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Erratum for Keele, Linn, and Webb (2016)

Published online by Cambridge University Press:  04 January 2017

Luke Keele
Affiliation:
Department of Political Science, Pennsylvania State University, State College, PA 16802 Email: ljk20.psu.edu
Suzanna Linn
Affiliation:
Department of Political Science, Pennsylvania State University, State College, PA 16802 Email: slinn@la.psu.edu
Clayton McLaughlin Webb
Affiliation:
Department of Political Science, University of Kansas, Lawrence, KS 66049 Email: webb767@ku.edu
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Abstract

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

References

An, S and Bloomfield, P. 1993. “Cox and Reid's modification in regression models with correlated errors.” Department of Statistics, North Carolina State University, Raleigh. Google Scholar
Babyak, Michael A. 2004. “What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models.” Psychosomatic medicine 66(3): 411421.Google Scholar
Baillie, Richard T. 1996. “Long memory processes and fractional integration in econometrics.” Journal of econometrics 73(1): 559.Google Scholar
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
Beck, Nathaniel. 1991. “Comparing Dynamic Specifications: The Case of Presidential Approval.” Political Analysis 3:2750.CrossRefGoogle Scholar
Bhardwaj, Geetesh and Swanson, Norman R. 2006. “An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series.” Journal of Econometrics 131(1): 539578.Google Scholar
Bhardwaj, Geetesh and Norman, R. 2003. “Swanson “An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series?? working paper of.”.Google Scholar
De Boef, Suzanna. 2001. “Testing for Cointegrating Relationships with Near-integrated Data.” Political Analysis 9:7894.Google Scholar
De Boef, Suzanna and Granato, Jim. 1997. “Near-integrated Data and the Analysis of Political Relationship.” American Journal of Political Science 41(2): 619640.CrossRefGoogle Scholar
De Boef, Suzanna and Granato, Jim. 1999. “Testing for Cointegrating Relationships with Near-integrated Data.” Political Analysis 8:99117.Google Scholar
De Boef, Suzanna and Keele, Luke. 2008. “Taking time seriously.” American Journal of Political Science 52(1): 184200.Google Scholar
Diebold, Francis X and Inoue, Atsushi. 2001. “Long memory and regime switching.” Journal of econometrics 105(1): 131159.Google Scholar
Engle, Robert F and Smith, Aaron D. 1999. “Stochastic permanent breaks.” Review of Economics and Statistics 81(4): 553574.Google Scholar
Granger, Clive WJ. 1999. Aspects of research strategies for time series analysis. In Presentation to the conference on New Developments in Time Series Economics, Yale University.Google Scholar
Granger, Clive WJ and Hyung, Namwon. 1999. “Occasional structural breaks and long memory.” Department of Economics, UCSD. Google Scholar
Grant, Tayler and Lebo, Matt. 2015. “Error Correction Methods with Political Time Series.” Political Analysis Forthcoming.Google Scholar
Hauser, Michael A. 1999. “Maximum likelihood estimators for ARMA and ARFIMA models: A Monte Carlo study.” Journal of Statistical Planning and Inference 80(1): 229255.Google Scholar
Keele, Luke J. 2015. “The Statistics of Causal Inference.” Political Analysis Forthcoming.Google Scholar
Keele, Luke J. and Kelly, Nathan J. 2006. “Dynamic Models for Dynamic Theories: The Ins and Outs of Lagged Dependent Variables.” Political Analysis 14:186205.Google Scholar
Keele, Luke J., Linn, Suzanna and McLaughlin Webb, Clayton. 2016. “Treating Time with All Due Seriousness.” Political Analysis 24(1): 3141.Google Scholar
Lebo, Matthew J, Walker, Robert XSW and Clarke, Harold D. 2000. “You must remember this: dealing with long memory in political analyses.” Electoral Studies 19(1): 3148.Google Scholar
Robinson, P.M. 1995. “Gaussian Semiparametric Estimator of Long Range Dependence.” Annals of Statistics 23:1630–61.Google Scholar
Sowell, Fallaw. 1992. “Modeling long-run behavior with the fractional ARIMA model.” Journal of Monetary Economics 29(2): 277302.Google Scholar
StataCorp. 2013. Stata 13 Base Reference Manual. College Station, TX: Stata Press.Google Scholar
Veenstra, Justin. 2013. Persistence and Anti-Persistence: Theory and Software (Thesis format: Monograph) PhD thesis Western University London.Google Scholar
Volscho, Thomas W and Kelly, Nathan J. 2012. “The Rise of the Super-Rich Power Resources, Taxes, Financial Markets, and the Dynamics of the Top 1 Percent, 1949 to 2008.” American Sociological Review 77(5): 679699.Google Scholar