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Testing for unit roots in time series with nearly deterministic seasonal variation

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  • Zacharias Psaradakis

Abstract

This paper addresses the problem of testing for the presence of unit autoregressive roots in seasonal time series with negatively correlated moving average components. For such cases, many of the commonly used tests are known to have exact sizes much higher than their nominal significance level. We propose modifications of available test procedures that are based on suitably prewhitened data and feasible generalized least squares estimators. Monte Carlo experiments show that such modifications are successful in reducing size distortions in samples of moderate size.

Suggested Citation

  • Zacharias Psaradakis, 1997. "Testing for unit roots in time series with nearly deterministic seasonal variation," Econometric Reviews, Taylor & Francis Journals, vol. 16(4), pages 421-439.
  • Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:421-439 DOI: 10.1080/07474939708800397
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    Cited by:

    1. Swanson, Norman R. & Urbach, Richard, 2015. "Prediction and simulation using simple models characterized by nonstationarity and seasonality," International Review of Economics & Finance, Elsevier, pages 312-323.
    2. Rotger, Gabriel Pons, "undated". "Testing for Seasonal Unit Roots with Temporally Aggregated Time Series," Economics Working Papers 2003-16, Department of Economics and Business Economics, Aarhus University.
    3. Antonio Rubia, 2001. "Testing For Weekly Seasonal Unit Roots In Daily Electricity Demand: Evidence From Deregulated Markets," Working Papers. Serie EC 2001-21, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    4. van Dijk, Frans & Sonnemans, Joep & van Winden, Frans, 2002. "Social ties in a public good experiment," Journal of Public Economics, Elsevier, vol. 85(2), pages 275-299, August.
    5. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, pages 985-1004.
    6. Taylor, A. M. Robert, 1997. "On the practical problems of computing seasonal unit root tests," International Journal of Forecasting, Elsevier, vol. 13(3), pages 307-318, September.

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