groups of localities and populations with different characteristics, since our experimental sample was selected through a series of filters and not a random sampling of eligible localities. In this exploratory analysis, we analyze each specific application, rather than the aggregated number of applications in each locality (i.e., the unit is the application, rather than the locality). Given T0 only had one application (which was not selected for a grant), comparing the characteristics of this unique application to average characteristics of applications from T1 and T2 (which had 214 applications) could be too noisy and not meaningful. While we cannot derive conclusive evidence from this exploratory analysis, it can help generate hypotheses as to why the experimental sample had a low number of applications that were selected for funding.

Only one application that was submitted to this call for proposals from localities in the RCT sample was selected for grants (0.4% - this application came from T2). While localities outside the RCT sample submitted a similar total number of applications (215 in the sample and 226 outside), the rate of applications selected was much higher outside the sample (11% – 26 applications from outside the RCT sample). Furthermore, administrative data shows that 93% of the applications submitted from the RCT sample lacked important details, while only 48% of applications from outside our localities had this characteristic. Unfortunately, we do not have more detailed data to assess and compare the “quality” of the proposals or to isolate the specific issue that caused the difference in success rate, although we include some hypotheses below. Also, the average number of applications per in-RCT-sample locality was much higher (mean from inside sample = 6.52, mean from outside sample = 1.39, t = -10.81, df = 179, p-value < 0.001), with 76% of localities that submitted an application from outside the sample submitting only one application. Furthermore, when comparing the demographic characteristics of these localities, the localities from the RCT sample that sent applications are smaller on average, have a larger proportion of the population that speaks indigenous languages, have fewer years of schooling, and have a slightly smaller proportion of women and adults in the population (this difference is the result of the selection criteria of the localities used for the RCT). Finally, applications outside the RCT sample were typically projects involving larger land areas and team sizes, and including a broad set of timber and nontimber activities in forest landscapes, possibly showing more diversity of activities.

# **Discussion, conclusions, and policy implications**

The strategies used to complement the standard outreach strategy through simplification and expanding the communication channels were effective in achieving the objective of increasing the number of applications sent by localities, including applications that included women. While the control group localities barely submitted applications (one application received from all 36 localities), the treatment groups sent, on average, more than 2.4 applications per locality. Complementing this with insights from behavioral sciences, a checklist, and proactive reminders and encouraging messages had an additional effect on the share of women taking part in these applications. However, this increased number of applications did not translate into more grants being awarded to these localities.

The evidence shows that the largest effect on the number of applications can be attributed to expanded communication channels and simplification process (T1). While the localities that received the content that leveraged behavioral sciences insights and provided proactive reminders 16