Keywords

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In addition to the established data collection instruments that have been developed by UN specialised agencies, Eurostat, or social science researchers to facilitate cross-national comparison of statistics or survey data, a number of databases have been created and/or are maintained by Eurostat, the European Commission, and the United Nations Economic Commission for Europe (UNECE). These databases differ significantly from one another. Some offer thematic collections, others provide collections of measurement instruments or questionnaires. Still others offer comparative statistical data in various formats. Moreover, the academically driven surveys in Europe, and the surveys conducted under the auspices of Eurostat and the European Commission, can serve as a reference for social researchers engaged in cross-national comparative research.

4.1 European Commission and Eurostat Data Sources

A number of databases maintained by the European Commission and/or Eurostat are extremely useful resources for comparative survey research in Europe.

  • Eurydice, the European Commission Network for Information on Education Systems and Policies in Europe offers comprehensive information and comparative thematic studies on education systems and policies in Europe.

  • Eurostat’s metadata server, RAMON, is an indispensable resource – as a comprehensive collection of standard classifications, a database for concepts and terms relating to survey statistics, and a collection of EU legislation and methodological manuals relating to statistics.

  • Eurostat’s database tables are a useful source of comparative data.

In addition to maintaining the databases, surveys are conducted under the auspices of Eurostat and/or the European Commission. Because these surveys are input or output harmonised, the results are comparable across EU member states and a number of other non-EU countries. While the questionnaires are openly accessible, access to the data is restricted to accredited users or researchers with access to scientific use files.

4.1.1 The Eurydice Network

The Eurydice Network ‘provides information on and analyses European education systems and policies’ (Eurydice, 2011a). The main focus is on the way in which education in Europe is structured and organised at all levels. The network covers the 27 EU Member States, the four EFTA countries (Iceland, Norway, Switzerland and Liechtenstein), and the candidate countries, Croatia and Turkey.

The information provided by Eurydice includes:

  • Detailed descriptions and overviews of national education systems,

  • Comparative thematic studies, and

  • Facts and figures relating to education.

The detailed descriptions and overviews of the education systems within the 33 countries in the Eurydice network are available on Eurypedia – The European Encyclopedia on National Education Systems. There, one can choose between (a) a short overview of about 10 pages in length, (b) a detailed description of the education system covering a large number of aspects and spanning approximately 100 pages, or (c) a description of the structures of the general and vocational education system, which ranges between 40 and 80 pages in length. Although there are 33 countries in the Eurydice network, there are 38 education systems because each language zone in Belgium has its own education system, as do the four constituent countries of the United Kingdom – England, Scotland, Wales, and Northern Ireland. By contrast, the 16 different education systems in Germany (each Land has its own system) are treated as one.

The description of the structure of the general and vocational education system (Eurydice, 2011b) begins with an overview of the national education system, which includes a schematic diagram of the structure of the national system organised according to ISCED-1997 levels. This is followed by a description of the structure of the individual educational sectors: first the general education sector, and then the vocational sector.

4.1.2 RAMON, Eurostat’s Metadata Server

RAMON is Eurostat’s metadata server (Eurostat, 2012a). It offers the metadata that statisticians require for the cross-national comparison of national data. The server is available in three language versions: English, French, and German.

The metadata are divided into the following six superordinate categories (description as of January 2012):

  • Concepts and Definitions: This category comprises CODED, Eurostat’s Concepts and Definitions Database) and the OECD glossary of statistical terms. CODED contains over 9,000 terms, which are defined for use in official statistics. The source of the term and the statistical theme(s) to which it belongs are also provided. The second large database in this category, the OECD Glossary of Statistical Terms, is ‘a comprehensive set of definitions of the main data items collected by the Organisation’ (OECD, 2008).

  • Classifications: In January 2012, this superordinate category comprised 134 classifications, the originals of which are openly accessible. The database contains not only the latest version of classifications, but also previous versions. For example, all four versions of the International Standard Classification of Occupations (ISCO) from ISCO-58 to ISCO-08 are available, as is the ISCO-08 (COM) variant. Therefore, the number of different classifications in the database is actually 61. First, the classifications and variants are listed in a table featuring the English abbreviation, the family to which the classification belongs, and a link to a general description of the classification, or version of the classification, in question. In addition to the name of the institution that developed the classification, its legal basis, its structure, and the instrument’s place in the history of the classification, a succinct description is provided. Finally, the responsible agency – or rather the agency that was the competent authority at the time when the instrument was uploaded to the database – is given. This agency may no longer be responsible for the instrument.

  • Standard Code Lists: The Standard Code Lists are a collection of 79 (as of January 2012) cross-domain code lists used in official statistics.

  • Legislation and Methodology: This category provides access to the EU legislation database relating to all areas of the EU’s work; to two collections of EU legislation relating to statistics – one including acts no longer in force, the other comprising only legal acts in force; and to 12 methodological manuals relating to statistics.

  • Glossaries and Thesauri: In addition to three thesauri, including the European Education Thesaurus, this category provides access to ten glossaries, including that of the International Statistical Institute, which is available in 29 languages.

  • National Methodologies: This category comprises, first, the methodological database MARS, which contains methodological tables for 29 countries for the period 2002–2006, and, second, a structural business statistics database.

  • Index of Correspondence Tables: This index contains correspondence tables between different versions of the standard classifications.

4.1.3 Eurostat Main Tables

In tables, graphs and maps, the ‘Main Tables’ section of Eurostat’s Statistics Database documents European statistics on a diverse range of themes across time (Eurostat, 2012b). Depending on the theme and the availability of data, the countries and regions covered are (a) the 27 EU Member States (EU-27), (b) the EU-25 (before the accession of Bulgaria and Romania in 2007), or (c) the EU-15 (before the EU expansion in 2004). In addition, many tables include also the EFTA countries (Norway, Iceland, Liechtenstein, and Switzerland) and the candidates for accession (Croatia, Montenegro, Macedonia, and Turkey). Especially in the case of economic themes, data for the USA and Japan serve as reference statistics.

As a rule, data are provided for the last 10–12 years. Because population statistics, in particular, are updated very quickly, the year previous to the current year is already available. Economic data, by contrast, are usually delayed for a further year. The themes include, for example:

  • Population statistics: such as ‘Population at 1 January’, ‘People by age group. Share of total population. Proportion of total population aged 65–79 years’, ‘Projected old-age dependency ratio 2010–2060’, and ‘Life expectancy at birth by sex’;

  • Share of non-nationals: e.g., ‘Population by citizenship – Foreigners’;

  • Employment: e.g., ‘Employment rate by sex’, ‘Average exit age from the labour force, by sex’;

  • Social inequality indicators: e.g., ‘At-risk-of-poverty before social transfers by sex’, ‘Gender pay gap in unadjusted form’;

  • National economic indicators: e.g., ‘General government gross debt’, ‘Real GDP growth rate – volume’;

  • Indicators of the financial situation of the population: ‘Comparative price levels of final consumption by private households including indirect taxes’; ‘HICP (Harmonised indices of consumer prices) – all headings’; ‘HICP – inflation rate’;

  • Indicators of the economic situation of industry: e.g., ‘Electricity prices for industrial consumers’;

  • Education: e.g., ‘Life-long learning by sex. Percentage of the adult population aged 25–64 participating in education and training’;

  • Environmental pollution: ‘Greenhouse gas emissions by sector’;

  • Information society statistics: e.g., ‘Market share of the leading operator in mobile telecommunication’, ‘Individuals using the Internet, by place of use’.

