Seminonparametric Maximum Likelihood Estimation Of Conditional Moment Restriction Models
This article studies estimation of a conditional moment restriction model with the seminonparametric maximum likelihood approach proposed by Gallant and Nychka ("Econometrica" 55 (March 1987), 363-90). Under some sufficient conditions, we show that the estimator of the finite dimensional parameter θ is asymptotically normally distributed and attains the semiparametric efficiency bound and that the estimator of the density function is consistent under "L" 2 norm. Some results on the convergence rate of the estimated density function are derived. An easy to compute covariance matrix for the asymptotic covariance of the θ estimator is presented. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.
Volume (Year): 48 (2007)
Issue (Month): 4 (November)
|Contact details of provider:|| Postal: 160 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104-6297|
Phone: (215) 898-8487
Fax: (215) 573-2057
Web page: http://www.econ.upenn.edu/ier
More information through EDIRC
|Order Information:|| Web: http://www.blackwellpublishing.com/subs.asp?ref=0020-6598 Email: |
When requesting a correction, please mention this item's handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1093-1118. 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: (Wiley-Blackwell Digital Licensing)or ()
If references are entirely missing, you can add them using this form.