LAUSR

This paper analyzes the role of risk aversion in biotechnology adoption with the application on the US genetically modified corn. A dynamic programming analysis of technology adoption is conducted using the Kalman filter as a representation of the associated learning process. The relevant Bellman equation is jointly solved within model estimation using a minimum-distance estimator. Results show that the more the risk-averse farmers are, the later they adopt GM technology, such effects being statistically significant. Sensitivity analysis results examine the factors affecting farmers’ behavior. They document the role of risk aversion in technology adoption. They also uncover the presence of farm heterogeneity in the process of adopting a new technology.