Gaussian inference in general AR(1) models based on difference
Article first published online: 26 APR 2013
© 2013 Wiley Publishing Ltd.
Journal of Time Series Analysis
Volume 34, Issue 4, pages 447–453, July 2013
How to Cite
Chen, J.-G. and Kuo, B.-S. (2013), Gaussian inference in general AR(1) models based on difference. Journal of Time Series Analysis, 34: 447–453. doi: 10.1111/jtsa.12031
- Issue published online: 18 JUN 2013
- Article first published online: 26 APR 2013
- Manuscript Received: 27 MAR 2012
- AR model;
- unit root
This article develops a simple difference transformation for estimation and inference in general AR(1) models. As in Paparoditis and Politis (2000, Test 9, 487–509) and Phillips and Han (2008, Econometric Theory 24, 631–650), a Gaussian limit theory with a convergence rate of is available, whether a unit root is present in the process. Yet the novelty of our limit results is that the same weak convergence applies to the models with or without a trend, unlike those established in the literature. The merits promise usefulness of the difference transformation in applications to dynamic panels.