Assess the Goodness of Fit for Risk Aversion Parameter of First Price Auction via Nonparametric Method

Xin An ； Shu-Lin Liu ； Shuo Xu

《管理科學與統計決策》 6卷4期 (2009/12) Pp. 38-42

https://doi.org/10.6704/JMSSD.2009.6.4.38

並列摘要

Traditional approaches estimated the parameter of risk aversion either from real-world auction data or laboratory data, but there is no way to validate how well it was estimated. This paper uses structurally nonparametric method to analyze the goodness of fit for risk aversion parameter via Monte Carlo simulation experiment. Experimental results show that the goodness of fit is quite good. In particular, for five different values of risk aversion parameter, our model independent of the preference of bidders can do a good job when the number of bidders is sufficiently large. Moreover, we find that the risk aversion model is more robust within the independent private value paradigm.

並列關鍵字

Risk Aversion ； Nonparametric Method ； Monte Carlo Simulation ； Goodness of Fit

參考文獻

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