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A Joint Chow Test for Structural Instability

Author

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  • Bent Nielsen

    (Dept of Economics, University of Oxford)

  • Andrew Whitby

    (Dept of Economics, University of Oxford)

Abstract

The classical Chow (1960) test for structural instability requires strictly exogenous regressors and a break-point speci ed in advance. In this paper we consider two generalisations, the 1-step recursive Chow test (based on the sequence of studentized recursive residuals) and its supremum counterpart, which relax these requirements. We use results on strong consistency of regression estimators to show that the 1-step test is appropriate for stationary, unit root or explosive processes modelled in the autoregressive distributed lags (ADL) framework. We then use results in extreme value theory to develop a new supremum version of the test, suitable for formal testing of structural instability with an unknown break-point. The test assumes normality of errors, and is intended to be used in situations where this can either be assumed or established empirically.

Suggested Citation

  • Bent Nielsen & Andrew Whitby, 2012. "A Joint Chow Test for Structural Instability," Economics Papers 2012-W07, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:1207
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    References listed on IDEAS

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    1. Bent Nielsen, 2008. "Singular vector autoregressions with deterministic terms: Strong consistency and lag order determination," Economics Series Working Papers 2008-W14, University of Oxford, Department of Economics.
    2. Kilian, Lutz & Demiroglu, Ufuk, 2000. "Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 40-50, January.
    3. D. W. K. Andrews, 2003. "End-of-Sample Instability Tests," Econometrica, Econometric Society, vol. 71(6), pages 1661-1694, November.
    4. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037, Decembrie.
    5. Søren Johansen & Bent Nielsen, 2014. "Outlier detection algorithms for least squares time series regression," Economics Papers 2014-W04, Economics Group, Nuffield College, University of Oxford.
    6. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
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    17. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
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    Cited by:

    1. Mayer, Alexander, 2020. "(Consistently) testing strict exogeneity against the alternative of predeterminedness in linear time-series models," Economics Letters, Elsevier, vol. 193(C).
    2. Jonas Harnau, 2018. "Misspecification Tests for Log-Normal and Over-Dispersed Poisson Chain-Ladder Models," Risks, MDPI, vol. 6(2), pages 1-25, March.
    3. Carlos Jurado-Rivas & Marcelino Sánchez-Rivero, 2022. "Investigating Change in the Willingness to Pay for a More Sustainable Tourist Destination in a World Heritage City," Land, MDPI, vol. 11(3), pages 1-10, March.
    4. Vassili Bazinas & Bent Nielsen, 2015. "Causal transmission in reduced-form models," Economics Papers 2015-W07, Economics Group, Nuffield College, University of Oxford.
    5. Ragnar Nymoen, 2017. "Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation," Econometrics, MDPI, vol. 5(1), pages 1-54, January.
    6. Vassilios Bazinas & Bent Nielsen, 2022. "Causal Transmission in Reduced-Form Models," Econometrics, MDPI, vol. 10(2), pages 1-25, March.

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    More about this item

    JEL classification:

    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C - Mathematical and Quantitative Methods
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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