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Cumulated sum of squares statistics for non-linear and non-stationary regressions

Author

Listed:
  • Vanessa Berenguer-Rico

    (Dept of Economics, Mansfield College and Programme for Economic Modelling, Oxford University)

  • Bent Nielsen

    (Dept of Economics, Nuffield College, Institute Programme for Economic Modelling, Oxford University)

Abstract

We show that the cumulated sum of squares test has a standard Brownian bridge-type asymptotic distribution in non-linear regression models with non-stationary regressors. This contrasts with cumulated sum tests which have been studied previously and where the asymptotic distribution involves nuisance quantities. Through simulation we show that the power is comparable in a wide of range of situations.

Suggested Citation

  • Vanessa Berenguer-Rico & Bent Nielsen, 2015. "Cumulated sum of squares statistics for non-linear and non-stationary regressions," Economics Papers 2015-W09, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:1509
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    File URL: https://www.nuffield.ox.ac.uk/economics/papers/2015/BerenguerRicoNielsenCUSQ2015.pdf
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    References listed on IDEAS

    as
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    13. Nielsen, Bent & Sohkanen, Jouni S., 2011. "Asymptotic Behavior Of The Cusum Of Squares Test Under Stochastic And Deterministic Time Trends," Econometric Theory, Cambridge University Press, vol. 27(4), pages 913-927, August.
    14. Kasparis, Ioannis, 2008. "Detection Of Functional Form Misspecification In Cointegrating Relations," Econometric Theory, Cambridge University Press, vol. 24(5), pages 1373-1403, October.
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    16. Paul Turner, 2010. "Power properties of the CUSUM and CUSUMSQ tests for parameter instability," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1049-1053.
    17. Berenguer Rico, Vanessa & Gonzalo, Jesús, 2013. "Co-summability from linear to non-linear cointegration," UC3M Working papers. Economics we1312, Universidad Carlos III de Madrid. Departamento de Economía.
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    Cited by:

    1. Jean-Yves Pitarakis, 2017. "A Simple Approach for Diagnosing Instabilities in Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 851-874, October.

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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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