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Testing for Unit Roots with Prediction Errors

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  • Sanchez, Ismael

Abstract

This paper analyzes the relationship between the properties of the prediction errors of a predictor that assumes an autoregressive unit root and its optimal detection. According with this relationship, new autoregressive unit root tests are proposed based on multi-step prediction errors. It is shown that the proposed tests have optimal properties. In the simple AR(1) case, they have similar power to existing tests and very close to the Gaussian power envelope. However, in the general ARMA case, the competing tests have a high size distortion whereas the size distortion of the proposed tests is very small.

Suggested Citation

  • Sanchez, Ismael, 1998. "Testing for Unit Roots with Prediction Errors," University of California at San Diego, Economics Working Paper Series qt8pc6n1j8, Department of Economics, UC San Diego.
  • Handle: RePEc:cdl:ucsdec:qt8pc6n1j8
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    References listed on IDEAS

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    6. Pantula, Sastry G & Gonzalez-Farias, Graciela & Fuller, Wayne A, 1994. "A Comparison of Unit-Root Test Criteria," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 449-459, October.
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