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Small sample estimation of a cointegrating vector: an empirical evaluation of six estimation techniques

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  • Tilak Abeysinghe
  • Tan Khay Boon
Abstract
A large number of techniques are now available for estimating a cointegrating regression. Although many of these techniques provide asymptotically equivalent estimators, their small-sample properties are known only with respect to a limited number of Monte Carlo studies. In light of the growing controversy over the nature of non-stationarity of economic time series, a comprehensive evaluation of these techniques within an applied framework can shed more light on the relative merits of these techniques. An estimation of long-run demand elasticities by six such techniques based on annual data from Canada, China and Singapore show rather disconcerting results. In small samples OLS may still be the best choice.

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  • Tilak Abeysinghe & Tan Khay Boon, 1999. "Small sample estimation of a cointegrating vector: an empirical evaluation of six estimation techniques," Applied Economics Letters, Taylor & Francis Journals, vol. 6(10), pages 645-648.
    • Handle: RePEc:taf:apeclt:v:6:y:1999:i:10:p:645-648
    DOI: 10.1080/135048599352420
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    1. Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393.
    2. Hargreaves, Colin P. (ed.), 1994. "Non-Stationary Time Series Analysis and Cointegration," OUP Catalogue, Oxford University Press, number 9780198773924.
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