1

The Economic Effects of Community Forest Management in the Maya Biosphere

Reserve

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Corinne Bocci

Graduate Program in Agricultural, Environmental & Developmental Economics

The Ohio State University

2019

Dissertation Committee

Brent Sohngen, Advisor

Daniela Miteva

Abdoul Sam

Frank Lupi

2

Copyrighted by

Corinne Bocci

2019

ii

Abstract

This dissertation examines the conservation and economic development effects of

community forest management in the Maya Biosphere Reserve (MBR). Maintaining the

world’s forest resources in developing countries has been a difficult, but necessary task

since conserving tropical forests is crucial for preserving biodiversity and sequestering

carbon. However, many communities located near the forest depend on extracting forest

resources as a source of income and many governments in developing countries cannot

devote enough resources to enforce forest protection efforts. This creates an

overexploitation problem since many of these forests are common-pool resources that are

rivalrous and non-excludable because of the lack of enforcement of the ill-defined

property rights.

To remedy this issue, some countries have provided communal property rights to

encourage sustainable resource use (Ostrom 1990; Schlager and Ostrom, 1992). The idea

is that households will work together and monitor each other to protect the area of land to

which they have property rights from over exploitation. In exchange, the group that

manages the area is given exclusive access to the forest resources and is able to earn a

sustainable source of income. However, for community-based forest management to

have a higher likelihood of being effective, households that are participating in the forest

management system can receive an incentive in addition to the forest being conserved.

iii

The goal of this dissertation is to assess whether the economic development and

conservation benefits of the community forest concessions in the Maya Biosphere

Reserve are effective and whether receiving payments for strict conservation would be

preferred by households. Chapter 1 is an introduction into community forestry and the

background of the Maya Biosphere Reserve. In Chapter 2, I examine the impact of

concession membership on annual household income to determine if the benefits of

participating in community forest management vary by community. Chapter 3 assesses

the private and social benefits of the forest concessions in the Maya Biosphere reserve

and examines whether the combined conservation and development benefits of

implementing the concessions outweigh the costs. In Chapter 4, I use results from a

discrete choice experiment I conducted in Maya Biosphere Reserve communities to

determine whether households would be willing to receive payments for conserving the

forest and sequestering carbon at the expense of sustainable timber harvesting.

ii

Acknowledgements

This work would not have been possible without the support of several

individuals. First, I would like to thank my advisor, Brent Sohngen, for being an

outstanding mentor who has not only provided funding for this life-changing opportunity,

but has given me continual advice, encouragement, and support for this project. Second, I

would like to thank my committee member Daniela Miteva for helping me develop my

skills as a researcher and providing me with research opportunities and supportive advice.

I would also like to thank my committee members Abdoul Sam and Frank Lupi for

serving on my committee and providing valuable feedback on my dissertation.

During my fieldwork in Guatemala, Bayron Milian was instrumental in making

the survey collection process a success by providing me with advice, resources, and

contacts. Additionally, I would like to thank Alexis Scharrer, Sarah Grossman, and

Shelby Stults for their help and support during the data collection process. I would also

like to thank my enumerators Patricia Hor, Gabriel Oliva, Paula Suntecún, Gilmer López,

and Jennefer Salas for their hard work and long hours administering the Guatemalan

household surveys. Finally, my friends and family have also given me endless support

and encouragement throughout my time as a doctoral student. I would especially like to

thank Shicong Xu, Jian Chen, John Dougherty, Beth Robison Botkins, Katy Bender,

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Tony Gallenstein, and Khushbu Mishra who have not only given me useful feedback on

this work, but have also been amazing friends.

iv

Vita

2010................................................................Nordonia High School

2014................................................................B.S.B.A. Business Economics, Youngstown

State University

2016................................................................M.S. Agricultural, Environmental, and

Development Economics, The Ohio State

University

2016 to present...............................................Graduate Teaching/Research Associate,

Agricultural, Environmental, and

Development Economics, The Ohio State

University

Publications

Bocci, C., Fortmann, L., Sohngen, B., & Milian, B. “The impact of community forest

concessions on income: an analysis of communities in the Maya Biosphere Reserve.”

World Development, 107, 10-21

Fields of Study

Major Field: Agricultural, Environmental, and Development Economics

v

Table of Contents

Abstract ............................................................................................................................... ii

Acknowledgements ............................................................................................................. ii

Vita ..................................................................................................................................... iv

List of Tables .................................................................................................................... vii

List of Figures .................................................................................................................. viii

Chapter 1. Community Forestry in the Maya Biosphere Reserve ...................................... 1

1.1 Community Forestry ................................................................................................. 1

1.2 Maya Biosphere Reserve Background ...................................................................... 5

Chapter 2. The Impact of Forest Concessions on Income ............................................... 10

2.1 Introduction ............................................................................................................. 10

2.2 Model of Household Labor Allocation ................................................................... 14

2.3 Data ......................................................................................................................... 22

2.4 Empirical Methods .................................................................................................. 28

2.5 Results ..................................................................................................................... 31

2.6 Conclusion .............................................................................................................. 38

Chapter 3: Assessing the private and social benefits of forest concessions in the Maya

Biosphere Reserve ............................................................................................................ 42

3.1 Introduction ............................................................................................................. 42

3.2 Data ......................................................................................................................... 47

3.2.1 Household Survey Data Collection .................................................................. 47

3.2.2 Biophysical Dara .............................................................................................. 52

3.3 Theory ..................................................................................................................... 53

3.4 Estimation ............................................................................................................... 55

3.4.1 Effect of concession membership on income .................................................. 55

3.4.2 Effect of concession management on conservation outcomes ......................... 61

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3.5 Results ..................................................................................................................... 65

