Household’s Allocation of Payment for Ecosystem Services in “La Antigua” Watershed,Veracruz,México

Abstract

Payment for ecosystem services (PES) is an environmental policy looking to improve ecosystem conservation and well-being. Assets have been used to evaluate socioeconomic outcomes of the program; however, the allocation of PES at a household level and its explaining variables have not been addressed. Thus, the aim of this article is to study the allocation of PES in nondurable and durable goods and the determinants of this household decision. Results from the La Antigua watershed located in Mexico indicate that the PES program is primarily used in durable goods, mainly on health, house infrastructure, agricultural inputs, and reforestation. Econometric models show that this allocation to one or several assets depends on the average age of the household head, on participation in a community organization, and on the average income. In contrast, government transfers are not significant. Based on this, policy recommendations are made related to the program’s socioeconomic outcomes and alignment with other conditional cash transfer.

Keywords

payment for ecosystem services assets conditional cash transfer Mexico environmental policy

Introduction

The Sustainable Development Goals encourage actions in all countries toward eradicating poverty, protecting the environment, and guaranteeing peace and prosperity (United Nations, 2015). Thus, public policies need to guide efforts to reach these goals. In many countries, payment for ecosystem services (PES) is a common policy instrument targeting environmental and human well-being outcomes. PES programs were conceptualized as economic instruments to reduce market failures related to natural resource conservation. Wunder (2015) defines PES as voluntary transactions between ecosystem service users and service providers, subject to agreed rules related to the management and generation of ecosystem services.

Initially, PES was conceptualized as a market-based approach; however, the real-world implementation of these programs has tended more toward a public or a hybrid line where a transaction between providers of the ecosystem service and the users involves several institutions, such as local governments and nongovernmental organizations (Muradian et al., 2013; Rodríguez-Robayo & Ávila Foucat, 2013, 2014; Wunder et al., 2018). In Mexico, where this study takes place, the PES program was initially implemented by the national government in a public approach (federal) due to the difficulties in marketing ecosystem services but also due to the opposition of neoliberal policies by landowners (McAfee & Shapiro, 2010). But in the last decade, Mexico has started matching funds, that is, a hybrid PES approach that can involve government, nongovernment, and private actors.

Matching funds are similar to the federal program in that they are also based on compensating ecosystem service suppliers conditioned on the providers maintaining ecosystem services through concrete natural resource management actions such as soil and forest conservation. Most of the time, this compensation is paid in cash (Costedoat et al., 2016) but at other times in kind. Conditionality is intended to increase the environmental outcomes that the program wants to reach, and often, land cover is used as an indirect measure of hydrological, biodiversity, or carbon ecosystem services targeted by the program (Alix-Garcia et al., 2012; Börner et al., 2017). Based on this conditionality on ecosystem services conservation (or land cover related to this service), PES programs are similar in their conceptual design with conditional cash transfer (CCT) programs created to alleviate poverty in the Global South (Persson & Alpiza, 2013).

In many countries of the Global South, conserved ecosystems are situated in the most vulnerable and poor regions, which has led to interest in using PES to also improve rural livelihoods. While there is debate over whether PES can or should be used to address poverty concerns (Börner et al., 2017; Pagiola et al., 2005), many PES programs, including the national program in Mexico, explicitly target participants that are located in marginalized regions (Muradian et al., 2013; Sims et al., 2014). PES programs can contribute to human well-being outcomes through the generation of ecosystem services, encouraging sustainable livelihood strategies, and through direct payments that are invested at the household or community level. Thus, PES programs can lead to tangible and intangible changes in human well-being (Jones et al., 2019) and thus can contribute to the Sustainable Development Goals.

Where PES programs explicitly mention the alleviation of poverty as a goal, these outcomes are generally not well defined. That is, the programs do not indicate which dimension of poverty, such as health, education, or social cohesion, the program aims to improve (OECD, 2017). When social outcomes have been considered in the evaluation of PES programs, they are often assessed in terms of the contribution of PES to income, followed by aggregated indicators of human development or wealth (e.g., Alix-Garcia et al., 2015; Blundo-Canto et al., 2018). Only very recently have the effects of PES programs on broader human well-being outcomes been analyzed, such as land tenure security (Jones et al., 2020), institutional arrangements (Muradian et al., 2010), and social capital (Alix-García et al., 2018; Rodriguez-Robayo et al., 2016). Although systematic reviews have shown that PES has more positive effects than negative ones on well-being, there is also consensus that these outcomes are rather limited, given the stated goals of PES programs (Blundo-Canto et al., 2018; Liu & Kontoleon, 2018).

The goal of this study is to assess the socioeconomic outcomes of PES in Mexico, in terms of the income and allocation of the payment to capital assets in order to have a deeper understanding of the potential impacts on long-term human well-being. The rural development literature has shifted focus from income indicators of poverty to multidimensional indicators showing the relevance of a household’s access to capacities, recognizing that different capital assets are relevant for long-term poverty eradication (OECD, 2017). Assets comprise different types of capital endowments that are both tangible and intangible and reflect the capabilities and skills necessary to survive and prosper in rural areas (Bebbington, 1999; Chambers & Conway, 1992; Ellis, 2000). Capitals are divided into social, human, financial, physical, and natural (Bebbington, 1999; Chambers & Conway, 1992; Ellis, 2000). Social capital refers to the relationships, trust, and cohesion that a household has with the community, with neighborhoods, or with other social networks. Human capital refers to education, training, and health. Financial capital is the cash flow (savings) a household has access to. Physical capital is composed of the infrastructure for agricultural production and house characteristics, and natural capital is the possession of land and the use of natural resources (Avila-Foucat & Rodríguez-Robayo, 2018).

The advantage of this asset approach is that nonmonetary attributes of well-being can be included. Income as a measure of poverty presupposes that markets exist for all attributes and has been deemed an insufficient measure especially in rural areas in developing countries (Bérenger et al., 2013). Capitals are considered durable goods since they are intended to yield utility over time. They can be reinvested in economic activities to generate income, livelihood diversification, or increase intangible benefits to improve well-being. In contrast, nondurable goods (NDGs) are those goods consumed over a short period of time providing immediate benefits, such as food. The more financially constrained the household, the less likely they may be to invest in capitals since they will give priority to the fulfillment of immediate needs such as food. While both durable and NDGs are important to well-being, PES programs aimed at long-term poverty alleviation emphasize increasing durable capital assets (Arriagada et al., 2015). Thus, understanding whether PES programs are able to influence investments in durable goods provides some evidence on whether they are achieving their long-term socioeconomic goals.