The aforementioned examples are just a small selection of the wide range of statistics offered by Eurostat.

Eurostat’s Main Tables constitute an openly accessible collection of country statistics that facilitates comparison across the EU Member States, the candidate countries, and the EFTA states and put these data into context by comparing them to those of the USA and Japan.

4.2 European Surveys Conducted by National Statistical Institutes

As the Statistical Office of the European Union, Eurostat’s task is to provide the EU with statistics that enable comparisons to be made between individual member states and between regions within these states. However, Eurostat does not collect the required data itself. Rather, they are supplied by the national statistical institutes of the member states. It is Eurostat’s task to ensure that the data requested by EU institutions and submitted by the national statistical institutes are cross-nationally comparable. This means that the data must be collected using comparable survey instruments and methodology, and must then be harmonised as far as possible. Ideally, harmonisation is achieved by using an input-harmonised questionnaire, as was the case, for example, in the European Community Household Panel survey (1994–2001). Alternatively, national statistical institutes are given a list of target variables based on common guidelines, and it is up to them to decide how the variables should be implemented and how the data should be collected. One example of such an output-harmonised survey is the ECHP’s successor, EU Statistics on Income and Living Conditions (EU-SILC). Other surveys, such as the Labour Force Survey, basically implement concepts developed by specialised agencies of the United Nations. In the case of the Labour Force Survey, for example, it is the concept for the differentiation of employment status.

Four surveys conducted under the auspices of Eurostat in all EU Member States are described briefly below. They have been selected because they are of most interest to social science researchers:

  • The European Community Household Panel (ECHP), conducted from 1994–2001;

  • European Union Statistics on Income and Living Conditions (EU-SILC), ECHP’s successor, which commenced in 2004;

  • The Labour Force Survey (LFS), which was introduced in 1983 and has been providing data on a quarterly basis since 2005;

  • The Household Budget Survey (HBS) introduced in 1989.

4.2.1 European Community Household Panel (ECHP)

The European Community Household Panel (ECHP) was a panel survey conducted in eight waves between 1994 and 2001 as an input-harmonised longitudinal study. The main focus was on the financial and social situation of private households in the EU Member States. In addition to collecting detailed data on the demographic characteristics and the household income of the respondents, aspects such as the respondents’ housing situation, household structure, labour force participation, social relations and health were surveyed in smaller item batteries. In the household questionnaire, the types of income accruing to the household as a whole were recorded, while in the individual questionnaire completed by all household members aged 16 years or over, the personal income of each respondent was determined by presenting the respondents with a list of every possible type of income in the country in question (see also Section 5.4).

The first wave of the ECHP survey was conducted in 1994 in the then 12 Member States of the European Community, namely Belgium, Denmark, Germany, France, Greece, Ireland, Italy, the Netherlands, Portugal, Spain, and the United Kingdom. New members Austria and Finland joined in 1995 and 1996 respectively. While these two countries fielded the original ECHP survey, new member Sweden provided data derived from the Swedish Living Conditions Survey (SLCS) from 1997 onwards. At first, Germany, the United Kingdom and Luxembourg supplemented the original ECHP survey with data derived from national household panel surveys. From Wave 4 (1997) onwards, these countries derived the ECHP variables entirely from their own national panels. Point 12 of the minutes of the meeting of the Working Group ‘European Community Household Panel’ in November 1997 (European Commission & Eurostat, 1999, p. 8) stated that the United Kingdom, Germany, and Luxembourg had integrated their national panels into the ECHP (see Table 4.1) and noted that, in the case of the UK, ‘it is possible to clone 84 % of the basic variables for Wave 1 of the ECHP on the basis of national panel data (BHPS)’, while in Luxembourg ‘it appears to be possible to reconstruct some 80 % of the ECHP data on the basis of PSELL II.’ No concrete figures were given for Germany.

Table 4.1 Data sources of the countries represented in the ECHP
Full size table

Methodologically speaking, the ECHP was typically based on a random sampling design using a two-stage stratified sample. In Wave 1, the sample comprised a total of 60,000 households, 5,000 of which were in Germany. One reference person was interviewed on behalf of each household (household questionnaire), and personal interviews were conducted with each member of the household aged 16 years or older (adult questionnaire). Interviews were conducted annually. The ECHP was discontinued after Wave 8 (2001).

In a panel survey, the same persons must be interviewed in each wave. However, the survey loses participants from wave to wave because some respondents cannot be reached, while others are unable, or refuse, to participate, or have passed away. Table 4.2 gives the sample size for each country in each ECHP wave. The total sample size can be found in the final (EU) column. In the case of the United Kingdom and Luxembourg, ECHP and national panel data are added in 1994, 1995 and 1996. After that, only national panel data are used. In the case of Germany, the EU total contains SOEP data every year; and in the case of Sweden, the EU total contains SLCS data from 1997 onwards.

Table 4.2 Number of households surveyed in the ECHP
Full size table

Total household income in the ECHP comprised a large number of income components. Missing answers to questions relating to income components or sub-components (item non-response) had to be imputed. However, because the income variables constituted a whole in which all the components were interdependent, the ECHP employed a multivariate technique to impute missing values using a sequence of multiple regressions (see European Commission & Eurostat, 2002; Lehmann & Wirtz, 2003, pp. 4f.).

The following structural indicators of social cohesion were derived from the ECHP data (Lehmann & Wirtz, 2003, p. 1):

  • Inequality of income distribution (S80/S20 income quintile share ratio),Footnote 1

  • The at-risk-of-poverty rate (before and after social transfers),

  • The persistent at-risk-of-poverty rate, and

  • The gender pay gap.

4.2.2 EU Statistics on Income and Living Conditions (EU-SILC)

The ECHP was discontinued in 2001. Its successor, the ‘European Union Statistics on Income and Living Conditions’ (EU-SILC), was launched on the basis of a gentlemen’s agreement in six EU Member States and in Norway in 2003, and was formalised in 2004. From 2004/2005 onwards, all EU-15 Member States and Estonia, Norway and Iceland were represented. Nine new Member States (the tenth state, Estonia, was already represented) joined in 2005. The survey was implemented in Bulgaria in 2006 and in Romania, Turkey and Switzerland in 2007, bringing to 31 the number of states represented in the EU-SILC (European Commission & Eurostat, 2012).

The aim of the instrument is to collect comparable cross-sectional and longitudinal data on ‘income, poverty, social exclusion and living conditions’ (European Commission & Eurostat, 2010). As Eurostat explains:

The instrument aims to provide two types of data:

  • Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions.

  • Longitudinal data pertaining to individual-level changes over time, observed periodically over, typically, a 4-year period (European Commission & Eurostat, 2010).

Methodologically speaking, the EU-SILC is based on a stratified probability sample. Only Germany makes use of an access panel recruited from the German Microcensus. The target population of the EU-SILC is confined to individuals aged 16 or older living in private households. The sample is a household sample. To do justice to the longitudinal dimension of the survey, a 4-year rotating panel design is recommended: three-quarters of the households interviewed in 1 year are retained in the panel in the next year, and so on (cf. Statistik Austria, 2012). Approaches to EU-SILC data collection vary considerably from country to country. This is due to the fact that the EU Member States can be divided into two groups: register- and non-register countries. The register countries (DK, FI, IS, NL, NO, SE, SI) obtain most of the income components and part of the demographic information for the EU-SILC from registers. In these countries, only a small number of the person-related variables have to be collected through interviews. As a rule, this information is obtained by telephone from a representative of the household (UNICEF IRC, 2011, p. 3). In the non-register countries, by contrast, the EU-SILC variables are collected through interviews. Approximately half of the non-register countries conduct face-to-face interviews; the other half carry out telephone interviews. Germany is the only country that conducts the survey by post.

