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Concluding Comments

Published online by Cambridge University Press:  04 January 2017

Luke Keele ,
Suzanna Linn  and
Clayton McLaughlin Webb
Luke Keele*
Affiliation:
Department of Political Science, Pennsylvania State University, State College, PA 16802
Suzanna Linn
Affiliation:
Department of Political Science, Pennsylvania State University, State College, PA 16802, e-mail: slinn@la.psu.edu
Clayton McLaughlin Webb
Affiliation:
Department of Political Science, University of Kansas, Lawrence, KS 66049, e-mail: webb767@ku.edu
*
e-mail: ljk20.psu.edu (corresponding author)
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Abstract

This issue began as an exchange between Grant and Lebo (2016) and ourselves (Keele, Linn, and Webb 2016) about the utility of the general error correction model (GECM) in political science. The exchange evolved into a debate about Grant and Lebo's proposed alternative to the GECM and the utility of fractional integration methods (FIM). Esarey (2016) and Helgason (2016) weigh in on this part of the debate. Freeman (2016) offers his views on the exchange as well. In the end, the issue leaves readers with a lot to consider. In his comment, Freeman (2016) argues that the exchange has produced little significant progress because of the contributors' failures to consider a wide array of topics not directly related to the GECM or FIM. We are less pessimistic. In what follows, we distill what we believe are the most important elements of the exchange–the importance of balance, the costs and benefits of FIM, and the vagaries of pre-testing.

Type
Time Series Symposium
Information
Political Analysis , Volume 24 , Issue 1 , Winter 2016 , pp. 83 - 86
Copyright
Copyright © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

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References

Bannerjee, Anindya, Dolado, Juan, Galbraith, John W., and Hendry, David F. 1993. Integration, error correction, and the econometric analysis of non-stationary data. Oxford: Oxford University Press.Google Scholar
Enders, Walter. 2015. Applied econometric time series. 4th ed. New York: Wiley and Sons.Google Scholar
Esarey, Justin. 2016. Fractionally integrated data and the autoregressive distributed lag model: Results from a simulation study. Political Analysis 24:42–49.CrossRefGoogle Scholar
Freeman, John. 2016. Progress in the study of nonstationary political time series? Political Analysis 24:50–58.Google Scholar
Grant, Tayler, and Lebo, Matt. 2016. Error correction methods with political time series. Political Analysis 24:3–30.CrossRefGoogle Scholar
Helgason, Agnar Freyr. 2016. Fractional integration methods and short time series: Evidence from a simulation study. Political Analysis 24:59–68.Google Scholar
Keele, Luke J., Linn, Suzanna, and McLaughlin Webb, Clayton. 2016. Treating time with all due seriousness. Political Analysis 24:31–41.Google Scholar