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Modeling Expectation Formation Involving Several Sources of Information

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  • Otwin Becker
  • Johannes Leitner
  • Ulrike Leopold-Wildburger

Abstract

Experimental studies of expectation formation of subjects are predominantly limited to the prediction of one single time series despite the practical relevance of expectations in situations with multiple sources of information. In this paper, we report on an experiment in which subjects are given time series (indicators) as additional information for the judgemental forecast of a stationary time series. The quality and the number of these indicators are varied in three versions of a forecasting experiment. We explore the effects on forecasting accuracy and we test the average forecasts of the subjects for consistency with the rational expectations hypothesis. A simple heuristic is presented that explains the average forecasting behavior better than the rational expectations if indicators are presented to the subjects. It is demonstrated by a simulation study that this result is representative for the considered stationary stochastic processes. Copyright Verein für Socialpolitik and Blackwell Publishing Ltd. 2008.

Suggested Citation

  • Otwin Becker & Johannes Leitner & Ulrike Leopold-Wildburger, 2008. "Modeling Expectation Formation Involving Several Sources of Information," German Economic Review, Verein für Socialpolitik, vol. 9, pages 96-112, February.
    • Handle: RePEc:bla:germec:v:9:y:2008:i::p:96-112
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    References listed on IDEAS

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    1. Dwyer, Gerald P, Jr, et al, 1993. "Tests of Rational Expectations in a Stark Setting," Economic Journal, Royal Economic Society, vol. 103(418), pages 586-601, May.
    2. Becker, Otwin & Leitner, Johannes & Leopold-Wildburger, Ulrike, 2007. "Heuristic modeling of expectation formation in a complex experimental information environment," European Journal of Operational Research, Elsevier, vol. 176(2), pages 975-985, January.
    3. Hey, John D., 1994. "Expectations formation: Rational or adaptive or ...?," Journal of Economic Behavior & Organization, Elsevier, vol. 25(3), pages 329-349, December.
    4. Lim, Joa Sang & O'Connor, Marcus, 1996. "Judgmental forecasting with time series and causal information," International Journal of Forecasting, Elsevier, vol. 12(1), pages 139-153, March.
    5. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
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    Cited by:

    1. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    2. Otwin Becker & Johannes Leitner & Ulrike Leopold-Wildburger, 2009. "Expectation formation and regime switches," Experimental Economics, Springer;Economic Science Association, vol. 12(3), pages 350-364, September.
    3. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.

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