The main explanatory variable of interest, as mentioned, is the natural logarithm of the absolute value of net exports of natural resources per worker. The trade data come from UNCOMTRADE, as downloaded from the World Bank’s data server. The commodity groups of products classified as being intensive in the use of natural resources are Leamer’s (1984, 1995) non-manufacturing commodities – see Table A1.

Regarding the conditioning variables, we follow the strategy in Lederman and Maloney (2007) by examining how changes in the specification of the model affect the coefficient on the natural-resource variables. The initial multi-variate regression model specification includes two variables in addition to the natural-resource proxies: (a) the share of years during 1980-1999 when the dummy variable for policy reform was observed, as per the data in Wacziarg and Welch (2002) and Sachs and Warner (1995);<sup>14</sup> (b) and the average annual growth of the terms of trade during 1980-2005, which comes from the World Bank’s World Development Indicators data, as downloaded in early 2008.

The augmented model includes the executive constraints variable, which is the institutional variable used in Acemoglu and Robinson (2002, 2005) and Glaeser et al. (2004). The data come from the Polity IV database, and has a value that ranges between 1 and 7, with higher values representing less executive-branch discretion. The econometric models include the natural logarithm of this variable, which makes it easier to interpret coefficient estimates as elasticities. The literature argues that constraints on the Executive should be negatively partially correlated, in the first stage of 2SLS estimations, with historical population density.<sup>15</sup> Due to the limited coverage of the historical population density variable, we present two sets of 3SLS estimations of the static and dynamic models; one with the limited sample and another with a sample that incorporates observations with imputed values for population density circa 1500. This allows for a discussion about how the limited sample affects the estimated coefficients.<sup>16</sup> 14 The policy reform index is one if import tariffs are below 40%, if there are not significant non-tariff barriers, if governments have privatized a significant share of public enterprises, and if the foreign-exchange black market premium is below a certain threshold – see the Data Appendix for details.

15 High population densities circa 1500 are presumably associated with the localization of extractive activities and slave trade rather than with permanent settlement. Acemoglu and Robinson (2005, 960) state: "The second determinant of European colonization strategy was initial indigenous population density. Where this was high, Europeans were more likely to “capture” the local population and put it to work in some form of forced labor system. Where initial population density was low, Europeans were more likely to settle themselves and less likely to develop extractive institutions even when they did not settle. Acemoglu et al (2002) provide evidence that for countries colonized by European powers there is a strong negative relationship between population density in 1500 and income per capita today. This relationship is driven by the fact that former colonies with greater population density in 1500 had, and still have, worse property rights institutions. The density of indigenous population per square kilometer in 1500 is therefore an appealing alternative instrument. Because settler mortality and population density in 1500 correspond to different sources of variation in practice (the correlation between the two measures is 0.4), but should have similar effects on property rights, using these two instruments separately is a good check on our results." If the cursevia-politics hypothesis is correct, then we also expect a negative partial correlation in the first-stage equation between our proxy for relative natural-resource abundance and the executive constraints index. It is noteworthy that Glaeser and coauthors (2004) argue that education trumps institutions. This issue will be important in the interpretation of our results, since we also control for capital accumulation and human capital.

16 The imputed values are estimated using all the other explanatory variables in the equation of the determinants of executive constraints, namely (log of the absolute value of) net exports of natural resources, 14