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Mode Preferences in Business Surveys: Evidence from Germany

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  • Christian Seiler

Abstract

With the world-wide spread of the internet in the 1990s, the conduction of web or e-mail surveys became popular in research. Although these surveys provide fast data collection and reduced costs, results may suffer from biases due to the survey mode. While a variety of studies concerning mode effects in household or individual surveys exists, only less is known in case of business surveys. To give a contribution to this topic, we analyse a large German business survey – the Ifo Business Survey – which is answered by about 7,000 respondents each month since 1949. In this paper, we focus on three different aspects with respect to the survey mode: data quality, respondents' profiles and response behavior. Our results show that e-mail or web surveys reduce nonresponse and are more likely used by larger firms which operate in technology-related business areas.

Suggested Citation

  • Christian Seiler, 2014. "Mode Preferences in Business Surveys: Evidence from Germany," ifo Working Paper Series 193, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_193
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    References listed on IDEAS

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    1. Andrea Carriero & Massimiliano Marcellino, 2011. "Sectoral Survey‐based Confidence Indicators for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 175-206, April.
    2. 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.
    3. Christian Seiler, 2014. "The determinants of unit non-response in the Ifo Business Survey," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 161-177, September.
    4. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
    5. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    6. Michael Kleemann & Manuel Wiegand, 2014. "Are Real Effects of Credit Supply Overestimated? Bias from Firms' Current Situation and Future Expectations," ifo Working Paper Series 192, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Florian Janik & Susanne Kohaut, 2012. "Why don’t they answer? Unit non-response in the IAB establishment panel," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(3), pages 917-934, April.
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    More about this item

    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

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