Garcia et al 2015),<sup>17</sup> so there may be little surplus wealth available to individual households. At the same time, estimates based on a referendum-style question conducted in the study’s 2016 survey (see Alix-Garcia, Phaneuf and Sims 2018) suggest that most participants would be willing to accept lower payments than they are currently receiving and still participate. Prior evaluations of PES in Mexico found that it likely had a small positive effect on assets of the 2003-2009 cohorts of the hydrological services program (with non-differentiated payments) and may have increased educational opportunities for some households (Alix-Garcia et al. 2015). Changes in program rules starting with the 2013 cohort mandated that more of the funds be spent directly on land management equipment or activities.

How this mandate affects household-level outcomes is theoretically ambiguous. This is because money does not necessarily flow directly to households from the pool of payment money. Ejido authorities, usually after discussion with the assembly, make decisions about how the money will be invested – this sometimes occurs through direct transfers to households, but more often it is through investment in public goods or by paying wages for forest work. If households receive wages for this work, as was the case in 65% of the ejidos surveyed in 2011 (Yañez-Pagans, 2015), then they may directly gain additional income compared to prior cohorts. However, if this compensation is less than their opportunity cost of labor, they could be worse off. In addition, the real value of the payments has eroded over time by 15-20%.

**Table 8** presents our results on multiple indicators of wealth. We observe no effects on household wealth, as measured by indices of housing characteristics, asset ownership and food consumption (Panel A). Regarding the detectable effects for these three wealth indices, they ranged between 0.10 and 0.12 (equivalent to 14-30% increases). Given the variation in the data, the sample would not have been able to detect these small effects. In addition to the household wealth indices, we analyzed other social variables that are meaningful on their own: migration, children’s education, ownership of livestock and whether the household was credit constrained. We do not observe statistically significant changes (p < .05) in any outcomes. The point estimates indicate treated households were 54.9% less likely to report a household member to have migrated (3.9 percentage points with respect to a control of 7.1 percent) which is a substantial change, but only marginally statistically significant (p < .10). The 2013-2014 cohort was also more likely to report having a household member enrolled in secondary school (18.6% increase with respect to a control of 59 percent) and enrolled in highschool (28.8% with respect to a control of 40.0 percent). Again, these are substantial changes in magnitudes but only marginally statistically significant. The point estimates for most of these social outcomes were similar for the 2011-2012 cohorts, though these were not statistically significant.

# _Heterogeneous Effects_

We tested for impact heterogeneity for our welfare indices across regions, deforestation risk and payment magnitude. There were smaller effects on the housing index in the Yucatan Peninsula in both cohorts and in the same region in the later cohort (see **Appendix Table A8** ). There were also consistently more positive effects for the housing and asset indices in the central region of the country, although the total effect (the sum of the threshold and the differential impacts) indicates very small

> 17 Previous work based on the survey of applicants from the 2008 cohort found that the program induced significant increases in the time dedicated to the forest and that the ratio of the cost of additional labor (i.e., increases in forest management in beneficiaries relative to non-beneficiaries) to the payment amounts was 0.84.

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