1993 raw means between producing and non-producing districts, once we introduce department fixed effects, all differences disappear except one. The only statistically significant difference that remains is among non-producing districts, where the ones located in producing provinces seem to display lower levels of basic necessities uncovered than those in non-producing provinces. However, once we add province fixed effects, comparing producing and non-producing districts in the same province, all differences disappear. Overall, results in Table 3 suggest that in 1993, prior to the mining boom, producing and non-producing districts did not differ in a statistically significant manner (conditional on the same controls used for the 2007 analysis).

With these results in hand, we move to analyzing whether the mining boom had any impact on mining districts, and how that impact may have trickled down to neighboring districts. In Table 4 we repeat the analysis of Table 3 except that now we use 2007 outcome variables and control for all 1993 variables (including district averages of the illiteracy rate and the index of basic necessities uncovered). In some specifications we also control for the amount of government transfers other than the _Canon_ (in logs, accumulated during 2002-06). This is to account for potential transfers aimed at compensating districts that are not favored by the distribution formula of the _Canon_ . It turns out that in all regressions the inclusion of other government transfers makes virtually no difference on the outcome variables, and therefore we will devote little time to discussing it.

Regression (1) in Table 4 suggests that in 2007 all districts in producing provinces had better socioeconomic outcomes than their counterparts in non-producing provinces: β0is always significantly different from zero, and β1 in all but two cases. The signs of these coefficients indicate that districts in mining provinces show higher average per capita expenditures; lower rates of poverty and extreme poverty (the latter for producing districts only); fewer households with basic necessities uncovered; and lower illiteracy rates (producing districts only). At the same time, districts in producing provinces exhibit higher consumption inequality, as measured by a higher Gini coefficient.

When we refine the control group and introduce department fixed effects (regression (2)), the differences between producing districts and districts in non-producing provinces (β0) remain large and significant: on average, households in producing districts display 14 percent higher per capita expenditures, poverty rates are between 3 and 4 percentage points lower, there are 4 percentage points fewer households with basic necessities uncovered, and illiteracy rates are 1.6 percentage points lower.<sup>8</sup> These beneficial impacts contrast with those regarding consumption inequality: the Gini coefficient in

> outcomes in 2007, where a clear causal relation can be asserted. Moreover, to correct for such biases we would need to use data on district characteristics prior to 1993, which are unavailable.

> 8 Observe that the last two estimates show the net impact after controlling for their 1993 levels.

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