IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v32y2015i24.html
   My bibliography  Save this article

Quality of demographic data in GGS Wave 1

Author

Listed:
  • Jorik Vergauwen

    (Universiteit Antwerpen)

  • Jonas Wood

    (Universiteit Antwerpen)

  • David De Wachter

    (Universiteit Antwerpen)

  • Karel Neels

    (Universiteit Antwerpen)

Abstract

Background: A key feature of the Generations & Gender Programme (GGP) is that longitudinal micro-data from the Generations and Gender Surveys (GGS) can be combined with indicators from the Contextual Database (CDB) that provide information on the macro-level context in which people live. This allows researchers to consider the impact of socio-cultural, economic, and policy contexts on changing demographic behaviour since the 1970s. The validity of longitudinal analyses combining individual-level and contextual data depends, however, on whether the micro-data give a correct account of demographic trends after 1970. Objective: This article provides information on the quality of retrospective longitudinal data on first marriage and fertility in the first wave of the GGS. Methods: Using the union and fertility histories recorded in the GGS, we compare period indicators of women’s nuptiality and fertility behaviour for the period 1970-2005 and cohort indicators of nuptiality and fertility for women born after 1925 to population statistics. Results: Results suggest that, in general, period indicators estimated retrospectively from the GGS are fairly accurate from the 1970s onwards, allowing exceptions for specific indicators in specific countries. Cohort indicators, however, were found to be less accurate for cohorts born before 1945, suggesting caution when using the GGS to study patterns of union and family formation in these older cohorts. Conclusions: The assessment of the validity of demographic data in the GGS provides country-specific information on time periods and birth cohorts for which GGS estimates deviate from population statistics. Researchers may use this information to decide on the observation period or cohorts to include in their analysis, or use the results as a starting point for a more detailed analysis of item nonresponse in union and fertility histories, which may further improve the quality of GGS estimates, particularly for these earlier periods and older birth cohorts. Comments: Detailed country-specific results are included in an appendix to this paper, available for download from the additional material section.

