A note on the double k-class estimator in simultaneous equations

Kajal Lahiri and Chuanming Gao

MPRA Paper from University Library of Munich, Germany

Abstract: Dwivedi and Srivastava (1984, DS) studied the exact finite sample properties of Nagar’s (1962) double k-class estimator as continuous functions of its two characterizing scalars k1 and k2, and provided guidelines for their choice in empirical work. In this note we show that the empirical guidelines provided by DS are not entirely valid since they did not explore the complete range of the relevant parameter space in their numerical evaluations. We find that the optimal values of k2 leading to unbiased and mean squared error (MSE) minimizing double k-class estimators are not symmetric with respect to the sign of the product ρω12, where ρ is the correlation coefficient between the structural and reduced form errors, and w12 is the covariance between the unrestricted reduced form errors. Specifically, when ρω12 is positive,the optimal value of k2 is generally positive and greater than k1, which partly explains the superior performance of Zellner’s (1998) Bayesian Method of Moments (BMOM) and Extended MELO estimators reported in Tsurumi (1990).

Keywords: Limited Information; Simultaneous Equations; Finite Sample; Mean Squared Error. (search for similar items in EconPapers)
JEL-codes: C30 (search for similar items in EconPapers)
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Journal of Econometrics 108 (2002): pp. 101-111

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/22323/1/MPRA_paper_22323.pdf original version (application/pdf)

Related works:
Journal Article: A note on the double k-class estimator in simultaneous equations (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:22323

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().