cutoffs (which represents 97% of applicants)<sup>1</sup> . For all analyses, we study “medium-term” and “short term” effects by using data on program recipients that began the five-year program in 2011-2012 (34 years in the program) and 2013-2014 (1-2 years in the program), respectively.

With respect to environmental impacts, we found that the program increased management activities by participant communities to protect land cover--such as patrolling for illegal conversion, building fire breaks, or combatting soil erosion. Compared to controls, we found a substantial and statistically significant increase in an index of community land cover management activities of 48% (or 0.60 standard deviation). We also found a statistically significant increase of approximately 2.7 days per year per household devoted to land management activities. This substantial increase in land-cover management activities suggests that the program is achieving its primary goal of behavior change to support ecosystem service provision.

Mexico’s program has sought to overcome the inherent adverse selection problem common to PES by targeting payments to certain eligible areas of the country, prioritizing land with higher risk of deforestation, and introducing differentiated payments depending on risk level and ecosystem type. Our analysis of avoided forest cover change found suggestive evidence that the program as a whole reduced the rate of loss of tree cover, with point estimates indicating a 30-34% reduction for the early cohorts and a 20-24% reduction overall, but not being statistically significant. Due to data limitations<sup>2</sup> and the overall low rates of forest cover change during this time period, the minimum detectable effect sizes for the full sample were of roughly the same order of magnitude as the rate of forest loss among controls, making it difficult to detect anything less than a 70% impact of the program, which is higher than prior estimates of PES impacts in the literature, and is unlikely to occur because of remaining natural forest losses due to events such as fires or hurricane damage. However, we did find that within areas at high risk of deforestation, the program statistically significantly reduced the loss of tree cover, by approximately 30 percent, with larger effects for those who have been in the program longer (38 percent). Although imprecise, this study’s estimates of the percentage change in loss rates due to PES are similar in magnitude to studies of the 2003-2010 cohorts, which found changes in the rate of expected forest loss of 20-50 percent (Alix-Garcia, Shapiro and Sims 2012, Alix-Garcia, Sims and Yanez-Pagans 2015, Sims and Alix-Garcia 2017). Unfortunately, given the limitations of the satellite data, we cannot draw conclusions about whether or not changes in targeting or more differentiated payments have increased the environmental impacts of the program compared to earlier cohorts.

With respect to socioeconomic outcomes, summary statistics show that the program continues to reach many marginalized and remote communities and is frequently used to support daily wages and community investments (see Appendix Figure A1). Analysis of the communal and household level impacts suggests the program has maintained socioeconomic indicators for program participants to be on par with non-participants. Estimated impacts were small and not statistically significant for indicators of average household assets, housing stock, food consumption and primary education. These results contrast somewhat with evidence from prior cohorts, which indicated small positive impacts of PES on household wealth (Alix-Garcia et al., 2015; Sims et al., 2017) and small positive effects on some educational opportunities and household and community-level assets for poor participant households compared to poor non-participant applicants (Alix-Garcia et al., 2015). In this

> 1 Applicants with scores within 25 points of the scoring cutoffs represent 97% of the possible applicants.  However, for the environmental analysis, we further restrict this group to only include individual polygons with more than 50% forest cover in 2000.  We will discuss this further below in the section on the environmental analysis.

> 2 The study was designed to use higher resolution land cover change data being prepared under the new MAD-MEX MRV system. Unfortunately, post-processing of that data was not completed in time to use.

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