OLS Bias in a Nonstationary Autoregression

Posted: 22 Jan 2012

See all articles by Karim M. Abadir

Karim M. Abadir

Imperial College Business School

Date Written: January 21, 2012

Abstract

An analytical formula is derived to approximate the finite sample bias of the ordinary least-squares (OLS) estimator of the autoregressive parameter when the underlying process has a unit root. It is found that the bias is expressible in terms of parabolic cylinder functions which are easy to compute. Numerical evaluation of the formula reveals that the approximation is very accurate. The derived formula inspires a heuristic approximation, obtained by leastsquares fitting of the asymptotic bias. More importantly, the formula proves analytically that the bias declines at a rate which is slower than the consistency rate, thus explaining some previous simulation findings. A case where the bias increases with the sample size is also given.

Suggested Citation

Abadir, Karim M., OLS Bias in a Nonstationary Autoregression (January 21, 2012). Available at SSRN: https://ssrn.com/abstract=1989462

Karim M. Abadir (Contact Author)

Imperial College Business School ( email )

South Kensington Campus
Exhibition Road
London SW7 2AZ, SW7 2AZ
United Kingdom

HOME PAGE: http://www3.imperial.ac.uk/portal/page?_pageid=61,629646&_dad=portallive&_schema=PORTALLIVE

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