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Unit Root Testing with Slowly Varying Trends

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  • Sven Otto

Abstract

A unit root test is proposed for time series with a general nonlinear deterministic trend component. It is shown that asymptotically the pooled OLS estimator of overlapping blocks filters out any trend component that satisfies some Lipschitz condition. Under both fixed-$b$ and small-$b$ block asymptotics, the limiting distribution of the t-statistic for the unit root hypothesis is derived. Nuisance parameter corrections provide heteroskedasticity-robust tests, and serial correlation is accounted for by pre-whitening. A Monte Carlo study that considers slowly varying trends yields both good size and improved power results for the proposed tests when compared to conventional unit root tests.

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  • Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    • Handle: RePEc:arx:papers:2003.04066
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