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Jackknife Bias Reduction in the Presence of a Unit Root

Chambers, MJ and Kyriacou, M (2010) Jackknife Bias Reduction in the Presence of a Unit Root. UNSPECIFIED. University of Essex, Department of Economics, Economics Discussion Papers 685.

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Abstract

This paper analyses the properties of jackknife estimators of the first-order autoregressive coefficient when the time series of interest contains a unit root. It is shown that, when the sub-samples do not overlap, the sub-sample estimators have different limiting distributions from the full-sample estimator and, hence, the jackknife estimator in its usual form does not eliminate fully the first-order bias as intended. The joint moment generating function of the numerator and denominator of these limiting distributions is derived and used to calculate the expectations that determine the optimal jackknife weights. Two methods of avoiding this procedure are proposed and investigated, one based on inclusion of an intercept in the regressions, the other based on adjusting the observations in the sub-samples. Extensions to more general augmented Dickey-Fuller (ADF) regressions are also considered. In addition to the theoretical results extensive simulations reveal the impressive bias reductions that can be obtained with these computationally simple jackknife estimators and they also highlight the importance of correct lag-length selection in ADF regressions.

Item Type: Monograph (UNSPECIFIED)
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Economics, Department of
Depositing User: Jim Jamieson
Date Deposited: 03 Jul 2012 22:02
Last Modified: 17 Aug 2017 18:11
URI: http://repository.essex.ac.uk/id/eprint/2785

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