|_PTA*Comlang ij_|0.402|0.645|||
|---|---|---|---|---|
||(0.776)|(0.852)|||
|_BIT*Comlang (ethno) ij_|||-0.535|-16.66***|
||||(0.619)|(3.325)|
|_PTA*Comlang (ethno)ij_|||-1.292**|-0.651|
||||(0.647)|(0.886)|
|_Pol stabilityj_|0.326|0.618**|||
||(0.213)|(0.269)|||
|_Constant_|-13.52***|-11.67***|-14.02***|-9.988**|
||(2.250)|(3.254)|(2.240)|(3.901)|
|Home FE|||||
|Sector FE|||||
|Observations|2,508|2,508|2,572|2,572|

Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1 Jointly considered, these results on cultural distance and those reported above on the geographical distance shed light on one mechanism operating within the channel that links IEAs (specifically BITs) and crossborder investment. BITs are more effective when firms invest in faraway, dissimilar environments, suggesting, as mentioned above, that they are imperfect substitutes for proximity and familiarity. PTAs, on the other hand, seem to, decrease in effectiveness as distance between partners grows.

These results hold in the face of several robustness tests, as shown in Table A2 in the Appendix. We begin by using alternative estimation strategies for each of the stages in the hurdle regressions, including Logit and Probit and Poisson and negative binomial. The coefficient for _BIT*Distance_ is positive and statistically significant in these models, except in the Poisson specification. In contrast, _PTA*Distance_ is only significant (and still negative) in the count models, suggesting that distance decreases the effect of PTAs on the quantity but not the likelihood of investments. Similarly, the coefficient of BIT*Contiguity is negative and significant across specifications, while PTA*Contiguity is only significant – and against our expectations also negative—in the Poisson model.<sup>17</sup> Finally, our findings concerning the interaction of BITs and cultural distance also continue to hold when using alternative estimation strategies. Both BITs and PTAs appear to have a stronger effect on investments between pairs that do not speak the same language.

It may be useful to show graphically the interactive relationship between IEAs and distance that our analysis has uncovered. Using the coefficients from the logistic and negative binomial regressions in Table A2 (Appendix), we plot the marginal effects of distance on FDI conditional of having or not BITs and PTAs (holding all other variables at their means). As Figure 2a shows, as distance between two countries’ capital cities grows, the likelihood of investment flows between them declines. However, it falls less rapidly for pairs of countries that have signed and ratified a BIT. Another way to interpret this conditional relationship is that for countries that are close to each other, the effect of having a BIT is insignificant. As distance between countries grows, however, the marginal effect of having a BIT also increases. In contrast, as Figure 2b shows, the marginal effect of having a PTA is substantially higher when distance between two countries is low. As distance grows, the effectiveness of a PTA in increasing the likelihood of investment, fades.

> 17 These results are only marginally altered when dropping the logarithmic transformation of _GDPpc_ and _Pop,_ and when using _LnDistance_ instead of Distance as in previous specifications.

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