Dynamic Modeling for Persistent Event-Count Time Series

Abstract

cycles in international relations. Scholars use event-count models to analyze a wide variety of political science data. For example, the large sets of data on cooperative and conflictual international events often use event-count models (Huang, Kim, and Wu 1992; Sayrs 1992; Volgy and Imwalle 1995). These data have also been analyzed using time-series methods, particularly when transformed into indices of conflict and cooperation that consider the severity of each event and are no longer purely event counts (Goldstein 1991; Goldstein and Freeman 1990; Schneider, Widmer, and Ruloff 1993; Ward and Rajmaira 1992). Other event counts commonly analyzed in international relations include the number of wars (Benoit 1996; Mansfield 1992), militarized interstate disputes (Gowa 1998; Pollins 1996; Senese 1997), or other incidents of conflict and cooperation between states (BrophyBaerman and Conybeare 1994; Eyerman and Hart 1996; Kinsella 1995; Kinsella and Tillema 1995; O'Brien 1996; Fordham 1998a, 1998b; Remmer 1998). Scholars in American politics have also employed event-count models for time-series data to analyze presidential activity (Brace and Hinckley 1993), Federal Reserve decisions (Krause 1994), federal contract awards (Mayer 1995), executive orders (Krause and Cohen 1997), and Supreme Court decisions (Caldeira and Zorn 1998). The same issues confront the smaller number of comparativists using such data (Moore, Lindstrom, and O'Regan 1996).