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The relative efficiency of method of moments estimators

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438.0 Kb
Date
1999-09-01
Authors
Gallant, AR
Tauchen, G
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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
Journal article
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https://hdl.handle.net/10161/1900
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Tauchen

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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