Some PES studies have used the capital asset approach to assess the PES program’s human well-being outcomes (e.g., Bremer et al., 2014; Hejnowicz et al., 2014). However, these studies find that financial capital is the most studied capital asset compared to others. Hejnowicz et al. (2014) show that two-thirds of the PES literature they analyzed consider financial capital variables such as income or poverty, as opposed to social or natural capital outcomes. They also find that while many studies demonstrate that PES payment is sufficient to meet immediate household needs (i.e., NDGs), payment is generally not sufficient for asset investment (Hejnowicz et al., 2014).

Rural regions around the world tend to diversify, and in Mexico, diversification is also present (Fierros-González et al., 2020). This economic process makes households invest in several capitals. Wealthier households tend to divserify more as this is a stronger economic position, especially in rural areas. Related to PES programs, Arriagada et al. (2015) show no effect of PES payments in Costa Rica on diversifying land use activities to off-farm or on-farm input use.

In this study, we add to the literature focused on the effects of PES programs on human well-being using a capital asset approach at the household level for PES programs in the La Antigua watershed in Mexico. As indicated above, most PES programs find that payments are allocated only to NDGs. While this is a necessary investment for many households, to improve long-term poverty alleviation and sustainable development, PES programs aim to influence spending on durable goods. Thus, our first research question is around whether households invest in any durable goods versus NDGs. It is important to understand what factors explain this allocation and particularly how preexisting asset conditions, which indicate preexisting poverty levels, influence households’ allocation decision. Second, we want to understand the diversification of investments in capital assets, given the importance of diversification in rural economies. Thus, we consider how many capital assets a household invests in with their PES payments. The findings in this study provide empirical information for improving the design of PES programs in terms of socioeconomic aspects, particularly regarding the complementarity with other public programs.

Study Area

The study presents evidence from two hydrological PES programs located in the Antigua watershed in Veracruz State, Mexico. These PES programs are situated in two subbasins, Gavilanes (4132 hectares) and Pixquiac (10,727 hectares) (Figure 1). The vegetation in the region is predominantly tropical cloud forest with pine-oak forest dominating at the highest elevations. Agriculture expansion has converted about 65% of the original forest for cattle pasture, shade-grown and intensive coffee, as well as for subsistence crops such as maize and beans (Asbjornsen et al., 2017) and also potatoes for commercial purposes. PES participants are located along different land use types and provide the hydrological service, assuring downstream drinking water supply for the urban areas of Xalapa (∼450,000 persons) and Coatepec (∼80,000 persons).

Figure 1.

Location of the Pixquiac and Gavilanes subbasins in the Antigua watershed in Veracruz State, Mexico (Jones et al., 2019).

The federal government implemented Mexico’s national PES program in 2003 as an environmental policy that compensates landowners for forest conservation (Rodríguez-Robayo & Ávila Foucat, 2013). This program is administered by the Mexican National Forestry Commission (CONAFOR). Starting in 2008, the national government started a second program that is not based solely on federal contributions but is a local, matching fund, where local users such as private companies or local governments provide part of the funding. In most cases, such as in La Antigua, nongovernmental organizations directly participate in the institutional arrangement for implementing the program. Although the intention is to move toward a user-financed PES instrument, the role of the federal government is still very important in this new arrangement as they provide 50% of the matching funds. In the Pixquiac and Gavilanes subbasins, a local, matching PES program is now in operation, with funds from CONAFOR and from the local water utility operator that provides funding from their budget or from consumer water bills. Each of these PES programs targets forest conservation and pays landowners $1100 MXN pesos/year/ha in 2015 (∼US$60/year/ha). Both matching programs have conditionality rules focused on conservation of the forest through a management program indicating monitoring and forest actions, such as fire prevention, reforestation, soil retention, avoiding agriculture expansion, and promoting sustainable activities (Fuentes & Paré, 2018; Nava-López et al., 2018). The total number of hectares involved in the program is 14,407 hectares (3680 in Gavilanes and 10,727 in Pixquiac). In this PES program, the compensation is through cash and also through technical assistance and training aimed at incentivizing other sustainable economic activities. The land tenure in the region can be private or common property. This last category includes “ejidos” and “comunidades” where landowners share part of the land as common property and the decisions of its use are taken in an assembly. This form of land tenure also has individual parcels; in “comunidades,” landowners have a tittle of possession of the land during the time they use it, and in “ejidos,” the parcel is owned by the landowner.

When land tenure is common property, or collective, PES can be distributed within communities in different forms. The money can be given to the representative of the community or can be distributed directly to the land owner. In general, the distribution mechanisms are discussed at community meetings. In the La Antigua watershed, both distribution mechanisms exist. However, in order to assess the PES allocation at a household scale, this article focuses on the households receiving the payment directly; that is, the sample is composed by private landowners and “ejidatarios” or “comuneros” both receiving directly an amount of cash from the PES program. The total amount received by households is the one declared in the Results section. Since the sample was at a household level, the total amount per locality was not recorded neither the exact amount retained by the assembly.

Methods

Data Collection

An in-person household survey was randomly implemented in 2016 to common property and private landowners that are enrolled in the PES program. The survey took an average of 50 minutes to complete, was pretested in the field, and implemented by trained enumerators. There was no compensation for answering the questionnaire. We surveyed a total of 146 participants of the PES programs, representing an estimated level of error below 10%. Only households answering how they spent the payment were included in this analysis, leaving us with a total of 113 observations.

The survey included five sections for describing each household capital: social, human, financial, physical, and natural. Also, a specific section was designed to ask about the distribution method of PES payment within the community (in order to identify the households receiving the payment), the amount of money each beneficiary receives from the PES program, and the allocation of this money for household expenses (open-ended response question), which were later classified into daily expenses, such as food (NDGs) or capital assets (durable goods). Therefore, this study is based on the respondent’s stated PES use and depends on the person’s recall; most household surveys on asset investments are based on declared consumptions or expenses. The allocation of PES payments to capital assets was classified as presented in Table 1 based on the analysis of the open-ended question and the definitions of each capital. For example, if PES money was used for reforestation purposes, it was classified as natural capital.

Table 1.

The Classification of Durable Goods (Capital Assets) and Nondurable Goods in which Households Allocated Payment for Ecosystem Service Income. These were used to Construct the Dependent Variables.

