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A SIEVE BOOTSTRAP TEST FOR COINTEGRATION INA CONDITIONAL ERROR CORRECTION MODEL

Published online by Cambridge University Press:  26 October 2009

Franz C. Palm ,
Stephan Smeekes  and
Jean-Pierre Urbain
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Abstract

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In this paper we propose a bootstrap version of theWald test for cointegration in a single-equationconditional error correction model. The multivariatesieve bootstrap is used to deal with dependence inthe series. We show that the introduced bootstraptest is asymptotically valid. We also analyze thesmall sample properties of our test by simulationand compare it with the asymptotic test and severalalternative bootstrap tests. The bootstrap testoffers significant improvements in terms of sizeproperties over the asymptotic test, while havingsimilar power properties. The sensitivity of thebootstrap test to the allowance for deterministiccomponents is also investigated. Simulation resultsshow that the tests with sufficient deterministiccomponents included are insensitive to the truevalue of the trends in the model and retain correctsize.

Information

Type
Research Article
Information
Econometric Theory , Volume 26 , Issue 3 , June 2010 , pp. 647 - 681
Copyright
Copyright © Cambridge University Press 2009

Footnotes

Previous versions of this paper have beenpresented at the Econometric Society EuropeanMeeting in Milan, August 2008; at theInternational Workshop on Recent Advances in TimeSeries Analysis in Cyprus, June 2008; at theWorkshop on Bootstrap and Time Series inKaiserslautern, June 2008; at the conferenceentitled Inference and Tests in Econometrics, ATribute to Russell Davidson in Marseille, April2008; at an Ente Luigi Einaudi Seminar inEconometrics in Rome, November 2007; and at thefirst workshop of the Methods in InternationalFinance Network in Maastricht, September 2007. Wegratefully acknowledge the comments byparticipants at these seminars and by AndersSwensen, Pentti Saikkonen, and three anonymousreferees. We thank NWO and the Royal NetherlandsAcademy of Arts and Sciences for financialsupport.

References

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