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Confidence Sets for the Break Date in Cointegrating Regressions

Author

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  • Eiji Kurozumi
  • Anton Skrobotov

Abstract

In this paper, we propose constructing confidence sets for a break date in cointegrating regressions by inverting a test for the break location, which is obtained by maximizing the weighted average of power. It is found that the limiting distribution of the test depends on the number of I(1) regressors whose coefficients sustain structural change and the number of I(1) regressors whose coefficients are fixed throughout the sample. By Monte Carlo simulations, we then show that compared with a confidence interval developed by using the existing method based on the limiting distribution of the break point estimator under the assumption of the shrinking shift, the confidence set proposed in the present paper has a more accurate coverage rate, while the length of the confidence set is comparable. By using the method developed in this paper, we then investigate the cointegrating regressions of Russian macroeconomic variables with oil prices with a break.

Suggested Citation

  • Eiji Kurozumi & Anton Skrobotov, 2018. "Confidence Sets for the Break Date in Cointegrating Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 514-535, June.
    • Handle: RePEc:bla:obuest:v:80:y:2018:i:3:p:514-535
    DOI: 10.1111/obes.12223
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    Cited by:

    1. Andrey Feliksovich Bedin & Alexander Vladimirovich Kulikov & Andrey Vladimirovich Polbin, 2021. "A Markov Switching VECM Model for Russian Real GDP, Real Exchange Rate and Oil Prices," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 402-412.
    2. Anton Skrobotov, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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