indicators, for example work related health and poverty or social exclusion. Without vignette models, the way to analyse this relation would be to look at the association between self-reported work- related health and self-reported poverty. Since self-reports are categorical, a framework that does more justice to the underlying structure of the economic and social processes will use the underlying continuous variables for work related health and poverty. Without vignettes, this can only be done with standard ordered probit models with thresholds that are the same for everyone, due to lack of identification. Vignette models allow to relax this assumption and make it possible to analyse the association correcting for DIF, avoiding the potential biases due to confounding factors that affect response scales rather than genuine poverty or work related health. Such an analysis can, for example, be based on imputing values of work related health and poverty, using the complete vignette models for both. The third application concerns using the vignette models estimated with the SHARE data to correct for DIF in other surveys that do not have vignettes, such as ECHP, SILC, ESS or Eurobarometer. The vignette models in SHARE will be used to generate predictions of individual specific thresholds for every respondent in SHARE. These can be called the “conversion factors” since they determine how thresholds of a given individual can be converted to benchmark thresholds (of some benchmark person in some benchmark country). Respondents from another survey can then be matched with SHARE respondents on the basis of their individual characteristics (e.g. country, gender, education, labour force status, age; variables included in all major household surveys in Europe). I this way one can obtain individual specific thresholds for all respondents in the other survey. This makes it possible for the researchers using the alternative data set to estimate similar models as our vignette models, but then using the thresholds that we provide, instead of estimating the thresholds using vignettes. In these models, the thresholds are known, and vignettes are no longer needed to identify the model. Therefore, providing the “conversion factors,” the estimated individual and country specific thresholds, makes it possible to correct for DIF in the same way as we do, improving international comparability and comparability across socio-economic groups, even in an analysis based upon a data set which does not itself have vignettes. Adding the conversion factors to the public release files of SHARE is also part of the proposed project (Workpackage 3). Extensive documentation with information on how the conversion factors are constructed and how they can be applied, will be provided by Workpackage 4.

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B.7 Other issues

B.7.1 Ethical issues If there are ethical issues associated with the subject of the proposal, show they have been adequately taken into ccount - indicate which national and international regulations are applicable and explain how they will be respected. Explore potential ethical aspects of the implementation of project results. Include the Ethical issues checklist given below6

Table A.

Does your proposed research raise sensitive ethical questions related to: YES NO Human beings X Human biological samples X Personal data (whether identified by name or not) X Genetic information X Animals X

Table B. Specification of the issues identified:

Please indicate whether the proposal involves Yes No • Research on human beings X Persons not able to give consent X Children X Adult healthy volunteers X • Human biological samples X Human foetal tissue/cells X Human embryonic stem cells X • Human embryos X • Human genetic information X • Other personal data X Sensitive data about health, sexual lifestyle, ethnicity, political X opinion, religious or philosophical conviction • Animals (any species) X Non- human primates X Transgenic small laboratory animals X Transgenic farm animals X Cloning of farm animals X • Research involving developing countries (e.g. clinical trials, use of human X and animal genetic resources…) • Dual use X

Statement concerning ethical issues and safety provisions When dealing with sensitive personal data, confidentiality is a major concern. Maintaining the strict procedures established during the FP5 funded SHARE baseline study, the co-ordinator will implement the research project in full respect of all relevant legal and ethical national requirements and codes of practice. As far as we deal with respondents ourselves, all persons involved will be volunteers. The data we will collect will not contain names or addresses, and the information that we keep cannot be linked to names or addresses. We will only carry a random number identifying each person. Most data, however, will be collected by a sub- contractor (“survey agency”). We will make sure that they will follow the same rules as indicated above. If proxy-interviews have to be performed because respondents in some cases may become unable to be interviewed, the sub-contracting fieldwork agency will in all cases obtain permission by the legal representative.

6 See Annex 3 for more information on ethical issues

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In addition to the removal of names and addresses from the datasets, data released to the public will be protected by “factual anonymity” as defined by the strict norms applied to the public use files of the ECHP. Data that are not factually made anonymous will remain on a secured server at CentERdata, which cannot be accessed through the central database. All work will be carried out in compliance with national and EU regulations on safety, such as the directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data.

We confirm that the proposed research does not involve: • Research activity aimed at human cloning for reproductive purposes, • Research activity intended to modify the genetic heritage of human beings which could make such changes heritable • Research activity intended to create human embryos solely for the purpose of research or for the purpose of stem cell procurement, including by means of somatic cell nuclear transfer.

B.7.2 Gender issues If there are gender issues associated with the subject of the proposal, show how they have been adequately taken into account (For gender issues see annex 4).

