Testing the equality of two positive-definite matrices with application to informationmatrix testing

Jin Seo Cho, Halbert White

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

We provide a new characterization of the equality of two positive-definite matrices A and B, and we use this to propose several new computationally convenient statistical tests for the equality of two unknown positivedefinite matrices. Our primary focus is on testing the information matrix equality (e.g. White, 1982, 1994). We characterize the asymptotic behavior of our new trace-determinant information matrix test statistics under the null and the alternative and investigate their finite-sample performance for a variety of models: linear regression, exponential duration, probit, and Tobit. The parametric bootstrap suggested by Horowitz (1994) delivers critical values that provide admirable level behavior, even in samples as small as n =50. Our new tests often have better power than the parametric-bootstrap version of the traditional IMT; when they do not, they nevertheless perform respectably.

Original languageEnglish
Pages (from-to)491-556
Number of pages66
JournalAdvances in Econometrics
Volume33
DOIs
Publication statusPublished - 2014 Jan 1

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Equality
Testing
Parametric bootstrap
Linear regression model
Asymptotic behavior
Finite sample
Tobit
Critical value
Statistical tests
Test statistic
Information matrix test
Probit

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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Testing the equality of two positive-definite matrices with application to informationmatrix testing. / Cho, Jin Seo; White, Halbert.

In: Advances in Econometrics, Vol. 33, 01.01.2014, p. 491-556.

Research output: Contribution to journalArticle

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