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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

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    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. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    3. 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.
    4. 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.
    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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