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Study Overview

Evaluating Mexico’s Payment for Environmental Services (PES) Scheme
Study ID:
Initial Registration Date:
Last Update Date:
Study Status:
Between 1990 and 2010, Mexico lost 5.5 million hectares or 7.8 percent of its forest cover (FAO 2010). Deforestation is largely driven by the conversion of forested land to more profitable land uses such as agriculture or pasture. In response to this issue, Mexico’s National Forestry Commission (CONAFOR) operates the Programa Nacional Forestal-Pago por Servicios Ambientales (PSA). PSA is designed to encourage the conservation of forest cover and maintenance of forest ecosystems through payments to owners of ecologically valuable land who apply to the program. This evaluation study will employ a regression discontinuity (RD) design which exploits two key features of the beneficiary selection process: a continuous eligibility score for applicants and a clearly defined budget cutoff unknown to applicants. The main aim is to assess the environmental impacts of the program in the short term, as well as after exiting the program, and possible leakages to non-enrolled land. Other goals are to assess the effects of the program on social capital (in Mexico a majority of forested land is held as common property) and the socio-economic impacts at the household level.
Environment and Disaster Management
Additional Keywords:
environment, deforestation, regression discontinuity, payments for environmental services, Mexico
Secondary ID Number(s):
P156100 - World Bank

Principal Investigator(s)

Name of First PI:
Jennifer Alix-Garcia
University of Wisconsin-Madison
Name of Second PI:
Katharine Sims
Amherst College

Study Sponsor

Comision Nacional Forestal (CONAFOR) Mexico
Study Sponsor Location:
Funding Proposal:

Research Partner

Name of Partner Institution:
World Bank -- DIME
Type of Organization:
Foreign or Multilateral Aid Agency
United States

Intervention Overview

Every year, CONAFOR issues a call for applications in each one of the country’s 32 states. While open to individual landholders, most PSA recipients (~60% of contracts, but accounting for 85% of enrolled land) are communities classified as poor and having lands at high risk of deforestation. Information campaigns are organized around these calls for applications and government surveyors facilitate and guide the application process. Applicants allocate specific areas within their properties to be protected under and receive payments from the PSA program. CONAFOR then scores the proposals on geographical and applicant characteristics, ranks them, and awards contracts in order of their score (starting from the highest) until it depletes that year’s PSA budget. Each state has its own budget, so the minimum points necessary to be accepted vary across states and from one year to the next, depending on the specific budget assigned and on the mix of applications received. PSA recipients receive payments for five years. Payments are conditioned on participants fulfilling their land use commitments and compliance is monitored annually using remote sensing imagery and field verification.
Multiple Treatment Arms Evaluated?

Implementing Agency

Name of Organization:
Comision Nacional Forestal (CONAFOR), Mexico
Type of Organization:
Public Sector, e.g. Government Agency or Ministry

Program Funder

Name of Organization:
Comision Nacional Forestal (CONAFOR), Mexico
Type of Organization:
Public Sector, e.g. Government Agency or Ministry

Intervention Timing

Intervention or Program Started at time of Registration?
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Evaluation Method

Evaluation Method Overview

Primary (or First) Evaluation Method:
Regression discontinuity
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Method Details

Details of Evaluation Approach:
The basic identification strategy for both all three analyses for this IE is regression discontinuity (RD). This approach takes advantage of the continuous eligibility score applied by CONAFOR in its selection process. The basic idea in the context that we are analyzing is that communities below the cutoff score for selection (the threshold score) can serve as a valid counterfactual for communities who were accepted. The key assumptions required for an RD is that individual communities cannot precisely manipulate their place in relation to the cutoff and that no key determinants of the outcomes also change discontinuously at the cutoff (Lee and Lemieux, 2010). If these assumptions hold, the RD estimator can be considered to be “as if random.” Therefore, we can interpret cross-sectional differences in outcomes across the discontinuity threshold as we would a randomized experiment. This allows us to interpret differences in current deforestation, social, and socio-economic across beneficiaries and non-beneficiaries as causal impacts of program participation.
Outcomes (Endpoints):
ENVIRONMENTAL 1. (Primary) Parcel level deforestation per year, 2011-2015: yearly change in forest cover measured using interpreted satellite data 2011-2015 for enrolled and rejected parcels from the 2011-2014 cohorts 2. (Secondary) Parcel level deforestation per year, 2011-2015: yearly change in forest cover for enrolled and rejected parcels from earlier cohorts (2006-2010) 3. (Secondary) Within-property spillovers of deforestation: yearly change in forest cover measured using interpreted satellite data 2011-2015 for parcels that are outside of enrolled areas but inside of communities that applied for the program. SOCIAL 4. (Primary) Social Capital 2016 measured at the community and household level: data on assemblies, trust in members of the community / other communities, participation of community members in unpaid community work, community institutions, internal conflicts and with other communities 5. (Primary) Asset and housing indices 2016: indices composed of common assets and housing characteristics, collected at the household level 6. (Primary) WTA values: Contingent valuation questions about willingness to accept contracts with different payment levels
Unit of Analysis:
Environmental analysis: parcel; Social capital analysis: community; Socio-economic analysis: household
1. If it is true that PSA increases the relative profitability of conservation to landholders, then the program will generate avoided deforestation or degradation. 2. If PSA works by increasing the relative profitability of forests, its effect will end when payments end so deforestation rates will increase upon expiry of payments. 3. Payments to avoid deforestation in one location may lead to deforestation in other locations. On the other hand, stronger collective institutions, changes in social norms, or investment in alternate income generation activities may lead to reduced deforestation. Based on ongoing work, we hypothesize that negative spillovers are likely to be present but small in magnitude. 4. We hypothesize that PSA participation strengthens social institutions through incentives to perform forestry activities that require collaboration. 5. We hypothesize that PSA participation has positive socio-economic impacts on participants. 6. We hypothesize that the differentiated payments system will correlate with stated valuation of willingness to accept by participants.
Unit of Intervention or Assignment:
communities (in Spanish: comunidades or ejidos)
Number of Clusters in Sample:
Number of Individuals in Sample:
The social capital and socio economic analyses will use survey data collected from 864 communities and 8640 households. The environmental analysis will use satellite data for 16,563 properties
Size of Treatment, Control, or Comparison Subsamples:
Environmental analysis (total in the program): Treatment - 3,887 , Control - 12,676 properties; Social analysis (total expected for the RDD estimation): Treatment - 484, Control - 380 communities

Supplementary Files

Analysis Plan:
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Outcomes Data

Environmental: processed satellite imagery will be collected through the MADMEX (Monitoring Activity Data for the Mexican REDD+ program) system developed by CONAFOR and other governmental agencies in Mexico Social capital : a community leader survey will administered to the village representative and will include questions related to social capital. Socio-economic: a household survey will be administered to a random sample of households in each community
Data Already Collected?
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Treatment Assignment Data

Participation or Assignment Information:
We will use CONAFOR administrative data on beneficiaries and applicants.
Data Obtained by the Study Researchers?
Data Previously Used?
Data Access:
Restricted -- Access requires a formal approval process
Data Obtained by the Study Researchers?
Data Approval Process:
The research team is working very closely with CONAFOR, which has provided the administrative data required.
Approval Status:
Yes-obtained approval and have received the data

Data Analysis

Data Analysis Status:

Study Materials

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Registration Category

Registration Category:
Prospective, Category 1: Data for measuring impacts have not been collected

Completion Overview

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Preliminary Report:
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Data Availability

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Other Materials

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Description of Changes:

Study Stopped