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Association: Name: International Studies Association URL: http://www.isanet.org
Citation: URL: http://www.allacademic.com/meta/p72678_index.html Direct Link: HTML Code:

Hwang, Wonjae. "Power Structure and Multilevel Hierarchical Modeling in International Political Studies" Paper presented at the annual meeting of the International Studies Association, Le Centre Sheraton Hotel, Montreal, Quebec, Canada, Mar 17, 2004 <Not Available>. 2009-05-26 <http://www.allacademic.com/meta/p72678_index.html>

Hwang, W. , 2004-03-17 "Power Structure and Multilevel Hierarchical Modeling in International Political Studies" Paper presented at the annual meeting of the International Studies Association, Le Centre Sheraton Hotel, Montreal, Quebec, Canada Online <.PDF>. 2009-05-26 from http://www.allacademic.com/meta/p72678_index.html

Publication Type: Conference Paper/Unpublished Manuscript Review Method: Peer Reviewed Abstract: From a theoretical view, strategic approach is powerful in explaining international political phenomena. By assuming that political leaders give the highest priority to maintaining themselves in power, strategic approach potentially makes a paradigmatic shift of substantial importance (Ray 1999). Such a theoretical innovation makes it possible to integrate domestic and international games (Putnam 1988; Morrow 1991; Fearon 1994; Mo 1994,1995) played by autocratic leaders as well as democratic leaders in a theoretically coherent manner. Strategic approach in international political studies, therefore, requires the analysis of multilevel data structures. This paper will discuss various statistical methods of exploiting the information found in multilevel data structures in international politics. While the use of multilevel hierarchical data structures is common in international political research, proper statistical methods to deal with multilevel data structures have not widely been used (Beck & Katz 2001; Rodriguez & Goldman 1995). Formal explaining about the interaction between multilevel actors and theoretical arguments about the relationship between agent-centric values and institutional structures should also be discussed in this data structure (Buzan 1995). As a result, this research attempts to build a multilevel hierarchical model that captures multilevel data structures and determines how different levels interact each other. Multilevel (hierarchical) modeling has rapidly become established as the appropriate tool for modeling data with complex hierarchical structures. Discussing theoretical and statistical issues in regard to modeling multilevel data structures, this research will show why multilevel modeling could be so powerful in international political studies in understanding power structure and decision-making. That is, monitoring how political institutions play out differently in different settings, this model attempts to explain causal heterogeneity, providing more accurate forecasts and estimates (Western. 1998). As substantive examples of hierarchical analysis, the heterogeneous effect of trade on interstate conflict will be discussed (Garztke & Li 2001; Maoz & Russett 1993; Oneal & Russet 1997, 1999, 2001; Barbieri & Schneider 1999; Beck & Tucker 1997; Beck, Katz, & Tucker 1998). Analyzing policy orientation or ideal point of international institutions such as the U.N. will also be important in explaining the probability of interstate conflict or war onset. In this case, international institutional level becomes another higher (power) level. Analyzing the role of the U.N. in interstate conflict will be another example. Meanwhile, this research will show how different methods of statistical inference for the multilevel model work out. That is, maximum likelihood estimation (Steenbergen and Jones 2002), Bayesian hierarchical estimation (Martin 2001; Browne and Draper 2000), and generalized estimating equations (Goldstein 1995; Zorn 2001) will be used and each statistical result will be compared for this purpose. In order to simultaneously estimate the first-level parameters and the hyper-parameters, I employ Markov Chain Monte Carlo (MCMC) estimation methods. The Winbugs statistical package will be used for this purpose. MLwiN statistical package will also be used for maximum likelihood estimation (Steenbergen and Jones 2002).

The Effects of Domestic Politics onthe Effectiveness of International Institutions in the 1987 MontrealProtocol

The Effects of Domestic Politics on the Effectiveness of International Institutions