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IGOs and the Determinants of Member State Interest Convergence
Unformatted Document Text:  + u x + e xt . Table 1 Here With regard to methodological considerations, it is important to use a long time- lag in order to avoid results that could be contaminated by reverse causality. Without a lag, one could argue that any supportive findings can be explained by the fact that states with more similar interests are more likely to form or join the same IGOs. While it is typical to use a one-year time lag to deal with potential problems of endogeneity, it is more appropriate to use a longer time lag in my model for the reasons specified above. Statistical Results Table 2 presents the estimates for Model 1. As mentioned above, this is a fixed effects model with robust standard errors clustered on the dyad. Consistent with interest convergence, the coefficient for the LOWMEMBERS IGO MEMBERSHIP variable is 0.0037 and is statistically significant at the 99% confidence interval, indicating a positive relationship between joint membership in IGOs with a low number of members and increases in interest similarity. The substantive impact, however, is quite modest as a one standard deviation increase in joint IGO membership in IGOs with few members leads to an increase of 0.002 in interest similarity. Although I made no assertions in my theory as to the direction of the control variables, it is interesting to note the results. The EXTRA - IGO CONTACT variable is negative and statistically significant, which is counter to what might have been expected. In 27

Authors: Bondanella, Stacy.
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background image
+ u
x
+ e
xt
.
Table 1 Here
With regard to methodological considerations, it is important to use a long time-
lag in order to avoid results that could be contaminated by reverse causality. Without a
lag, one could argue that any supportive findings can be explained by the fact that states
with more similar interests are more likely to form or join the same IGOs. While it is
typical to use a one-year time lag to deal with potential problems of endogeneity, it is
more appropriate to use a longer time lag in my model for the reasons specified above.
Statistical Results
Table 2 presents the estimates for Model 1. As mentioned above, this is a fixed
effects model with robust standard errors clustered on the dyad. Consistent with interest
convergence, the coefficient for the
LOWMEMBERS
IGO
MEMBERSHIP
variable is 0.0037 and is
statistically significant at the 99% confidence interval, indicating a positive relationship
between joint membership in IGOs with a low number of members and increases in
interest similarity. The substantive impact, however, is quite modest as a one standard
deviation increase in joint IGO membership in IGOs with few members leads to an
increase of 0.002 in interest similarity.
Although I made no assertions in my theory as to the direction of the control
variables, it is interesting to note the results. The
EXTRA
-
IGO
CONTACT
variable is negative
and statistically significant, which is counter to what might have been expected. In
27


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