Suggested Citation

  • Jorik Vergauwen & Jonas Wood & David De Wachter & Karel Neels, 2015. "Quality of demographic data in GGS Wave 1," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(24), pages 723-774.
    • Handle: RePEc:dem:demres:v:32:y:2015:i:24
    DOI: 10.4054/DemRes.2015.32.24
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol32/24/32-24.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2015.32.24?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Katharine G. Abraham & Aaron Maitland & Suzanne M. Bianchi, 2006. "Non-response in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?," NBER Technical Working Papers 0328, National Bureau of Economic Research, Inc.
    2. John Gibson & Bonggeun Kim, 2010. "Non‐Classical Measurement Error in Long‐Term Retrospective Recall Surveys," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 687-695, October.
    3. Cheti Nicoletti & Franco Peracchi, 2005. "Survey response and survey characteristics: microlevel evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 763-781, November.
    4. Sheila C. Jacobs, 2002. "Reliability and recall of unemployment events using retrospective data," Work, Employment & Society, British Sociological Association, vol. 16(3), pages 537-548, September.
    5. Zvi Eckstein & Ron Shachar, 2007. "Correcting for bias in retrospective data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 657-675.
    6. Andrew Cherlin & Jeanne Griffith & James McCarthy, 1983. "A Note on Maritally-Disrupted Men’s Reports of Child Support in the June 1980 Current Population Survey," Demography, Springer;Population Association of America (PAA), vol. 20(3), pages 385-389, August.
    7. Lynn, Peter & Martin, Jean & Beerten, Roeland & Laiho, Johanna, 2001. "Recommended standard final outcome categories and standard definitions of response rate for social surveys," ISER Working Paper Series 2001-23, Institute for Social and Economic Research.
    8. repec:cai:popine:popu_p1984_39n1_0146 is not listed on IDEAS
    9. Michaela R. Kreyenfeld & Kryštof Zeman & Marion Burkimsher & Ina Jaschinski, 2011. "Fertility data for German speaking countries. What is the potential? Where are the pitfalls?," MPIDR Working Papers WP-2011-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. Lawrence L. Wu & Steven P. Martin & Daniel A. Long, 2001. "Comparing Data Quality of Fertility and First Sexual Intercourse Histories," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 520-555.
    11. Megan Beckett & Julie Da Vanzo & Narayan Sastry & Constantijn Panis & Christine Peterson, 2001. "The Quality of Retrospective Data: An Examination of Long-Term Recall in a Developing Country," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 593-625.
    12. Cheti Nicoletti & Franco Peracchi & Vincenzo Atella, 2005. "Survey Response and Survey Characteristics: Micro-level Evidence from the European Commission Household Panel," CEIS Research Paper 64, Tor Vergata University, CEIS.
    13. repec:cai:popine:popu_p1998_10n2_0318 is not listed on IDEAS
    14. Gerry Redmond & Nadezhda Aleshina & UNICEF Innocenti Research Centre. MONEE project, 2003. "How High is Infant Mortality in Central and Eastern Europe and the CIS?," Papers inwopa03/26, Innocenti Working Papers.
    15. Michaela R. Kreyenfeld & Anne Hornung & Karolin Kubisch & Ina Jaschinski, 2010. "Fertility and union histories from German GGS data: some critical reflections," MPIDR Working Papers WP-2010-023, Max Planck Institute for Demographic Research, Rostock, Germany.
    16. Cordula Zabel, 2009. "Do imputed education histories provide satisfactory results in fertility analysis in the Western German context?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 21(6), pages 135-176.
    17. H. Elizabeth Peters, 1988. "Retrospective Versus Panel Data in Analyzing Lifecycle Events," Journal of Human Resources, University of Wisconsin Press, vol. 23(4), pages 488-513.
    18. James P. Smith & Duncan Thomas, 2003. "Remembrances of things past: test–retest reliability of retrospective migration histories," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 23-49, February.
    19. C. Swicegood & S. Morgan & Ronald Rindfuss, 1984. "Measurement and Replication: Evaluating the Consistency of Eight U. S. Fertility Surveys," Demography, Springer;Population Association of America (PAA), vol. 21(1), pages 19-33, February.
    20. Sarah Hayford & S. Morgan, 2008. "The quality of retrospective data on Cohabitation," Demography, Springer;Population Association of America (PAA), vol. 45(1), pages 129-141, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eugenio Paglino & Tom Emery, 2020. "Evaluating interviewer manipulation in the new round of the Generations and Gender Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 43(50), pages 1461-1494.
    2. Victor Antunes Leocádio & Anne Gauthier & Monika Mynarska & Rafael Costa, 2023. "The quality of fertility data in the web-based Generations and Gender Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(3), pages 31-46.
    3. Gunnar Andersson & Elizabeth Thomson & Aija Duntava, 2017. "Life-table representations of family dynamics in the 21st century," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(35), pages 1081-1230.
    4. Judith C. Koops & Aart C. Liefbroer & Anne H. Gauthier, 2017. "The Influence of Parental Educational Attainment on the Partnership Context at First Birth in 16 Western Societies," European Journal of Population, Springer;European Association for Population Studies, vol. 33(4), pages 533-557, October.
    5. Alessandra Trimarchi & Jan Van Bavel, 2017. "Pathways to marital and non-marital first birth: the role of his and her education," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 15(1), pages 143-179.
    6. Maria Winkler-Dworak & Eva Beaujouan & Paola Di Giulio & Martin Spielauer, 2019. "Simulating Family Life Courses: An Application for Italy, Great Britain, and Scandinavia," VID Working Papers 1908, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    7. Gerrit Bauer, 2016. "Gender Roles, Comparative Advantages and the Life Course: The Division of Domestic Labor in Same-Sex and Different-Sex Couples," European Journal of Population, Springer;European Association for Population Studies, vol. 32(1), pages 99-128, February.
    8. Angela Greulich & Aurélien Dasre, 2017. "The quality of periodic fertility measures in EU-SILC," Post-Print hal-01726581, HAL.
    9. Angela Greulich & Aurélien Dasré, 2017. "The quality of periodic fertility measures in EU-SILC," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(17), pages 525-556.
