Efficient Estimation of Risk Preferences

Feng Wu and Zhengfei Guan

American Journal of Agricultural Economics, 2018, vol. 100, issue 4, 1172-1185

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.

Keywords: Estimation efficiency; GMM; Monte Carlo; risk distribution; risk preferences; seminonparamtric estimation (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:100:y:2018:i:4:p:1172-1185.

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