As was the case with the ECHP, data are collected both at household level and at household-member level (all household members aged 16+). At household level, data are collected on the social exclusion, living conditions and income of the household as a whole. The variables collected at household-member level include income (the focal variable), employment, education, and health. Income is surveyed to a similar level of detail in the EU-SILC as in its predecessor, the ECHP.

Like the ECHP, the EU-SILC aims to furnish data from which structural indicators of social cohesion, such as the at-risk-of-poverty rate, the S80/S20 income quintile share ratio, and the gender pay gap can be derived.

4.2.3 EU Labour Force Survey (LFS)

The Labour Force Survey (LFS) is an international household-based sample survey of the employment circumstances of the population. The underlying concept was developed by the ILO (1982; see also Section 5.2.2). The LFS (Eurostat, 2009b) is implemented on a regular basis in 238 countries and territories worldwide (ILO INFORM, 2011) using the same concepts and definitions, the same international classifications, and measuring the same set of variables. The LFS was conducted for the first time in the European Union in 1983. Since 1992, ‘on a regular basis’ means annually. On 9 March 1998, the Council of the European Union adopted Regulation (EC) No. 577/98 laying down that the LFS was to be conducted by the Member States as a continuous survey providing quarterly and annual results (Brown, 1998, p. 3). By 2005 all Member States had fully complied with this requirement (Eurostat, 2009a).

Data are collected on the following themes (Brown, 1998, pp. 4f.):

  • Demographic background,

  • Labour status,

  • Employment characteristics of the main job and second job,

  • Search for employment,

  • Education and training,

  • Previous work experience of persons not in employment,

  • Main labour status (optional),

  • Income (optional).

The structural indicators on employment [derived from the LFS] include the employment rate, the employment rate of older workers, the average exit age from the labour force, the participation in life-long learning and the unemployment rate. The sustainable development indicators also include employment rates by age and educational attainment as well as the population living in jobless households and the long-term unemployment rate (Eurostat, 2010b).

Responsibility for selecting the sample, preparing the questionnaires, and conducting the interviews lies with the national statistical institutes of the Member States. However, the above-mentioned Council Regulation of 9 March 1998 provides detailed instructions about the frequency of the survey, the sample characteristics, the relative standard error for the estimation of annual average, and a complete list of the variables to be surveyed (Brown, 1998, pp. 3ff.). Article 2, para. 2 of the Regulation states: ‘The principal scope of the survey consists of persons residing in private households in the economic territory of each Member State. If possible, this main population of persons living in private households is supplemented by persons living in collective households’ (Brown, 1998, p. 4). The population of the EU-LFS comprises persons aged 15 years or older.

In the majority of cases, households or dwellings are randomly selected using a two-stage stratified cluster sample design. One respondent is randomly selected from each identified household. Because all Member States use a rotation pattern, part of the observations in one quarter can be directly paired with observations in the previous quarter. It is up to the individual national statistical institutes to decide which rotation pattern to use: ‘These rotation patterns range from 2-() (participating for two quarters consecutively before leaving the sample) through 2-(2)-2 (stay two quarters then skip two quarters and finally participating for two quarters) to 8-()’ (Eurostat, 2009a).

As stipulated in Article 2, para. 3 of the Council Regulation of 1998, ‘The variables used to determine labour status and underemployment must be obtained by interviewing the person concerned. …’ (Brown, 1998, p. 4). Other information may be obtained from administrative registers. The interview with the person who has been randomly selected from the identified household must be conducted face to face. Proxy interviews with another member of the household are, however, permitted. Because the LFS follows a rotating panel sample design, telephone interviewing is permissible from the second wave onwards. In Germany, the Labour Force Survey is conducted as part of the Microcensus.

In 2011, the quarterly LFS sample in the EU as a whole comprised approximately 1.5 million persons (Eurostat, 2010b).

A considerable amount of data from the EU LFS is available in tabular form in Eurostat’s online database. This database is regularly updated and can be accessed free of charge (Eurostat, 2010b).

4.2.4 Household Budget Survey (HBS)

Like the EU LFS and the EU-SILC, the Household Budget Survey (HBS) is a sample survey of private households that is conducted in the EU Member States, the candidate countries, and the EFTA countries. The HBS investigates the consumption patterns of private households in different population groups by measuring household expenditure on goods and services. The results of this cross-national comparative survey of consumption expenditure of national populations are used to calculate weights for macro-economic indicators such as the Consumer Price Index (Eurostat, 2010c).

The HBS was launched in most EU Member States in the 1960s. However, unlike the EU-SILC and the EU LFS, which are governed by Council Regulations, it is a voluntary survey. In 1988, Eurostat assumed responsibility for collating the survey data, which it publishes at 5-year intervals: 1988, 1994, 1999, 2005.

Despite the fact that all the national HBS have a common focus – the consumption patterns of private households – they differ in terms of structure and design.

The German HBS comprises two separate surveys: the Income and Consumption Sample (EVS) Survey, which is conducted every 5 years, and the Continuous Household Budget Survey, which is carried out annually.

4.3 The European Commission’s Eurobarometer Surveys

The Eurobarometer (EB) is a series of surveys conducted regularly on behalf of the European Commission in all EU Member States and in the candidate countries. The surveys are commissioned and coordinated by the European Commission via the competent Directorates General and departments, and implemented by renowned social research institutes. The Eurobarometer programme comprises four survey instruments or series: the Standard EB, the Special EB, the Flash EB, and the EB Qualitative Studies. The aim of these surveys is to monitor the evolution of public opinion in the Member States and the candidate countries. The survey data support decision-making at the European level while at the same time serving as a basis for the evaluation of the Commission’s work. From 2000 to 2004, separate surveys – the Candidate Countries Eurobarometer (CCEB) – were conducted in the 13 countries that joined the EU in 2004. The CCEB replaced the Central and Eastern Eurobarometer (CEEB), an annual survey conducted from 1990 to 1998 as a supplement to the EB in the Member States.

The first EB series – the Standard Eurobarometer – has been conducted on a regular basis since 1973. It is a general public survey that is now fielded bi-annually. On average, about 1,000 persons aged 15 or over are interviewed face-to-face in each country. However, the actual number depends on the size of the population. In Germany, for example, 1,500 persons are interviewed; in Luxembourg, 600; in the UK, 1,300 (of which 300 are in Northern Ireland) (European Commission, 2012a). Reports are published twice yearly. To a large extent, the items in the Candidate Countries Eurobarometer questionnaire (CCEB) were the same as those in the Standard Eurobarometer.

The socio-demographic questions in the Standard EB are posed in such a way that comparison with other surveys is difficult. The following is a small selection of the demographic items in the Eurobarometer 72.5 questionnaire of November 2009 (European Commission, 2009a):

  • D 11: ‘How old are you?’

  • D 08: ‘How old were you when you stopped full-time education?’

  • D 40a: ‘Could you tell me how many people aged 15 years or more live in your household, yourself included?’ (The term ‘household’ is not defined.)

  • D 60: ‘During the last 12 months, would you say you had difficulties to pay your bills at the end of the month…?’

  • D 61: ‘On the following scale, step “1” corresponds to “the lowest level in the society”; step “10” corresponds to “the highest level in the society”. Could you tell me on which step you would place yourself?’