	Definition	Description
Natural capital	Refers to the investments on reforestation	Purchase of plants to reforest
		Purchase of compost for reforestation plants
		Cleaning for reforestation
Human capital	Related to the investments that maintain or enforce villagers’ health and knowledge	Expenses related to health (medical appointments and medicines)
Human capital		Expenses related to skills and knowledge (school supplies and school transport)
Social capital	Associated with investments to preserve traditions and rules and solve conflicts	Family celebrations
		Solving land disputes
		Assisting assemblies
Physical capital	Refers to the investments in households’ goods and appliances	Building materials
		Improvements to the family home
		Household appliances
Financial capital	Related to the investments that increase the annual monetary income of households	Agricultural and livestock inputs
		Payment of temporary external farm labor
		Payment of credits
		Savings
		Nonagricultural activity
Nondurable goods	Refers to the use of daily expenses	Food
Nondurable goods	Refers to the use of daily expenses	Personal care items

Data Analysis

Following the classification of the allocation of PES payments, two regression models were run to first explain the choice of investment in nondurable versus any durable goods and second to understand the choice of diversifying investments across assets. In both regressions, the role of preexisting assets in these decisions was studied. For the first outcome of interest, a logistic model was used to explain the binary decision (dependent variable) to invest in NDGs (0) versus in any form of durable goods or capital assets (1). Thus, if a household used PES payment for any durable goods found in Table 1, it was assigned a “1,” and if it only used payment for NDGs, it was labeled as “0.” We report marginal effects from the logistic model and the pseudo R² and the percentage correctly classified as indicators of model fit.

For the second outcome of interest, a multivariate linear regression was used that explains the household decision to invest in a specific number of durable goods (dependent variable) or capital assets. This discrete variable varies from 0 (NDGs only) to 5 (investment in natural, human, social, physical, and financial capitals). We estimated this regression using ordinary least squares regression and report the coefficients and R². Before estimating the multilinear regression, multicollinearity, heteroscedasticity tests, and omitted variable tests were conducted. Both regression models were estimated by using Stata.

For both regression models, the independent variables used are presented in Table 2. These independent variables were constructed using the capital assets framework as a measure of the households’ preexisting conditions, and it is important to point out that the variables in Table 1 (dependent variables) and Table 2 (independent variables) are completely different in order to avoid statistical problems. Our hypothesis was that the household’s preexisting assets, which indicate preexisting wealth, determine their livelihood strategies and, in the case of this study, the decision to allocate PES income to NDGs or to durable capital assets in order to have medium or long-term benefits such as starting other economic activities.

Table 2.

Independent Variables: Household Capital Assets.

Capital Assets	Variable	Description
Natural	Land area	Land area of the household (hectares)
Natural	Inclined land	Household has inclined land (yes or no)
Human	Household size	Number of household members
Human	Age	Average age of two household heads (years)
Social	Organization	Household head participates in community organization (yes or no)
Social	Land tenure	Household’s land tenure is collective (yes or no)
Physical	Washing machine	Household had a washing machine in 2010 (yes or no)
Physical	Gas stove	Household had a gas stove in 2010 (yes or no)
Financial	Income generated	Average annual household income generated in 2015 (without transfers and payment for ecosystem service) (in US$2015)
Financial	Transfers	Number of transfers received by the household

Under natural capital (Table 2), land area is considered as an independent variable since, if the household’s land is larger, they increase the probability of having forest and the proportion of hectares that can be enrolled in the PES program. Larger land area might indicate larger cash payment from the PES program and be correlated with overall higher wealth for the household. This would most likely lead to more investment in durable assets. The amount of steep land that a household manages is considered an important explanatory variable under natural capital as well because the household has fewer agricultural possibilities on steep lands, which might negatively affect the decision to invest PES payment in durable capital assets, versus short-term needs such as food.

For human capital, household size might imply that the household has the labor force that positively influences productive activities (Fierros & Avila-Foucat, 2017), but could also imply more food consumption, meaning that PES would be used for NDGs. Bhandari (2013), for example, finds that family labor benefits agricultural activities in India; however, Fierros and Avila-Foucat (2017) have shown that this variable is significant for any livelihood strategy. In the case of Mexico, the empirical evidence suggests that the average age of households, as well as education and work experience, is relevant for the selection of economic activities (Yúnez-Naude & Meléndez-Martínez, 2007), as well as for economic diversification (Avila-Foucat & Rodríguez-Robayo, 2018; Fierros & Avila-Foucat, 2017; Mora-Rivera & Cerón-Monroy, 2015). Average age of household heads is expected to negatively influence asset investment since older people might be less interested in enhancing long-term economic activities and prioritize immediate food expenses, especially if they have difficulties in cultivating crops. In contrast, younger average household heads might be more interested in diversifying capital assets.

If the household participates in a community organization such as a community committee or in a productive cooperative, this might influence the household decision to invest PES in assets to increase productivity derived from this organization. In addition, it has been shown that households in Mexico involved in community cooperatives are not necessarily the poorest, meaning that they are more likely to have their food needs covered (Avila-Foucat & Rodríguez-Robayo, 2018; Yúnez-Naude & Meléndez-Martínez, 2007). Land tenure, measured as whether the household is a private or collective landowner, might influence how the PES payment is allocated due to social norms or pressures in communal land tenure arrangements.

Two independent variables were included under physical capital that were expected to be correlated with the decision on how to invest PES payments. Owning a washing machine has recently been included in labor studies (Blau et al., 2014) and is strongly associated with allowing women to save time and engage in other productive activities. Similarly, household use of gas stoves has been found to allow more time for economic activities since the family will spend less time on wood collection. Thus, both variables are expected to influence positively the allocation of PES to durable capital assets since they indicate greater wealth and labor.

Last, annual income and the number of government transfers (CCT programs outside of the PES program) describe the overall income distribution of households and are expected to be positively related to household investment in other capitals.

Results

Descriptive statistics of Household Capital Assets

For the households in our survey, the average area of land available per household is 9.4 hectares (much larger than 2.5 hectares, the average in Mexico (ENA, 2014)) and 5.8 of those are forested, but 70% indicated that their land is steep (Appendix 1). The sociodemographic conditions show that the average age of households is 58 years and education is minimum. In the area, 86% pertain to “ejidos” or “comunidades,” and a large majority participates in assemblies or community organization. The main economic activity is agriculture, and summing the sources of income for a household results in an average yearly income per household of US$3697.50 (2015 dollars).

Regarding government transfers, households receive one or two CCTs outside the PES program. The most frequent programs are Prospera (57%), a social program for education and health, Procampo (37%), a program for agriculture, and a Seniors’ Program (29%) that provides pensions. The annual government transfers represent on average US$418.10 per household, which is 11% of the annual income generated by households. Regarding PES payment, it represents 8% of the total household income, which is relatively high compared to the sum of other transfers mentioned above. This is despite the low amount per hectare (US$60/ha).

