Risk, Risk Aversion, and Agricultural Technology Adoption ─ A Novel Valuation Method Based on Real Options and Inverse Stochastic Dominance

Alisa Spiegel,Wolfgang Britz,Robert Finger

doi:10.1093/qopen/qoab016

Alisa Spiegel, Wolfgang Britz + Show 1 more

Open Access

https://doi.org/10.1093/qopen/qoab016

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Journal: Q Open	Publication Date: Jul 22, 2021
Citations: 9	License type: CC BY 4.0

Affiliation: University of Bonn, ETH Zurich

Abstract

AbstractRisk and risk preferences belong to the key determinants of investment-based technology adoption in agriculture. We develop and apply a novel approach in which an inverse second order stochastic dominance approach is integrated into a stochastic dynamic farm-level model to quantify the effect of both risk and risk aversion on the timing and scale of agricultural technology adoption. Our illustrative example on short rotation coppice adoption shows that risk aversion leads to technology adoption that takes place earlier, but to a smaller extent. In contrast, higher levels of risk exposure lead to postponed but overall larger adoption. These effects would be obscured if technology adoption is not analyzed in a farm-scale context or considered as a now-or-never decision, the still dominant approach in the literature.

Highlights

Decisions to take up new activities and/or adopt new technologies are of crucial relevance for farm success (Blandford and Hill 2006, p.43; Kumar and Joshi 2014) and reflect production, market, technological and institutional risks as inherent properties of agriculture (e.g. Chavas 2004), as farmers are often risk averse (e.g. Iyer et al 2020)
We develop and apply a novel approach in which an inverse second order stochastic dominance approach is integrated into a stochastic dynamic farm-level model to quantify the effect of both risk and risk aversion on the timing and scale of agricultural technology adoption
We assume that the decision about optimal time and scale of a new technology adoption is based on an Net Present Value (NPV) maximization; subject to existing resource endowments and other farmlevel constraints; conditional to possible future developments of stochastic variables; while ISSD constraints approximate inverse second order stochastic dominance over the endogenously simulated distribution of discounted terminal wealth

Summary

Introduction

Decisions to take up new activities and/or adopt new technologies are of crucial relevance for farm success (Blandford and Hill 2006, p.43; Kumar and Joshi 2014) and reflect production, market, technological and institutional risks as inherent properties of agriculture (e.g. Chavas 2004), as farmers are often risk averse (e.g. Iyer et al 2020). We here contribute to close this gap by developing a novel farm-level stochastic dynamic programming approach that quantifies the effects of risk and risk preferences on optimal scale and timing of investment-based technology adoption. We discuss the advantages and disadvantages of the dominant approaches suggested by the literature, namely the expected utility function, using a risk-adjusted discount rate, and the concept of stochastic dominance We show that they are limited when optimal time and scale of technology adoption are considered, and competition among different farm activities for limited resources. Capturing level of risk and risk aversion by one joint parameter excludes their separate analysis Based on these considerations, we regard second-order stochastic dominance (SSD) as a promising option; its application offers new insights on how risk and risk aversion affect the timing and scale of technology adoption at farm-level.

Inverse stochastic dominance and stochastic dynamic programming

Risk analysis and hypotheses

Solution process

Stochastic component

Results

Discussion and conclusion