Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

Simulation-Based Estimation of Models with Lagged Latent Variables

G. Laroque and B. Salanié
Journal of Applied Econometrics
Vol. 8, Supplement: Special Issue on Econometric Inference Using Simulation Techniques (Dec., 1993), pp. S119-S133
Published by: Wiley
Stable URL: http://www.jstor.org/stable/2285077
Page Count: 15
  • Download ($42.00)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Simulation-Based Estimation of Models with Lagged Latent Variables
Preview not available

Abstract

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 nondifferentiable models.

Page Thumbnails

  • Thumbnail: Page 
[S119]
    [S119]
  • Thumbnail: Page 
S120
    S120
  • Thumbnail: Page 
S121
    S121
  • Thumbnail: Page 
S122
    S122
  • Thumbnail: Page 
S123
    S123
  • Thumbnail: Page 
S124
    S124
  • Thumbnail: Page 
S125
    S125
  • Thumbnail: Page 
S126
    S126
  • Thumbnail: Page 
S127
    S127
  • Thumbnail: Page 
S128
    S128
  • Thumbnail: Page 
S129
    S129
  • Thumbnail: Page 
S130
    S130
  • Thumbnail: Page 
S131
    S131
  • Thumbnail: Page 
S132
    S132
  • Thumbnail: Page 
S133
    S133