D 61 is an unconventional way of asking respondents to assess their social class. It poses grave analytical problems because, as a rule, respondents allocate themselves to a level within their own group rather than within society as a whole (Hoffmeyer-Zlotnik & Krebs, 1993, pp. 25 f.).

The thematical questions – some of which are asked regularly, others as and when required – ask respondents for their opinion on a wide range of issues, for example: the EU as a whole, EU institutions, citizenship of the European Union, EU expansion, the social situation, and topics such as culture, health, the environment, and information technology.

The second EB series – the Special Eurobarometer – consists of in-depth thematic studies conducted for various Directorates General or departments of the European Commission or other EU institutions (European Commission, 2012a). The special surveys measure attitudes and behaviour of respondents in the Member States with regard to specific topics such as the European elections (2009), e-communications (2010), or climate change (2011). The special surveys are conducted in the Member States within the framework of the Standard EB.

The third series – the Flash Eurobarometer – are ad-hoc thematical telephone surveys conducted at the request of any of the services of the European Commission. Flash interviews allow the Commission to focus on specific target groups as and when required. They can be carried out in order to gauge the reaction of the population of the Member States to specific events. In such cases, it is a question of quickly obtaining an up-to-date snap shot. However, flash interviews are also used to solicit the views of selected target groups in specific countries or regions, for example in big cities, on a particular topic (European Commission, 2012b).

The fourth series – the Eurobarometer Qualitative Studies – consists of qualitative studies that investigate in depth the opinions, motivations, attitudes and reactions of selected social groups. For example, studies have been conducted on journalists’ views and attitudes to social media (2012), local authorities’ awareness and perceptions of the governance of the Single Market (2011), and the rights of the child from the perspective of children aged between 15 and 17 (2010) (European Commission, 2012c).

The primary data of the Eurobarometer and the accompanying documentation can be accessed via

  • The GESIS Data Archive for the Social Sciences and

  • The data archive of the Inter-University Consortium for Political and Social Research (ICPSR).

4.4 Eurofound’s European Quality of Life Survey (EQLS)

Eurofound, the European Foundation for the Improvement of Living and Working Conditions, was set up in 1975 by the Council of the European Communities with the aim of contributing to the ‘planning and establishment of better living conditions through action designed to increase and disseminate knowledge likely to assist this development’ (Council of the European Communities, Article 2 of Regulation No. 1365/75 of 26 May 1975). In keeping with its mission, Eurofound advises EU policymakers, national governments, employers, and trade unions on the basis of findings from independent and comparative research. One of these research projects is the European Quality of Life Survey, which is carried out every 4 years.

The first Quality of Life Survey took place in 28 countries in 2003. The second survey, in 2007, was fielded in 31 countries: the EU Member States, Norway, and the candidate countries, Turkey, Macedonia, and Croatia.

The topics addressed in the survey include employment, income, education, housing, family, health, work-life balance, life satisfaction, social and political participation, quality of social services, and subjective well-being (Eurofound, 2010).

The targeted sample size for most countries was 1,000. The targeted sample size was higher in countries with larger populations: France, Italy, Poland, and the UK (N = 1,500) and Germany and Turkey (N = 2,000). Targets were achieved in all cases. The universe comprised all persons aged 18 or over resident in private households. A multi-stage stratified probability sampling design was used. In the third stage, a ‘random walk’ procedure was used to select households to contact for interviewing (Eurofound, 2009, pp. 92 f.). The average duration of the interviews was 36 minutes Face-to-face interviews were conducted in 28 countries; in the remaining three countries, the interviews were carried out by telephone (Eurofound, 2009).

4.5 Data Sources of the United Nations Economic Commission for Europe

The Geneva-based United Nations Economic Commission for Europe (UNECE) is one of the five regional economic commissions of the UN. The UNECE region also comprises all non-European CIS states, the USA, Canada, and Israel. The commission’s main areas of work include economic cooperation and integration, environmental policy, housing and land management, sustainable energy, transport, population, and statistics. Therefore, UNECE deals with many different aspects of demographic change. In order to do so it needs population statistics.

UNECE’s Conference of European Statisticians (CES) is integrated into the network of UN institutions and specialised agencies. It develops statistical standards itself and communicates the statistical norms and standards developed by the EU Statistical Office (Eurostat) to countries outside the EU.

4.5.1 2000/2001 Censuses of Population

UNECE supplies all its member countries with census forms and other census-related information on a special web page (UNECE, 2011):

  • The first column of this web page contains the national census forms. With the exception of France, Monaco, Spain, and Kazakhstan, the forms are available both in the/a national language and in English. Depending on the country, there are joint or separate household and person questionnaires, and housing and place of work questionnaires, if surveyed. The quality of reproduction of most of the questionnaires is poor because the PDFs are merely scanned copies of the originals. If several forms were used, they are all available, sometimes in one file.

  • The second column contains instructions for enumerators and/or respondents. In the case of countries with register-based censuses – for example Finland – this column may feature a handbook describing the content and key concepts of the census.

  • The third column contains the census acts or statistics acts that constitute the legal basis for the census. The column also features a diverse range of other documents, for example background information on the design of the census questionnaire, pre-test reports, definitions and classifications of the census topics, a description of the effects of the changeover to a register-based census, a report on the testing of a new register-based census model, and – in Hungary’s case – a description of the national classification of occupations.

  • The fourth column contains the link to the website of the respective national statistical institute – as a rule to the page featuring information on the 2000/2001 census, and, in exceptional cases (Germany, the USA), to the home page of the NSI.Footnote 2

4.5.2 2010/2011 Censuses of Population

In 2006, the Conference of European Statisticians, in cooperation with Eurostat, issued recommendations for the 2010 round of censuses of population and housing. The purpose of the recommendations were:

  • To provide guidance and assistance to countries in the planning and conducting of their population and housing census;

  • To facilitate and improve the comparability of the data at regional level through the selection of a core set of census topics and the harmonization of definitions and classifications (UNECE, 2006, p. 1).

The publication is divided into four parts (UNECE, 2006):

  • The first part deals with census methodology and technology.

  • The second part is devoted to key population topics. This part is interesting insofar as it discusses, and defines in detail, core topics, derived core topics, and non-core topics and their underlying concepts. Therefore, not only is the publication of relevance to the 2010/2011 census, it also offers social researchers a useful collection of definitions formulated with an eye to their suitability for use in a cross-cultural context.

  • Part three deals with topics relating to the housing census – namely, living quarters, dwellings, and housing arrangements.

  • The fourth part constitutes a collection of appendices, starting with a list of proposed core and non-core topics for the 2010 census.

The collection of questionnaires is kept by the UN Statistics Division (2012); it covers all states. However, unlike the UNECE web page for the 2000/2001 census, which was described above, the UN Statistics Division does not offer a complete collection of census forms and census-related documents, but only the survey instruments. And although these instruments comprise the complete population census forms – i.e., the household and person questionnaires – and the housing census form, no background information on, or definitions of, the core and non-core topics are available.

As a rule, the documents are the survey instruments for the 2010/2011 census. However, the time period is very loosely defined, and stretches from 2004 to 2014. In most cases, the survey instruments for the 2010/2011 census are supplemented by those for the previous census, which was conducted in or around 2000. In the case of a number of countries – including some EU member states – no questionnaires are available for the 2010/2011 census. The quality of reproduction of the 2010/2011 census forms is generally good because the documents were not merely scanned. However, whereas the 2000/2001 census instruments provided by UNECE are often available in English, the 2010/2011 census documentation is, for the most part, available only in the original language(s). This renders the collection somewhat less useful for research purposes.

