Recursive demeaning and deterministic seasonality
In this paper, a mean adjustment scheme for unit root tests in the presence of deterministic seasonality is discussed. The Cauchy estimator for autoregressive processes provides some advantages in the application to unit root tests. In particular, it allows for asymptotically standard normal tests and does not require any tabulation of the critical values. The approach can also be employed for testing seasonal unit root. In both cases, a special scheme of mean adjustment based on recursive coefficients, so-called recursive mean adjustment, is essential to maintain the martingale property of regressors. However, the straightforward recursive estimation of seasonal dummies in the case of deterministic seasonal effects leads to a strong positive bias of the estimated autoregressive parameter and therefore to invalid tests. This paper shows how to overcome this problem and to use the Cauchy estimator for unit root testing in the presence of deterministic seasonality.
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Volume (Year): 72 (2005)
Issue (Month): 3 (May)
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References listed on IDEAS
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- Chang, Yoosoon, 2002.
"Nonlinear IV unit root tests in panels with cross-sectional dependency,"
Journal of Econometrics,
Elsevier, vol. 110(2), pages 261-292, October.
- Chang, Yoosoon, 2002. "Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency," Working Papers 2000-08, Rice University, Department of Economics.
- Yoosoon Chang, 2000. "Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency," CIRJE F-Series CIRJE-F-85, CIRJE, Faculty of Economics, University of Tokyo.
- Phillips, Peter C. B. & Park, Joon Y. & Chang, Yoosoon, 2004.
"Nonlinear instrumental variable estimation of an autoregression,"
Journal of Econometrics,
Elsevier, vol. 118(1-2), pages 219-246.
- Peter C.B. Phillips & Joon Y. Park & Yoosoon Chang, 2001. "Nonlinear Instrumental Variable Estimation of an Autoregression," Cowles Foundation Discussion Papers 1331, Cowles Foundation for Research in Economics, Yale University.
- Shin, Dong Wan & So, Beong Soo, 2002. "Recursive mean adjustment and tests for nonstationarities," Economics Letters, Elsevier, vol. 75(2), pages 203-208, April.
- So, Beong Soo & Shin, Dong Wan, 1999. "Cauchy Estimators For Autoregressive Processes With Applications To Unit Root Tests And Confidence Intervals," Econometric Theory, Cambridge University Press, vol. 15(02), pages 165-176, April.
- Hylleberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988.
"Seasonal, Integration And Cointegration,"
6-88-2, Pennsylvania State - Department of Economics.
- Shin, Dong Wan & So, Beong Soo, 2000. "Gaussian tests for seasonal unit roots based on Cauchy estimation and recursive mean adjustments," Journal of Econometrics, Elsevier, vol. 99(1), pages 107-137, November.
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