2003
DOI: 10.2307/3186145
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Contagion Effects and Ethnic Contribution Networks

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Cited by 59 publications
(64 citation statements)
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“…In contrast, with few exceptions diffusion analysis remains nonexistent in studies adopting a dyadic framework, that is, a setting where, as in much of international relations research, the unit of analysis is the pair or dyad of two political units representing an interaction or a relation between the two units such as the conclusion of a bilateral treaty or the initiation of violent conflict between two countries+ 3 This is surprising because spatial dependence exists whenever the marginal utility of one unit of analysis depends on the choices of other units of analysis+ What one unit does in relation to other units, with which it forms a dyad, will often influence and be influenced by the relations of other dyads, such that spatial dependence is likely to exist in many dyadic settings+ For example, the conclusion of bilateral treaties by some countries often affects the expected payoffs of other countries from entering into similar treaties themselves+ One potential reason for the lack of studies analyzing spatial dependence in a dyadic framework is that political scientists are not aware of the many specification options for modeling such dependence in dyadic data+ Recognizing the various ways in which spatial effects in dyadic data can be modeled will enable scholars to formulate and test different and novel diffusion channels, thus facilitating and hopefully spurring a whole new generation of studies analyzing spatial dependence between dyads of political units at all levels of the political system-from the global and international right down to the local+ This research note makes two contributions+ First, our analysis enriches the thriving literature applying dyadic data and calls on researchers to take spatial dependence in such data seriously+ Spatial dependence often seems to be theoretically warranted but is practically always ignored+ For example, the conclusion of bilateral and multilateral trade, investment, alliance, and other agreements among some dyads most likely influences the incentives for other dyads to conclude similar agreements+ The conclusion of such agreements often generates externalities, increases competition, induces cooperation, or leads to coercion, learning, emulation, or other effects by which the policy choices of other dyads are affected+ Yet, to our knowledge only three studies analyze spatial dependence in the diffusion of bilateral investment treaties~BITs!, preferential trade agreements, and bilateral alliance formation, respectively+ 4 Another good example is the democratic peace literature+ King argues that "dyadic observations in international conflict data have complex dependence structures+ + + + @I#n dyadic data, observation 1 may be U+S+-Iraq; observation 2, U+S+-Iran; and observation 3, Iraq-Iran+ The dependence among these separate observations is complicated, central to our theories and the inter-2+ See, for example, Cho 2003;Murdoch and Sandler 2004;Simmons and Elkins 2004;Jahn 2006;Franzese and Hays 2006;Gleditsch and Ward 2006;Salehyan and Gleditsch 2006;Swank 2006;and Brooks 2007+ 3+ The rare examples of studies analyzing spatial dependence in dyadic data include Porojan 2001;Manger 2006;…”
mentioning
confidence: 99%
“…In contrast, with few exceptions diffusion analysis remains nonexistent in studies adopting a dyadic framework, that is, a setting where, as in much of international relations research, the unit of analysis is the pair or dyad of two political units representing an interaction or a relation between the two units such as the conclusion of a bilateral treaty or the initiation of violent conflict between two countries+ 3 This is surprising because spatial dependence exists whenever the marginal utility of one unit of analysis depends on the choices of other units of analysis+ What one unit does in relation to other units, with which it forms a dyad, will often influence and be influenced by the relations of other dyads, such that spatial dependence is likely to exist in many dyadic settings+ For example, the conclusion of bilateral treaties by some countries often affects the expected payoffs of other countries from entering into similar treaties themselves+ One potential reason for the lack of studies analyzing spatial dependence in a dyadic framework is that political scientists are not aware of the many specification options for modeling such dependence in dyadic data+ Recognizing the various ways in which spatial effects in dyadic data can be modeled will enable scholars to formulate and test different and novel diffusion channels, thus facilitating and hopefully spurring a whole new generation of studies analyzing spatial dependence between dyads of political units at all levels of the political system-from the global and international right down to the local+ This research note makes two contributions+ First, our analysis enriches the thriving literature applying dyadic data and calls on researchers to take spatial dependence in such data seriously+ Spatial dependence often seems to be theoretically warranted but is practically always ignored+ For example, the conclusion of bilateral and multilateral trade, investment, alliance, and other agreements among some dyads most likely influences the incentives for other dyads to conclude similar agreements+ The conclusion of such agreements often generates externalities, increases competition, induces cooperation, or leads to coercion, learning, emulation, or other effects by which the policy choices of other dyads are affected+ Yet, to our knowledge only three studies analyze spatial dependence in the diffusion of bilateral investment treaties~BITs!, preferential trade agreements, and bilateral alliance formation, respectively+ 4 Another good example is the democratic peace literature+ King argues that "dyadic observations in international conflict data have complex dependence structures+ + + + @I#n dyadic data, observation 1 may be U+S+-Iraq; observation 2, U+S+-Iran; and observation 3, Iraq-Iran+ The dependence among these separate observations is complicated, central to our theories and the inter-2+ See, for example, Cho 2003;Murdoch and Sandler 2004;Simmons and Elkins 2004;Jahn 2006;Franzese and Hays 2006;Gleditsch and Ward 2006;Salehyan and Gleditsch 2006;Swank 2006;and Brooks 2007+ 3+ The rare examples of studies analyzing spatial dependence in dyadic data include Porojan 2001;Manger 2006;…”
mentioning
confidence: 99%
“…The following section draws on this literature to distinguish between spatial and aspatial explanations for nationalization. Whereas spatial explanations emphasize horizontal dynamics and the role of geographic factors, such as proximity, aspatial explanations highlight variables unrelated to geography (see Cho, 2003). Even though they are conceptually distinct, both types of explanations may complement each other empirically and explain different aspects of the broader phenomenon.…”
Section: The Spatial Dimension Of Party and Party System Developmentmentioning
confidence: 99%
“…At the outset, however, it is important to highlight that in spatial analysis evidence for the spatial process is indirect, as the precise nature of the datagenerating process is unobservable (e.g. Cho and Gimpel, 2012;Cho, 2003;Baller et al, 2001). Instead, researchers look for patterns that are consistent with the hypothesized process.…”
Section: Empirical Implications Of Aspatial and Spatial Explanations mentioning
confidence: 99%
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“…The participation literature asserts that social and information networks raise individuals' levels of political interest and knowledge, increasing their likelihood of engaging in activism (Johnson, Stein and Wrinkle 2003;McClurg 2003;Bowers 2004;Cho, Gimpel and Dyck 2006). Furthermore, Cho (2003) shows that campaign contributions by Asians follows a pattern of diffusion, and Kenny (1992) finds that people participate more when they are part of an active social network. The relationship between networks and participation is amplified in black politics.…”
Section: The Importance Of Networkmentioning
confidence: 99%