4.6 Academic Datasets

In addition to the statistical agency data sources, there are academic social research databases and initiatives aimed at processing and harmonising microdata from NSIs for use in academically driven research. The two most prominent institutions will be presented below. For many decades now, they have been thematically processing and harmonising NSI microdata for the purposes of cross-national comparative research.

  1. a.

    The LIS Cross-National Data Centre in Luxembourg maintains two cross-national databases. First, the Luxembourg Income Study Database (LIS), which is the largest available collection of harmonised income microdata from a great number of countries – some datasets span decades. And second, the Luxembourg Wealth Study Database (LWS), the only cross-national wealth micro-database in existence.

  2. b.

    The Integrated Public Use Microdata Series (IPUMS), created and maintained by the Minnesota Population Center at the University of Minnesota, is the largest collection of census microdata in the world.

A third example is the German Data Forum (Rat für Sozial- und Wirtschaftsdaten – RatSWD), which was established on the initiative of the German Federal Ministry of Education and Research. The Forum’s main aim is to sustainably improve the research data infrastructure for empirical research in Germany.

c. The German Data Forum sets up research data centres and data service centres in order to give German social researchers access to official statistics microdata from various sources and to data from academically driven surveys.

4.6.1 Luxembourg Income Study (LIS)

The Luxembourg Income Study (LIS), now called the LIS Cross-National Data Centre, was founded in 1983. The negotiations and discussions regarding the First European Poverty Programme (1975–1980)Footnote 3 showed that cross-national comparative data on the income situation of EU citizens and their households were of importance for the formulation and monitoring of political measures to combat poverty. Hence, the data-oriented activities of the LIS focus on the statistical implementation of the definitions of poverty, the harmonisation of the measurement of poverty, and the definition of the ‘net disposable household income’ concept.

The Luxembourg Income Study (LIS) database makes income-related household- and person-level data available to researchers around the world, thereby enabling them to test their hypotheses against microdata on socio-economic inequality, income distribution, and their causes. To this end, national datasets are harmonised into a common template to ensure that the financial and demographic content of the variables is comparable across countries. In a second harmonisation step, the classifications and coding of the variables are recoded into common values and categories. And finally, in a third step, missing values are unified. To enable researchers to work with the LIS microdata, the harmonisation steps, the underlying harmonisation principles, and the LIS variables are documented. This, and other, documentation, including a description of the characteristics of the national surveys from which the datasets are derived, is available online. Events such as the annual Introductory Summer Workshop in Luxembourg and LIS workshops in individual countries serve to train researchers to use the LIS databases independently. In addition, Web-based self-teaching packages help new LIS users to acquaint themselves with programming syntax issues. These packages are available for SAS, IBM SPSS Statistics, and STATA.

As of June 2012, the LIS database comprised 44 countries and 212 national datasets, which are available for non-commercial use. The data are organised into 5-year waves. While the datasets generally date back to 1980, historical data for the 1960s and 1970s are available for selected countries. The LIS variables are comparable both across countries and over time.

The harmonised household characteristics variables comprise:

  • Region

  • Rural area (dummy)

  • Size of locality of residence

  • Type of area

  • Owned/rented housing

  • Type of dwelling

  • Value of dwelling

  • Farm household (dummy)

  • Ownership and cultivation of agricultural land

  • Grows crops and/or owns livestock

  • Household composition

  • Head living with partner

  • Number of household members

  • Number of household members 65 or older

  • Number of household members 17 or younger

  • Number of household members 13 or younger

  • Number of household members 5 or younger

  • Age of youngest household member

  • Number of earners

(see Luxembourg Income Study, 2012)

The cross-nationally comparable socio-demographic variables at person level cover living arrangements, sex, age, marital status, immigration characteristics, health, and educational attainment:

  • Relationship to household head

  • Partner

  • Living with parents

  • Living with own children

  • Number of own children living in household

  • Age of youngest own child living in household

  • Age in years

  • Sex

  • Marital status

  • Immigrant (dummy)

  • Citizenship

  • Country of birth

  • Years since arrived in country

  • Ethnicity/race

  • Previous place of residence

  • Other immigration characteristics

  • Disabled (dummy)

  • Disability status

  • Chronic illness

  • Subjective health status

  • Highest completed education level (low, middle, high)

  • Highest education level

  • Currently enrolled in education

  • Education level currently enrolled in

  • Age when completed education

  • Literate

  • Education of mother

  • Education of father

(see Luxembourg Income Study, 2012)

The characteristics of the financial situation at household and person level comprise 153 variables:

  • Current income (93 variables)

  • Windfall income (21 variables)

  • Non-consumption expenditure (21 variables)

  • Consumption (23 variables)

  • Assets/liabilities transactions (16 variables)

(see Luxembourg Income Study, 2012)

In 2007, LIS broadened its focus by creating the Luxembourg Wealth Study (LWS) database. The LWS facilitates research on the household income situation at the top end of the income distribution scale. Some 20 wealth datasets from 12 countries are available. As of May 2012 the earliest dataset dated back to 1994 (Finland), while the latest was from 2007 (Luxembourg). The variables used in the LWS database include 24 socio-demographic background variables relating to the head of the household and spouse, 17 expenditure variables, 44 household wealth variables, and 16 variables relating to the labour force status of the head of the household and spouse. Hence, cross-national comparison is possible. The income concepts of the LWS database are compatible with the definitions of the income variables in the LIS database.

4.6.2 Integrated Public Use Micro Data Series (IPUMS)

The Integrated Public Use Micro Data Series (IPUMS) is the largest academic archive of individual-level census data in the world. The archive is hosted by the Minnesota Population Center, an inter-disciplinary research centre at the University of Minnesota. IPUMS comprises two major projects: IPUMS-International und IPUMS-USA.

IPUMS-International (IPUMS-I) (2012a; 2012b) is devoted to collecting and processing census data from all over the world and making them available for use in social science and economic research. The goals of IPUMS-International are:

  • To collect and preserve international census data and documentation,

  • To harmonise the data across countries/cultures,

  • And to make the data freely accessible.

As of December 2011, IPUMS-I contained data from 62 countries and one autonomous region (Palestine). In the case of nine of these countries, the census data begin around 1960. Data for the 2000/2001 census are available for all but six countries, one of which is Germany, which skipped that census. Another country for which no 2000/2001 census data are available is China. However, data for 1982 and 1990 are available. Sudan did not join the archive until its 2008 census, while Peru conducted its last censuses in 2007 and 1993 respectively. Data for more than one census are available for 50 of the countries represented in IPUMS-I.

In order that the scientific use files can be used as such, the data available to interested researchers are samples. In other words, all datasets are subsets of full population data. As a rule, they comprise several hundred thousand persons (IPUMS International, 2012a). Where possible, IPUMS draws 10 % samples by selecting every tenth household from the census dataset. The German datasets (Federal Republic of Germany before reunification) comprise between three and four million persons. Although the US census datasets for the years between 1980 and 2000 comprise between 11 and 14 million persons, earlier datasets contain only about two million persons. The largest dataset, with almost 20 million persons, is from France. It covers about 30 % of the population. The smallest dataset comes from the Caribbean state of Saint Lucia. It comprises 11,000 persons – 7 % of the population. Caution is warranted in the case of the German datasets because under ‘Germany’ one finds datasets from the survey years 1970 (West Germany), 1971 (East Germany), 1981 (East Germany), and 1987 (West Germany). Only when one clicks on the information icons does one find out that the datasets are for two different countries.

