Advanced Search

Query:

Fill in the form and click »Search«...

Format:

Display: entries per page entries

Zbl 1014.62012
Hall, Alastair R.; Inoue, Atsushi
The large sample behaviour of the generalized method of moments estimator in misspecified models. (English)
[J] J. Econom. 114, No.2, 361-394 (2003). ISSN 0304-4076

Summary: This paper presents the limiting distribution theory for the GMM estimator when the estimation is based on a population moment condition which is subject to non-local (or fixed) misspecification. It is shown that if the parameter vector is overidentified then the weighting matrix plays a far more fundamental role than it does in the corresponding analysis for correctly specified models. \par Specifically, the rate of convergence of the estimator depends on the rate of convergence of the weighting matrix to its probability limit. The analysis is presented for four particular choices of the weighting matrix which are commonly used in practice. In each case the limiting distribution theory is different, and also different from the limiting distribution in a correctly specified model. Statistics are proposed which allow the researcher to test hypotheses about the parameters in misspecified models.

MSC 2000:: *62E20 Asymptotic distribution theory in statistics
62P20 Appl. of statistics to economics
62H12 Multivariate estimation

Keywords: misspesification; generalized method of moments; asymptotic distribution theory

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering Article Journal

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Advanced Search

Zentralblatt MATH Berlin [Germany]