IDEAS home Printed from https://ideas.repec.org/p/diw/diwsop/diw_sp288.html
   My bibliography  Save this paper

Individual and Neighborhood Determinants of Survey Nonresponse: An Analysis Based on a New Subsample of the German Socio-Economic Panel (SOEP), Microgeographic Characteristics and Survey-Based Interviewer Characteristics

Author

Listed:
  • Jörg-Peter Schräpler
  • Jürgen Schupp
  • Gert G. Wagner

Abstract

This study examines the phenomenon of nonresponse in the first wave of a refresher sample (subsample H) of the German Socio-Economic Panel Study (SOEP). Our first step is to link additional (commercial) microgeographic data on the immediate neighborhoods of the households visited by interviewers. These additional data (paradata) provide valuable information on respondents and nonrespondents, including milieu or lifestyle, dominant household structure, desire for anonymity, frequency of moves, and other important microgeographic information. This linked information is then used to analyze nonresponse. In a second step, we also use demographic variables for the interviewer from an administrative data set about the interviewers, and, in a third step, we use the results of a special interviewer survey. We use multilevel statistical modeling to examine the influence of neighborhoods and interviewers on non-contacts, inability to participate, and refusals. In our analysis, we find our additional variables useful for understanding and explaining non-contacts and refusals and the inability of some respondents to participate in surveys. These data provide an important basis for filling the information gap on response and nonresponse in panel surveys (and in cross-sectional surveys). However, the effect sizes of these effects are negligible. Ignoring these effects does not cause significant biases in statistical inferences drawn from the survey under consideration.

Suggested Citation

  • Jörg-Peter Schräpler & Jürgen Schupp & Gert G. Wagner, 2010. "Individual and Neighborhood Determinants of Survey Nonresponse: An Analysis Based on a New Subsample of the German Socio-Economic Panel (SOEP), Microgeographic Characteristics and Survey-Based Intervi," SOEPpapers on Multidisciplinary Panel Data Research 288, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Handle: RePEc:diw:diwsop:diw_sp288
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.354686.de/diw_sp0288.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter Hintze & Tobia Lakes, 2009. "Geographically Referenced Data in Social Science: A Service Paper for SOEP Data Users," Data Documentation 46, DIW Berlin, German Institute for Economic Research.
    2. Peter Hintze & Tobia Lakes, 2009. "Geographically Referenced Data for Social Science," RatSWD Working Papers 125, German Data Forum (RatSWD).
    3. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
    4. Jörg-Peter Schräpler, 2002. "Respondent Behavior in Panel Studies: A Case Study for Income-Nonresponse by Means of the German Socio-Economic Panel (GSOEP)," Discussion Papers of DIW Berlin 299, DIW Berlin, German Institute for Economic Research.
    5. F. Kreuter & K. Olson & J. Wagner & T. Yan & T. M. Ezzati‐Rice & C. Casas‐Cordero & M. Lemay & A. Peytchev & R. M. Groves & T. E. Raghunathan, 2010. "Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 389-407, April.
    6. Gundi Knies & C. Katharina Spieß, 2007. "Regional Data in the German Socio-Economic Panel Study (SOEP)," Data Documentation 17, DIW Berlin, German Institute for Economic Research.
    7. Jörg-Peter Schräpler, 2006. "Explaining Income Nonresponse – A Case Study by means of the British Household Panel Study (BHPS)," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(6), pages 1013-1036, December.
    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. Jürgen Schupp & Joachim R. Frick, 2010. "Multidisciplinary Household Panel Studies under Academic Direction," RatSWD Working Papers 140, German Data Forum (RatSWD).
    2. Kristen Olson, 2013. "Paradata for Nonresponse Adjustment," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 142-170, January.

