This article is concerned with detecting additive outliers using extreme value methods. The test recently proposed for use with possibly non-stationary time series by Perron and Rodriguez [Journal of Time Series Analysis (2003) vol. 24, pp. 193-220], is, as they point out, extremely sensitive to...

A possibly nonstationary autoregressive process, of unknown finite order, with possibly infinite-variance innovations is studied. The ordinary least squares autoregressive parameter estimates are shown to be consistent, and their rate of convergence, which depends on the index of stability,...

We investigate the behaviour of rolling and recursive augmented Dickey-Fuller (ADF) tests against processes which display changes in persistence. We show that the power of the tests depend crucially on the window width and warm up parameter for the rolling and recursive procedures respectively,...

In this paper, we suggest a new set of regression-based statistics for testing the seasonal unit root null hypothesis. These tests are based on combining conventional Hylleberg et al. (1990) -type seasonal unit root test statistics calculated from both forward and reverse estimation of the...

Conventional unit root tests are known to be unreliable in the presence of permanent volatility shifts. In this paper, we propose a new approach to unit root testing which is valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt...

This paper builds on the existing literature on tests of the null hypothesis of deterministic seasonality in a univariate time-series process. Under the assumption of independent Gaussian errors, we derive the class of locally weighted mean most powerful invariant tests against unit roots at the...