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Structural breaks, unit roots and methods for removing the autocorrelation pattern

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  • Montañés, Antonio
  • Reyes, Marcelo

Abstract

This paper examines the asymptotic and finite sample behaviour of the ADF and Phillips-Perron statistics under the presence of a break in the trend function. We prove that the break magnitude affects these two statistics in a similar way, drawing them closer the acceptance zone, the higher the break magnitude. By contrast, the influence of the lag truncation parameter does not have a similar effect on them, being very important for the ADF whilst negligible for the Phillips-Perron statistics.

Suggested Citation

  • Montañés, Antonio & Reyes, Marcelo, 2000. "Structural breaks, unit roots and methods for removing the autocorrelation pattern," Statistics & Probability Letters, Elsevier, vol. 48(4), pages 401-409, July.
    • Handle: RePEc:eee:stapro:v:48:y:2000:i:4:p:401-409
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    References listed on IDEAS

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    1. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
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    5. Pierre Perron, 1994. "Trend, Unit Root and Structural Change in Macroeconomic Time Series," Palgrave Macmillan Books, in: B. Bhaskara Rao (ed.), Cointegration, chapter 4, pages 113-146, Palgrave Macmillan.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    7. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
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    Cited by:

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    2. Kim, Dukpa & Perron, Pierre, 2009. "Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses," Journal of Econometrics, Elsevier, vol. 148(1), pages 1-13, January.
    3. Brodsky, Boris, 2008. "Structural Changes and Unit Roots: Distinguishing Models of Nonstationary Time Series," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 11(3), pages 52-63.
    4. Michael C. Dillbeck & Kenneth L. Cavanaugh, 2016. "Societal Violence and Collective Consciousness," SAGE Open, , vol. 6(2), pages 21582440166, April.
    5. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    6. Melo, Patricia C. & Sobreira, Nuno & Goulart, Pedro, 2019. "Estimating the long-run metro demand elasticities for Lisbon: A time-varying approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 360-376.
    7. Aparicio, Felipe M. & Escribano, Álvaro, 2003. "Cointegration tests based on record counting statistics," DES - Working Papers. Statistics and Econometrics. WS ws036615, Universidad Carlos III de Madrid. Departamento de Estadística.

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