Exploiting Infinite Variance Through Dummy Variables In Nonstationary Autoregressions
We consider estimation and testing infinite-order autoregressive models with a (near) unit root and infinite-variance innovations. We study the asymptotic properties of estimators obtained by dummying out ?large?innovations, i.e., exceeding a given threshold. These estimators reflect the common practice of dealing with large residuals by including impulse dummies in the estimated regression. Iterative versions of the dummy-variable estimator are also discussed. We provide conditions on the preliminary parameter estimator and on the threshold which ensure that (i) the dummy-based estimator is consistent at higher rates than the OLS estimator, (ii) an asymptotically normal test statistic for the unit root hypothesis can be derived, and (iii) order of magnitude gains of local power are obtained.
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Volume (Year): 29 (2013)
Issue (Month): 06 (December)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Carlos Santos & David Hendry & Soren Johansen, 2008.
"Automatic selection of indicators in a fully saturated regression,"
Springer, vol. 23(2), pages 317-335, April.
- David Hendry & Søren Johansen & Carlos Santos, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 337-339, April.
- Pagan,Adrian & Ullah,Aman, 1999.
Cambridge University Press, number 9780521355643, December.
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