Econometric Modelling of Time Series with Outlying Observations

David Hendry and Grayham Mizon

Journal of Time Series Econometrics, 2011, vol. 3, issue 1, 26

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.

Keywords: econometric modelling; food expenditure; outliers; impulse-indicator saturation; robust forecasting; autometrics (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (37)

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DOI: 10.2202/1941-1928.1100

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