Which moments to match?
Abstract
We describe an intuitive, simple, and systematic approach to generating moment conditions
for generalized method of moments (GMM) estimation of the parameters of a structural
model. The idea is to use the score of a density that has an analytic expression to
define the GMM criterion. The auxiliary model that generates the score should closely
approximate the distribution of the observed data, but is not required to nest it.
If the auxiliary model nests the structural model then the estimator is as efficient
as maximum likelihood. The estimator is advantageous when expectations under a structural
model can be computed by simulation, by quadrature, or by analytic expressions but
the likelihood cannot be computed easily. © 1996 Cambridge University Press.
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https://hdl.handle.net/10161/2542Collections
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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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