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Forecasting Errors: Yet More Problems for Identification?


  • Contini, Bruno

    () (LABORatorio R. Revelli)


Forecasting errors pose a serious problem of identification, often neglected in empirical applications. Any attempt of estimating choice models under uncertainty may lead to severely biased results in the presence of forecasting errors even when individual expectations on future events are observed together with the standard outcome variables.

Suggested Citation

  • Contini, Bruno, 2009. "Forecasting Errors: Yet More Problems for Identification?," IZA Discussion Papers 4035, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp4035

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    References listed on IDEAS

    1. Manski, Charles F, 1999. "Analysis of Choice Expectations in Incomplete Scenarios," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 49-66, December.
    2. Luigi Guiso & Giuseppe Parigi, 1999. "Investment and Demand Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 185-227.
    3. Lusardi, Annamaria & Mitchell, Olivia S., 2007. "Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 205-224, January.
    4. Contini, Bruno & Morini, Matteo, 2007. "Testing Bounded Rationality against Full Rationality in Job Changing Behavior," IZA Discussion Papers 3148, Institute for the Study of Labor (IZA).
    5. Christelis, Dimitris & Jappelli, Tullio & Padula, Mario, 2010. "Cognitive abilities and portfolio choice," European Economic Review, Elsevier, vol. 54(1), pages 18-38, January.
    6. Bruno Contini, 1966. "A Note on Arrow's Postulates for a Social Welfare Function," Journal of Political Economy, University of Chicago Press, vol. 74, pages 278-278.
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    More about this item


    identification; forecasting errors; subjective probabilities;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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