Academic journal article Demographic Research

Generations and Gender Programme Wave 1 Data Collection: An Overview and Assessment of Sampling and Fieldwork Methods, Weighting Procedures, and Cross-Sectional Representativeness

Academic journal article Demographic Research

Generations and Gender Programme Wave 1 Data Collection: An Overview and Assessment of Sampling and Fieldwork Methods, Weighting Procedures, and Cross-Sectional Representativeness

Article excerpt

(ProQuest: ... denotes formulae omitted.)

1. Introduction

The Generations and Gender Survey (GGS) was developed to stimulate the study of a broad range of topics of relevance to population scientists. It is designed as a threewave panel study conducted at three-year time intervals across as many developed countries as possible, and covers a range of demographically relevant topics such as leaving home, union formation, fertility decision-making, combining employment and parenthood, intergenerational solidarity, and retirement. So far, at least one wave of the GGS has been conducted in 19 countries.

If scholars want to use the GGS for comparative purposes it is not just essential that the quality of the data collected in each specific country be high, but also that there be cross-national equivalence in terms of survey implementation and representativeness. The Generations and Gender Programme (GGP) provides a broad set of country-specific documentation to facilitate the understanding of data collection procedures and data quality for each participating country.8 However, a comparative description and analysis of the quality of data collection is still lacking. Against this backdrop, this article has two main goals:

1. To describe the main features of the implementation of the GGS in participating countries; and

2. To describe and evaluate the quality of GGS data collection in terms of its crosssectional representativeness.

To achieve these goals, we will first describe and discuss characteristics of the sampling procedures. Next, fieldwork procedures and response rates achieved will be discussed. Finally, attention will be paid to the cross-sectional representativeness of the datasets by reviewing the weighting procedures applied to correct for design effects and for post-stratification differences between the national samples and national populations. We will also compare explicitly - both before and after weighting - the distribution of our national samples on a set of key characteristics with population estimates based on national census data and other official sources. The article will conclude with a summary of the main findings and recommendations for data users.

2. Sample

Clear prescriptions about the main sampling characteristics have been developed within the Generations and Gender Programme (GGP) by Simard and Franklin (2005). The three most important elements of these sample design guidelines were:

1. The target population in a country is the resident non-institutionalised population aged 18-79 at the time of the first wave;

2. The sample size of wave 1 should be high enough to interview at least 8,000 respondents in wave 3. In general, a realised sample size of at least 10,000 in wave 1 was deemed necessary;

3. Apply probability sampling. The exact method used was allowed to vary across countries based on the availability and cost-effectiveness of different sampling frames.

Table 1 presents information on sampling for wave 1 country datasets that have thus far been released. The first two columns give information on whether one-stage or multi-stage sampling was applied and whether stratification was applied. A one-stage procedure was used in only five countries (Austria, Estonia, the Netherlands, Norway, and Sweden), with respondents being drawn without first selecting higher-order units. In all other countries except Australia a two-stage sampling strategy was used. In a first stage, areas were selected followed by a selection of individual sample elements - names, addresses, or dwellings. In Australia a three-stage procedure was used: dwellings were selected within selected areas, followed by a random sample of three households if a dwelling was occupied by four or more households. Stratification was applied in the majority of countries. Only in Bulgaria, Germany, the Netherlands, Romania, and the Russian Federation was no stratification used. …

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