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Dynamic Modelling of Nonresponse in Business Surveys

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  • Christian Seiler

Abstract

It is well-known that nonresponse affects the results of surveys and can even cause bias due to selectivities if it cannot be regarded as missing at random. In contrast to household surveys, response behaviour in business surveys has been examined rarely in the literature. This paper is one of the first which analyses a large business survey on micro data level for unit nonresponse. The data base is the Ifo Business Tendency Survey, which was established in 1949 and has more than 5,000 responding firms each month. The panel structure allows to use statistical modelling including time-varying effects to check for the existence of a panel fatigue. The results show that there are huge differences in business characteristics such as size or sub-sector and that nonresponse is more frequent in economically good times.

Suggested Citation

  • Christian Seiler, 2010. "Dynamic Modelling of Nonresponse in Business Surveys," ifo Working Paper Series 93, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:ifowps:_93
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    File URL: https://www.ifo.de/DocDL/IfoWorkingPaper-93.pdf
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    References listed on IDEAS

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    5. Klaus Abberger & Manuel Birnbrich & Christian Seiler, 2009. "Der »Test des Tests« im Handel – eine Metaumfrage zum ifo Konjunkturtest," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 34-41, November.
    6. Anja Hönig, 2009. "The New EBDC Dataset: An Innovative Combination of Survey and Financial Statement Data," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(04), pages 62-63, January.
    7. Janik, Florian & Kohaut, Susanne, 2009. "Why don't they answer? Unit non-response in the IAB Establishment Panel," FDZ Methodenreport 200907_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    Cited by:

    1. Seiler, Christian & Heumann, Christian, 2013. "Microdata imputations and macrodata implications: Evidence from the Ifo Business Survey," Economic Modelling, Elsevier, vol. 35(C), pages 722-733.
    2. Strasser, Georg, 2013. "Exchange rate pass-through and credit constraints," Journal of Monetary Economics, Elsevier, vol. 60(1), pages 25-38.
    3. Torres van Grinsven Vanessa & Bolko Irena & Bavdaž Mojca, 2014. "In Search of Motivation for the Business Survey Response Task," Journal of Official Statistics, Sciendo, vol. 30(4), pages 579-606, December.
    4. Christian Seiler, 2015. "On the robustness of balance statistics with respect to nonresponse," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 45-62.
    5. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52.
    6. Patrick Gleiser & Joseph W. Sakshaug & Marieke Volkert & Peter Ellguth & Susanne Kohaut & Iris Möller, 2022. "Introducing Web in a mixed‐mode establishment survey: Effects on nonresponse," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 891-915, July.
    7. James R. Hines & Niklas Potrafke & Marina Riem & Christoph Schinke, 2019. "Inter vivos transfers of ownership in family firms," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(2), pages 225-256, April.
    8. Earp Morgan & Toth Daniell & Phipps Polly & Oslund Charlotte, 2018. "Assessing Nonresponse in a Longitudinal Establishment Survey Using Regression Trees," Journal of Official Statistics, Sciendo, vol. 34(2), pages 463-481, June.
    9. Christian Seiler, 2012. "Zur Robustheit des ifo Geschäftsklimaindikators in Bezug auf fehlende Werte," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(17), pages 19-22, September.
    10. Alireza Rezaee & Mojtaba Ganjali & Ehsan Bahrami Samani, 2022. "Sample selection bias with multiple dependent selection rules: an application to survey data analysis with multilevel nonresponse," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-15, December.
    11. 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).
    12. Anja Hönig, 2010. "Linkage of Ifo Survey and Balance-Sheet Data: The EBDC Business Expectations Panel & the EBDC Business Investment Panel," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 130(4), pages 635-642.
    13. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.

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