Epidemiological research consistently shows gender differences in health. At each age, women report to be in worse health than men. At the same time, women have a higher survival probability at each age. Average life expectancy at birth is higher for women than for men. Previous research also finds gender differences in other domains of well-being, for instance job satisfaction or general life satisfaction. Women often report to be happier at work than men although they earn less. Our proposed method of anchoring vignettes allows detecting how gender identities, gender inequalities, and gendered ideologies affect self-report measures of well-being. Cross-national data from such diverse backgrounds as the Scandinavian and the Mediterranean countries provide leverage to detect and explain why self-reports and objective measures of well-being appear to diverge by gender. The conversion factors that we will construct correct self-reported assessments for differences in response scales. If response scales for self-reported assessments in a certain domain vary systematically by gender, the vignette evaluations will show this, and the conversion factors can be used to correct for it. Thus our project will be helpful to distinguish between gender differences in indicators of well-being, quality of work, health, etc., that are due to differences in the way men and women interpret response categories in survey questions, and genuine differences in well-being, quality of work, health, etc., between men and women in each country.

B.7.3 Policy issues Are there other EC-policy related issues, and are they taken into account? Demonstrate a readiness to engage with actors beyond the research to help spread awareness and knowledge and to explore the wider societal implications of the proposed work; if relevant set out synergies with education at all levels. (No recommended length – depends on the number of such other issues which the project involves)

This research will inform and influence scientific policy consulting on a national as well as EU level. Many participants of this project’s team, including this project’s co-ordinator and the SHARE co-ordinator, are actively involved in policy consulting in the areas of labour

Citizens and governance in a knowledge based society COMPARE 13 APR 2005 Call Identifier CITIZENS-5 Area 8.2.2. Page 52 market, pension system and health care reform, some in rather prominent and influential positions. Synergies between this research and policy consulting are therefore large. They have been proven to be effective and fruitful in the past, and we are ready to engage in such scientific policy consulting on the EU and national level also in the future. The cross-national dimension of this project specifically adds to its value far beyond the scientific issues stressed in this proposal, since learning from each other belongs to the fundamental advantages created by the European Union.

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STREP Project Effort Form Full duration of project (insert person-months for activities in which participants are involved) Project acronym –COMPARE

Project acronym: COMPARE 123456 7891011121314TOTAL Full project duration [person months] UTILB MEA JKULINZ ULG UNIANT CERGE-EI SDU IRDES UPANTE UNIPADUA WNE-UW CEMFI UNIUPPS UNIL PARTICIPANTS

Research/innovation activities WP2: Vignette development 8,2 8,2 WP4: Evaluation and conversion rules 4,2 4,2 WP5: Austrian vignette survey 42,8 42,8 WP6: Belgian vign. survey (Dutch) 21,4 21,4 WP7: Belgian vign. survey (French) 21,4 21,4 WP8: Czech vignette survey 42,8 42,8 WP9: Danish vignette survey 42,8 42,8 WP10: Dutch vignette survey 42,8 42,8 WP11: French vignette survey 42,8 42,8 WP12: German vignette survey 42,8 42,8 WP13: Greek vignette survey 42,8 42,8 WP14: Italian vignette survey 42,8 42,8 WP15: Polish vignette survey 42,8 42,8 WP16: Spanish vignette survey 42,8 42,8 WP17: Swedish vignette survey 42,8 42,8 WP18: Swiss vignette survey 42,8 42,8

Total 55,2 42,8 42,8 21,4 21,4 42,8 42,8 42,8 42,8 42,8 42,8 42,8 42,8 42,8 568,8

Demonstration activities none 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Consortium management activities WP1: Overall management 11 11 WP3: Survey management 7,4 7,4

Total 117,4000 0000 0 0000 18,4

Grand total 66,2 50,2 42,8 21,4 21,4 42,8 42,8 42,8 42,8 42,8 42,8 42,8 42,8 42,8 587,2

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Deliverables list (full duration of project)

