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On the robustness of balance statistics with respect to nonresponse

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  • Christian Seiler

Abstract

A general problem for survey conductors is the fact that the response decision can be connected to the intended answer of the non-respondents. This nonresponse bias might have a substantial effect on the aggregated results. In this paper, a participation framework for the widely used business cycle balance statistics indicators is examined. An extensive simulation study is performed to analyse their effects. The analyses show that these indicators are extremely stable towards nonresponse biases.

Suggested Citation

  • 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.
    • Handle: RePEc:oec:stdkab:5jrxqbwcjdr3
    DOI: 10.1787/jbcma-2014-5jrxqbwcjdr3
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    Cited by:

    1. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    2. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    3. 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.
    4. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    5. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.
    6. Christian Seiler, 2012. "On the Robustness of the Ifo Business Climate Index in Relation to Missing Values," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(17), pages 19-22, September.
    7. 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.
    8. David Leuwer & Bernd Süssmuth, 2013. "The Exchange Rate Susceptibility of Some European Core Industries and the Currency Union," CESifo Working Paper Series 4253, CESifo.
    9. Leuwer, David & Süßmuth, Bernd, 2017. "The exchange rate susceptibility of European core industries, 1995-2010," Working Papers 147, University of Leipzig, Faculty of Economics and Management Science.

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    More about this item

    Keywords

    balance statistics; business tendency survey; nonresponse bias; simulation study;
    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

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