In this paper, we propose finite-sample inference procedures for parametric econometric models whose likelihood function is intractable and require simulation-based estimation methods, like indirect inference (Gourieroux, Monfort and Renault, 1993) or the efficient method of moments (Gallant and Tauchen, 1996). The procedures proposed are based on extensions of the technique of Monte Carlo tests which applies naturally to any model that can simulated. In particular, we show that the method of maximized Monte Carlo tests allows to control perfectly the level of test procedures for which only asymptotic justifions are typically proposed. The technique is applied to inference on stochastic differential equations.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).
Related research
Keywords:
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Gourieroux, C & Monfort, A & Renault, E, 1993.
"Indirect Inference,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
[Downloadable!] (restricted)
Other versions:
Gourieroux, C. & Monfort, A. & Renault, E., 1992.
"Indirect Inference,"
Papers
92.279, Toulouse - GREMAQ.
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)