Quasi-maximum likelihood estimation revisited using the distance and direction method

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We examine an asymptotic analysis of differentiable econometric models using the distance and direction (DD) method introduced by Cho and White (2012), in which the conventional analysis for the quasi-maximum likelihood estimation and inference can be treated as a special case. We extend their approach and revisit the conventional quasi-likelihood ratio, Wald, and Lagrange multiplier test statistics through a different perspective. This new perspective is further analyzed in a unified framework, and we exploit this to introduce new classes of test statistics.

Original languageEnglish
Pages (from-to)89-112
Number of pages24
JournalJournal of Economic Theory and Econometrics
Volume23
Issue number2
Publication statusPublished - 2012 Jun 1

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Quasi-maximum likelihood estimation
Test statistic
Econometric models
Likelihood ratio
Quasi-likelihood
Lagrange multiplier test
Inference
Asymptotic analysis

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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abstract = "We examine an asymptotic analysis of differentiable econometric models using the distance and direction (DD) method introduced by Cho and White (2012), in which the conventional analysis for the quasi-maximum likelihood estimation and inference can be treated as a special case. We extend their approach and revisit the conventional quasi-likelihood ratio, Wald, and Lagrange multiplier test statistics through a different perspective. This new perspective is further analyzed in a unified framework, and we exploit this to introduce new classes of test statistics.",
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Quasi-maximum likelihood estimation revisited using the distance and direction method. / Cho, Jin Seo.

In: Journal of Economic Theory and Econometrics, Vol. 23, No. 2, 01.06.2012, p. 89-112.

Research output: Contribution to journalArticle

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