Diagnostic testing and evaluation of maximum likelihood models

dc.contributor.author	Tauchen, George	en_US
dc.date.accessioned	2010-03-09T15:29:34Z
dc.date.available	2010-03-09T15:29:34Z
dc.date.issued	1985	en_US
dc.identifier.uri	http://hdl.handle.net/10161/1912
dc.description.abstract	The paper develops a unified theory of likelihood specification testing based on M-estimators of auxiliary parameters. The theory is sufficiently general to encompass a wide class of specification tests including moment-based tests, Pearson-type goodness of fit tests, the information matrix test, and the Cox test. The paper also presents a framework based on Frechet differentiation for determining the effects of misspecification on the almost sure limits of parameter estimates and specification test statistics.	en_US
dc.format.extent	3944953 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.publisher	Journal of Econometrics	en_US
dc.subject	likelihood specification testing	en_US
dc.subject	misspecification	en_US
dc.title	Diagnostic testing and evaluation of maximum likelihood models	en_US
dc.type	Journal Article	en_US
dc.department	Economics