This 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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Length: 16 pages Date of creation: Jan 2006 Date of revision: Publication status: Published in Econometric Theory (June 2008), 24(3): 631-650 Handle: RePEc:cwl:cwldpp:1546
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