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Detecting shocks: Outliers and breaks in time series

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  • Atkinson, A. C.
  • Koopman, S. J.
  • Shephard, N.

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  • Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
    • Handle: RePEc:eee:econom:v:80:y:1997:i:2:p:387-422
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    6. Andrew Harvey (ed.), 1994. "Time Series," Books, Edward Elgar Publishing, volume 0, number 599.
    7. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    8. Pena, Daniel, 1990. "Influential Observations in Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 235-241, April.
    9. Rappoport, Peter & Reichlin, Lucrezia, 1989. "Segmented Trends and Non-stationary Time Series," Economic Journal, Royal Economic Society, vol. 99(395), pages 168-177, Supplemen.
    10. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-389, October.
    11. Harvey, A. C., 1986. "The effects of seat belt legislation on British road casualities: A case study in structural modelling : A.C. Harvey and J. Durbing, Journal of the Royal Statistical Society, Series A 149 (1986) (in p," International Journal of Forecasting, Elsevier, vol. 2(4), pages 496-497.
    12. Genshiro Kitagawa, 1981. "A Nonstationary Time Series Model And Its Fitting By A Recursive Filter," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(2), pages 103-116, March.
    13. R.J. O'Hara Hines & E. M. Carter, 1993. "Improved Added Variable and Partial Residual Plots for the Detection of Influential Observations in Generalized Linear Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(1), pages 3-16, March.
    14. Balke, Nathan S, 1993. "Detecting Level Shifts in Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 81-92, January.
    15. Arthur P. Dempster & Chandu M. Patel & Murray R. Selwyn & Arthur J. Roth, 1984. "Statistical and Computational Aspects of Mixed Model Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(2), pages 203-214, June.
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    2. Atkinson, Anthony C. & Riani, Marco & Corbellini, Aldo, 2021. "The box-cox transformation: review and extensions," LSE Research Online Documents on Economics 103537, London School of Economics and Political Science, LSE Library.
    3. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    5. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
    6. Amélie Charles & Olivier Darné, 2021. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 15(2), pages 419-442, May.
    7. Amélie Charles & Olivier Darné & Laurent Ferrara, 2018. "Does The Great Recession Imply The End Of The Great Moderation? International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 745-760, April.
    8. Oesterreich Maciej, 2020. "On the Method of Identification of Atypical Observations in Time Series," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 1-16, June.
    9. Byungsoo Kim & Junmo Song & Changryong Baek, 2021. "Robust test for structural instability in dynamic factor models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 821-853, August.
    10. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    11. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    12. Pelagatti, Matteo M., 2011. "State Space Methods in Ox/SsfPack," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i03).
    13. Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    15. repec:hum:wpaper:sfb649dp2006-050 is not listed on IDEAS
    16. Fan, Jianqing & Ke, Yuan & Liao, Yuan, 2021. "Augmented factor models with applications to validating market risk factors and forecasting bond risk premia," Journal of Econometrics, Elsevier, vol. 222(1), pages 269-294.
    17. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    18. Tommaso Proietti, 2003. "Leave‐K‐Out Diagnostics In State‐Space Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 221-236, March.
    19. Manuel Salvador & Pilar Gargallo, 2003. "Automatic selective intervention in dynamic linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1161-1184.

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