The study of parameter structural estimation of first price auction based on the case of risk aversion

As a parameter structural estimation used in many fields, improved MLE (maximum likelihood estimation) only applies to the case of risk neutrality, which cannot explain agents´ behavior well. This paper generalizes the method to the risk aversion case when there exists two kinds of bid numbers, and gives a simple estimation procedure. Monte Carlo simulation experiment with four different risk aversion parameters including risk neutral case is used to verify the feasibility of the estimation procedure. The experimental results suggests that the estimation procedure can do a reasonable job in estimating the structural parameters of the first-price sealed-bid auction for risk aversion as well as risk neutrality cases, which provides an new idea for the application of the improved MLE.