A Positive Semi-definite Covariance Matrix for Hausman Specification Tests of Conditional and Marginal Densities
Oxford Bulletin of Economics and Statistics, 1995, vol. 57, issue 2, 277-81
When the joint density of data can be factorized into conditional and marginal densities, the Hausman (1978) test can be used for diagnosing misspecifications of these densities. However, since common covariance estimates of the difference of the two estimators used in the Hausman test need not be positive semidefinite in finite samples, the test statistic may be negative. This paper presents a simple and consistent covariance matrix that is positive semidefinite in any finite sample. Copyright 1995 by Blackwell Publishing Ltd
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bla:obuest:v:57:y:1995:i:2:p:277-81
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049
Access Statistics for this article
Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple
More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().