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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: http://www.cesifo-group.de/DocDL/IfoWorkingPaper-93.pdf
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    References listed on IDEAS

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    1. repec:ces:ifosdt:v::y:2009:i::p:34-41 is not listed on IDEAS
    2. Maindonald, John, 2006. "Generalized Additive Models: An Introduction with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(b03).
    3. 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].
    4. Denise Hawkes & Ian Plewis, 2006. "Modelling non-response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491.
    5. Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.
    6. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
    7. 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(4), pages 62-63, January.
    8. 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.
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    Citations

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    Cited by:

    1. 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).
    2. James R Hines Jr & Niklas Potrafke & Marina Riem & Christoph Schinke, 2015. "Inter vivos transfers of ownership in family firms," Working Papers 1523, Oxford University Centre for Business Taxation.
    3. Strasser, Georg, 2013. "Exchange rate pass-through and credit constraints," Journal of Monetary Economics, Elsevier, vol. 60(1), pages 25-38.
    4. 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.
    5. Grinsven Vanessa Torres van & Bolko Irena & Bavdaž Mojca, 2014. "In Search of Motivation for the Business Survey Response Task," Journal of Official Statistics, De Gruyter Open, vol. 30(4), pages 1-28, December.
    6. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," ifo Working Paper Series 126, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. 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, June.
    8. 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.
    9. 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.
    10. 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.

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