Working Papers by Nathaniel Beck
Showing 1 to 5 of 5 records.
| # | Title | Authors | Date | Length | Paper | Abstract | |
|---|---|---|---|---|---|---|---|
| 1304 | Modeling dynamics in time-series-cross-section political economy data | Beck, Nathaniel Katz, Jonathan N. | 06/01/2009 | 35 pages | sswp1304.pdf | ||
| 1205 | Random Coefficient models for time-series-cross-section data | Beck, Nathaniel Katz, Jonathan N. | 09/01/2004 | 31 pages | wp1205.pdf | This paper considers random coefficient models (RCMs) for time-series-cross-section data. These models allow for unit to unit variation in the model parameters. After laying out the various models, we assess several issues in specifying RCMs. We then consider the finite sample properties of some standard RCM estimators, and show that the most common one, associated with Hsiao, has very poor properties. These analyses also show that a somewhat awkward combination of estimators based on Swamy's work performs reasonably well; this awkward estimator and a Bayes estimator with an uninformative prior (due to Smith) seem to perform best. But we also see that estimators which assume full pooling perform well unless there is a large degree of unit to unit parameter heterogeneity. We also argue that the various data drive methods (whether classical or empirical Bayes or Bayes with gentle priors) tends to lead to much more heterogeneity than most political scientists would like. We speculate that fully Bayesian models, with a variety of informative priors, may be the best way to approach RCMs. | |
| 1090 | Throwing out the Baby with the Bath Water: A Comment on Green, Yoon and Kim | Beck, Nathaniel Katz, Jonathan N. | 05/01/2000 | 9 pages | wp1090.pdf | ||
| 1017 | Beyond Ordinary Logit: Taking Time Seriously in Binary Time-Series-Cross-Section Models | Beck, Nathaniel Katz, Jonathan N. Tucker, Richard | 08/01/1997 | 29 pages | wp1017.pdf | Researchers typically analyze time-series{cross-section data with a binary dependent variable (BTSCS) using ordinary logit or probit. However, BTSCS observations are likely to violate the independence assumption of the ordinary logit or probit statistical model. It is well known that if the observations are temporally related that the results of an ordinary logit or probit analysis may be misleading. In this paper, we provide a simple diagnostic for temporal dependence and a simple remedy. Our remedy is based on the idea that BTSCS data is identical to grouped duration data. This remedy does not require the BTSCS analyst to acquire any further methodological skills and it can be easily implemented in any standard statistical software package. While our approach is suitable for any type of BTSCS data, we provide examples and applications from the field of International Relations, where BTSCS data is frequently used. We use our methodology to re-assess Oneal and Russett's (1997) findings regarding the relationship between economic interdependence, democracy, and peace. Our analyses show that 1) their finding that economic interdependence is associated with peace is an artifact of their failure to account for temporal dependence and 2) their finding that democracy inhibits conflict is upheld even taking duration dependence into account. | |
| 848 | Government Partisanship, Labor Organization and Macroeconomic Performance: A Corrigendum | Beck, Nathaniel Katz, Jonathan N. Alvarez, R. Michael Garrett, Geoffrey Lange, Peter | 05/01/1993 | sswp848c.pdf |