Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained From Financial Market Data
通过模拟随机交换经济中的资产回报数据，检验广义矩方法估计效用函数参数的性质，发现工具变量滞后长度会导致方差与偏差的权衡，且过度识别检验在小样本中表现良好。
The article examines the properties of generalized method of moments GMM estimators of utility function parameters. The research strategy is to apply the GMM procedure to generated data on asset returns from stochastic exchange economies; discrete methods and Markov chain models are used to approximate the solutions to the integral equations for the asset prices. The findings are as follows: (a) There is variance/bias trade-off regarding the number of lags used to form instruments; with short lags, the estimates of utility function parameters are nearly asymptotically optimal, but with longer lags the estimates concentrate around biased values and confidence intervals become misleading, (b) The test of the overidentifying restrictions performs well in small samples; if anything, the test is biased toward acceptance of the null hypothesis.