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.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 72 (2005)
Issue (Month): 3 (May)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Hyllerberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988.
"Seasonal Integration And Cointegration,"
0-88-2, Pennsylvania State - Department of Economics.
- 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.
- 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.
- Chang, Yoosoon, 2002.
"Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency,"
2000-08, Rice University, Department of Economics.
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:72:y:2005:i:3:p:195-204. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.