Journal of Econometrics

Volume 74, Issue 1, 01-September-1996

J. Econometrics Vol. 74 (1) pp. 77-118

Qualitative and asymptotic performance of SNP density estimators

a Victor M Fenton
b A. Ronald Gallant

a Department of Economics, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico
b Department of Economics, University of North Carolina, Chapel Hill, NC 27599-3305, USA


The SNP estimator is the most convenient nonparametric method for simultaneously estimating the parameters of a nonlinear model and the density of a latent process by maximum likelihood. To determine if this convenience comes at a price, we assess the qualitative behavior of SNP in finite samples using the Marron--Wand test suite and verify theoretical convergence rates by Monte Carlo simulation. Our results suggest that there is no price for convenience because the SNP estimator is both qualitatively and asymptotically similar to the kernel estimator which is optimal.

Keyword(s): Density estimation; Convergence rates; SNP; Nonparametric

JEL Classification: C14