Deliverable Deliverable title Delivery Nature9 Disseminat No7 date8 ion level 10 1 Report on overall project 24 R PU 2 a,b,c Vignette questionnaire 3,7,9 P PU 3 a,b,c Reports on survey management 6,9,18 R PU 4 b,c Austrian vignette data 9,17 P PU 5 b,c Belgian vignette data (Dutch) 9,17 P PU 6 b,c Belgian vignette data (French) 9,17 P PU 7 b,c Czech vignette data 9,17 P PU 8 b,c Danish vignette data 9,17 P PU 9 b,c Dutch vignette data 9,17 P PU 10 b,c French vignette data 9,17 P PU 11 a,b,c German vignette data 4, 9,17 P PU 12 b,c Greek vignette data 9,17 P PU 13 a,b,c Italian vignette data 4, 9,17 P PU 14 b,c Polish vignette data 9,17 P PU 15 b,c Spanish vignette data 9,17 P PU 16 b,c Swedish vignette data 9,17 P PU 17 b,c Swiss vignette data 9,17 P PU 18 Cross-national vignette data set 19 P PU 19 Conversion factors 24 P PU Note: a refers to pilot, b to pre-test, and c to main survey results

7 Deliverable numbers in order of delivery dates: D1 – Dn 8 Month in which the deliverables will be available. Month 0 marking the start of the project, and all delivery dates being relative to this start date. 9 Please indicate the nature of the deliverable using one of the following codes: R = Report, P = Prototype, D = Demonstrator, O = Other 10 Please indicate the dissemination level using one of the following codes: PU = Public PP = Restricted to other programme participants (including the Commission Services). RE = Restricted to a group specified by the consortium (including the Commission Services). CO = Confidential, only for members of the consortium (including the Commission Services).

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Workpackage list (full duration of project)

Workpackage Workpackage title Lead Person Start End Deliverable No11 Contractor12 Months13 month14 Month15 No16 1 Co-ordination 1 11.0 1 24 1 2 Vignette development 1 8.2 1 7 2 a,b,c

3 Survey management 2 7.4 4 19 3 a,b,c; 18 4 Conversion factors 1 4.2 20 24 19 5 Austrian survey 3 42.8 4 19 4 b,c 6 Belgian survey (Dutch) 4 21.4 4 19 5 b,c 7 Belgian survey (French) 5 21.4 4 19 6 b,c 8 Czech survey 6 42.8 4 19 7 b,c 9 Danish survey 7 42.8 4 19 8 b,c 10 Dutch survey 1 42.8 4 19 9 b,c 11 French survey 8 42.8 4 19 10 b,c 12 German survey 2 42.8 4 19 11 a,b,c 13 Greek survey 9 42.8 4 19 12 b,c 14 Italian survey 10 42.8 4 19 13 a,b,c 15 Polish survey 11 42.8 4 19 14 b,c 16 Spanish survey 12 42.8 4 19 15 b,c 17 Swedish survey 13 42.8 4 19 16 b,c 18 Swiss survey 14 42.8 4 19 17 b,c TOTAL 587.2

Note: a refers to pilot, b to pre-test, and c to main survey results

11 Workpackage Number: WP1-WP n. 12 Number of the contractor leading the work in this workpackage. 13 The total number of person-months allocated to each workpackage. 14 Relative start date for the work in the specific workpackages, month 0 marking the start of the project, and all other start dates being relative to this start date. 15 Relative end date, month0 marking the start date of the project, and all end dates being relative to this start date. 16 Deliverable number: Number for the deliverable(s)/result(s) mentioned in the workpackage:D1-Dn.

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Workpackage description

Workpackage number WP1 Start date or starting event: Month 1 Workpackage title Co-ordination, central management and quality control Participant id 1 Person-months per participant: 11

Objectives Ensure timely delivery of a high-quality 13-nation comparable vignette survey attached to the basic questionnaire of SHARE. Ensure co-ordinated cross-national data evaluation in order to construct conversion rules for self-reported items in a broad range of domains. Ensure timely and consistent reports. Ensure overall adherence to project guidelines and principles, including budget and reporting requirements.

Description of work Leadership of project, responsible for all deliverables to timetable and for the overall budget and contract. Assembling and co-ordinating project teams. Assembling central advisory panel. Arranging and accounting for plenary sessions, board meetings and specialist meetings throughout the project. Ultimate responsibility for subcontracting. Design and implement consistent survey methods, instruments and procedures in all 13 participating countries, and ensure compliance throughout the entire project. Oversee the specified tasks allocated to all partners, and the working groups and advisory panels. Assess equivalence of procedures and standards and remedy deviations, giving practical assistance where necessary. Enforce quality control mechanisms on subcontractors, administer strict checks. Embed methodological experiments, analyse them and document in detail the procedures and outcomes in methodological reports and papers to aid future cross-national research.

Deliverables D1: Final report on overall project results and performance.

