the destination country, the natural log of the population in _j_ ( _Pop_ j) is included. _Exports_ ij, the average exports of country _i_ to country _j_ over 2007-2009 seeks to both size-related market attractiveness and all the gravity type of factors that impede or facilitate economic relations between a pair of countries, and control for the complementarities that may exist between investment and trade. All else equal, it is expected that the larger the size of the host country’s market and the higher the level of commercial exchange between the home and host countries, the more attractive the latter would be as an investment destination.

In line with gravity models used widely in the trade literature, our model controls for the geographic and cultural distances between home and host countries. _Dist_ ij is the capital to capital distance in kilometers (logs) from country of origin to country of destination, while _Contig_ ij, is a dummy variable equal to 1 if countries _i_ and _j_ are contiguous and zero otherwise. The greater the physical distance between two countries, the lower the expected investment levels between them, given higher transaction and information costs associated with distance. To capture the effect of cultural differences, we include two control variables: _Comlang_ ij is a binary variable equal to 1 if the countries _i_ and _j_ share the official language, and zero otherwise, while _Colon_ yij takes the value 1 if there was a shared colonial history between countries _i_ and _j_ and zero otherwise. We expect that sharing a common language and a colonial history to facilitate investment ties between two countries. Finally, eijs is the error term assumed to be orthogonal to the regressors, and the set of “ � ” and “ _b_ ” are parameters.<sup>13</sup> We also control for political stability and institutional quality, using data from the International Country Risk Guide (ICRG), published by the Political Risk Services Group, and from the World Bank Governance Indicators (WGI). We include two indicators in different models: the ICRG quality of government index and the WGI political stability index. _Gov quality_ is an average of three ICRG variables – Corruption, Law and Order, and Bureaucratic Quality. While the first two are measured on a scale from 0 to 6, Bureaucratic quality ranges from 0 to 4. The average of these scores is then scaled 0-1. _Pol stability_ measures perceptions of the likelihood of a government being overthrown by violent and/or unconstitutional means. In most circumstances, we would expect a positive relationship between the coefficient for these indicators and FDI count. However, if “adversity advantage” arguments are true, then the sign of the coefficient should be negative.

Our variables of interest are _BITij_ and _PTAij_ . _BITij_ is a dummy taking value 1 if countries _i_ and _j_ have a bilateral investment treaty signed and ratified. Similarly, _PTAij_ takes the value 1 if countries _i_ and _j_ have signed or are part of a bilateral or plurilateral preferential trade agreement.

It is possible that the direction of causality between international economic agreements and investment runs the other way. The case of the bilateral investment agreement between Uruguay and Finland helps illustrate this reverse causality problem. The agreement signed between the two countries in 2002 was part of the conditions required for a billion-dollar investment of a Finish cellulose pulp company in Uruguay. While formally, the treaty preceded the investment, the signature of the former, was a consequence of the interest in the latter. The standard approach to tackle this reverse causality problem that introduces a potential source of inconsistency to standard estimators is to instrument the endogenous variable – in this case the international economic agreement dummies. As a robustness check, we estimate instrumental variable models. We follow Hallward-Driemeier (2003) and Busse et al. (2008) and as instrument the

> 13 The specification also includes dummies for countries of origin (Brazil being the baseline) and sectors.

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