Showing papers by "George Tauchen published in 1986"
TL;DR: In this article, the authors developed a procedure for finding a discrete-valued Markov chain whose sample paths approximate well those of a vector autoregression, which has applications in economics, finance, and econometrics where approximate solutions to integral equations are required.
1,586 citations
TL;DR: In this paper, the authors examined the properties of generalized method of moments estimators of utility function parameters and found that with short lags, the estimates are nearly asymptotically optimal, but with longer lags the estimates concentrate around biased values and confidence intervals become misleading.
Abstract: 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.
355 citations
TL;DR: In this paper, the authors derived an explicit expression for the lower bound on the variance of the GMM estimate of the curvature parameter of the CRR utility function under simplifying assumptions, and showed that qualitative conclusions reached on the basis of the expression are reliable indicators of what can be expected in complicated estimation situations where explicit formulae are not available.
1 citations