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Work description

Work Packages (WP)

A. Work packages managed by ESS partners:

CEPS/INSTEAD

  • A.1) Modelling the determinants of disadvantage: a paper on multi-level modelling, probably applied to child poverty and social exclusion, which will illustrate the application of advanced statistical techniques.
  • A.2) Income mobility: using the longitudinal data, the paper will investigate the extent of mobility over time and differences in income mobility across EU Member States.
  • A.3) The economic vulnerability of the elderly: The paper will compare the economic security portfolios of the elderly in a cross-national perspective. Income, assets and employment rates will be examined in countries with varying income support systems in order to gain a broader understanding of people’s financial situation at retirement in European countries. First, income portfolios of the elderly, as well as income levels and employment rates will be compared across countries with different retirement income support systems. Next, cross-national differences in the importance of housing wealth, a dominating component of asset portfolios will be brought to light by comparing 5 homeownerships rates. Finally, in comparing the poor across countries the paper will assess their ability to make ends meet. Where possible, the robustness of EU-SILC results will also be assessed.
  • A.4) Income distribution and financial poverty, within Member States and for the EU as a whole. The paper will make comparisons between EU-SILC and national data sources. Among the subjects investigated will be child poverty and social exclusion, as well as the incidence of persistent poverty.
     

Czech Statistical Office

  • A.5) Attrition effects: a methodological paper on the attrition effects on indicators' annual trends and time series in connection with the EU-SILC rotational design.
     

Statistics Finland

  • A.6) Housing: The paper will cover the following: - concise discussion of the concepts, including treatment of monetary aspects of housing in other statistical systems (National Accounts, Consumer Price Index, HBS); - EU-SILC variables on housing, including a review of imputed rent methodology and the models applied in the forthcoming 2007 UDB; - empirical part using the 2007 UDB, impact of imputed rent/housing costs on the whole distribution and the lower part of the distribution, regional aspects; and - discussion of indicators and imputed rent/housing costs/cash income. The EU-SILC module on housing (including the local environment information) will also be analysed. Finally, a review of the institutional differences in housing in EU countries will be carried out.
     

Statistics Austria

  • A.7) Monetary and non-monetary disadvantage in a dynamic perspective. The analysis will cover all the Member States for which the (relevant) data are available and will look at life styles, housing, employment, health and education. The relationships between different transitions will also be explored (e.g. “How many changes in economic activity were followed by subsequent changes in deprivation”). Finally, some multivariate models will be applied.
     

Statistics Norway

  • A.8) Municipal and government services. The paper will analyse the feasibility of including the value of municipal services in an “extended income concept” across a selection of countries (which will include both “register” and “non-register countries”).
     

Statistics UK (ONS)

  • A.9) Distributional effects of direct taxes and social transfers. EU-SILC will be used to analyse the distributional effect of direct taxes and social transfers on household incomes. The analysis will start from the EU social indicators "before" and "after social transfers (including and excluding pensions from the original income)", which shows the effect of transfers, but will be extended to cover direct taxation as well as, based on demographic characteristics, non-cash benefits (education and health). The analysis will take a number of countries in order to investigate comparability across countries with different types of welfare and differing fiscal structures.
     

Statistics Italy (ISTAT)

  • A.10) Employment: The paper will investigate the relation between EU-SILC employment and the Lisbon targets on employment rates, and the implications of rising employment rates for well-being. This will include a comparison of EU-SILC with the Labour Force Survey (which is used to measure progress towards the Lisbon targets). The analysis will cover all the Member States for which the (relevant) data are available. The paper will explore how the information available in EU-SILC can complement the quite limited information available in the LFS, asking for example whether higher employment in the age group 55-64 has led to fewer in poverty in that group.
     

Statistics Estonia

  • A.11) Self-consumption. The contribution will be twofold: - a methodological document describing/ comparing how countries have collected the information required for assessing the self-consumption of individual households and how they have then “valued” this information (this will require liaising with countries and with Eurostat, looking at the national quality reports…); and - a scientific paper which will build on (and refer to) the methodological document and which will investigate: a) the importance of self-consumption in the various countries (including how it is distributed in the various social groups etc…); and b) the impact of self-consumption on the income-based EU indicators for social inclusion (e.g. impact on size and composition of the poverty risk rate).
     

