of 2019, and 7 percent by the end of 2020. Firms assigned to treatment are more likely to survive by 3 percentage points in 2019, and 5 percentage points in 2020. Firms may not appear in the PILA because they have closed, or because of reporting issues. For example, a couple of the firms appear to be registered only under the owner’s name as a natural person, rather than as companies. We therefore consider a second definition of survival, which involves cross-checking data from formal employment reported in the PILA with data on the firm from the export database, from the RUES (Mercantile Registry), and from IPA calling and visiting firms to verify their status. We believe this is the most accurate measure of firm survival as a result. Column 3 looks at impacts on this measure of survival for the full 200 firms, and again finds treated firms are 5.1 percentage points more likely to survive, with this effect significant at the 10 percent level.

The firms that closed were considerably smaller to begin with on average than those that survived. For the control group, mean (median) January 2018 employment was 87 (48) for the survivors, compared to 51 (21) for firms that closed; for the treatment group it was 73 (43) for the survivors, compared to 23 (11) for firms that closed. Moreover, the firms that died were much less likely to be engaged in exporting: 0 out of the control firms that died had exported in the past three years prior to applying for the program compared to 64 percent of the control firms that survived, and only 1 of the treated firms that died had exported in the three years prior to applying for the program. Since we code exports as zero for firms that are closed, closure effectively results in replacing 0 exports for an open firm with 0 exports for a closed firm.

Panel B of Table E2 provides treatment estimates on monthly firm employment using the PILA. Column 1 and 2 show an impact on the level of employment of 0.49 workers relative to a control mean of 81 workers in 2019, and of 0.44 workers relative to a control mean of 79 workers. This effect is small in magnitude (0.6% of the control mean), and not statistically significant. Column 3 restricts to the sample of surviving firms, and again finds a small impact. The 95 percent confidence interval for the treatment impact in 2020 is (-3.5 workers, +4.4 workers), which includes changes of up to 5 percent in employment. Employment changes may take longer to manifest, but at least in the first two years, the program did not result in large changes in employment.

**Impact on Sales, Profits and Labor Productivity Using the RUES** After our pre-registration, we became aware of an additional source of administrative data on firms, which is the _Registro Único Empresarial_ (RUES), which contains data from firms’ annual renewal in the _Registro Mercantil_ (Mercantile Registry).<sup>13</sup> Colombia Productiva provided

> 13Our pre-analysis plan also said we would attempt to link the firms to the Encuesta Anual Manufacturera (Annual Manufacturing Survey, or EAM). These data are released with a considerable lag, and can only be accessed in a data lab in Colombia, with the pandemic making access to the lab more limited. We had a consultant work with these data, with only data up to the end of 2019 available. 181 firms were matched in the 2017 data, and 182 firms in the 2018 and 2019 data. The point estimates suggest a

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