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From Statistical Nuisances to Serious Modeling: Changing How We Think About the Analysis of Time-Series—Cross-Section Data

Published online by Cambridge University Press:  04 January 2017

Nathaniel Beck
Nathaniel Beck*
Affiliation:
Department of Politics, New York University, New York, NY 10012-1119. e-mail: [email protected]
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Extract

This special issue of Political Analysis hopefully marks a watershed in how we as a discipline think about modeling time-series—cross-section (TSCS) data. By that I mean moving beyond thinking of TSCS data as only presenting a series of technical estimation problems that are seen as violations of the Gauss-Markov assumptions, problems that can be treated by better estimation methods. The articles in this special issue point to ways of moving forward in thinking of TSCS data as providing opportunities to model intrinsic and important features of the data (while also paying attention to the various statistical issues).

Type
Research Article
Information
Political Analysis , Volume 15 , Issue 2: Special Issue: Time-Series Cross-Sectional Analysis , Spring 2007 , pp. 97 - 100
Copyright
Copyright © The Author 2007. Published by Oxford University Press on behalf of the Society for Political Methodology 

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References

Adolph, Christopher, Butler, Daniel M., and Wilson, Sven E. 2005. Which time-series cross-section estimator should I use now? Guidance from Monte Carlo experiments. Paper presented at the 2005 annual meeting of the American Political Science Association, Washington, DC.Google Scholar
Beck, Nathaniel, and Katz, Jonathan N. 1995. What to do (and not to do) with time-series cross-section data. American Political Science Review 89: 634–47.Google Scholar
Beck, Nathaniel, and Katz, Jonathan N. 1996. Nuisance vs. substance: Specifying and estimating time-series-cross-section models. Political Analysis 6: 1–36.Google Scholar
Stimson, James. 1985. Regression in space and time: A statistical essay. American Journal of Political Science 29: 914–47.CrossRefGoogle Scholar