Testing for structural Change in Regression: An Empirical Likelihood Ratio Approach
AbstractIn this paper we derive an empirical likelihood type Wald (ELW)test for the problem testing for structural change in a linear regression model when the variance of error term is not known to be equal across regimes. The sampling properties of the ELW test are analyzed using Monte Carlo simulation. Comparisons of these properties of the ELW test and of three other commonly used tests (Jayatissa, Weerahandi, and Wald) are conducted. The finding is that the ELW test has very good power properties.
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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0405.
Length: 46 pages
Date of creation: 06 Dec 2004
Date of revision:
Note: ISSN 1485-6441
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Empirical Likelihood; Wald test; Monte Carlo Simulation; Power and size; structural change;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
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- Weerahandi, Samaradasa, 1987. "Testing Regression Equality with Unequal Variances," Econometrica, Econometric Society, vol. 55(5), pages 1211-15, September.
- Ohtani, Kazuhiro & Toyoda, Toshihisa, 1985. "Small Sample Properties of Tests of Equality between Sets of Coefficients in Two Linear Regressions under Heteroscedasticity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 37-44, February.
- Giles, Judith A & Giles, David E A, 1993. " Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 7(2), pages 145-97, June.
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