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What can we learn from the fifties?

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  • Fabian Gouret

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

Economists have increasingly elicited from survey respondents probabilistic expectations. Subjective probabilistic expectations show great promise to improve the estimation of structural models of decision-making under uncertainty. However, a robust finding in these surveys is an inappropriate heap of responses at “50 percent”, suggesting that some of these responses are uninformative. The way these 50s are treated in the subsequent analysis is of major importance. Taking the 50s at face value will bias any aggregate statistics. On the reverse deleting them is not appropriate if some of these answers do convey some information. Furthermore, the attention of researchers is so focused on this heap of 50s that they do not consider the possibility that other answers may be uninformative as well. This paper proposes to take a fresh look at these questions using a new method based on extremely weak assumptions to identify the informativeness of an answer. Applying the method to probabilistic expectations of equity returns in three waves of the Survey of Economic Expectations in 1999-2001, I find that: (i.) at least 65 percent of the 50s convey no information at all; (ii.) it is the answer most often provided among the uninformative answers; (iii.) but even if the 50s are a major contributor to noise, they represent at best 70 percent of the identified uninformative answers. These findings have various implications for survey design.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Fabian Gouret, 2017. "What can we learn from the fifties?," Post-Print hal-02980367, HAL.
  • Handle: RePEc:hal:journl:hal-02980367
    DOI: 10.1002/for.2468
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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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