A description in English is available for each dataset. As a rule, this description comprises a translation of the items and the response categories, and, in many cases, details of the census characteristics. In a small number of cases, additional information, for example national definitions of variables, is also provided.

Because the datasets are samples, a whole section of the website is devoted to sampling error and variance estimation. It offers more detailed information on the data quality and the technical handling of the samples (IPUMS International, 2012a).

Taking a look at the variables, it soon becomes clear that each country collects data on the topics that it considers to be important. Therefore, many variables are very specifically tailored to individual countries. Nonetheless, researchers engaged in cross-national comparative research can find a whole range of interesting data. IPUMS-I describes each individual variable and discusses its comparability across surveys and cultures. From the harmonised description of each variable, researchers can access at any time the text of the item in the national questionnaire. The following key socio-demographic variables are included (IPUMS-International, 2012b):

  • Sex

  • Age: either in years, or grouped into intervals, or measured via year and month of birth

  • Marital status: de jure, age at first marriage or union, duration of current marriage or union, number of marriages or unions, also same-sex couples

  • Consensual union

  • Nationality/Nativity status

  • Country, province of birth

  • Race or colour, self-identified or assigned by enumerator

  • Ethnicity, country-specific variable

  • Member of an indigenous group

  • Migration status; refugee status

  • First language spoken, second language spoken, mother tongue,

  • Religion

  • Educational attainment

  • Employment status

  • Employment: full-time, part-time, casual

  • Class of worker: self-employed, worked for somebody else either for pay or as an unpaid family worker

  • Days worked last week

  • Hours worked last week

  • Work disability

  • Occupation, ISCO-88, 3-digit

  • Household: Classification, number of persons, also by sex

  • Respondent’s relationship to household head

  • Children: Number and sex; month and year of birth; month and year of death; children surviving

  • Income: of the household, of the respondent; total income; type of income; main income components.

In addition, the possession of consumer durables is frequently surveyed.

IPUMS-USA, the second major data project of the Minnesota Population Center, is dedicated to collecting, preserving and disseminating United States census data (IPUMS-USA, 2012). The collection begins with the US census of 1850 and includes all the censuses taken every 10 years since then up to 2000 as well as the 2000–2010 American Community Survey (ACS) samples. Besides the census and the ACS data, the database comprises data from a wide variety of other sources, for example the Puerto Rican Community Surveys (PRCS), neighbourhood samples, and labour market area samples.

4.6.3 German Data Forum (RatSWD)

The German Data Forum (RatSWD) is an independent body made up of representatives of empirical social and economic research from universities and scientific research institutes, and representatives of the data-producing community. The Forum was established by the German Federal Ministry of Education and Research with the aim of sustainably improving the research data infrastructure for empirical research in Germany.

The core tasks of the Forum are:

  • Making recommendations on how to further secure and improve data access, especially by means of establishing, standardizing and continually evaluating research data centers and data service centers.

  • Making recommendations on how to improve the use of data by means of providing adequate documentation and scientific and statistical data (research data portals, metadata).

  • Advising scientific institutions and organizations on how to incorporate infrastructure data into teaching and research (German Data Forum, 2012a).

Other tasks include making recommendations on research topics and tasks and on ways to enhance the efficiency of the production and provision of access to data of relevance to social research, and advising data producers (German Data Forum, 2012a).

Research data centres (RDCs) are hosted by scientific institutes or public bodies such as the Federal Statistical Office or the statistical offices of the Laender, whose datasets are of interest to researchers. These datasets are made available to researchers in the form of scientific use files. Access to sensitive data can be provided by creating visiting scientist positions (German Data Forum, 2012b).

The data service centres (DSCs) help researchers to use data by producing data documentation, establishing metadata portals, and ensuring qualified user advice (German Data Forum, 2012b).

The research data centers (RDCs) and the data service centers (DSCs) are accredited and supported by the German Data Forum (RatSWD) with the aim of improving the research data infrastructure for the social, economic, and behavioral sciences, both at German as well as at international level. Whilst pursuing this goal, the German Data Forum also bears in mind that infrastructure also has to be installed in areas that go beyond the scope of traditional infrastructure as given by governmental statistics (for example, departmental research, evaluation studies, and research-based surveys using public funding) (German Data Forum, 2010).

As of May 2012, the following research data centres were in operation (German Data Forum, 2012b):

  • The Research Data Centre of the German Federal Statistical Office

  • The Research Data Centre of the Statistical Offices of the Laender

  • The Research Data Centre of the Federal Employment Agency at the Institute for Employment Research (IAB)

  • The Research Data Centre of the Deutsche Rentenversicherung Bund (the German statutory pension insurance agency)

  • The Research Data Centre at the Federal Institute for Vocational Education and Training (BIBB)

  • The Research Data Centre at the Institute for Educational Progress (IQB)

  • The Research Data Centre of the Socio-Economic Panel Study (SOEP)

  • The ALLBUS Research Data Centre at GESIS – Leibniz Institute for the Social Sciences

  • The Research Data Centre ‘International Survey Programmes’ at GESIS – Leibniz Instiute for the Social Sciences

  • The Research Data Centre ‘Elections’ at GESIS – Leibniz Institute for the Social Sciences

  • The SHARE Research Data Centre

  • The Research Data Centre of the German Ageing Survey

  • The PsychData Research Data Centre of the Leibniz Institute for Psychology Information (ZPID)

  • The Research Data Centre of the Panel Analysis of Intimate Relationships and Family Dynamics (pairfam)

  • The Ruhr Research Data Centre at the Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI)

  • The LMU-ifo Economics & Business Data Centre maintained jointly by the University of Munich and the ifo Institute,

  • The ‘Health Monitoring’ Research Data Centre at the Robert Koch Institute.

As of May 2012, the following data service centres were in operation (German Data Forum, 2012b):

  • The German Microdata Lab (GML) Service Centre for Microdata at GESIS – Leibniz Institute for the Social Sciences

  • The International Data Service Centre of the Institute for the Study of Labour (IZA)

  • The German Data Service Centre for Business and Organisatinal Data at the University of Bielefeld.

4.7 Academically Driven Surveys

In addition to surveys conducted by official statistical agencies, there are a number of academically driven cross-national comparative surveys. These include the following barometer surveys (see also ESDS International, 2012):

  • The Afrobarometer measures attitudes on social, political, and economic issues in sub-Saharan Africa. The first survey began in 1999, with 12 participating countries. Round 5 got underway in 2011 in 20 countries (Afrobarometer, 2012).

  • The Latino Barometer is an annual population survey currently conducted in 18 Latin American countries.

  • The Asian Barometer Survey is a population survey conducted in 13 East Asian and five Southeast Asian countries. The regional survey network was established in 2001. In 2011, the survey entered its third round.

  • The AsiaBarometer got underway in 2003 with ten participating countries from all over Asia. The sixth wave took place in 2008 with just five Asian countries, including Russia.

  • The Arab Democracy Barometer was set up in 2005 to measure the attitudes of the resident population in six countries. One survey has been carried out to date.

  • The New Democracies Barometer was a study conducted between 1991 and 1998. Twelve East and Southeast European countries participated.

Besides the barometer surveys, there are also a number of general population surveys that measure attitudes on social and political issues or on social values. These surveys include:

  • The European Social Survey (ESS), which was established in 2001. It measures attitudes on political and social issues.

