Simulation Based Inference in Models with Heterogeneity
In this paper we discuss the usefulness, for models with heterogeneity, of simulation techniques in inference procedures, like maximum likelihood method, generalized moments method or pseudo maximum likelihood methods. These procedures are studied from the point of view of consistency, asymptotic normality, convergence rates and possible asymptotic bias. We carefully distinguish the case where the simulations are different for all the observations from the case where they are identical.
Volume (Year): (1991)
Issue (Month): 20-21 ()
|Contact details of provider:|| Postal: |
Web page: http://annales.ensae.fr/Email:
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:adr:anecst:y:1991:i:20-21:p:04. 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: (Robert Gary-Bobo)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.