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What to do (and not to do) with Time-Series Cross-Section Data
Nathaniel Beck and Jonathan N. Katz
The American Political Science Review
Vol. 89, No. 3 (Sep., 1995), pp. 634-647
Published by: American Political Science Association
Stable URL: http://www.jstor.org/stable/2082979
Page Count: 14
You can always find the topics here!Topics: Standard error, Political science, Least squares, Estimators, Correlations, Error rates, Statistical estimation, Economic models, Economic growth models, Estimation methods
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We examine some issues in the estimation of time-series cross-section models, calling into question the conclusions of many published studies, particularly in the field of comparative political economy. We show that the generalized least squares approach of Parks produces standard errors that lead to extreme overconfidence, often underestimating variability by 50% or more. We also provide an alternative estimator of the standard errors that is correct when the error structures show complications found in this type of model. Monte Carlo analysis shows that these "panel-corrected standard errors" perform well. The utility of our approach is demonstrated via a reanalysis of one "social democratic corporatist" model.
The American Political Science Review © 1995 American Political Science Association