  • The International Social Survey Programme (ISSP), one of the oldest annual social science surveys. Established in 1984, it measures attitudes on social and political themes. ISSP 2012 was fielded in 48 countries on all five continents.

  • The World Values Survey (WVS). Some 50 countries are participating in Wave 6 (2010–2014) of the survey, which, as the name suggests, measures values.

  • The European Values Study (EVS), which started in 1981 in the then Member States of the EU. In 2008, the fourth round covered 47 European countries or regions.

In addition to the surveys that measure values, or attitudes on social and political conditions, there are a number of surveys that focus on very specific topics such as elections, child development, or health. By way of example, just a few shall be mentioned here:

  • The European Election Studies (EES) analyse election participation and voting behaviour in European Parliament elections. Although the EES project started in 1979, and five studies were conducted between then and 1999, the studies gained greater visibility from 2004 onwards, when 24 EU states began conducting post-election surveys within the framework of the ESS network.

  • Young Lives – an international comparative study of childhood poverty – is a collaborative research project. It is currently following the lives of 12,000 children in the four study countries, namely Ethiopia, India (Andhra Pradesh), Peru and Vietnam.

  • The Survey of Health, Ageing and Retirement in Europe (SHARE) is a cross-national comparative panel study of the ageing process over time. Wave 4 (the third regular panel wave) was fielded in 2012 in 20 European countries. Twelve countries participated in the SHARE baseline study in 2004.

  • The Demographic and Health Surveys (DHS) program is funded by the United States Agency for International Development (USAID). To date some 260 surveys on population, health, and nutrition have been conducted in over 90 developing countries worldwide.

The next section briefly presents four major cross-national comparative social science surveys – the European Social Survey, the International Social Survey Programme, the European Values Study and the World Values Survey – and the Council of European Social Science Data Archives (CESSDA).

4.7.1 European Social Survey (ESS)

The European Social Survey is an academically driven biennial social science survey. Twenty-two countries participated in the first round, which was conducted in 2002/2003. Round 5, which was fielded in 2010/2011, covered 28 countries. The ESS is not a longitudinal but rather a repeat cross-sectional survey that ‘is designed to chart and explain the interaction between Europe’s changing institutions and the attitudes, beliefs and behaviour patterns of its diverse populations’ (ESS, 2011c).

The ESS questionnaire comprises, first, a core module of questions relating to values, attitudes and behaviour patterns. Besides questions of interest to social scientists, the core module also probes respondents’ political opinions and behaviour. In addition to the core module, there are two rotating modules that focus on specific topics.

Methodologically speaking, the ESS is a cross-sectional survey based on a stratified random (probability) sampling design. The target population comprises all persons aged 15 and older resident within private households in each country. The survey is administered via face-to-face interviewing. Because each participating country is free to choose its own sampling procedures, the sample designs vary from country to country. However, countries must ensure that each unit has an equal probability of selection. If the primary sampling unit is a spatial unit (e.g., a municipality), households are selected. Then, one household member per household is randomly selected using a Kish table (Kish, 1994).

Two features distinguish the European Social Survey from other surveys:

  • The design, coordination, and monitoring of the ESS is carried out by small teams of experts to whom the national researchers are subordinate. These teams of experts are independent of the national researchers and – to date – they are paid from European Science Foundation funds. Multinational questionnaire design teams draft a centralised source language questionnaire in British English, which is then translated into all languages spoken as a first language by 5 % or more of the population of the participating countries. Translations are executed, assessed and documented in accordance with the ESS translation guidelines (Harkness, van de Vijver, & Mohler, 2003; see also Section 4.2.1 above). The statisticians on the ESS sampling expert panel advise national researchers on sample selection and assess their sampling designs. As in the case of the questionnaire translation, the ESS makes guidelines available for the design and implementation of sampling strategies, the subsequent statistical processing of the datasets, and the documentation of these procedures. In addition to providing methodological advice and monitoring the implementation, centrally funded accompanying methodological research is conducted on a variety of aspects. Subsequent waves draw on the results of this research.

  • Because the questionnaire is centrally designed, and translation is centrally regulated, ESS is an input-harmonised survey. In principle, variables – including demographic variables – are measured with comparable stimuli in all participating countries.

The socio-demographic items in the ESS questionnaire cover all the main variables, and they are measured thoroughly rather than superficially. However, because it is drafted in British English, a certain British influence on the wording of these items in the source questionnaire is undeniable at times. As will be demonstrated in Chapter 5, the stimuli are not comparable in every participating culture – even under controlled translating conditions.

The ESS data are freely accessible to researchers once they register on the ESS Data Archive website. Access is provided by the Norwegian Social Science Data Services (NSD).

4.7.2 The International Social Survey Programme (ISSP)

The International Social Survey Programme (ISSP) is an academically driven annual social survey that started in 1985 in six countries located on three continents. Research teams from 48 countries on all five continents took part in the 2011 round. In contrast to the ESS, each participating research organisation funds all its own costs. The ISSP consists of two parts: an approximately 60-item topical module, which takes about 15 minutes to administer, and a set of standard background variables. Although most participating countries field the ISSP as a supplement to a larger national survey, Gendall (2011, p. 12) reports that about one fifth of the ISSP members fielded the 2009 ISSP module as an individual survey.

To date, 11 topics have been covered by the ISSP (see Table 4.3). Because the ISSP is interested in studying how social processes evolve over time, most of the topics are repeated at regular intervals. However, this does not stop the ISSP researchers from introducing new topics from time to time (ISSP, 2011a).

Table 4.3 ISSP module topics and survey years
Full size table

The annual topics (ISSP, 2009a, p. 5) are developed by a drafting group made up of between three and six national teams from the member organisations and are pre-tested in various countries. The annual plenary meeting of the ISSP then decides on the final questionnaire. The items in the topical module are effectively input-harmonised because the questions and the underlying variables are developed jointly. However, the standard socio-demographic variables, which are fielded together with the 60-item topical module, have traditionally posed problems because the measurement goals were defined but the wording, etc. was left up to the individual organisations (2009a, p. 3). For years now, the ISSP Methodology Committee has been trying to harmonise these variables by defining what exactly they are supposed to measure (ISSP DMG, 2009). Since 2010, the participating countries that field ISSP as an individual survey are requested to use the wording for the background variables that is proposed by the Methodology Committee. The ISSP members who field the survey as a supplement to another survey will continue to harmonise the standard background variables ex post.

The ISSP is a cross-sectional survey based on national stratified random samples designed to be representative of (a) the adult population resident in private households, or (b) the adult population resident in private or institutional households, or (c) the adult citizens of the participating countries. In most cases, the lower age cut-off is 18, but lower cut-off ages of 16, 17, and 19 have also been reported (Gendall, 2011, pp. 15f.). In three member countries upper age cut-offs of 74, 79, and 80 respectively have been reported (Gendall, 2011, pp. 17f.). ISSP members are not obliged to draw the sample in a particular way. However, care is taken to ensure that countries do not deviate from the principle of random selection. The respondent is either randomly selected from within a household with the help of a Kish grid (Kish, 1994) or the birthday method (Gendall, 2011, p. 20), or the sample is drawn from the population register. The respondent is regarded as the representative of the household. The data collection methods used are: face-to-face interview, self-completion with interviewer involvement, or self-completion by mail (Gendall, 2011, pp. 22 f.). While the sample is supposed to be designed to achieve a norm of 1,400 completed questionnaires per country, member countries are expected to reach at least a minimum of 1,000 (ISSP, 2009a, p. 3).

The data are freely accessible to researchers through the ISSP Group’s data archive, the GESIS Data Archive for the Social Sciences.

