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A note on monitoring time-varying parameters in an autoregression

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  • Frédéric Carsoule
  • Philip Franses

Abstract

We develop a sequential testing approach for a structural change in the parameters of an autoregression, which amounts to an adaptation of the monitoring procedure, outlined in Chu, Stichcombe and White (1996). This procedure has a controlled asymptotic size as one repeats the test. Our method can be used as a general misspecification test. We apply our method to monthly US industrial production in order to investigate if its autoregressive behavior and/or its innovation variance have changed during the twentieth century. Copyright Springer-Verlag 2003

Suggested Citation

  • Frédéric Carsoule & Philip Franses, 2003. "A note on monitoring time-varying parameters in an autoregression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 57(1), pages 51-62, February.
  • Handle: RePEc:spr:metrik:v:57:y:2003:i:1:p:51-62
    DOI: 10.1007/s001840200198
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    References listed on IDEAS

    as
    1. Watson, Mark W, 1994. "Business-Cycle Durations and Postwar Stabilization of the U.S. Economy," American Economic Review, American Economic Association, vol. 84(1), pages 24-46, March.
    2. Chu, Chia-Shang James & Stinchcombe, Maxwell & White, Halbert, 1996. "Monitoring Structural Change," Econometrica, Econometric Society, vol. 64(5), pages 1045-1065, September.
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    Cited by:

    1. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    2. David Bock, 2008. "Aspects on the control of false alarms in statistical surveillance and the impact on the return of financial decision systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(2), pages 213-227.
    3. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    4. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Pierre Perron & Eduardo Zorita & Eiji Kurozumi, 2017. "Monitoring Parameter Constancy with Endogenous Regressors," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 791-805, September.

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