Adaptive Estimation of Cointegrated Models: Simulation Evidence and an Application to the Forward Exchange Market
Abstract
The paper reports simulation and empirical evidence on the finite-sample performance of adaptive estimators in cointegrated systems. Adaptive estimators are asymptotically efficient, even when the shape of the likelihood function is unknown. We consider two representations of cointegrated systems--triangular cointegrating regressions and error correction models. The motivation for and advantages of adaptive estimators in such systems are discussed and their construction is described. We report results from the estimation of a forward exchange market unbiasedness regression using the adaptive and competing estimators, and provide related Monte Carlo simulation evidence on the performance of the estimators.Download Info
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.
Volume (Year): 14 (1999)
Issue (Month): 6 (Nov.-Dec.)
Pages: 627-50
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Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Douglas Hodgson, 2002. "Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form," Cahiers de recherche CREFE / CREFE Working Papers 146, CREFE, Université du Québec à Montréal.
- Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 0, pages 325-353, November.
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