Expected results and relevant corresponding milestones Data set on vignettes together with covariates collected in baseline SHARE CAPI instrument, evaluation of these data and construction of widely applicable conversion rules. These conversion factors will advance multidisciplinary analyses of cross-national data, and it will provide the basis for extended substantive analyses for scientists and policy analysts. Relevant to all milestones in the project, especially: M5: Midterm review M9: Final report delivered

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Workpackage description

WP2 Start date or starting event: Month 1 Workpackage title Vignette development Participant id 1 Person-months per participant: 8.2

Objectives Develop vignette questions for six domains of general health, work related health, political efficacy, quality of health care, quality of employment, well-being, and poverty/social exclusion. Field pilots to validate vignettes. Adjust vignettes if necessary for incorporating them in main survey. Analyse vignettes and use them to produce conversion factors. Analyse distribution of indicators of general health, work related health, political efficacy, quality of health care, quality of employment, well-being, and poverty/social exclusion.

Description of work The work starts by analysing and validating vignettes used in the 2004 baseline SHARE wave (general health and work related health) and adjusting these vignettes for the SHARE vignette survey if necessary. This will be done by the workpackage leader (Arthur van Soest) and his team at CentER. At the same time, vignettes for the other domains will be developed and piloted in two SHARE countries (most likely Germany and Italy). Experts of the country teams in this project and the working groups that had been formed under the AMANDA project in the domains of the vignettes will help out. In particular, Johannes Siegrist and his team will work on developing vignettes for quality of work and well-being, Brigitte Santos-Eggiman and Alberto Holly will help developing quality of health care vignettes, Karel van den Bosch and Sergio Perelman will help designing the vignettes the vignettes on social exclusion and poverty. Arthur van Soest will co-ordinate this. On the basis of pilot interviews, a final set of vignettes will then be selected for inclusion in the full SHARE vignette questionnaire. Selection will be based upon validations comparing 1) consistency of vignettes among each other and 2) consistency of self-reports adjusted for differential item functioning (DIF) using the vignettes with objective measurements, where available (cf. King et al., 2004). Part of the vignettes will be included in the main survey and part in the drop-off. Here the choice will be based on length and complexity of vignettes, avoiding cognitive problems with telephone interviewing. The selected vignettes will be translated in the languages of all SHARE countries. Translations will be checked by back translation and by having a panel of experts looking at them. Country teams will help out with the translations. The vignettes will be included in the pre-test and will be adjusted for the final version of the SHARE vignette survey where necessary (CentER, in co-ordination with country teams) The final version of the vignettes will then go into the field, with the core survey. This will be the task of WP3. When the fieldwork is completed, documentation will be developed to add to a public release user-friendly version of the data. This will be done by CentER.

Deliverables D2 (a,b,c): Vignette questionnaire. Comes in three stages: a=pilot, b=pre-test, c=main survey. D19: Conversion factors (including documentation and report on analysis)

Milestones17 and expected results M1: First draft of vignette questionnaire, M3: Selection of vignettes for inclusion in pre-test and main survey

17 Milestones are control points at which decisions are needed; for example concerning which of several technologies will be adopted as the basis for the next phase of the project.

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Workpackage description

Workpackage number WP3 Start date or starting event: Month 4 Workpackage title Fieldwork organisation and control Participant id 2 Person-months per participant: 7.4

Objectives To co-ordinate fieldwork in terms of timing, procedures, quality control, and cost-effectiveness.

Description of work The work starts by drawing up guidelines for the fieldwork. The guidelines are used to select fieldwork organisations in the different countries and to control the fieldwork. The specification will contain minute details of what is required and when. A non-exhaustive (due to space constraints) list includes: details of the sampling principles and methods required to satisfy them; target minimum response rate (75%) and required procedures to maximise it; outcome codes for each address so that response rates and non- response can be calculated uniformly; target maximum non-contact rate (3%) and required procedures for minimising it; detailed procedures to be adopted for the random selection of individuals at each address (or other primary unit); procedures to identify ‘difficult-to-contact’ cases so that they can be tackled flexibly; requirements to conduct quality-control back-checks and to document them in a standardised form on 10% of refusals and 10% of non-contacts; ethical guidelines to be followed (Jowell 1986); deadlines and forms of data delivery. The country teams lead the discussions with the fieldwork organisation in their country, but all contract decisions require approval of the project and fieldwork co-ordinators. Organisation of the fieldwork also involves information requirements regarding progress and success of the fieldwork, and monitoring of the progress of the fieldwork in all stages. Part of the work will be subcontracted to specialists. Data (both from the pilots and from the main test survey) are put into a centrally managed database (with access for all teams). To ensure speediness of data availability for purposes of evaluation and analysis, the fieldwork agencies will be required to produce the data in a uniform format. The data dissemination system will enforce three stages of access restrictions. Raw data from experiments and pilots will remain strictly confidential. The recoded data sets will be purged from sampling identifiers and have restricted access according to national requirements. Publicly available data will be factually anonymised adhering to the strict rules established in Müller et al. (1991) and using the methods developed by the German Statistical Office (Statistisches Bundesamt , 2000). Data will be disseminated over the Internet, following these confidentiality rules. Considerable effort will be devoted to a uniform documentation, together with help files and a user-friendly interface. All codebooks will be publicly available. The database will include a help system and tabular evaluations of the main data items.

