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Performance of seasonal unit root tests for monthly data

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  • Paulo Rodrigues
  • Denise Osborn

Abstract

This paper uses Monte Carlo simulations to analyze the performance of several seasonal unit root tests for monthly time series. The tests are those of Dickey, Hasza and Fuller (DHF), Hylleberg, Engle, Granger and Yoo (HEGY), and Osborn, Chui, Smith and Birchenhall (OCSB). The unit root test of Dickey and Fuller (DF) is also considered. The results indicate that users have to be particularly cautious when applying the monthly version of the HEGY test. In general, the DHF and OCSB tests are preferable in terms of size and power, but these procedures may impose invalid restrictions. An empirical illustration is undertaken for UK two-digit industrial production indicators.

Suggested Citation

  • Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
  • Handle: RePEc:taf:japsta:v:26:y:1999:i:8:p:985-1004
    DOI: 10.1080/02664769921981
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    References listed on IDEAS

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    Cited by:

    1. Roberto Martínez-Espiñeira, 2007. "An estimation of residential water demand using co-integration and error correction tec hniques," Journal of Applied Economics, Universidad del CEMA, vol. 10, pages 161-184, May.
    2. Artur Silva Lopes, 2006. "Deterministic seasonality in Dickey–Fuller tests: should we care?," Empirical Economics, Springer, vol. 31(1), pages 165-182, March.
    3. Swanson, Norman R. & Urbach, Richard, 2015. "Prediction and simulation using simple models characterized by nonstationarity and seasonality," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 312-323.
    4. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    5. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    6. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    7. Capistrán, Carlos & Constandse, Christian & Ramos-Francia, Manuel, 2010. "Multi-horizon inflation forecasts using disaggregated data," Economic Modelling, Elsevier, vol. 27(3), pages 666-677, May.
    8. Denise Osborn & Paulo Rodrigues, 2002. "Asymptotic Distributions Of Seasonal Unit Root Tests: A Unifying Approach," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 221-241.
    9. del Barrio Castro, Tomas, 2006. "On the performance of the DHF tests against nonstationary alternatives," Statistics & Probability Letters, Elsevier, vol. 76(3), pages 291-297, February.
    10. da Silva Lopes, Artur C. B., 2001. "The robustness of tests for seasonal differencing to structural breaks," Economics Letters, Elsevier, vol. 71(2), pages 173-179, May.
    11. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.
    12. Carlos Capistrán & Christian Constandse & Manuel Ramos Francia, 2009. "Using Seasonal Models to Forecast Short-Run Inflation in Mexico," Working Papers 2009-05, Banco de México.
    13. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    14. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex.

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