Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data
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.
Type
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https://hdl.handle.net/10161/1886Collections
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Show full item recordScholars@Duke
George E. Tauchen
William Henry Glasson Distinguished Professor Emeritus
George Tauchen is the William Henry Glasson Professor of Economics and professor of
finance at the Fuqua School of Business. He joined the Duke faculty in 1977 after
receiving his Ph.D. from the University of Minnesota. He did his undergraduate work
at the University of Wisconsin. Professor Tauchen is a fellow of the Econometric Society,
the American Statistical Association, the Journal of Econometrics, and the Society
for Financial Econometrics (SoFie). He is also the 2003 Duke University Sc

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