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Journal of Time Series Econometrics

Editor-in-Chief: Hidalgo, Javier

2 Issues per year

Mathematical Citation Quotient (MCQ) 2016: 0.10

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Econometric Modelling of Time Series with Outlying Observations

David F Hendry / Grayham E Mizon
Published Online: 2011-02-03 | DOI: https://doi.org/10.2202/1941-1928.1100

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

About the article

Published Online: 2011-02-03

Citation Information: Journal of Time Series Econometrics, ISSN (Online) 1941-1928, DOI: https://doi.org/10.2202/1941-1928.1100.

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©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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