PES allocation in the Household Economy

On average, households receive US$277 (US$2015) per year for participating in PES programs. The allocation of PES payments only to NDGs occurs in 27% of the households surveyed (Figure 2). However, 12% of households allocate payments to NDGs and to one capital asset. Thus, the sum of the total households investing in NDGs (only NDG and NDG +assets) is 39%. The largest number of households, 45%, invested PES payments in one durable good or capital asset, but no NDGs. In contrast, only 16% of the households surveyed invested payments in more than one capital asset.

Figure 2.

Allocation of household’s payment for ecosystem service income in nondurable goods and in one or many capital assets.

It is interesting to note that when the household decides to invest in capital assets, the human capital category is the most important. When looking specifically within each capital, we observe that 30% of households invested in health, followed by improvements to the family home (14%), agricultural and livestock inputs (12%), and plants for reforestation (12%) (Figure 3). In sum, households spend PES income mainly on human capital assets (32%), followed by financial capital (30%) and then physical capital (28%) (Figure 3).

Figure 3.

Payment for ecosystem service income expenditure by capital assets and nondurable goods.

To explain the allocation of PES shown in Figures 2 and 3, we turn to the results of our binomial logit model and multivariate linear model presented in Table 3. Model 1 presents the determinants for investing PES payment in durable goods versus NDGs. The binary model shows that the average age of the two household heads and average income (without transfers included) are positive and statistically significant variables. Thus, these variables positively influence the decision by the household to invest in capital assets instead of NDGs. In contrast, having a washing machine and land tenure are statistically significant but negative and have the largest marginal effect. It is interesting to note that the number of transfers is not significant but has a negative sign. That is, CCT does not influence the decision to invest in capital assets using PES payments, but if it eventually does, a household that has more cash transfers is less susceptible to invest in capitals.

Table 3.

Determinants of PES Allocation.

Assets	Household assets	M1	M2
		Household decision to invest in capital assets (binomial logit)	Number of capitals in which households invest PES income (multiple lineal)
		Marginal effect (SE)	Coefficient (Robust SE)
Natural	Land area	−0.002 (0.004)	−0.006 (0.005)
Natural	Inclined land	0.122 (0.101)	0.082 (0.168)
Human	Household size	0.018 (0.021)	0.001 (0.034)
Human	Age	0.006^∗ (0.003)	0.008^∗ (0.005)
Social	Organization	0.109 (0.094)	0.360^∗^∗ (0.158)
Social	Land tenure	−0.161^∗ (0.095)	−0.484^∗^∗ (0.227)
Physical	Washing machine	−0.247^∗ (0.138)	−0.387^∗^∗ (0.162)
Physical	Gas stove	−0.004 (0.107)	−0.261^∗ (0.153)
Financial	Income generated	0.098^∗^∗ (0.042)	0.212^∗^∗ (0.090)
Financial	Transfers	−0.049 (0.058)	0.047 (0.097)
N		113	113
R² adjusted		—	0.120
Pseudo R²		0.111	—
Correctly classified		75.2%	—

Note. Levels of significance: ^∗ 90%, ^∗^∗ 95%, and ^∗^∗^∗ 99%. PES = Payment for ecosystem service.

Model 2 explains the households’ decision to invest in capitals as a discrete variable ranging from 0 to 5 and shows that the average age of the two household heads, being part of a community organization, and average income (without transfers) are positive and statistically significant variables. Similar to the binary model, owning a washing machine is statistically significant and negative, as well as owning a gas stove. Additionally, collective land tenure is statistically significant and negative in this model, suggesting that households in collective land tenure invest in fewer number of capitals than private households. Again, transfer is not a significant variable but has a positive sign in this model. Natural capital variables are not significant in either of the two models, suggesting that those variables do not directly influence the household decision of how to invest the PES payments. Similarly, household size does not explain asset allocation in either model.

Discussion

PES Allocation Determinants

We found that households allocate PES primarily to capital assets compared to NDGs, which varies somewhat from the findings in other PES studies (Arriagada et al., 2015). While the contribution of payments to food security is important to alleviate poverty conditions, this study uses a development perspective emphasizing the role of capital assets investments for the medium and long-term improvement of rural capacities to reach Sustainable Developmetn Goals. In this sense, our results show that households are most likely to use PES revenues for health (30%), house infrastructure (14%), farm inputs, and reforestation (12%). Few studies have also shown evidence that PES is sometimes used for agriculture, home improvements, and medical services (Alix-García et al., 2015; Tacconi et al., 2013).

It is interesting to note that the allocation of PES payments is equally distributed between farm inputs and reforestation (12% for both), indicating that the program is at the same time affecting on-farm economic productivity and environmental benefits. This is opposed to Hejnowicz et al. (2014) and Arriagada et al. (2015), who indicate that PES is sufficient to meet basic needs but does not allow investments in farm-based productive activities. However, if the program is used for on-farm activities such as intensive agriculture (instead of shade coffee, for example), PES could be incentivizing nonsustainable agricultural activities and may be leading to leakage effects.

Investment in reforestation might be due to the conditional rules of the program or because participants have changed their attitude toward conservation. Jones et al. (2019) showed that many landowners in this region expressed interest in participating in the PES program because of their environmental values. Similarly, Bottazzi et al. (2018) showed that intrinsic and pro-environmental motivations have been linked to participation in PES programs. This is an interesting outcome in that it suggests that additional ecosystem service outcomes, over and above those from conserving forest, are being generated and could indicate crowding-in effects.

With respect to the allocation of PES to health and farm inputs, this indicates that the program is used as a complement to other Mexican CCT programs such as Progresa and Procampo. Particularly in Latin America, a large proportion of social policies focus on CCT to alleviate market failures that lead to poverty by providing incentives for pro-social behavior such as visiting health clinics and attending schools (Fiszbein et al., 2009). This is in the case of the Progresa program in Mexico (Kronebusch & Damon, 2019), and this program has had positive impacts in reducing short-term poverty (Ham & Michelson, 2018). However, when looking at the determinants of PES allocation in this study, government transfers were not statistically significant. It may be that the households receiving CCT use PES as a complement and that the households not receiving other cash transfers use PES as a substitute. Izquierdo-Tort (2020) has pointed out that PES and cash transfers are allocated differently but complement each other. PES payments in this study area are equivalent to 8% of the household’s total income, and other CCTs represent 11% of the total income. This confirms Bremer et al.’s (2014) finding that even if PES is a small amount in terms of opportunity costs and welfare, it is an important economic support for households in poverty conditions.

