Testing for Flexible Nonlinear Trends with an Integrated or Stationary Noise Component

Pierre Perron, Mototsugu Shintani, Tomoyoshi Yabu

研究成果: Article査読

8 被引用数 (Scopus)


This paper proposes a new test for the presence of a nonlinear deterministic trend approximated by a Fourier expansion in a univariate time series for which there is no prior knowledge as to whether the noise component is stationary or contains an autoregressive unit root. Our approach builds on the work of Perron and Yabu () and is based on a Feasible Generalized Least Squares procedure that uses a super-efficient estimator of the sum of the autoregressive coefficients α when α = 1. The resulting Wald test statistic asymptotically follows a chi-square distribution in both the I(0) and I(1) cases. To improve the finite sample properties of the test, we use a bias-corrected version of the OLS estimator of α proposed by Roy and Fuller (). We show that our procedure is substantially more powerful than currently available alternatives. We illustrate the usefulness of our method via an application to modelling the trend of global and hemispheric temperatures.

ジャーナルOxford Bulletin of Economics and Statistics
出版ステータスPublished - 2017 10月

ASJC Scopus subject areas

  • 統計学および確率
  • 社会科学(その他)
  • 経済学、計量経済学
  • 統計学、確率および不確実性


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