Agricultural Economics Department

 

First Advisor

Simanti Banerjee

Second Advisor

Taro Mieno

Third Advisor

Christopher Gustafson

Date of this Version

Summer 8-2-2019

Citation

B. Ronspies. "MEASURING IMPACTS OF UNCERTAINTY, IRREVERSIBILITY, AND LOSS AVERSION ON THE ADOPTION OF CROP CANOPY SENSORS AMONG NEBRASKA CORN PRODUCERS." Masters Thesis.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of a Master of Science, Major: Agricultural Economics, Under the Supervision of Professor Simanti Banerjee and Taro Mieno. Lincoln, Nebraska: August, 2019

Copyright © 2019 Brooks Ronspies

Abstract

Understanding barriers to adoption of Precision Agricultural Technologies (PATs) is important to the growth of agricultural productivity, efficiency, and sustainability. This thesis proposes and evaluates a model for estimating the impact of uncertainty, irreversibility, and loss aversion on producers’ adoption of crop canopy sensors in order to explain adoption behavior that contradicts previous expectations about the conditions necessary for technology adoption. The model is evaluated using estimated statistical distributions of price and field characteristics designed to match observations of actual corn and nitrogen prices, and of conventional and crop canopy sensor based nitrogen application. Results from this model using expected utility theory indicate that producers maximize their profit if they adopt crop canopy sensors immediately when their expected value becomes greater than the expected value of their previous nitrogen application method. According to prospect theory, producers maximize their subjective utility when they defer adoption of crop canopy sensors until they become 1.03 times more profitable than uniform rate application, greatly reducing the speed at which we expect producers to adopt crop canopy sensors. This difference implies that risk preferences and the manner in which producer utility/value under risk and uncertainty is modeled play a significant role in the adoption of PATs such as crop canopy sensors.

Advisors: Simanti Banerjee and Taro Mieno

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