Determinants of PES allocation presented in the results show that in both models, the average age of heads of households and income are positively related to the use of the payment for investing in durable assets. Regarding the average age of the households, we expected a negative influence on capital investment based on the evidence of rural studies that older households diversify less into productive activities. However, a large part of PES is used for health expenses, which might explain our model results. Older people have in general more health problems and thus may be more likely to invest PES payments in health than younger households. There is also evidence that older households are more likely to enroll in PES programs (Jones et al., 2019). Thus, asset investment and use is clearly linked to the household livelihood strategy. Also, in this study area, food consumption is often partially covered by the government cash transfer program, Progresa, that provides $580pesos a month (US$36/month) to older households, which might explain their willingness to allocate PES payments into durable goods.

The relationship between income and allocation to capital assets is consistent with the literature, and studies show that the poorest households are not the ones that diversify livelihood activities (De Janvry & Sadoulet, 2011). Therefore, a minimum of financial capital is required for diversifying (Davis et al., 2010), and starting new activities often requires investment in different capitals. This sharpens the poverty traps in which more vulnerable households are trapped and at the same time indicates a possible effect of inequality. Previous studies have warned about inequalities in PES distribution (Fisher et al., 2013) and the effect on reinforcing actual power relationships (Pascual et al., 2014). PES inequalities depends in part at a national scale on the eligibility criteria of the program and at a local scale on the community’s agreements regarding the distribution of the program (Narloch et al., 2013).

Collective land tenure in this study negatively influences the investment in assets, meaning that households that are part of community tenure prioritize NDGs or only one asset. On the other hand, we find a positive effect of participation in community organizations, such as community committees or productive organizations, on investment in durable assets. This could be because PES is often being used for reforestation, which is generally done at a community level. The relationship between household allocation and the community is important, especially in many communal land tenure systems, and as mentioned by Hayes et al. (2019), determines the outcomes of PES programs. That is, social capital, as measured by individual participation in community organizations, is influencing PES allocation to assets that should cause a positive effect on household welfare. Our findings show that land tenure and participation in community organizations have a different effect on the program outcomes. This is an interesting element that needs to be discussed and further researched.

Finally, households investing in capital assets were less likely to have a washing machine and a gas stove. We hypothesized, based on the literature, that owning washing machines and gas stoves would indicate more time and labor, especially for women, to invest in productive activities. We do not have a good explanation for why, in the case of PES, having these home appliances would be correlated with investing in NDGs, like food. Typically, having a washing machine reflects a certain level of income in the study area, and these households were not expected to be the ones that need to invest in NDGs.

Policy Recommendations

Socioeconomic outcomes presented in previous sections provide elements to discuss aspects of the PES design such as the program objective, the target population, and the payment conditions including conditionality, as well as complementarity with other CCT programs.

The ability of PES to achieve win–win outcomes has been questioned (Muradian et al., 2013; Wunder, 2008), and we argue in this study that this is partly because the socioeconomic outcomes are not precisely defined. In our study in La Antigua, Mexico, our results show that the PES programs have the potential to contribute to food security as well as increase investments in durable assets from which health, reforestation, and farm inputs were prioritized. Local PES program design and implementation are context dependent, and thus the aim of the program needs to reflect the needs of the region in terms of socioeconomic priorities.

Many countries, including Mexico, have taken as a core goal the development of capacities to alleviate poverty, and capital assets have been adopted as an important measure of the PES program’s socioeconomic outcomes (Almeida-Leñero et al., 2017; Arriagada et al., 2015; Bremer et al., 2014; Hejnowicz et al., 2014). As mentioned by Phadera et al. (2019), households are resilient if the capacity to avoid poverty remains high over time, and maintaining household capitals (including natural capital and ecosystem services) is one of the important elements of rural development. Also, household resilience is determined by the connectivity and diversity of capital assets (Avila-Foucat & Martínez, 2018). Thus, PES programs need to define depending on the context if food security is a priority versus increasing durable goods. Additionally, PES programs should decide if and how they want to be aligned with other CCT programs or oriented to promote sustainable farm-based activities. In La Antigua, sustainable resource management activities are allowed in the program rules; however, apart from farm activities, households did not invest their PES payments on these outcomes. In contrast, households are investing in reforestation which is clearly a positive aspect for the region. We believe that clarifying the aims of the program in terms of socioeconomic outcomes as part of a participatory process with different actors involved in the institutional arrangement of the PES programs would provide more clear outcomes and possibilities to optimize the effectiveness of the program. This is a very important aspect for the Mexican case study since the program has evolved from a very coercive program focused on maintaining forest cover to a sustainable forest management approach (Sims et al., 2014), and PES in our study area includes land covered by forest mixed with shade coffee (Nava-López et al., 2018). Defining clearly the aims of the program determines the conditionality of the program.

Socioeconomic conditionality is especially relevant when the payments meet opportunity and transaction costs (Liu & Kontoleon, 2018); when the amount is too low, conditionality is less likely to be effective. As mentioned previously, conditionality would depend on the program’s local context and specific aims for the region. However, Rodríguez et al. (2011) show that in most cases, the amount transferred through CCT programs and PES to households is similar, highlighting the potential of PES for poverty alleviation outcomes such as those found under CCT programs. Generally, cash transfers have been found to benefit human capital (education and health), financial capital (productive activities), and social capital (capacity building or networks) (Asfaw et al., 2012). In Pixquiac and Gavilanes subbasins, PES is used as a complement or substitute to other cash transfer programs. Long-term poverty alleviation requires a strategy for optimizing cash transfers in a coherent policy framework that links multiple local incentives and programs. Relatedly, there has been little effort, or at least success, for PES programs in coordinating with cash transfer programs that may go against the environmental outcomes promoted by PES. This is the case in Mexico, where Procampo subsidies promoted the use of fertilizers in agricultural activities, or the Sembrando Vida actual program that might be increasing deforestation. These programas could be aligned to other environmental ones supporting sustainable agriculture, agroforestry, silvopastoral production, and biodiversity protection, generating policy coherence.

Specifying socioeconomic goals of PES programs includes indicating the population that needs to be targeted. Using a poverty index is often not enough to ensure avoiding redistribution inequalities or crowding out (Ezzine-de Blas et al., 2018). For instance, if the PES program wants to promote sustainable activities, information about the preexisting asset conditions is needed. However, no national statistics use the five capital asset approach in the case of Mexico, but at a local scale, data collection is possible in order to better define the target population.

