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Fractional Integration Methods and Short Time Series: Evidence from a Simulation Study

Published online by Cambridge University Press:  04 January 2017

Agnar Freyr Helgason*
Affiliation:
Social Research Centre, University of Iceland, Gimli G-201, Sæmundargötu 2, 101 Reykjavík, Iceland
*
e-mail: [email protected] (corresponding author)

Abstract

Grant and Lebo (2016) and Keele, Linn, and Webb (2016) provide diverging recommendations to analysts working with short time series that are potentially fractionally integrated. While Grant and Lebo are quite positive about the prospects of fractionally differencing such data, Keele, Linn, and Webb argue that estimates of fractional integration will be highly uncertain in short time series. In this study, I simulate fractionally integrated data and compare estimates from the general error correction model (GECM), which disregards fractional integration, to models using fractional integration methods over thirty-two simulation conditions. I find that estimates of short-run effects are similar across the two models, but that models using fractionally differenced data produce superior predictions of long-run effects for all sample sizes when there are no short-run dynamics included. When short-run dynamics are included, the GECM outperforms the alternative model, but only in time series that consist of under 250 observations.

Type
Time Series Symposium
Copyright
Copyright © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: The author thanks Janet Box-Steffensmeier for comments. Replication materials are available online as Helgason (2016).

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