# **Treatment Effects on WMS and MOPS measures of management**

Table A7.3 reports the estimated treatment impacts on the WMS and MOPS measures. Since these data are only available for a subset of our firms, we report several different specifications. In Panel A, we use all 70 firms for which follow-up WMS data are available (or the 95 firms with MOPS data for the last column). We do not control for randomization triplet fixed effects given that this would result in relatively few triplets being included. Instead, panel A includes no other controls, while Panel B controls linearly for key baseline variables used in the randomization (region, size, employment, labor productivity, and baseline Anexo K). Panels C through E then use the set of 50 firms for which both baseline and endline WMS data are available.

In panels A and B, we find very small and statistically insignificant impacts of either treatment on any of the WMS or MOPS management measures. Restricting to the sample for which we also have baseline data in panels C, D and E results in larger point estimates for the WMS, but the impacts are still far from statistically significant.

Our results show that both treatments resulted in significant increases in the Anexo K measure of management practices, and in each of its five subcomponents. This raises the question of why we do not see such a change in the WMS and MOPS? A first potential explanation is that the WMS and MOPS are only available for subsamples of the data, so that the difference in results could stem from sample composition and sample size. To investigate this hypothesis, Table A7.4 reestimates the management treatment effect regressions for common sub-samples. The first column repeats our estimated impact on the Anexo K measure for the balanced panel. Columns 2 and 3 then consider the 52 firms for which we have both the 2016 WMS and Anexo K measured during and after the intervention. We continue to see a statistically significant impact of the individual treatment on the Anexo K measure using this sub-sample both during and post-intervention, and a significant impact of the group treatment during the intervention, with the magnitude of the estimated effect only falling in a substantive way for the group treatment post-intervention, although with a wide confidence interval. In contrast, there is no significant impact on the WMS using this same sample. The foot of the table converts the estimated treatment effects into confidence intervals expressed in terms of standard deviation changes in the respective management practice. We see that not only are the WMS treatment effects statistically insignificant while those for the Anexo K outcome are statistically significant, but the 95 percent confidence interval for the effect of the individual treatment effect does not even overlap for the two outcomes. This suggests that the lack of impact on the WMS is not simply a matter of the sample composition or statistical power. Likewise, when we restrict to the same sample as the MOPS in columns 4 and 5, we find significant treatment impacts on the Anexo K, and no significant impact on the MOPS, although in this case the confidence intervals do overlap.

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