Rice, irrigation and downside risk: a quantile analysis of risk exposure and mitigation on Korean farms

Abstract

This article develops a new quantile approach utilizing partial moments to evaluate risk exposure and illustrate risk valuation, and then applies it to examine the potential importance of 'fat tails', downside risk, and risk mitigation options associated with a highly controlled but stochastic production system − irrigated rice production in Korea. The econometric approach exploits a rich panel dataset to develop consistent and robust econometric estimates of the partial moments needed to implement the quantile-based decomposition of risk outcomes.Our results demonstrate that the costs of downside risk associated with Korean rice production system are quite large, providing an empirical validation of Weitzman's dismal theory.

Production Risks and Food Security under Alternative Technology Choices in Malawi: Application of a Multinomial Endogenous Switching Regression

“…Joint adoption reduces the cost of risk by 9% of the mean maize yield compared to non-adoption under moderate risk aversion (b = 2). Similar to the results of Kim et al (2014), our findings show that the cost of risk comes from exposure to downside risk and that this cost is quite large. The contribution of downside risk to the cost of risk is higher for non-adoption than adoption of SIPs (Figures 4b-d).…”

“…Similar to the results of Kim et al . (), our findings show that the cost of risk comes from exposure to downside risk and that this cost is quite large. The contribution of downside risk to the cost of risk is higher for non‐adoption than adoption of SIPs (Figures b–d).…”

“…The specifications of the production and risk functions follow the Antle (1983) flexible moment-based stochastic production function approach. A quantile moment-based risk analysis involving the first, second, and third moments of the production function as well as farmers' risk preferences is used to compute the cost of risk (Kim et al, 2014).…”

“…Third, this paper extends the empirical and methodological approach in the literature by implementing a quantile moment‐based risk analysis (Kim et al ., ). Our approach, apart from using a flexible moment‐based specification of a stochastic production function (Antle, ) in a multinomial endogenous switching treatment regression (MESTR) framework, also jointly analyzes the impacts of SIPs adoption while controlling for the selection bias in the production and risk functions stemming both from observed and unobserved heterogeneity.…”

Farmers' Adaptation to Extreme Weather Events through Farm Management and Its Impacts on the Mean and Risk of Rice Yield in China

“…In general, downside risk refers to the risk located in the lower tail of the payoff distribution (Kim et al 2014). While useful information about the risk effects of input adjustments can be obtained from understanding their impact on yield variance, analyzing the variance effect alone would not help differentiate between unexpected bad and good events (Di Falco and Veronesi 2014).…”