ROBUST INFERENCE IN AUTOREGRESSIONS WITH MULTIPLE OUTLIERS

Giuseppe Cavaliere () and Iliyan Georgiev

Econometric Theory, 2009, vol. 25, issue 06, pages 1625-1661

Abstract: We consider robust methods for estimation and unit root (UR) testing in autoregressions with infrequent outliers whose number, size, and location can be random and unknown. We show that in this setting standard inference based on ordinary least squares estimation of an augumented Dickey Fuller critical values, yields the best combination of finite-sample size and power.

Date: 2009

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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:25:y:2009:i:06:p:1625-1661_99

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