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Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach

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  • Christian M. Dahl

  • Lin Xia

Abstract

In this paper, we develop a likelihood approach for quantification of qualitative survey data on expectations and perceptions and we propose a new test for expectation consistency (unbiasedness). Our quantification scheme differs from existing methods primarily by using prior information (perhaps derived from economic theory or well established empirical relations) on the underlying process driving the variable of interest. To investigate the properties of our novel quantification scheme and to analyze the size and power properties of the new expectation consistency test, we perform Monte Carlo simulation studies. Overall, the simulation results are very encouraging and show that efficiency gains from including prior information can be substantial relative to existing quantification schemes. Finally, we provide an empirical illustration...

Suggested Citation

  • Christian M. Dahl & Lin Xia, 2004. "Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 71-92.
  • Handle: RePEc:oec:stdkaa:5lmqcr2jfbd3
    DOI: 10.1787/jbcma-v2004-art5-en
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    Cited by:

    1. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
    2. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    3. Malgarini, Marco & Margani, Patrizia & Martelli, Bianca Maria, 2005. "Re-engineering the ISAE manufacturing survey," MPRA Paper 42440, University Library of Munich, Germany.

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