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M-estimator based unit root tests in the ESTAR framework

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  • Rickard Sandberg

Abstract

Building on work of Lucas (Econom Theory 11:331–346, 1995a ) we derive the limiting distribution for M-estimator based unit root tests in the ESTAR model. This yields that the LS based unit root tests by Kapetanios et al. (J Econom 112:359–379, 2003 ) and Rothe and Sibbertsen (Allg Stat Arch 90:439–456, 2006 ) are robustified in an outlier context. We also consider an LS based heteroscedasticity robust version (White’s) of one of our unit root tests as a “quick fix” solution to the problems of outliers. Finite sample properties of the tests are examined, and in the case of additive outliers it is shown that the LS based tests are grossly over-sized whereas the size of our tests is close to the nominal size. If an ESTAR model with innovation outliers is considered, significant power gains over the LS based tests are shown by using our robust tests. Copyright Springer-Verlag Berlin Heidelberg 2015

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  • Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    • Handle: RePEc:spr:stpapr:v:56:y:2015:i:4:p:1115-1135
    DOI: 10.1007/s00362-014-0628-0
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    Cited by:

    1. Rickard Sandberg, 2017. "Sample Moments and Weak Convergence to Multivariate Stochastic Power Integrals," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1000-1009, November.

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