observed comparative statics. As noted in the context section, worker-level data from the 752 garment making firms in the **?** baseline dataset reveals that 91% of the workforce in that baseline sample are unskilled workers. Though skilled workers comprise only 9% of the labor force, they earn 61% of all wages paid by firms in the baseline data. Skilled and unskilled workers average similar hours of work per week and skilled workers earn many multiples the hourly and weekly wage of an unskilled worker.

Though it is not possible to categorize workers as skilled or unskilled in the analysis panel dataset, the labor information in the February 2014 census differentiates workers by skill level. At that time, the sample employed 256 apprentices, 76 family workers, and 27 skilled workers, a workforce composition that was 92% unskilled workers, remarkably similar to the ratios in the national-level **?** data. The preponderance of unskilled workers in this setting implies that the first of the key comparative statics, that worker hours increase in response to outages, is likely explained by firms employing this type of worker. Likewise, the contextual similarities between this study and **?** (and the experience of the research team in the field) imply that skilled workers in this sample are also much better paid than their unskilled counterparts, suggestive evidence that large changes in firm-level weekly wages paid (the second key comparative static) are driven by firms employing skilled workers.

An alternative explanation of rising hours and falling earnings could be that in the presence of falling productivity, skilled workers being paid at a piece rate simply experience a reduction in hourly wages.<sup>18</sup> Though it is not possible to test for this directly given data limitations in the firm-level panel, in the third key comparative static of the paper the analysis fails to reject that outages have no effect on within-firm worker hourly wages, consistent with reductions in both wages and hours for skilled workers and inconsistent with the simplest version of this alternative interpretation. **?** provides complementary evidence in this regard, using the World Bank Enterprise and Afrobarometer surveys to show that unreliable electricity supplies reduce both employment and the share of high-skilled jobs in the local labor market.

Another interpretation issue to consider is whether increases in worker labor inputs result from hiring or from shift changes among unskilled labor in the existing workforce. Again, data limitations in the firm-level panel preclude a direct test. However, total blackout exposure reported by each firm owner during the panel does not predict the changes in employment seen between February 2014 and March and April 2015, limited but suggestive evidence that extensive margin labor may be less important in the short-term than intensive margin staffing changes.<sup>19</sup> This preliminary conclusion is also consistent with evidence from **?** that small firms in Ghanaian artisan manufacturing are labor constrained.

Finally, although the data includes no direct information on capital utilization by firm owners and skilled and unskilled workers, evidence from Table 1 on available production technologies shows that the vast majority of firms with and without workers have access to manual sewing machines that can

> 18We thank two anonymous referees for this insight.

> 19See Appendix Table 8.

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