Despite PES payments representing 8% of household income, most households felt the payment was too low to compensate them for their opportunity costs (Jones et al., 2019). Households also expressed interest in noncash forms of assistance as part of the PES program. Bremer et al. (2014) argue that a direct payment in cash allows the household to decide how to invest it. However, in-kind payments may provide more opportunities for sustainable livelihood outcomes and are less likely to lead to crowding out nonfinancial motivations. Results from our analysis do not allow us to define which is the best compensation mechanism, but more discussion with local actors needs to occur when defining the program goals and considering potential impacts on human well-being.

Conclusion

Households in Pixquiac and Gavilanes subbasins allocate their PES program incentives primarily on durable goods compared to NDGs. Specifically, households spend PES income mainly on health and house infrastructure, followed by agricultural inputs and reforestation. These results show that PES can be used as a complement to other rural development and poverty alleviation programs, especially those focused on health. In addition, PES incentives used for reforestation suggest a positive environmental effect of the program, over and above forest conservation outcomes. However, investments in on-farm inputs raise the question of whether PES investments are being made in intensive agriculture, which could lead to some leakage effects.

Overall, our results show the relevance of preexisting capital assets for explaining PES allocation in durable goods. The models show that household allocation of PES payments depends on the average age of the household heads (human capital), on participating in a community organization (social capital), and on the average income (financial capital). We found that other government transfers were not significant in explaining PES allocation to assets, showing that PES payments can be used as a complement to other CCT programs or as a substitute for the families not receiving any transfers.

Based on our findings, the policy recommendations are to more clearly define specific socioeconomic aims of the PES programs that reflect the local context and needs. The latter could occur through better defining the target population, making payment conditional on socioeconomic outcomes, and ensuring complementarity of PES with other CCT programs operating in a region. PES programs have the potential to generate socioeconomic outcomes associated with food security and capital investments that promote sustainable activity livelihoods, but as of yet, have not reached their full potential. PES will always be part of a mix of policies in the livelihood portfolio of households; thus, in order to increase socioeconomic outcomes associated with these environmental policies, policy coherence and coordination is needed.

Footnotes

Acknowledgments

This research would not have been possible without the collaboration and cooperation of staff at FIDECOAGUA and SENDAS and the households that graciously participated in this study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Science Foundation under grant no.1313804 Dynamics of Coupled Natural-Human Systems (CNH), Consejo Nacional de Ciencia y Tecnología (CONACYT) Postgraduate grants program.

ORCID iD

Veronique Sophie Avila-Foucat

Appendix 1 Author Biographies

Veronique S. Avila-Foucat, Professor in the Economics Research Institute at the National Autonomous University of Mexico (UNAM) and PhD in Environmental Economics and Ecosystem Management in York University, United Kingdom. Her research has been focused on studying the diversification of rural households, social-ecological resilience, and environmental policies.

Karla J. Rodriguez Robayo, PhD in Natural Resource Economics and Sustainable Development from the Universidad Nacional Autónoma de México. Her research has been focused on the analysis of economic instruments and different alternatives for natural resource preservation, seeking an equitable distribution of costs and benefits from preservation policies in Colombia and Mexico.

Kelly W. Jones, Associate Professor in the Department of Human Dimensions of Natural Resources at Colorado State University (CSU) and PhD and MA from the University of Wisconsin-Madison. Her research has been focused on payments for ecosystem services, impact evaluation, land tenure and property rights, and drivers of land cover change.

Erin C. Pischke, Research Analyst in the Ecosystem Workforce Program at the University of Oregon and Doctorate in Michigan Technological University’s environmental and energy policy program. Her research has been focused on renewable energy policy, bioenergy policy, transdisciplinary research, and rural development policy in Mexico.

David Torrez, Doctor in Economics graduated from the Division of Postgraduate Studies of the Faculty of Economics of the National Autonomous University of Mexico (DEPFE-UNAM). His research has been focused on using the theoretical and methodological principles of ecological and environmental economics to analyze the sustainable use and management of natural recourses.

Jacob Salcone, Technical Consultant in The Economics of Ecosystems and Biodiversity (TEEB) and MS in Agricultural and Resource Economics from Colorado State University. His research has been focused on impact analysis, international development, cost-benefit analysis of Ag, and natural resources.

Theresa Selfa, Associate Professor, Environmental Studies at SUNY-ESF and PhD from College of Agriculture and Life Sciences, Development Sociology from Cornell University. Her research has been focused on social dimensions of food–energy–water systems, politics of agrifood systems and agricultural biotechnology, environmental governance, sustainability certification, and labeling and US and Latin America

Kathleen E. Halvorsen, Associate Vice President for Research Development and Professor of Natural Resource Policy at Michigan Technological University and PhD in Forest Resource Management from the University of Washington. Her research has been focused on water, land use, public health, climate change, biodiversity, and energy issues.

References

Alix-Garcia

J. M.

Shapiro

E. N.

Sims

K. R. E.

(2012). Forest conservation and slippage: Evidence from Mexico’s national payments for ecosystem services program. Land Economics, 88, 613-638.

Alix-García

J. M.

Sims

K. R. E.

Orozco-Olvera

V. H.

Costica

L. E.

Fernández Medina

J. D.

Romo Monroy

(2018). Payments for environmental services supported social capital while increasing land management. Proceedings of the National Academy of Sciences, 115(27): 7016-7021.

Alix-Garcia

J. M.

Sims

K. R. E.

Yañez-Pagans

(2015). Only one tree from each seed? Environmental effectiveness and poverty alleviation in Mexico’s payments for ecosystem services program. American Economic Journal: Economic Policy, 7, 1-40. doi:10.1257/pol.20130139

Almeida-leñero

Revollo-fernández

Caro-Borrero

Ruiz-Mallén

Corbera

Mazari-Hiriart

Figueroa

(2017). Not the same for everyone: Community views of Mexico’s payment for environmental services programmes. Environmental Conservation. 44, 201-211. doi:10.1017/S0376892916000564

Arriagada

R. A.

Sills

E. O.

Ferraro

P. J.

Pattanayak

S. K.

(2015). Do payments pay off? Evidence from participation in Costa Rica’s PES program. Plos One, 10(7), 1-17.

Asbjornsen

Manson

R. H.

Scullion

J. J.

Holwerda

Munoz-Villers

L. E.

AlvaradoBarrientos

M. S.

Geissert

Dawson

T. E.

McDonnell

J. J.

Bruijnzeel

L. A.

(2017). Interactions between payments for hydrolgocial services, landowner decisions, and ecohydrological consequences: Synergies and disconnection in the cloud forest zone of central Veracruz, Mexico. Ecology and Society, 22(2), 25.

