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Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence

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  • Christian Seiler

Abstract

Surveys are a widely used tool to answer socio-economic research question across disciplines. However, data collection can face certain problems such as nonresponding units. For household and population surveys, a large body of literature about the effects of nonresponse exist but only less is known in case of business surveys. This thesis deals with the missing values in the Ifo Business Survey which is conducted in similar form in nearly all OECD countries. The most prominent result of this survey is the Ifo Business Climate Index, a business cycle indicator for the German economy. This indicator is highly observed by entrepreneurs, analysts, politicians, journalists, academics and the general public. The results of this thesis show that business cycle indicators based on this type of questioning are very stable towards any kind of non-random missing data processes. This is shown by simulation studies as well as an estimation of the missing values. In particular, the missing values do not lead to a significant reduction in forecasting performance.

Suggested Citation

  • 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, September.
    • Handle: RePEc:ces:ifobei:52
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    Cited by:

    1. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    2. Michael Weinhardt & Alexia Meyermann & Stefan Liebig & Jürgen Schupp, 2016. "The Linked Employer-Employee Study of the Socio-Economic Panel (SOEP-LEE): Project Report," SOEPpapers on Multidisciplinary Panel Data Research 829, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Matthias Bannert & Andreas Dibiasi, 2014. "Unveiling Participant Level Determinants of Unit Non-Response in Business Tendency Surveys," KOF Working papers 14-363, KOF Swiss Economic Institute, ETH Zurich.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • 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
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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