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Microdata imputations and macrodata implications: Evidence from the Ifo Business Survey

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  • Seiler, Christian
  • Heumann, Christian

Abstract

A widespread method for forecasting economic macro level parameters such as GDP growth rates is survey-based indicators that contain early information in contrast to official data. But surveys are commonly affected by nonresponding units, which can cause biased results. Many papers have examined the effect of nonresponse in individual or household surveys, but less is known in the case of business surveys. For this reason, we analyse and impute the missing observations in the Ifo Business Survey, a large business survey in Germany. The most prominent result of this survey is the Ifo Business Climate Index, a leading indicator for the German business cycle. To reflect the underlying latent data generating process, we compare different imputation approaches for longitudinal data. After this, the microdata are aggregated and the results are compared with the original indicators to evaluate their implications at the macro level. Finally, we show that the differences between the original and imputed indicators do not lead to substantial changes in the interpretation and the forecasting performance of the indicators.

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Bibliographic Info

Article provided by Elsevier in its journal Economic Modelling.

Volume (Year): 35 (2013)
Issue (Month): C ()
Pages: 722-733

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Handle: RePEc:eee:ecmode:v:35:y:2013:i:c:p:722-733

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Web page: http://www.elsevier.com/locate/inca/30411

Related research

Keywords: Business survey; Imputation; Longitudinal data; Nonresponse;

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References

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  1. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics 0308001, EconWPA.
  2. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer, vol. 92(1), pages 101-114, February.
  3. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," Ifo Working Paper Series Ifo Working Paper No. 126, Ifo Institute for Economic Research at the University of Munich.
  4. 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.
  5. James Honaker & Gary King & Matthew Blackwell, . "Amelia II: A Program for Missing Data," Journal of Statistical Software, American Statistical Association, vol. 45(i07).
  6. Christian Seiler, 2010. "Dynamic Modelling of Nonresponse in Business Surveys," Ifo Working Paper Series Ifo Working Paper Nr. 93, Ifo 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.
  8. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data : A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
  9. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
  10. Jörg Drechsler, 2011. "Multiple imputation in practice—a case study using a complex German establishment survey," AStA Advances in Statistical Analysis, Springer, vol. 95(1), pages 1-26, March.
  11. Kristian Kleinke & Mark Stemmler & Jost Reinecke & Friedrich Lösel, 2011. "Efficient ways to impute incomplete panel data," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 351-373, December.
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Citations

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Cited by:
  1. Robert Lehmann & Antje Weyh, 2014. "Forecasting employment in Europe: Are survey results helpful?," Ifo Working Paper Series Ifo Working Paper No. 182, Ifo Institute for Economic Research at the University of Munich.
  2. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute for Economic Research at the University of Munich, number 52.
  3. Christian Seiler, 2012. "Zur Robustheit des ifo Geschäftsklimaindikators in Bezug auf fehlende Werte," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(17), pages 19-22, 09.

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