Taking Time Seriously: Time-Series-Cross-Section Analysis with a Binary Dependent Variable

Abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. 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 are 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 Intemnational Relations, where BTSCS data are frequently used. We use our methodology to reassess 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 yet (2) their finding that democracy inhibits conflict is upheld even taking duration dependence into account.

Exporting the Bomb: Why States Provide Sensitive Nuclear Assistance

“…To begin the investigation, I examine the simple bivariate relationship between the key strategic and economic variables and Sensitive nuclear assistance (Table 3). For each measure, I also examine the bivariate relationship after the inclusion of cubic splines to control for temporal dependence in the dependent variable (Beck, Katz, and Tucker 1998). The bivariate analysis is only the first step, however.…”

“…Robust standard errors are in parentheses and are adjusted for clustering by dyad. The model is estimated after including spline corrections for temporal dependence (Beck, Katz, and Tucker 1998 Table 4. Since the Superpower pact variable is not included in model 3, the probabilities for this variable are calculated using the ReLogit estimates in model 2 of Table 4.…”

Population size, concentration, and civil war. A geographically disaggregated analysis

“…We calculated the number of days since a conflict event happened in the same location, analogous to the 'peace years' variable in country-year setups (e.g. Beck, Katz & Tucker, 1998). As in Raknerud & Hegre (1997) assume that the effect of the previous event decrease at a constant rate, and compute a decay function with half-life of α: pes = 2 (−days/α) .…”

Testing Conflicting Political Economy Theories? Full-Fledged versus Partial-Scope Regional Trade Agreements

“…Applications with similar data structure as RTAs in this paper have been found in international relations literature, such as Beck, Katz and Tucker (1998). They applied duration analysis to international disputes (a binary dependent variable) using a panel dataset over years 1951-1985. In the trade literature, duration analysis was only recently introduced to study the duration of trading relations as in Besedes and Prusa (2006) and RTA formation as in Liu (2008).…”