Publication


Vergauwen, J. and Neels, K. and Wood, J.
Quality of demographic data in GGS wave 1
European Population Conference, 2012,
URL, JabRef BibTex, Abstract
A key feature of the Generations & Gender Programme is that the individual-level survey data are intended to be combined with contextual databases providing information on the macro-level context within which the individuals and families live. This would allow researchers to gauge the impact of changing socio-cultural, economic and policy contexts on demographic behaviour. The contextual databases are compiled from existing national and international sources of both quantitative and qualitative aggregate-level information extending back a couple of decades, typically to the early 1970s. As macro-level data in many cases involve aggregate-time series of population based statistics, the validity of analyses combining micro data collected in GGS with contextual data drawn from the CDB and other sources critically depends on the ability of the individual-level data to give a correct account of demographic trends in previous decades. In this contribution we aim to provide information on the validity of demographic data in the Generations & Gender Survey (GGS) from a longitudinal perspective. To this end, we retrospectively estimate demographic indicators on nuptiality and fertility from wave 1 data of the GGS and validate these estimates against indicators drawn from vital registration over the period considered. Indicators considered are period total female first marriage rates (PTFFMR), period mean age at female first marriage (PMAFFM), total first marriage rates in female birth cohorts (CTFFMR), mean age at first marriage in female cohorts (CMAFFM), period total fertility rate (PTFR), period mean age at childbearing (PMAC), completed fertility of female birth cohorts (CTFR) and mean age at childbearing in female birth cohorts (CMAC). Results from the longitudinal validation of the GGS may prove useful for the research community using this infrastructure to decide, depending on the topic studied, on the time-frame to be considered for each of the GGS countries included in the analysis.

Reference


@inproceedings{Vergauwen2012,
  author = {Vergauwen, J. and Neels, K. and Wood, J.},
  title = {Quality of demographic data in GGS wave 1},
  year = {2012},
  booktitle = {European Population Conference},
  url = {http://epc2012.princeton.edu/abstracts/120390},
  timestamp = {20.04.2012},
  owner = {Barbuscia},
  address = {Stockholm, Sweden},
  abstract = {A key feature of the Generations & Gender Programme is that the individual-level survey data are intended to be combined with contextual databases providing information on the macro-level context within which the individuals and families live. This would allow researchers to gauge the impact of changing socio-cultural, economic and policy contexts on demographic behaviour. The contextual databases are compiled from existing national and international sources of both quantitative and qualitative aggregate-level information extending back a couple of decades, typically to the early 1970s. As macro-level data in many cases involve aggregate-time series of population based statistics, the validity of analyses combining micro data collected in GGS with contextual data drawn from the CDB and other sources critically depends on the ability of the individual-level data to give a correct account of demographic trends in previous decades. In this contribution we aim to provide information on the validity of demographic data in the Generations & Gender Survey (GGS) from a longitudinal perspective. To this end, we retrospectively estimate demographic indicators on nuptiality and fertility from wave 1 data of the GGS and validate these estimates against indicators drawn from vital registration over the period considered. Indicators considered are period total female first marriage rates (PTFFMR), period mean age at female first marriage (PMAFFM), total first marriage rates in female birth cohorts (CTFFMR), mean age at first marriage in female cohorts (CMAFFM), period total fertility rate (PTFR), period mean age at childbearing (PMAC), completed fertility of female birth cohorts (CTFR) and mean age at childbearing in female birth cohorts (CMAC). Results from the longitudinal validation of the GGS may prove useful for the research community using this infrastructure to decide, depending on the topic studied, on the time-frame to be considered for each of the GGS countries included in the analysis.}
}

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