Asfaw

Daidone

Davis

Dewbre

Romeo

Djebbari

Winters

(2012). Analytical framework for evaluating the productive impact of cash transfer programmes on household behaviour. FAO. www.fao.org

Avila-Foucat

V. S.

Martínez

A. F.

(2018). Households’ resilience to hurricanes in coastal communities of Oaxaca, Mexico. Society & Natural Resources, 31, 807-821. doi:10.1080/08941920.2018.1443236

Avila-Foucat

V. S.

Rodríguez-Robayo

K. J.

(2018). Determinants of livelihood diversification: The case wildlife tourism in four coastal communities in Oaxaca, Mexico. Tourism Management, 69, 223-231.

10.

Bebbington

(1999). Capitals and capabilities: A framework for analyzing peasant viability, rural livelihoods and poverty. World Development, 27, 2021-2044.

11.

Bérenger

Deutsch

Silber

(2013). Durable goods, access to services and the derivation of an asset index: Comparing two methodologies and three countries. Economic Modelling, 35, 881-891.

12.

Bhandari

P. B.

(2013). Rural livelihood change? Household capital, community resources and livelihood transition. Journal of Rural Studies, 32, 126-136.

13.

Blau

Ferber,

Winkler

(2014). The economics of women, men and work (7th ed.). Pearson.

14.

Blundo-Canto

Bax

Quintero

Cruz-Garcia

G. S.

Groeneveld

R. A.

Perez-Marulanda

(2018). The different dimensions of livelihood impacts of payments for environmental services (PES) schemes: A systematic review. Ecological Economics, 149, 160-183. doi:10.1016/j.ecolecon.2018.03.011

15.

Börner

Baylis

Corbera

Ezzine-de-Blas

Honey-Rosés

Persson

U. M.

Wunder

(2017). The effectiveness of payments for environmental services. World Development, 96, 359-374. doi:10.1016/j.worlddev.2017.03.020

16.

Bottazzi

Wiik

Crespo

Jones

J. P. G.

(2018). Payment for environmental “self-service”: Exploring the links between farmers’ motivation and additionality in a conservation incentive programme in the Bolivian Andes. Ecological Economics, 150, 11-23. doi:10.1016/j.ecolecon.2018.03.032

17.

Bremer

L. L.

Farley

K. A.

Lopez-Carr

Romero

(2014). Conservation and livelihood outcomes of payment for ecosystem services in the Ecuadorian Andes: What is the potential for “win-win”? Ecosystem Services, 8, 148-165. doi:10.1016/j.ecoser.2014.03.007

18.

Chambers

Conway

G.R.

(1992). Sustainable rural livelihoods: Practical concepts for the 21st century. Institute of Development Studies.

19.

Costedoat

Koetse

Corbera

Ezzine-de-Blas

(2016). Cash only? Unveiling preferences for a PES contract through a choice experiment in Chiapas, Mexico. Land Use Policy, 58, 302-317. doi:10.1016/j.landusepol.2016.07.023

20.

Davis

Winters

Carletto

Covarrubias

Quiñones

E. J.

Zezza

Stamoulis

Azzarri

DiGiuseppe

(2010). A cross-country comparison of rural income generating activities. World Development, 38, 48-63. doi:10.1016/j.worlddev.2009.01.003

21.

de Janvry

Sadoulet

(2011). Subsistence farming as a safety net for food-price shocks. Development in Practice, 21, 472-480. doi:10.1080/09614524.2011.561292

22.

Ellis

(2000). The determinants of rural livelihood diversification in developing countries. Journal of Agricultural Economics, 51, 289-302. doi:10.1111/j.1477-9552.2000.tb01229.x

23.

Encuesta Nacional Agropecuaria (ENA) . (2014). [WWW Document], n.d. URL https://www.inegi.org.mx/programas/ena/2014/ (accessed 4 2 2020).

24.

Ezzine-de-Blas

Corbera

Lapeyre

(2018). Payments for environmental services and motivation crowding: Towards a conceptual framework. Ecological Economics. 156, 434-443. doi:10.1016/j.ecolecon.2018.07.026

25.

Fierros-González

Mora-Rivera

Avila-Foucat

V.S.

(2020). Vulnerability, family assets, and income-generating strategies of households in rural Mexico, Community Development, 51, 667-684. doi:10.1080/15575330.2020.1825976

26.

Fierros

Ávila-Foucat

V. S.

(2017). Medios De Vida Sustentables y Contexto De Vulnerabilidad De Los Hogares Rurales De México. Problemas del Desarrollo, 48, 107-131. doi:10.1016/j.rpd.2017.11.006

27.

Fisher

J. A.

Patenaude

Meir

Nightingale

A. J.

Rounsevell

M. D. A.

Williams

Woodhouse

I. H.

(2013). Strengthening conceptual foundations: Analysing frameworks for ecosystem services and poverty alleviation research. Global Environmental Change, 23, 1098-1111. doi:10.1016/j.gloenvcha.2013.04.002

28.

Fiszbein

Schady

Ferreira

Grosh

Kelecher

Olinto

Skoufias

(2009). Conditional cash transfers- reducing present and future poverty- A world bank policy research report. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/2597 License: CC BY 3.0 IGO.

29.

Fuentes

Paré

(2018). El comitpe de cuenca del Río Pixquiac:ensayos para 191 la creación de una plataforma social de cogestión y su instrumento de financiamiento. In Al filo del agua: Co-gestión de la subcuenca del Río Pixquiac, México Coord. Luisa Paré y Patricia Gerez, 191-218.

30.

Ham

Michelson

H. C.

(2018). Does the form of delivering incentives in conditional cash transfers matter over a decade later? Journal of Development Economics. 134, 96-108. doi:10.1016/j.jdeveco.2018.05.007

31.

Hayes

Grillos

Bremer

L. L.

Murtinho

Shapiro

(2019). Collective PES: More than the sum of individual incentives. Environmental Science & Policy, 102, 1-8. doi:10.1016/j.envsci.2019.09.010

32.

Hejnowicz

A. P.

Raffaelli

D. G.

Rudd

M. A.

White

P. C. L.

(2014). Evaluating the outcomes of payments for ecosystem services programmes using a capital asset framework. Ecosystem Services, 9, 83-97. doi:10.1016/j.ecoser.2014.05.001

33.