4.7.3 European Values Study (EVS)

The European Values Study is a cross-national survey programme that ‘provides insights into the ideas, beliefs, preferences, attitudes, values and opinions of citizens all over Europe. It is a unique research project on how Europeans think about life, family, work, religion, politics and society’ (EVS, 2011a). The idea for the study was born in the late 1970s, and the first survey was conducted in 1981. Research groups from 14 European countries, the USA and Canada participated in the inaugural survey. The USA and Canada remained on board for the 1990 wave. Subsequent waves took place at 9-year intervals (1999 and 2008). The aim was to get as many European countries as possible to participate. In 2008, the EVS was administered in 47 European countries or regions (Northern Ireland, Northern Cyprus, Kosovo).

Care is taken to ensure comparability across time in order to be able to measure developments or changes in values. Therefore, the variables surveyed are comparable with those used in previous waves. The 2008 wave measured respondents’ attitudes to the following topics (EVS, 2011c; EVS & GESIS, 2010, pp. 13f.):

  • Life, with the sub-topics: Well-being; Happiness; Life satisfaction;

  • Family, with the sub-topics: Marriage; Children; Role of women; Respect for parents; Transmission of values;

  • Work, with the sub-topics: Importance of work; Work qualities; Job satisfaction; Work ethos; Obedience to one’s supervisor;

  • Religion, with the sub-topics: Church attendance; Confidence in the church; Importance of God; Traditional beliefs;

  • Politics, with the sub-topics: Political interest; Willingness to join in political actions; Left-right placement; Post-materialism; Support for democracy;

  • Society, with the sub-topics: Social networks; Confidence in others; Solidarity; Tolerance.

Two groups share responsibility for the methodology of the study: ‘The questionnaire is developed by the Theory Group; the quality of the project is taken care of by the Methodology Group’ (EVS, 2011b).

EVS 2008 was based on representative stratified random samples. With the exception of two countries, the population universe was made up of all persons aged 18 or over who were resident in private households and who had a command of the national language. The translation of the British-English master questionnaire into the national languages was monitored by the Methodology Group. In almost all cases, data collection was administered through face-to-face interviews – sometimes computer assisted (CAPI). The norm is 1,500 completed interviews per country but it is dependent on the size of the population. In Northern Ireland, for example, 500 interviews were conducted, and in Germany 2,000 units were achieved – 1,000 for Germany-East and 1,000 for Germany-West (EVS & GESIS, 2010, pp. 15, 22f.).

The EVS data are freely accessible to researchers through the GESIS Data Archive for the Social Sciences.

4.7.4 World Values Survey (WVS)

The World Values Survey (2011a; 2011b) is organised as a network of primarily university-based social researchers whose activities are coordinated by a central body, the World Values Survey Association. The first World Values Survey was conducted in 1981 as an offshoot of the European Values Study. The second survey took place in 1990. It was originally conducted by the European Values Study and was replicated by the WVS. Ten countries in Western Europe participated in the second wave via the EVS and a further 14 countries did so as part of the WVS network. Since then, the surveys have taken place at 5-year intervals. The 2010–2014 wave is currently underway. Some 57 countries took part in the 2005 wave although nine of these fielded only a short-version of the questionnaire. Fifty countries located on all continents, including Europe, are participating in the current wave (2010–2014). When it is completed it will provide a 30-year time series for the analysis of social and political change throughout the world.

The WVS covers the following topical areas:

  • Perceptions of life

  • Environment

  • Work

  • Family

  • Politics and society

  • Religion and morale

  • National identity.

The questionnaire is centrally drafted and communicated to the researchers in the participating countries.

Methodologically speaking, the WVS is usually based on a stratified random sample. In some countries, quota samples are possible. A technical description of the sample is not available for many of the countries. Data collection takes place mostly through face-to-face interviews; in some cases telephone interviews are conducted (Inglehart et al., 2004; DíezMedrano, 2009). The sample size varies considerably – ranging between 300 and 3,000 interviews. However, the bulk of samples range between 1,000 and 1,500 units. The lower cut-off age is sometimes 16, but more often 18. Sometimes an upper age cut-off of between 70 and 85 years applies.

The data are freely accessible to academic researchers. They are processed and made available through the ASEP/JDS Data Archive in Madrid.

4.7.5 Council of European Social Science Data Archives (CESSDA)

The Council of European Social Science Data Archives (CESSDA) is an umbrella organisation that coordinates the activities of European archives and other scientific organisations that make social science data available for research, teaching, and secondary analysis purposes. As of June 2012, the network had 21 members:

  • ADP, Arhiv družboslovnih podatkov, Ljubljana

  • ADPPS Sociodata, Archivio Dati Programmi per le Scienze Sociali, Milan

  • ARCES, Archivo de Estudios Sociales, Madrid

  • CEPS/INSTEAD, Centre d’Etudes de Populations, de Pauvreté et de Politiques Socio-Economiques/International Networks for Studies in Technology, Environment, Alternatives, Development, Esch sur Alzette, Luxembourg

  • DANS, Data Archiving and Networked Services, Den Haag

  • DDA, Danish Data Archives, Odense

  • ESTA/ESSDA, Eesti Sotsiaalteaduslik Andmearhiiv/Estonian Social Science Data Archive, Tartu

  • FORS, Swiss Foundation for Research in Social Sciences, Lausanne

  • FSD, Finnish Social Science Data Archiv, Tampere

  • GESIS – Leibniz Institute for the Social Sciences, Cologne,

  • GSDB-EKKE, Greek Social Data Bank, Athens

  • ISSDA, Irish Social Science Data Archive, Dublin

  • LiDA, Lithuanian Data Archive for Social Science and Humanities, Kaunas, Lithuania

  • NSD, Norwegian Social Science Data Services, Bergen

  • Réseau Quetelet, Paris

  • RODA, Romanian Social Data Archive, Bucharest

  • SDA, Sociological Data Archive, Prague

  • SND, Swedish National Data Services, Göteborg

  • TARKI, Social Research Informatics Center, Budapest

  • UKDA, UK Data Archive, Essex

  • WISDOM, Wiener Institut für Sozialwissenschaftliche Dokumentation und Methodik, Vienna.

The archive network was founded in 1976 with the aim of facilitating a freer and more intensive exchange of data and experience. In addition, the umbrella organisation contributes to defining documentation standards, regulates the data traffic within the network, and promotes cross-national exchanges.

The CESSDA Catalogue (CESSDA, 2011) offers a multi-lingual interface to the datasets, which are processed and made available by the individual members of the network. Access to the data descriptions and the online documentations is free. The required datasets can be searched in different ways. Besides the full-text search, the CESSDA classification and a multilingual thesaurus developed by UK data archive UKDA are available. As a further data search option, users can search the individual data archives by following the links from the CESSDA member organisations page.

CESSDA is currently shifting into CESSDA-ERIC – the European Research Infrastructure Consortium – which was founded in 2010 to meet the challenges posed by archiving social science optimally and ensuring access to data across national borders (CESSDA http://www.cessda.org/about/research/). The new organisation will eventually become the central European institution for the social sciences in the area of data documentation, data archiving and data transfer carried out by the personnel responsible for international exchanges in the individual archives. The aim is to achieve greater integration and coordination of those resources and aids, thereby helping the international research community to handle data more effectively. For this reason, CESSDA conducts expert seminars. The expert seminar in 2011 dealt with the strategic, conceptual, and technical challenges of implementing a cross-national question database (FORS, 2011).