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On the Power of GLS‐Type Unit Root Tests

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  • Peter Burridge
  • A. M. Robert Taylor

Abstract

Elliott, Rothenberg and Stock (1996), (ERS), present a ‘GLS’ variant of the Dickey‐Fuller (DF) unit root test. Their statistic is approximately point‐optimal invariant at a chosen local alternative, and usually displays better finite sample power than the DF test. Following the usual efficiency motive for GLS estimation, the higher finite sample power of the ERS test has often been attributed to the greater accuracy of the estimate of the series’ non‐stochastic component under stationary alternatives close to the null. This paper shows that the GLS estimates of the non‐stochastic component are not, in general, more accurate. The power gain arises from the fact that the GLS statistic's null distribution has a greater positive shift relative to the DF test, than its distribution under relevant alternatives, and this persists even when the GLS estimates of the non stochastics have higher variance than the OLS estimates.

Suggested Citation

  • Peter Burridge & A. M. Robert Taylor, 2000. "On the Power of GLS‐Type Unit Root Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(5), pages 633-645, December.
    • Handle: RePEc:bla:obuest:v:62:y:2000:i:5:p:633-645
    DOI: 10.1111/1468-0084.00194
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    Cited by:

    1. Patrick Marsh, 2007. "Constructing Optimal tests on a Lagged dependent variable," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 723-743, September.
    2. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.

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