Izquierdo-Tort

(2020). Payments for ecosystem services and conditional cash transfers in a policy mix: Microlevel interactions in Selva Lacandona, Mexico. Environmental Policy and Governance, 30, 29-45. doi:10.1002/eet.1876

34.

Jones

K. W.

Avila Foucat

Pischke

E. C.

Salcone

Torrez

Selfa

Halvorsen

K. E.

(2019). Exploring the connections between participation in and benefits from payments for hydrological services programs in Veracruz State, Mexico. Ecosystem Services, 35, 32-42. doi:10.1016/j.ecoser.2018.11.004

35.

Jones

K. W.

Etchart

Holland

M. B.

Naughton-Treves

Arriagada

(2020). The impact of paying for forest conservation on perceived tenure security in Ecuador. Conservation Letters, 13, . doi:10.1111/conl.12710.

36.

Kronebusch

Damon

(2019). The impact of conditional cash transfers on nutrition outcomes: Experimental evidence from Mexico. Economics and Human Biology, 33, 169-180. doi:10.1016/j.ehb.2019.01.008

37.

Liu

Kontoleon

(2018). Meta-analysis of livelihood impacts of payments for environmental services programmes in developing countries. Ecological Economics, 149, 48-61. doi:10.1016/j.ecolecon.2018.02.008

38.

McAfee

Shapiro

E. N.

(2010). Payments for ecosystem services in Mexico: Nature, neoliberalism, social movements, and the state. Annals of the Association of American Geographers, 100(3), 579-599.

39.

Mora Rivera

J. J.

Cerón Monroy

(2015). Diversificación De Ingresos En El Sector Rural Y Su Impacto En La Eficiencia: Evidencia Para México. Cuadernos de Desarrollo Rural, 12, 57. doi:10.11144/javeriana.cdr12-76.disr

40.

Muradian

Arsel

Pellegrini

Adaman

Aguilar

Agarwal

Corbera

Ezzine de Blas

Farley

Froger

Garcia-Frapolli

Gómez-Baggethun

Gowdy

Kosoy

Le Coq

J. F.

Leroy

May

Méral

Mibielli

Urama

(2013). Payments for ecosystem services and the fatal attraction of win-win solutions. Conservation Letters, 6, 274-279. doi:10.1111/j.1755-263X.2012.00309.x

41.

Muradian

Corbera

Pascual

Kosoy

May

P. H.

(2010). Reconciling theory and practice: An alternative conceptual framework for understanding payments for environmental services. Ecological Economics, 69, 1202-1208. doi:10.1016/j.ecolecon.2009.11.006

42.

Narloch

Pascual

Drucker

A. G.

(2013). How to achieve fairness in payments for ecosystem services? Insights from agrobiodiversity conservation auctions. Land Use Policy, 35, 107-118. doi:10.1016/j.landusepol.2013.05.002

43.

Nava-López

Shelfa

Pishcke

Torres

Ávila-Foucat

V. S.

(2018). Decentralizing payments for ecosystem services programs on coupled human and natural systems in Mexico. Society and Natural Resources, 31(12), 1389–1399.

44.

OECD . (2017). Well-being indicators. doi:10.1787/eco_surveys-isl-2017-graph1-

45.

Pagiola,

Arcenas

Platais

(2005). Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date from Latin America. World Development, 33, 237-253. doi:10.1016/j.worlddev.2004.07.011

46.

Pascual

Phelps

Garmendia

Brown

Corbera

Martin

Gomez-Baggethun

Muradian

(2014). Social equity matters in payments for ecosystem services. Bioscience, 64, 1027-1036. doi:10.1093/biosci/biu146

47.

Persson Martin

Alpízar

(2013). Conditional cash transfers and payments for environmental services-a conceptual framework for explaining and judging differences in outcomes. World Development, 43, 124-137. doi:10.1016/j.worlddev.2012.10.006

48.

Phadera

Michelson

Winter-Nelson

Goldsmith

(2019). Do asset transfers build household resilience? Journal of Development Economics, 138, 205-227. doi:10.1016/j.jdeveco.2019.01.003

49.

Rodríguez-Robayo

K. J.

Ávila Foucat

V. S.

(2013). Instrumentos económicos voluntarios para la conservación: una mirada a su surgimiento y evolución en México. Sociedad y Economía, 25, 75-106.

50.

Rodríguez-Robayo

K.J.

Avila-Foucat

V.S.

(2014). Instrumentos de política pública para la conservación: su nacimiento y evolución en Colombia. Perfiles Latinoamericanos, 22, 127-158.

51.

Rodríguez

L. C.

Pascual

Muradian

Pazmino

Whitten

(2011). Towards a unified scheme for environmental and social protection: Learning from PES and CCT experiences in developing countries. Ecological Economics, 70, 2163-2174. doi:10.1016/j.ecolecon.2011.06.019

52.

Rodriguez-Robayo

Avila-Foucat

V. S.

Maldonado

(2016). Indigenous communities’ perception regarding payments for environmental services program in Oaxaca Mexico. Ecosystem services, 17, 163-171.

53.

Sims

K. R. E.

Alix-Garcia

J. M.

Shapiro-Garza

Fine

L. R.

Radeloff

V. C.

Aronson

Castillo

Ramirez-Reyes

Yañez-pagans

(2014). Improving environmental and social targeting through adaptive management in Mexico’s payments for hydrological services program. Conservation Biology, 28, 1151-1159. doi:10.1111/cobi.12318

54.

Tacconi

Mahanty

Suich

(2013). The livelihood impacts of payments for environmental services and implications for REDD+. Society & Natural Resources, 26, 733-744. doi:10.1080/08941920.2012.724151

55.

United Nations . 2015. Transforming our world: The 2030 agenda for sustainable development. Sustainable Development Knowledge Platform [WWW Document], n.d. URL https://sustainabledevelopment.un.org/post2015/transformingourworld (accessed 3 3 2020).

56.

Wunder

(2008). Payments for environmental services and the poor: Concepts and preliminary evidence. Environment and Development Economics, 13, 279-297. doi:10.1017/S1355770X08004282

57.

Wunder

(2015). Revisiting the concept of payments for environmental services. Ecological Economics, 117, 234-243.

58.

Wunder

Brouwer

Engel

Ezzine-De-Blas

Muradian

Pascual

Pinto

(2018). From principles to practice in paying for nature’s services. Nature Sustainability, 1, 145-150. doi:10.1038/s41893-018-0036-x

59.

Yúnez-Naude

Meléndez-Martínez,

Á.

(2007). Efectos de los activas familiares en la selección de actividades y en el ingreso de los hogares rurales de México. Investigación Economica, 66, 49-80.