    10. Eva Beaujouan & Kryštof Zeman & Mathías Nathan, 2023. "Delayed first births and completed fertility across the 1940–1969 birth cohorts," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(15), pages 387-420.
    11. Kerstin Ruckdeschel & Lenore Sauer & Robert Naderi, 2016. "Reliability of retrospective event histories within the German Generations and Gender Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(11), pages 321-358.
    12. Maria Winkler-Dworak & Eva Beaujouan & Paola Di Giulio & Martin Spielauer, 2021. "Simulating family life courses: An application for Italy, Great Britain, Norway, and Sweden," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(1), pages 1-48.
    13. Jonas Wood & Karel Neels & Jorik Vergauwen, 2016. "Economic and Institutional Context and Second Births in Seven European Countries," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 35(3), pages 305-325, June.
    14. Elizabeth Thomson & Maria Winkler-Dworak & Éva Beaujouan, 2019. "Contribution of the Rise in Cohabiting Parenthood to Family Instability: Cohort Change in Italy, Great Britain, and Scandinavia," Demography, Springer;Population Association of America (PAA), vol. 56(6), pages 2063-2082, December.
    15. Michaela Kreyenfeld & Esther Geisler & Teresa Castro Martín & Tina Hannemann & Valerie Heintz-Martin & Marika Jalovaara & Hill Kulu & Silvia Meggiolaro & Dimitri Mortelmans & Inge Pasteels & Marta Sei, 2017. "Social policies, separation, and second birth spacing in Western Europe," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(37), pages 1245-1274.
    16. Brienna Perelli-Harris & Mark Amos, 2015. "Changes in partnership patterns across the life course," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(6), pages 145-178.
    17. Tineke Fokkema & Andrej Kveder & Nicole Hiekel & Tom Emery & Aart C. Liefbroer, 2016. "Generations and Gender Programme Wave 1 data collection," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(18), pages 499-524.
    18. Angela Greulich & Aurélien Dasre, 2017. "The quality of periodic fertility measures in EU-SILC," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01726581, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John Gibson & Bonggeun Kim, 2007. "Measurement Error in Long-term Retrospective Recall Surveys Of Earnings," Working Papers in Economics 07/03, University of Waikato.
    2. Jonas Wood & Karel Neels & Tine Kil, 2014. "The educational gradient of childlessness and cohort parity progression in 14 low fertility countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(46), pages 1365-1416.
    3. John Gibson & Bonggeun Kim, 2010. "Non‐Classical Measurement Error in Long‐Term Retrospective Recall Surveys," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 687-695, October.
    4. Isabella Buber-Ennser, 2014. "Attrition in the Austrian Generations and Gender Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(16), pages 459-496.
    5. Elizabeth Thomson & Helen Eriksson, 2013. "Register-based estimates of parents' coresidence in Sweden, 1969-2007," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(42), pages 1153-1186.
    6. Müggenburg, Hannah, 2021. "Beyond the limits of memory? The reliability of retrospective data in travel research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 302-318.
    7. Becchetti, Leonardo & Conzo, Pierluigi & Salustri, Francesco, 2017. "The impact of health expenditure on the number of chronic diseases," Health Policy, Elsevier, vol. 121(9), pages 955-962.
    8. Eric J. Tchetgen Tchetgen & Kathleen E. Wirth, 2017. "A general instrumental variable framework for regression analysis with outcome missing not at random," Biometrics, The International Biometric Society, vol. 73(4), pages 1123-1131, December.
    9. Adrian Chadi, 2019. "Dissatisfied with life or with being interviewed? Happiness and the motivation to participate in a survey," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 519-553, October.
    10. Leonardo Becchetti & Pierluigi Conzo & Fabio Pisani, 2018. "Education and health in Europe," Applied Economics, Taylor & Francis Journals, vol. 50(12), pages 1362-1377, March.
    11. McCarthy, Jaki S. & Jacob, Thomas & McCraken, Amanda, 2010. "Modeling Non-response in National Agricultural Statistics Service (NASS) Surveys Using Classification Trees," NASS Research Reports 235029, United States Department of Agriculture, National Agricultural Statistics Service.
    12. Crossley, Thomas F. & Fisher, Paul & Low, Hamish, 2021. "The heterogeneous and regressive consequences of COVID-19: Evidence from high quality panel data," Journal of Public Economics, Elsevier, vol. 193(C).
    13. Kerstin Ruckdeschel & Lenore Sauer & Robert Naderi, 2016. "Reliability of retrospective event histories within the German Generations and Gender Survey," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(11), pages 321-358.
    14. repec:ags:unassr:235029 is not listed on IDEAS
    15. Sarah Brown & Mark N. Harris & Christopher Spencer & Karl Taylor, 2024. "Financial Expectations and Household Consumption: Does Middle‐Inflation Matter?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(4), pages 741-768, June.
    16. Ragui Assaad & Caroline Krafft & Shaimaa Yassin, 2018. "Comparing retrospective and panel data collection methods to assess labor market dynamics," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-34, December.
    17. Marcus Klemm, 2011. "You Don‘t Know what You‘ve got till It‘s Gone! Unemployment and Intertemporal Changes in Self-Reported Life Satisfaction," Ruhr Economic Papers 0297, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    18. Andrew M. Jones & Xander Koolman & Nigel Rice, 2006. "Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 543-569, July.
    19. Klemm, Marcus, 2011. "You Don't Know what You've got till It's Gone! Unemployment and Intertemporal Changes in Self-Reported Life Satisfaction," Ruhr Economic Papers 297, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    20. Hanly, Mark & Clarke, Paul & Steele, Fiona, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," LSE Research Online Documents on Economics 64896, London School of Economics and Political Science, LSE Library.
    21. Sarah Brown & Mark N. Harris & Preety Srivastava & Karl Taylor, 2018. "Mental Health and Reporting Bias: Analysis of the GHQ - 12," Working Papers 2018013, The University of Sheffield, Department of Economics.

    More about this item

    Keywords

    data quality; Generations and Gender Survey (GGS); GGP; GGS; fertility; nuptiality; demographic indicators; validation; vital registration;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dem:demres:v:32:y:2015:i:24. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.