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Simulation‐based estimation of models with lagged latent variables
Author(s) -
Laroque G.,
Salanié B.
Publication year - 1993
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950080508
Subject(s) - econometrics , latent variable , estimation , disequilibrium , monte carlo method , computer science , latent class model , differentiable function , statistics , mathematics , economics , management , medicine , mathematical analysis , ophthalmology
We extend here our earlier work (Laroque‐Salanié, 1989) and propose a dynamic simulated pseudo‐maximum likelihood method to deal with a very general class of dynamic non‐linear models, including models with lagged latent variables. We test this method on Monte Carlo‐generated data for a canonical disequilibrium model. It appears to provide very satisfactory estimates at little computational cost. However, accurate estimation of the standard errors of the estimates may require some care in non‐differentiable models.