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Testing for a Unit Root in Time Series Regression

Biometrika· 1988-01-01· article· 19,288 citationsclosed

Monetary Policy and Economic Impact Complex Systems and Time Series Analysis Diverse Scientific and Economic Studies

Abstract

This paper proposes new tests for detecting the presence of a unit root in quite general time series models. Our approach is nonparametric with respect to nuisance parameters and thereby allows for a very wide class of weakly dependent and possibly heterogeneously distributed data. The tests accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend. The limiting distributions of the statistics are obtained under both the unit root null and a sequence of local alternatives. The latter noncentral distribution theory yields local asymptotic power functions for the tests and facilitates comparisons with alternative procedures due to Dickey & Fuller. Simulations are reported on the performance of the new tests in finite samples.

Cite this

Peter C.B. Phillips, Pierre Perron Z (1988). Testing for a Unit Root in Time Series Regression. Biometrika. https://doi.org/10.1093/biomet/75.2.335

@article{cb1988testing,
  title  = {Testing for a Unit Root in Time Series Regression},
  author = {Phillips, Peter C.B. and Z, Pierre Perron},
  year   = {1988},
  journal = {Biometrika},
  doi    = {10.1093/biomet/75.2.335}
}

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References

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1984Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order

1987Time Series Regression with a Unit Root

1988Trends and random walks in macroeconomic time series

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1999Spurious regression and residual-based tests for cointegration in panel data

1996Efficient Tests for an Autoregressive Unit Root