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IGOs and the Determinants of Member State Interest Convergence
Unformatted Document Text:  1970-1991. 3 Since I am testing whether joint membership in IGOs with low membership leads to a convergence in state interests over time, I use the similarity in two states’ interests as the dependent variable and, for the key independent variable I count the number of IGOs with six or fewer members to which the two states are members. Gartzke et al. question the use of count variables for testing IGO effects because a simple count of IGOs does not allow one to model the specific attributes of IGOs and instead assumes that all IGOs are alike and that their impact “accumulates in a quasi- linear fashion.” The goal of this project is precisely to code and test the effects of specific IGO attributes on interest convergence, but I do so by counting the number of IGOs with those specific attributes to which the two states both belong. Boehmer, Gartzke, and Nordstrom have coded IGOs into three categories corresponding to increasing levels of institutionalized structure. However, because I am testing for IGO effects on interest convergence, I need to distinguish IGOs by attributes that are expected to be conducive to interest convergence rather than simply those that may lead to the absence of conflict or some other type of state behavior. Gartzke et al. use the IGO-state-year unit of analysis in their test of IGO effects on international conflict behavior, claiming that this allows them to evaluate the impact of each IGO on each member state. There are two potential problems with such an approach. First, if one focuses on each IGO separately for each state, how does one control for the effects of all of the other IGOs to which the state belongs? Second, I assert that IGOs have an affect on state interests because they promote interaction. It is 3 Future tests will include all post-World War II dyads for which the relevant data is available. However, since I used the Correlates of War IGO dataset as a template to generate a dyadic version of my data and since that data is only available in five year increments until 1965, my current sample starts in 1970. Note that, due to the use of a five year time-lag, I could not start in 1965. Data for other important variables is not available past 1991 at this time. 19

Authors: Bondanella, Stacy.
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Since I am testing whether joint membership in IGOs with low membership
leads to a convergence in state interests over time, I use the similarity in two states’
interests as the dependent variable and, for the key independent variable I count the
number of IGOs with six or fewer members to which the two states are members.
Gartzke et al. question the use of count variables for testing IGO effects because a
simple count of IGOs does not allow one to model the specific attributes of IGOs and
instead assumes that all IGOs are alike and that their impact “accumulates in a quasi-
linear fashion.” The goal of this project is precisely to code and test the effects of
specific IGO attributes on interest convergence, but I do so by counting the number of
IGOs with those specific attributes to which the two states both belong. Boehmer,
Gartzke, and Nordstrom have coded IGOs into three categories corresponding to
increasing levels of institutionalized structure. However, because I am testing for IGO
effects on interest convergence, I need to distinguish IGOs by attributes that are expected
to be conducive to interest convergence rather than simply those that may lead to the
absence of conflict or some other type of state behavior.
Gartzke et al. use the IGO-state-year unit of analysis in their test of IGO effects
on international conflict behavior, claiming that this allows them to evaluate the impact
of each IGO on each member state. There are two potential problems with such an
approach. First, if one focuses on each IGO separately for each state, how does one
control for the effects of all of the other IGOs to which the state belongs? Second, I
assert that IGOs have an affect on state interests because they promote interaction. It is
3
Future tests will include all post-World War II dyads for which the relevant data is available. However,
since I used the Correlates of War IGO dataset as a template to generate a dyadic version of my data and
since that data is only available in five year increments until 1965, my current sample starts in 1970. Note
that, due to the use of a five year time-lag, I could not start in 1965. Data for other important variables is
not available past 1991 at this time.
19


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