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Econometric Modelling of Time Series with Outlying Observations

Author

Listed:
  • Hendry David F

    (University of Oxford)

  • Mizon Grayham E

    (University of Southampton)

Abstract

Economies are buffeted by natural shocks, wars, policy changes, and other unanticipated events. Observed data can be subject to substantial revisions. Consequently, a correct theory can manifest serious mis-specification if just fitted to data ignoring its time-series characteristics. Modelling U.S. expenditure on food, the simplest theory implementation fails to describe the evidence. Embedding that theory in a general framework with dynamics, outliers and structural breaks and using impulse-indicator saturation, the selected model performs well, despite commencing with more variables than observations (see Doornik, 2009b), producing useful robust forecasts. Although this illustration involves a simple theory, the implications are generic and apply to sophisticated theories.

Suggested Citation

  • Hendry David F & Mizon Grayham E, 2011. "Econometric Modelling of Time Series with Outlying Observations," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-26, February.
  • Handle: RePEc:bpj:jtsmet:v:3:y:2011:i:1:n:6
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    References listed on IDEAS

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    Cited by:

    1. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).
    2. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.

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