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How Serious is the Measurement-Error Problem in a Popular Risk-Aversion Task?

Fabien Perez (), Guillaume Hollard (), Radu Vranceanu () and Delphine Dubart
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Fabien Perez: ENSAE - Ecole Nationale de la Statistique et de l'Analyse Economique - Ecole Nationale de la Statistique et de l'Analyse Economique
Guillaume Hollard: CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Delphine Dubart: ESSEC Business School - Essec Business School

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: This paper uses the test/retest data from the Holt and Laury (2002) experiment to provide estimates of the measurement error in this popular risk-aversion task. Maximum likelihood estimation suggests that the variance of the measurement error is approximately equal to the variance of the number of safe choices. Simulations confirm that the coefficient on the risk measure in univariate OLS regressions is approximately half of its true value. Unlike measurement error, the discrete transformation of continuous riskaversion is not a major issue. We discuss the merits of a number of different solutions: increasing the number of observations, IV and the ORIV method developed by Gillen et al. (2019).

Keywords: ORIV; Experiments; Measurement error; Risk-aversion; Test/retest (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-upt
Date: 2019-09-17
Note: View the original document on HAL open archive server: https://hal-essec.archives-ouvertes.fr/hal-02291224
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