B. Work packages managed by academic partners (outside ESS)

  • B.1) WZB-Berlin
    The paper will be on Labour market returns to education in the EU. The paper will explore the nexus between educational credentials and various dimensions of labour market returns at the individual level. In addition to earnings and their temporal stability, the authors will focus on career mobility, and the chances for individuals to avoid unstable working careers as well as inferior employment relations. The design of their analyses will include cross-national as well as long-term perspectives in order to analyse changes over time. Moreover, by comparing these educational returns across countries they will seek to analyse the impact of institutional settings, both of the educational system and the labour market, on individual labour market returns.
     
  • B.2) IWEPS (with CEPS/INSTEAD)
    Different dimensions of deprivation: The paper will put in perspective income poverty, subjective poverty and material deprivation. It will analyse both cross-sectional and longitudinal data.
     
  • B.3) European Centre for Social Welfare Policy and Research
    Social participation: Social participation contributes to the strand of the economic (and social science) literature which discusses how individuals’ behaviour interact (so-called “spill-over” effects). The paper will explore in particular the following issues: (1) levels and form of social participation and the differences across countries, (2) relationship between social participation and social exclusion (employment and low income), (3) relationship between social participation and attitudes towards public policies. The empirical analysis will draw on the special thematic module in EU-SILC as well as on all the relevant variables pertaining to the core EU-SILC questionnaire. It will cover all the Members States for which the (relevant) data are available. It will also look at the European Social Surveys and aim at putting the two surveys in perspective for those countries where this is possible. It might also look at the Eurobarometer survey.
     
  • B.4) London School of Economics
    Socio-economic determinants of health: Drawing on the existing commonly agreed EU indicators, the authors will produce a paper on the measurement of the socio-economic determinants of health. The paper will cover all the Member States for which the (relevant) data are available. It will discuss the related concepts and methodological issues, and it will comment on the national differences in EU-SILC results. It will also:
    - put forward recommendations with regard to the use of EU-SILC data and to their
      future development;
    - confront EU-SILC based results with results drawn from other sources (e.g. SHARE
      survey, national health surveys…) for countries where (some of) this information is
      available in order to test the robustness of the data.
     
  • B.5-6) ISER, University of Essex
     
  • B.7-8) Vijay Verma
    Measurement error and data reliability. The work package will cover two areas:
    • B.7) The first study will analyse both sampling and non-sampling errors in EU-SILC. It will examine the impact of these errors on international comparisons at one point in time as well as on comparisons for a given country between 2 different years. It will do that for a few EU indicators of income poverty and income inequality ("Laeken indicators"), including the EU "persistent risk of poverty" indicator.
    • B.8) The second study on the robustness of a few EU-SILC based "Laeken indicators" at regional level will: - look at statistical reliability at one point in time, primarily though not solely sampling reliability (at least half of the paper will be devoted to this issue); and - explore what can be done for calculating regional estimates by (1) cumulating waves or (2) using small areas estimates techniques. For (1) and (2), the study will also address the issue of robustness of the indicators calculated through these techniques. Again, the study will not concentrate solely on poverty risk estimates; it will also look at a few other EU Laeken indicators.
       
  • B.9-10) Academic partners to be identified in due time.
    It should be noted that the topics described under B.9 and B.10 below are only proposals. They are not finalised yet and could be amended on the suggestion of Eurostat:
    • B.9) Reconciliation of EU-SILC income data with the national accounts: The income data in EU-SILC differ from the national accounts in two major respects: a) the definitions of income are close but not identical; and b) variables with the same definitions may be measured differently. For a selection of countries, different income categories will be compared in order to assess the reliability of the income data and suggest ways in which the income data can be improved.
    • B.10) Polarisation and horizontal aspects of distribution: Recent literature has identified two “related” problems with the standard way of measuring inequality, as in some of the agreed social indicators. The distribution may be becoming hollow in the middle, as jobs become either highly skilled or completely unskilled. This change in the shape of the distribution will be investigated. Related to this is the possibility that certain groups of the population (e.g. the Roma, recent migrants…) may systematically be losing out. The paper will examine how far the EU-SILC data can be used to throw light on the change in the distribution between such groups.