# _2.6 Survey_

We conducted a survey to gather representative individual-level data from women in the study area. The survey took place in a subsample of the 113 localities. The survey covered 52 localities of Oaxaca and Yucatán, where data were gathered from 1,485 women between 18 and 45 years old. This sample was constructed using a probabilistic systematic stratified sampling method (with the strata being the state and experimental group), with a margin of error of +/- 2.9% and a confidence level of 95%.

The instrument included questions related to knowledge and awareness of the call for proposals of the WB project and recognition of posters used for the call for proposal. Given the survey was conducted in the middle of the RCT in February 2019, variables that come from this survey should not be considered as outcome variables but as measures of intermediate outputs.

We perfomed an additional balance test between experimental groups with the survey individuallevel sample. Details of it can be found in the appendix. Importantly, the sample of T1 versus T0 was significantly unbalanced (Wald χ<sup>2</sup> (8) = 23.56, p-value = 0.0027), mainly driven by “has children” and “speaks indigenous language”. The other omnibus tests were not statistically significant (p-value > 0.288). These variables were used as covariates in the main models to control for this potential unbalance. Still, results from these individual-level regressions should be interpreted with caution given the potential unbalance.

# _2.7 Analytical approach_

The main outcomes of our RCT were captured at the locality level. They include the number of applications sent by locality (either by men or women), the number of women by locality that participated in these applications, the number of applications led by women by locality, and the number of applications by locality whose teams are all women. Secondary outcomes of relevance are the number of applications selected for grants by locality and the total number of people by locality that are part of an application. For these outcomes, we used OLS regressions with treatment status of the locality, controlling for the total adult population in the locality in 2010, the proportion of adult woman in the locality in 2010, the proportion of females three years or older speaking an indigenous language in 2010, the localities’ continuous marginalization index in 2010, the number of grants awarded from CONAFOR between 2007 and 2017, and a dummy variable for state entity. We clustered the standard errors by agrarian unit to account for the randomization.<sup>11</sup> The main estimates of interest were the coefficients for the treatment variable, particularly the difference between T0 versus T1 and T1 versus T2 to capture the additional effects of the componentes that were added in each group. We also looked at T0 versus T2 given the limitations we have on power, capturing the full package of additions to the standard outreach strategy. These represent Intention-to-Treat (ITT) estimates.

Additionally, the survey data provided us with individual-level outputs, namely whether women had heard about the WB project and call for proposals, and whether they recognized any of the

> 11 The conclusions do not change if we analyze them without clustering.

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