J. Econometrics Vol. 92 (1) pp. 149-172
a A. Ronald Gallant
b George Tauchen
aDepartment of Economics, University of North Carolina,
Chapel Hill NC 27599-3305, USA
bDepartment of Economics, Duke University, Durham NC
27708-0097, USA
Received 1 June 1998; received in revised form 1 September 1998; accepted 8 October 1998
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.
JEL Classification: C13; C14; C15
Keyword(s): Simulation estimators; Efficient method of moments; Conventional method of moments; Financial market data; Auction data