Use this identifier to quote or link this document:

Estimation of dynamic latent variable models using simulated nonparametric moments
Creel, Michael D.
Universitat Autònoma de Barcelona. Unitat de Fonaments de l'Anàlisi Econòmica; Institut d'Anàlisi Econòmica
Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.
Estimació, Teoria de l'
Estadística no paramètrica
Aquest document està subjecte a una llicència d'ús de Creative Commons, amb la qual es permet copiar, distribuir i comunicar públicament l'obra sempre que se'n citin l'autor original, la universitat, la unitat i l’institut i no se'n faci cap ús comercial ni obra derivada, tal com queda estipulat en la llicència d'ús (
Working Paper
Working papers; 725.08

Full text files in this document

Files Size Format
72508.pdf 164.9 KB PDF

Show full item record