Deliverables D3 (a,b,c): Reports on survey management: adherence to fieldwork contracts, systematic overview of the results of the fieldwork at every stage of the process. Comes in three stages: a=pilot, b=pre-test, c=main survey. D18: Final cross-national vignette data set.

Expected results and relevant corresponding milestones Successful execution of pilots (milestone 2), of pre-tests (milestone 4) and main vignettes survey (milestone 6). Database assembled for all countries (milestone 7).

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Workpackage description

Workpackage number WP4 Start date or starting event: Month 20 Workpackage title Vignette evaluation and conversion factor construction Participant id 1 Person-months per participant: 4.2

Objectives Estimation of econometric models explaining differential item functioning and construction of conversion factors

Description of work Once the fieldwork has started and data are becoming available, this workpackage has the task to analyse the vignettes and use them to construct conversion factors. This will require the use of econometric models extending the models introduced by King et al. (2004). Preliminary analysis of the vignettes will help to select the appropriate specification of the model. The appropriately specified model will be estimated using vignette evaluations for all countries, building on explanatory variables provided by the core questionnaire. Predictions of the model will be used to construct the conversion factors, the tools to adjust individual self-assessments in the data for differences in response scales (DIF). The conversion factors and the vignette data will then be used to analyse the distribution of the indicators of interest (describing health, well-being, quality of employment, social exclusion, etc. in each country) separately, as well as to analyse the interrelations between them and their associations with background variables provided in the core questionnaire. Arthur van Soest will take the lead in these analyses and the construction of the conversion factors, assisted by the CentER team, but also with help of the experts in the country teams of this project and the working groups that had been formed in the AMANDA project. Arthur van Soest will also be responsible for the final report on vignettes and conversion factors, which will be one of the main components of the final report of the project as a whole.

Deliverables D18: Conversion factors

Expected results and relevant corresponding milestones M8: Successful construction of conversion factors.

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WP5-18 are identical and describe the data collection in each of the 13 participating countries.*

Workpackage description

Workpackage number WP5-18 Start date or starting event: Month 4 Workpackage title Vignette data collection Participant id Each country team Person-months per participant: 42.8

Objectives Collection and electronic delivery of survey data in the respective country, according to fieldwork specifications made in WP3.

Description of work Select national fieldwork organisation according to guidelines specified in WP3. In almost all cases, these national fieldwork organisations will be the same agencies as in SHARE 2004. (Re-)negotiate contract including minute details of what is required and when, following a check list set up by WP3. Set up subcontract for approval by survey and overall co-ordinator. Select subcontracts for translation. Supervise translation of vignette questionnaire provided by WP2. Arrange translation checks by selected specialists. The country team leader needs to sign off the translated vignette questionnaire for application in the country. The main task in this workpackage is to supervise the organisation and success of the fieldwork in the respective country, carried out by the national fieldwork agency. Collect and forward information regarding national progress and success of the fieldwork to central evaluation performed WP3 to help monitoring of fieldwork progress in all three stages. Stay in weekly contact with agency. Interfere speedily in case of problems and failures. Ensure timely deposit of data (from pilots where applicable, pre-test, and main vignette survey) into centrally managed database. Makes sure all national confidentiality restrictions are met (purged from sampling identifiers, minimum sample requirements). Provide uniform documentation to central website. All these tasks have been successfully executed in SHARE 2004, and we will rely on the procedures developed there, notwithstanding improvements derived from our 2004 experiences.

Deliverables D4-D18 (b,c): Data set of vignettes in the respective country matched with SHARE CAPI core data, together with technical report. Comes in three stages: a=pilot (where applicable), b=pre-test, c=main survey.

Expected results and relevant corresponding milestones Successful execution of pre-test (milestone 4), and main test vignette survey (milestone 6). Matched data ready for analysis by WP2 (milestone 7).

*For practical reasons, the Belgian country team is split along language lines; human and financial resources are split accordingly. The two teams, however, will work closely together as they have done in the 2004 baseline wave.

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Appendix: List of references

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