agricultural production after a mine closing. In contrast, male partners increase agricultural selfemployment after mine closings, but experience a contraction in skilled manual and agricultural employment. There is a small increase in clerical jobs and a small decrease in professional work, but the magnitudes are negligible.

We further explore whether jobs are created in mining per se. A subset of the surveys includes information on whether a woman or her partner work in mining. The categorization unfortunately differs between DHS survey rounds, and hence these variables can only be taken as indicators of engagement in mine activities.<sup>11</sup> We run regressions on whether a woman or her partner is engaged in mining using three different mine datasets (RMG, USGS or the CSCW diamond dataset). Table 5 shows that industrial scale mining has no effect on employment in mining for women, as there is no statistically significant difference between active and inactive in Column 1. Neither do we find any statistically significant correlation for USGS mines. The USGS mine measure does not contain information on the type, timing, or significance of the mining activities. Anecdotal evidence suggests that it is common for women to engage in some type of artisanal and small-scale mining (ASM) activities, which this mine measure partly captures. Using the diamond dataset from CSCW, no correlation is found for women. In contrast, being within 20 kilometers of a mine is significantly and positively associated with the woman’s partner being engaged in mining for all three mine estimates, and there is an effect of mine industrialization in the RMG data. Mine openings increase the likelihood of the husband being a miner by 4.1 percentage points, which is a large increase relative to the sample mean of 2.6%.

Despite women seldom taking part in the large-scale mining, their labor market outcomes are substantially affected by industrial mining. The sectoral composition of the labor market effects for women is different from that of their partners. We continue by further assessing the robustness of the findings for women because we do not have all the necessary variables for the partners. In Section 5.2, however, we will conduct some extra analysis for a smaller sample of men for whom we have information on cash earnings and seasonality of work. We furthermore choose to restrict the focus to our four main outcome variables due to their relative importance. Results for all other variables are available upon request.

# **4.1 Other measures of occupation**

To further assess the effects on employment changes, we investigate the effects of mining on remuneration and seasonality of work. We have data on how women are paid for work outside the household and whether they work all year, seasonally, or occasionally. The sample is smaller because the question is not asked in all DHS survey rounds. Being close to an inactive mine is associated with a higher probability of earning in-kind only and negatively correlated with earning cash (Panel A of Table 6), and women are less likely to work seasonally after mine opening,

> 11Possible categories include: mine blasters and stone cutters; laborers in mining; miners and drillers; miners and shot firers; laborers in mining and construction; gold panners; extraction and building workers; mining and quarrying workers; and laborers in mining, construction and manufacturing.

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