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Fully modified semiparametric GLS estimation for regressions with nonstationary seasonal regressors

Title
Fully modified semiparametric GLS estimation for regressions with nonstationary seasonal regressors
Authors
Shin D.W.Oh M.-S.
Ewha Authors
오만숙신동완
SCOPUS Author ID
오만숙scopus; 신동완scopus
Issue Date
2004
Journal Title
Journal of Econometrics
ISSN
0304-4076JCR Link
Citation
Journal of Econometrics vol. 122, no. 2, pp. 247 - 280
Indexed
SCIE; SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
Regression models with seasonally integrated and possibly endogenous regressors and serially correlated regression errors are studied. Spectral decompositions of generalized sums of cross products of regressors and regression errors are used to develop a feasible generalized least squares estimator (FGLSE) which does not require parametric specifications for error processes. Using the FGLSE and following the spirit of "Fully Modified estimation" of Phillips and Hansen (Rev. Econ. Stud. 57 (1990) 99), a fully modified GLSE (FM-GLSE) and inference procedures are constructed. The distribution of the FM-GLSE is shown to be asymptotically a mixed normal distribution which validates standard inference based on the FM-GLSE with normal theory. A Monte-Carlo simulation shows that the FM-GLSE is more efficient than the ordinary least squares estimator (OLSE) in the cases of endogeneity or serial correlation and more efficient than the FM-estimator based on the OLSE in the case of serial correlation. © 2003 Published by Elsevier B.V.
DOI
10.1016/j.jeconom.2003.07.001
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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