Random Coefficient Models for Time-Series-Cross-Section Data: Monte Carlo Experiments

Jonathan N. Katz Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125 e-mail: jkatz{at}caltech.edu e-mail: nathaniel.beck{at}nyu.edu (corresponding author) This article considers random coefficient models (RCMs) fortime-series–cross-section data. These models allow forunit to unit variation in the model parameters. The heart ofthe article compares the finite sample properties of the fullypooled estimator, the unit by unit (unpooled) estimator, andthe (maximum likelihood) RCM estimator. The maximum likelihoodestimator RCM performs well, even where the data were generatedso that the RCM would be problematic. In an appendix, we showthat the most common feasible generalized least squares estimatorof the RCM models is always inferior to the maximum likelihoodestimator, and in smaller samples dramatically so. Authors' note: We gratefully acknowledge the financial supportof the National Science Foundation. Katz also acknowledges thesupport of the Center for Advanced Study in the Behavioral Sciences.We are thankful to Jake Bowers, Rob Franzese, Andy Gelman, SandyGordon, Bill Greene, and Luke Keele for comments; to Larry Bartelsfor always reminding us that our judgment may outperform thedata; as well as to the anonymous reviewers of Political Analysis.     

More on measuring budget-related rent-seeking: A comment

We wish to thank the Israel Center for Social and Economic Progress, Jerusalem, for supporting our work on this topic.     

Correcting for Survey Misreports Using Auxiliary Information with an Application to Estimating Turnout

Misreporting is a problem that plagues researchers who use survey data. In this article, we develop a parametric model that corrects for misclassified binary responses using information on the misreporting patterns obtained from auxiliary data sources. The model is implemented within the Bayesian framework via Markov Chain Monte Carlo (MCMC) methods and can be easily extended to address other problems exhibited by survey data, such as missing response and/or covariate values. While the model is fully general, we illustrate its application in the context of estimating models of turnout using data from the American National Elections Studies.     

Political Data in 1999

European Journal of Political Research -     

Some Implications of Corporate Taxation for Rent-Seeking Activity

In this paper we show that corporate taxes are likely to have considerable implications for rent-seeking activity. We find that corporate taxation tends to significantly reduce rent-seeking, and that it favors rent-seeking by established firms and discriminates against new and zero profit firms. Indeed, we show that corporate tax regulations may completely block rent-seeking by new corporations, and that rent-seeking competitions may be characterized by an equilibrium that features a small number of profitable and well established firms. Tax regulations may therefore impart an oligopolistic tendency to rent-seeking markets. Moreover, our results may have significant implications for the effects of corporate taxes on patent races, tournaments, and other first-past-the-post competitions.