Minimum-data analysis of ecosystem service supply with risk averse decision makers

Abstract

There is a need for models that produce results that are both timely and sufficiently accurate to be useful to policy makers. The minimum-data approach of Antle and Valdivia (2006) responds to this need by supplying a spatially explicit first order approximation that models ecosystem supply by producers. However, producers in developing nations often are observed to deviate from simple expected profit maximization. Risk is one possible explanation for this divergence. This study builds upon the minimum-data approach by allowing for risk averse producer preferences. The study presents a framework for translating relative risk aversion measurements into the parameters needed for the mean-standard deviation utility function. This study utilizes experimental and econometric measurements of risk aversion by other researchers to parameterize the model. Historic weather data are used with crop yield models to simulate temporal variation in crop yields. The model is used to simulate the supply of carbon sequestration in Machakos, Kenya. At low levels of risk, producers behave in a manner consistent with risk neutrality. However as risks and risk aversion levels increase, there is an increasing divergence from the behavior implied by expected profit maximization. The effects of varying the structure of risk preferences were also examined. This study finds that, consistent with the results in a number of other studies, the level of risk aversion is generally a more important factor in simulated behavior than the structure of risk preferences. This study also examines the effects of increasing the spatial variation of returns. As the spatial variation of returns increases, the predicted producer behavior converges on a fifty percent rate of adoption of the carbon sequestering system, regardless of other parameters. Overall, this study finds that - at levels of risk aversion measured in similar populations in developing nations - the inclusion of risk aversion in the model provides an explanation for why the observed behavior of producers appears to diverge from expected profit maximization.