Gaussian Inference in Ar(1) Time Series with or without a Unit Root
This paper introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite-sample bias and 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 ... rate of convergence. En route, a useful central limit theorem (CLT) for sample covariances of linear processes is given, following Phillips and Solo (1992, Annals of Statistics, 20, 971-1001). The approach also has useful extensions to dynamic panels. (ProQuest-CSA LLC:: ... denotes formulae/symbols omitted.)
Cambridge University Press
PHILLIPS, Peter C. B. and Han, Chirok.
Gaussian Inference in Ar(1) Time Series with or without a Unit Root. (2008). Econometric Theory. 24, (3), 631-650. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/249
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.