Table 7a reports the regressions based on the scale of mining operations. When we estimate the models using the USGS data, the results show statistically insignificant effects on per capita growth, population density, spatial Gini and Sen Index in treated districts with small-scale mining operations. With the exception of the significant negative effect on population density, the results in districts with small-scale mining operations remain the same for other outcome variables when we estimated the models using the World Bank’s real prices data. The table also shows that, when fitting the model using the USGS data, the estimates on treated districts with large-scale mining operations are statistically not different from zero for average annual lights per capita growth, population density, and spatial inequality, but positive and different from zero for the Sen Index. Similarly, when we use the World Bank’s real prices data, the lights per capita growth, population, and spatial inequality remain statistically insignificant, while the Sen Index remained significant, albeit at the margins. Moreover, when we use the World Bank price data the coefficients of real prices remain insignificant for all variables except the Sen Index, indicating the significant welfare impacts of changing real mineral prices. The expectation effect remains the same as before, but at the 10 percent significance level with the USGS data compared to a 1 percent significance level with the World Bank data.

Table 7b reports the regressions based on the aggregate extracted minerals’ values. When we fit the models using the USGS data, the results show insignificant effects on the average annual lights per capita growth, population density, spatial Gini, and Sen Index in the treated districts engaged in extracting the high-value minerals. Similar results hold when we fit the models using the World Bank’s real price data. Additionally, the table, using USGS price data, reports statistically insignificant impacts on average annual lights per capita growth, population density, and spatial inequality in the treated districts engaged in extraction of low-value minerals. Nonetheless, the impacts on the Sen Index are positive and statistically significant. Similar to Table 7a, when we fit the models using the World Bank’s real price data, the results remain qualitatively unchanged. Further, except for the changes in coefficient sizes, the sign of the impacts of minerals prices and the expectation effects remain similar to those in Table 7a.

We now turn our attention to the heterogeneous effects based on the different types of mining activities; namely, extraction or transformation activities. Table 7c presents these results again, indicating statistically insignificant impacts on all our outcome variables in the treated districts compared to control districts engaged in the minerals extraction activities. These results remain qualitatively robust using both the USGS and the World Bank data. Furthermore, when we fit the models using both the USGS and the World Bank data, the results indicate similar insignificant impacts on all the outcome variables in the treated relative to control districts engaged in minerals’ transformation activities. Again, except for the changes in coefficient sizes, the sign of the impacts of minerals prices and the expectation are qualitatively similar to those in Tables 7a and 7b.

20