Gaussian Inference In Ar(1) Time Series With Or Without A Unit Root
AbstractThis note introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite sample bias, are not sensitive to initial conditions, and the approach has the unusual advantage that a Gaussian central limit theory applies and is continuous as the autoregressive coefficient passes through unity with a uniform vn rate of convergence. En route, a useful CLT for sample covariances of linear processes is given, following Phillips and Solo (1992). The approach also has useful extensions to dynamic panels.
Download InfoIf 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.
Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 24 (2008)
Issue (Month): 03 (June)
Contact details of provider:
Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Fax: +44 (0)1223 325150
Web page: http://journals.cambridge.org/jid_ECTProvider-Email:firstname.lastname@example.org
Other versions of this item:
- Peter C. B. Phillips & Chirok Han, 2006. "Gaussian Inference in AR(1) Time Series with or without a Unit Root," Cowles Foundation Discussion Papers 1546, Cowles Foundation for Research in Economics, Yale University.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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.:
- Phillips, Peter C.B. & Magdalinos, Tassos, 2007.
"Limit theory for moderate deviations from a unit root,"
Journal of Econometrics,
Elsevier, vol. 136(1), pages 115-130, January.
- Peter C.B. Phillips & Tassos Magdalinos, 2004. "Limit Theory for Moderate Deviations from a Unit Root," Cowles Foundation Discussion Papers 1471, Cowles Foundation for Research in Economics, Yale University.
- Peter C.B. Phillips & Victor Solo, 1989. "Asymptotics for Linear Processes," Cowles Foundation Discussion Papers 932, Cowles Foundation for Research in Economics, Yale University.
- Qiankun Zhou & Jun Yu, 2010.
"Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes,"
20-2010, Singapore Management University, School of Economics.
- Qiankun Zhou & Jun Yu, 2012. "Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes," Working Papers 11-2012, Singapore Management University, School of Economics.
- Gorodnichenko, Yuriy & Mikusheva, Anna & Ng, Serena, 2012.
"Estimators For Persistent And Possibly Nonstationary Data With Classical Properties,"
Cambridge University Press, vol. 28(05), pages 1003-1036, October.
- Yuriy Gorodnichenko & Anna Mikusheva & Serena Ng, 2011. "Estimators for Persistent and Possibly Non-Stationary Data with Classical Properties," NBER Working Papers 17424, National Bureau of Economic Research, Inc.
- Han, Chirok & Phillips, Peter C. B. & Sul, Donggyu, 2011.
"Uniform Asymptotic Normality In Stationary And Unit Root Autoregression,"
Cambridge University Press, vol. 27(06), pages 1117-1151, December.
- Chirok Han & Peter C.B. Phillips & Donggyu Sul, 2010. "Uniform Asymptotic Normality in Stationary and Unit Root Autoregression," Cowles Foundation Discussion Papers 1746, Cowles Foundation for Research in Economics, Yale University.
- Chirok Han & Peter C.B. Phillips & Donggyu Sul, 2010.
"X-Differencing and Dynamic Panel Model Estimation,"
Cowles Foundation Discussion Papers
1747, Cowles Foundation for Research in Economics, Yale University.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Keith Waters).
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.