We randomly assign a spot in the course together with a scholarship to cover 65 percent of the cost of a computer coding course in Argentina, 80 percent of the cost in Colombia. Given a limitation on the sample sizes, we analyze the effects of the training on the pooled sample of beneficiaries in both countries.<sup>4</sup> We analyze the effects of the program on two sets of primary outcomes of interest: skills, and employment in technology. We find strong impacts of the program on skills, measured by an exam that resembles a coding test that an employer would apply during an interview to a candidate for an entry-level coding job. We also find positive and significant effects of the program on the probability of getting a job in technology. Importantly, we compare key characteristics of these jobs to the other jobs in our sample (which we call non-technology jobs). We show that even though technology jobs pay the same rate, they are more likely to offer flexible hours and workfrom-home arrangements (in line with Goldin (2014)), and they generate a higher job satisfaction when compared to non-technology jobs. We interpret this as a net improvement in overall job quality.

The analysis in this paper focuses on the short-term impacts of the program, since our follow-up data gathered information referring to February 2020, between 2 and 5 months after program completion. Moreover, we also gather employment information referring to May 2020. This provides us with a unique opportunity to measure whether the program effects make beneficiaries more resilient to the onset of a COVID-19 labor market crisis.<sup>5</sup> We hypothesize that the bootcamps could equip beneficiaries with an alternative source of employment and earnings should they face an adverse employment situation –either hours, pay cuts, or the loss of the job–. Compared to the control group, the treated group could exploit, for instance, the value added of the bootcamp on their CVs to find a better job, or take advantage of the possibility of self-employment in coding-related jobs, where self-employment and freelance jobs are frequent. The evidence suggests so, especially for the sub-sample of the self-employed.

> 4We worked closely with the coding schools in Buenos Aires and Bogotá and carefully designed the intervention so that it was as similar as possible between both countries. This included making the targeting of the program similar, as well as the content and structure. Minor differences across locations were adopted to adjust to the local context and/or constraints. The amount of the subsidy varies across locations to adapt to the local context, local cost of full tuition, and local costs of living.

> 5Employment data of February 2020 gathers information for a period before the COVID-19 crisis hit Argentina and Colombia. Both countries experienced the outbreak in COVID-19 cases long after the Northern Hemisphere. The first measures of lockdowns in Buenos Aires occurred in March 20, 2020, while in Bogotá it was in March 25, 2020. These lockdowns happened still when both cities had very few cases: by the time this first lockdown took place in Argentina (Colombia), there were only 97 (92) infections, and 3 (1) deaths nationwide. Still by May 2020, the COVID-19 outbreak was at its earliest in both countries.

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