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.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 24 (2008)
Issue (Month): 03 (June)
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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.:
- 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.
- 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 & Victor Solo, 1989. "Asymptotics for Linear Processes," Cowles Foundation Discussion Papers 932, Cowles Foundation for Research in Economics, Yale University.
- 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.
- Han, Chirok & Phillips, Peter C. B. & Sul, Donggyu, 2011. "Uniform Asymptotic Normality In Stationary And Unit Root Autoregression," Econometric Theory, Cambridge University Press, vol. 27(06), pages 1117-1151, December.
- 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.
- Qiankun Zhou & Jun Yu, 2012.
"Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes,"
11-2012, Singapore Management University, School of Economics.
- Qiankun Zhou & Jun Yu, 2010. "Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes," Working Papers 20-2010, Singapore Management University, School of Economics.
- 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.
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