The relative efficiency of method of moments estimators
Abstract
The asymptotic relative efficiency of efficient method of moments when implemented
with a seminonparametric auxiliary model is compared to that of conventional method
of moments when implemented with polynomial moment functions. Because the expectations
required by these estimators can be computed by simulation, these two methods are
commonly used to estimate the parameters of nonlinear latent variables models. The
comparison is for the models in the Marron-Wand test suite, a scale mixture of normals,
and the second largest order statistic of the lognormal distribution. The latter models
are representative of financial market data and auction data, respectively, which
are the two most common applications of simulation estimators. Efficient method of
moments dominates conventional method of moments over these models. © 1999 Elsevier
Science S.A. All rights reserved.
Type
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https://hdl.handle.net/10161/1900Collections
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George E. Tauchen
William Henry Glasson Distinguished Professor of Economics
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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