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.
Publisher
Cambridge University Press (CUP)
Subject
Political Science and International Relations,Sociology and Political Science
Reference21 articles.
1. Fractional integration methods in political science
2. While the choice of t = 10 is arbitrary, the results are substantively similar for other forecasting horizons. Since fractional integration primarily affects the persistence of shocks over time, there is less (more) divergence between estimates from the two models for shorter (longer) time horizons.
3. Treating Time with All Due Seriousness
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