Calibrarion By Simulation for Small Sample Bias Correction
This paper is interested in small sample properties of the indirect inference procedure which has been previously studied only from an asymptotic point of view. First, we highlight the fact that the Andrews(1993) median-bias correction procedure for autoregresssive parameter of an AR(1) process is closely related to indirect inference; we prove that the counterpart of the midian-bias correction for indirect inference estimator is an exact bias correction in the sense of a generalized mean. Next, assuming that the auxiliary estimator admits an Edgeworth expansion, we prove that indirect inference operates automatically a second order bias correction. The latter is a well known property of the Bootstrap estimator; we therefore provide a precise comparison between these two simulation based estimators.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1996|
|Date of revision:|
|Contact details of provider:|| Postal: GREMAQ, Universite de Toulouse I Place Anatole France 31042 - Toulouse CEDEX France.|
Fax: 05 61 22 55 63
Web page: http://www-gremaq.univ-tlse1.fr/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:fth:gremaq:96.428. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.