In addition, drawing on responses from the household-level survey, we find that individual households increased their participation in land-cover maintenance activities. Panel B of **Table 7** presents program effects on work days.<sup>16</sup> For the full sample, we find statistically significant impacts (p<0.01) on total land-cover work, which includes both work that is paid for through wages and work that is not financially compensated. Transforming the estimated impact into days, land-cover work in treated communities increased by approximately 4.2 days for the earlier cohorts and 2.3 days for the later cohorts (about 2.7 days for the combined sample). These are large percentage changes compared to the means among controls of (2.4 and 3.8 days per household).

## _Heterogeneous Effects_

For the heterogeneous effects analysis, the research team re-classified the survey zones to better group states that had similar communities on the basis of characteristics measured by the surveys. These five regions were: North (Chihuahua and Durango states), North-east (Nuevo Leon and San Luis Potosi states), Center (Jalisco, Michoacan, and Puebla states), South (Chiapas and Oaxaca states), and Yucatan Peninsula (Campeche, Quintana Roo and Yucatan). We investigated possible impact heterogeneity by region ( **Appendix Table A6** ) and found that enrolled communities in the northeast states of Nuevo Leon and San Luis Potosi increased their land-cover management activities with the greatest magnitude. However, this region is also the one with the lowest baseline level among controls, suggesting perhaps higher effectiveness where activities were low to start. We also estimated impacts for communities whose parcels were at high risk of deforestation and did not find any significant differences in land-cover management activities ( **Appendix Table A7** ).

## _Robustness checks_

Our impact estimates for the land management index analysis are consistent across a series of robustness checks. Point estimates are robust to excluding state fixed-effects, and to the inclusion of a series of controls (see Table S4 in the Supplementary information for Alix-Garcia et al., 2018). Following Barreca et al. (2016), we restricted the analysis to communities whose point scores were within certain bandwidths of the threshold (-5 to 5, -4 to 4, -3 to 3). Our point estimates on land management are robust to these changes (see columns 1-5 in Table S13 of the Supplementary information for Alix-Garcia et al., 2018). Our results are also consistent when dropping any properties just over the cutoff (point scores that are positive but less than 0.05) and using a fuzzy RD regression (columns 5 and 6 in the same table).

# **5.3 HOUSEHOLD SOCIO-ECONOMIC INDICATORS**

Because PES is voluntary, we would generally expect that communities would not agree to participate unless it made them better off. However, there are several reasons to be concerned about whether payments given to communities will necessarily improve household-level indicators. One reason is that households may need to devote substantial labor time in order to fulfill the management plan submitted to CONAFOR. Previous research suggests that program participation costs are high (Alix-

> 16 The values of work days are log transformed according to w w w w 2 + 1 ), which is equivalent to the inverse hyperbolic sine with a shift parameter of 1. YY= ln (w wwss+ �w wwss

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