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Assessing the Rationality of Survey Expectations: The Probability Approach

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  • Breitung Jörg

    (University of Bonn, Institute of Econometrics, Adenauerallee 24–42, 53113 Bonn, Germany)

Abstract

This paper considers popular methods for the quantification of survey expectations. We investigate the asymptotic properties of two variants of the probability approach originally suggested by Carlson and Parkin (1975). It is argued that the traditional method can be interpreted as an instrumental variable estimator that suffers from a severe loss of efficiency if the mean of the target variable is close to zero. The regression approach advocated by Pesaran (1984) can be seen as a special case assuming that expectations of survey participants are uniformly distributed. Applying alternative variants of these approaches to the ZEW survey of expected changes in the inflation rate demonstrates that the regression variant of the Carlson-Parkin methodology yields the best fit to the realized changes of the inflation rate. It turns out, however, that even the best performing quantification method fails to fulfill the requirement of rational expectations, as the variance of the expectation error is significantly reduced by including additional variables such as the lagged inflation rate.

Suggested Citation

  • Breitung Jörg, 2008. "Assessing the Rationality of Survey Expectations: The Probability Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 630-643, October.
    • Handle: RePEc:jns:jbstat:v:228:y:2008:i:5-6:p:630-643
    DOI: 10.1515/jbnst-2008-5-613
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    References listed on IDEAS

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    Cited by:

    1. Piotr Białowolski & Tomasz Kuszewski & Bartosz Witkowski, 2010. "Business Survey Data in Forecasting Macroeconomic Indicators with Combined Forecasts," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 4(4), December.
    2. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.

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