    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. Dang, Rui, 2015. "Spillover effects of local human capital stock on adult obesity: Evidence from German neighborhoods," Ruhr Economic Papers 585, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    2. Thomas K. Bauer & Rui Dang, 2016. "Do Welfare Dependent Neighbors Matter for Individual Welfare Dependency?," SOEPpapers on Multidisciplinary Panel Data Research 848, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Michael Berlemann & Max Steinhardt & Jascha Tutt, 2015. "Do Natural Disasters Stimulate Individual Saving? Evidence from a Natural Experiment in a Highly Developed Country," SOEPpapers on Multidisciplinary Panel Data Research 763, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. Billari, Francesco C. & Giuntella, Osea & Stella, Luca, 2018. "Broadband internet, digital temptations, and sleep," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 58-76.
    5. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    6. Arnaud Chevalier & Benjamin Elsner & Andreas Lichter & Nico Pestel, 2018. "Immigrant Voters, Taxation and the Size of the Welfare State," SOEPpapers on Multidisciplinary Panel Data Research 994, DIW Berlin, The German Socio-Economic Panel (SOEP).
    7. Knies, Gundi, 2010. "Income comparisons among neighbours and life satisfaction in East and West Germany," ISER Working Paper Series 2010-11, Institute for Social and Economic Research.
    8. Philipp Huebler & Andreas Kucher, 2016. "Ashes to ashes, time to time - Parental time discounting and its role in the intergenerational transmission of smoking," Discussion Paper Series 326, Universitaet Augsburg, Institute for Economics.
    9. Osea Giuntella & Lorenzo Rotunno & Luca Stella, 2022. "Globalization, Fertility and Marital Behavior in a Lowest-Low Fertility Setting," CESifo Working Paper Series 9755, CESifo.
    10. Steffen Otterbach & Alfonso Sousa-Poza, 2016. "Job insecurity, employability and health: an analysis for Germany across generations," Applied Economics, Taylor & Francis Journals, vol. 48(14), pages 1303-1316, March.
    11. Spiess, C. Katharina & Wrohlich, Katharina, 2010. "Does distance determine who attends a university in Germany?," Economics of Education Review, Elsevier, vol. 29(3), pages 470-479, June.
    12. Jan Goebel & Michael Wurm & Gert G. Wagner, 2010. "Exploring the Linkage of Spatial Indicators from Remote Sensing Data with Survey Data: The Case of the Socio-Economic Panel (SOEP) and 3D City Models," SOEPpapers on Multidisciplinary Panel Data Research 283, DIW Berlin, The German Socio-Economic Panel (SOEP).
    13. Gundi Knies, 2012. "Income Comparisons Among Neighbours and Satisfaction in East and West Germany," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 106(3), pages 471-489, May.
    14. Jörg-Peter Schräpler & Jürgen Schupp & Gert G. Wagner, 2013. "Conversion of Non-Respondents in an Ongoing Panel Survey: The Case of the German Socio-Economic Panel (SOEP)," SOEPpapers on Multidisciplinary Panel Data Research 626, DIW Berlin, The German Socio-Economic Panel (SOEP).
    15. Cabane, Charlotte & Hille, Adrian & Lechner, Michael, 2015. "Mozart or Pelé? The effects of teenagers’ participation in music and sports," Economics Working Paper Series 1509, University of St. Gallen, School of Economics and Political Science.
    16. Heineck, Guido & Süssmuth, Bernd, 2013. "A different look at Lenin’s legacy: Social capital and risk taking in the Two Germanies," Journal of Comparative Economics, Elsevier, vol. 41(3), pages 789-803.
    17. Kemptner, Daniel & Tolan, Songül, 2018. "The role of time preferences in educational decision making," Economics of Education Review, Elsevier, vol. 67(C), pages 25-39.
    18. Eibich, Peter & Siedler, Thomas, 2020. "Retirement, intergenerational time transfers, and fertility," European Economic Review, Elsevier, vol. 124(C).
    19. Geyer, Johannes & Haan, Peter & Wrohlich, Katharina, 2015. "The effects of family policy on maternal labor supply: Combining evidence from a structural model and a quasi-experimental approach," Labour Economics, Elsevier, vol. 36(C), pages 84-98.
    20. Falk, Armin & Abeler, Johannes & Kosse, Fabian, 2021. "Malleability of preferences for honesty," CEPR Discussion Papers 16164, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Nonresponse; interviewer effects; microgeographic data; multilevel modeling; SOEP;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. SOEP based publications

    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:diw:diwsop:diw_sp288. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/sodiwde.html .

    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.