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 language | English |
|---|---|
| Pages (from-to) | 89-112 |
| Number of pages | 24 |
| Journal | Journal of Economic Theory and Econometrics |
| Volume | 23 |
| Issue number | 2 |
| Publication status | Published - 2012 Jun 1 |
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All Science Journal Classification (ASJC) codes
- Economics and Econometrics
Cite this
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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 journal › Article
TY - JOUR
T1 - Quasi-maximum likelihood estimation revisited using the distance and direction method
AU - Cho, Jin Seo
PY - 2012/6/1
Y1 - 2012/6/1
N2 - 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.
AB - 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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UR - http://www.scopus.com/inward/citedby.url?scp=84863454582&partnerID=8YFLogxK
M3 - Article
VL - 23
SP - 89
EP - 112
JO - Journal of Economic Theory and Econometrics
JF - Journal of Economic Theory and Econometrics
SN - 1229-2893
IS - 2
ER -