Robust unit root tests with autoregressive errors Articles uri icon

authors

  • MORENO WARLETA, MARTA
  • ROMO URROZ, JUAN

publication date

  • January 2016

start page

  • 5997

end page

  • 6021

issue

  • 20

volume

  • 45

International Standard Serial Number (ISSN)

  • 0361-0926

Electronic International Standard Serial Number (EISSN)

  • 1532-415X

abstract

  • This article presents a new test for unit roots based on least absolute deviation estimation specially designed to work for time series with autoregressive errors. The methodology used is a bootstrap scheme based on estimating a model and then the innovations. The resampling part is performed under the null hypothesis and, as it is customary in bootstrap procedures, is automatic and does not rely on the calculation of any nuisance parameter. The validity of the procedure is established and the asymptotic distribution of the statistic proposed is proved to converge to the correct distribution. To analyze the performance of the test for finite samples, a Monte Carlo study is conducted showing a very good behavior in many different situations.

keywords

  • autoregressive errors; autoregressive process; bootstrap; least absolute deviation; unit root; 62f40; 62m10; 62g10; time-series regression; bootstrap tests; stochastic integrals; infinite-variance; lad estimation