Microdata imputations and macrodata implications: evidence from the Ifo Business Survey
AbstractA widespread method for now- and forecasting economic macro level parameters such as GDP growth rates are survey-based indicators which contain early information in contrast to official data. But surveys are commonly affected by nonresponding units which can produce biases if these missing values can not be regarded as missing at random. As many papers examined the effect of nonresponse in individual or household surveys, only less is known in the case of business surveys. So, literature leaves a gap on this issue. 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 on the macro level. Finally, we show that the bias is minimal and ignorable.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 37045.
Date of creation: 2012
Date of revision:
Business survey; Longitudinal data; Imputation; Nonresponse;
Find related papers by JEL classification:
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-03-08 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
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- 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.
- 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.
- 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, 11.
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