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Efficient Estimation of Risk Preferences

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  • Feng Wu
  • Zhengfei Guan

Abstract

Risk and the risk attitude of agents are two fundamental elements of decision making under risk and uncertainty. Recent developments in risk and risk preference analyses have raised questions on conventional approaches to estimating risk preferences. This study proposes an estimation procedure that employs a seminonparametric estimator to estimate the density function of risk without imposing distributional assumptions, as well as a numerical integration method to construct closed-form expressions of conditional moment conditions for efficient estimation. The method achieves a substantial efficiency improvement relative to the conventional GMM approach in Monte Carlo simulations. The proposed approach is general and applies to the estimation of behavioral choice models under risk, or models that require expectation operations and closed-form equations for estimation.

Suggested Citation

  • Feng Wu & Zhengfei Guan, 2018. "Efficient Estimation of Risk Preferences," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(4), pages 1172-1185.
  • Handle: RePEc:oup:ajagec:v:100:y:2018:i:4:p:1172-1185.
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    File URL: http://hdl.handle.net/10.1093/ajae/aay015
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    Cited by:

    1. André, Pierre & Delesalle, Esther & Dumas, Christelle, 2021. "Returns to farm child labor in Tanzania," World Development, Elsevier, vol. 138(C).
    2. Robert G. Chambers & Margarita Genius & Vangelis Tzouvelekas, 2021. "Invariant Risk Preferences and Supply Response under Price Risk," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1802-1819, October.
    3. Joshua Huang & Teresa Serra & Philip Garcia, 2021. "The Value of USDA Announcements in the Electronically Traded Corn Futures Market: A Modified Sufficient Test with Risk Adjustments," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 712-734, September.
    4. Ng'ombe, John, 2019. "Economics of the Greenseeder Hand Planter, Discrete Choice Modeling, and On-Farm Field Experimentation," Thesis Commons jckt7, Center for Open Science.

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