An Aysmptotically Optimal Modification of the Panel LIML Estimation for Individual Heteroscedasticity
AbstractWe consider the estimation of coefficients of a dynamic panel structural equation in the simultaneous equation models. As a semi-parametric method, we introduce a class of modifications of the limited information maximum likelihood (LIML) estimator to improve its asymptotic properties as well as the small sample properties when we have individual heteroscedasticities. We shall show that an asymptotically optimal modification of the LIML estimator, which is called AOM-LIML, removes the asymptotic bias caused by the forward-filtering and improves the LIML and other estimation methods with individual heteroscedasticities.
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Date of creation: Dec 2010
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- Kentaro Akashi & Naoto Kunitomo, 2010.
"Some Properties of the LIML Estimator in a Dynamic Panel Structural Equation,"
CIRJE-F-707, CIRJE, Faculty of Economics, University of Tokyo.
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- Kentaro Akashi & Naoto Kunitomo, 2010. "The Limited Information Maximum Likelihood Approach to Dynamic Panel Structural Equations," CIRJE F-Series CIRJE-F-708, CIRJE, Faculty of Economics, University of Tokyo.
- Kazuhiko Hayakawa, 2007. "A Simple Efficient Instrumental Variable Estimator in Panel AR(p) Models," Hi-Stat Discussion Paper Series d07-213, Institute of Economic Research, Hitotsubashi University.
- Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
- T. W. Anderson & Naoto Kunitomo & Yukitoshi Matsushita, 2008. "On Finite Sample Properties of Alternative Estimators of Coefficients in a Structural Equation with Many Instruments," CIRJE F-Series CIRJE-F-577, CIRJE, Faculty of Economics, University of Tokyo.
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