The Granger Centre for Time Series Econometrics

GC 08/04: Testing for unit roots and the impact of quadratic trends, with an application to relative primary commodity prices



A limit theory is developed for mildly explosive autoregression under both weakly and strongly dependent innovation errors. We find that the asymptotic behaviour of the sample moments is affected by the memory of the innovation process both in the in the form of the limiting distribution and, in the case of long range dependence, in the rate of convergence. However, this effect is not present in least squares regression theory as it is cancelled out by the interaction between the sample moments. As a result, the Cauchy regression theory of Phillips and Magdalinos (2007a) is invariant to the dependence structure of the innovation sequence even in the long memory case.

Download the paper in PDF format


David I. Harvey, Stephen J. Leybourne and A. M. Robert Taylor


View all Granger Centre discussion papers | View all School of Economics featured discussion papers


Posted on Sunday 1st June 2008

The Granger Centre for Time Series Econometrics

School of Economics
University of Nottingham
University Park
Nottingham, NG7 2RD