3.5.1 Income effect ................................................................................................... 65

3.5.2 Conservation effect .......................................................................................... 69

3.5.3 Conservation and income trade-offs ................................................................ 72

3.5.4 Concession valuation ....................................................................................... 74

3.6 Conclusion .............................................................................................................. 76

Chapter 4: Timber or Carbon? Evaluating forest conservation strategies through a

discrete choice experiment ................................................................................................ 80

4.1 Introduction ............................................................................................................. 80

4.2 Methods and Data ................................................................................................... 84

4.2.1 Maya Biosphere Reserve Household Characteristics ...................................... 84

4.3.2 The Choice Experiment Instrument ................................................................. 89

4.3 Model Specification ................................................................................................ 92

4.4 Results and Discussion ........................................................................................... 95

4.5 Conclusion ............................................................................................................ 104

Bibliography ................................................................................................................... 108

Appendix A.1: Chapter 2 ................................................................................................ 122

Appendix A.2: Chapter 2 ................................................................................................ 125

Appendix B.1: Chapter 3 ................................................................................................ 126

Appendix B.2: Chapter 3 ................................................................................................ 131

Appendix C.1: Chapter 4 ................................................................................................ 133

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List of Tables

Table 1. Community Concessions in the Maya Biosphere Reserve ................................... 9

Table 2. Member and Non-member Sample Statistics ..................................................... 23

Table 3. Recently inhabited and Nonresident Member and Non-Member Sample

Statistics ............................................................................................................................ 25

Table 4. Income activities by concession classification ................................................... 27

Table 5. Regression results for effect on income .............................................................. 34

Table 6. ATE/ATT/DR Results for effect on income ....................................................... 37

Table 7. Income and wage-earning Activities .................................................................. 47

Table 8. Concession members and nonmember characteristics by community type ....... 50

Table 9. Variable Descriptions for Income Analysis ........................................................ 60

Table 10. Variable descriptions for conservation analysis ............................................... 64

Table 11. Two-stage least squares results for the effect of concession membership on

income ............................................................................................................................... 67

Table 12. Effect of concession management on deforestation ......................................... 70

Table 13. Effect of concession management on CO2 sequestered on lost forest .............. 71

Table 14. Cumulative value of land under concession management from 2012 to 2017 . 75

Table 15. Maya Biosphere Reserve Household Characteristics ....................................... 86

Table 16. Likert Scale questions on attitudes towards various environmental and

concession related issues in the MBR (1=strongly disagree; 5=strongly agree) .............. 87

Table 17. Choice experiment levels and attributes ........................................................... 90

Table 18. Mixed logit results for contract attributes ......................................................... 97

Table 19. Willingness to accept estimates (U.S. dollars) ............................................... 100

Table 20 Most and least important contract attributes .................................................... 103

Table 21. Reasons why only status quo was chosen ....................................................... 104

Table 22. Logit model results for likelihood of being a concession member ................. 125

Table 23. 2SLS first stage results for instrument on concession membership ............... 126

Table 24. Falsification test results for instrument ........................................................... 127

Table 25. Logistic regression results for likelihood of being a concession member ...... 128

Table 26. Matched ordinary-least squares regression results for the effect of concession

membership on income ................................................................................................... 129

Table 27. Panel results for effect of concession membership on income ....................... 130

Table 28. Logistic regression results for likelihood of concession placement ............... 131

Table 29. CO2 values adjusted for specific carbon sequestration values ...................... 132

viii

List of Figures

Figure 1. Maya Biosphere Reserve ..................................................................................... 8

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Chapter 1. Community Forestry in the Maya Biosphere Reserve

1.1 Community Forestry

Many tropical forests are located in developing regions where local households

depend on forest resources or the land on which forest resources exist for their

livelihoods. Developing regions also may not have the strong governance that is

necessary to protect large areas of tropical forests from being overexploited by

households. Forests are then susceptible to open access concerns, where over-extraction

occurs to the point where land rents converge to zero, the forest no longer sequesters

carbon and provide provisions for biodiversity, and low-income households cannot

benefit from the resource. (Gordon, 1954; Scott, 1955).

Some developing countries have tried to resolve this issue by giving property

rights over forestland to local communities. The idea behind devolving land use rights to

communities is to encourage sustainable resource use and conservation (Ostrom, 1990;

Schlager & Ostrom, 1992). Typically, the property rights come with stipulations that the

households protect the forest from deforestation and degradation. However, for

households to be willing to participate in forest conservation efforts in exchange for land

use rights, they must have an incentive to abide by the restrictions. In the case of

community forestry in the MBR and in other developing countries, the incentive for

households to continue protecting the forest occurs when they receive income from

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sustainable resource extraction. There is evidence that community-managed forest

concessions have succeeded in decreasing deforestation (Primack et al, 1998; Kumar

2002; Nittler & Tschinkel, 2005; Agrawal & Chhatre, 2006; Bray et al, 2008; García-

Amado et al, 2012; Blackman, 2015; Fortmann et al, 2017). However, whether

community forestry provides enough incentive for households (i.e. increased livelihoods)

to continue to participate in conservation efforts is an underexplored issue.

The goal of this dissertation is to assess the benefits and costs of community

forest management in the context of the MBR in the Petén department in northern

Guatemala. In addition, I examine the conservation and development objectives of

community forestry, and I assess whether the existing incentives can sustain the forest

management system. I contribute to the existing literature by assessing whether the

combined conservation and development benefits of forest concessions in the MBR

outweigh the costs as well as determine whether households would prefer to receive

payments for carbon sequestration instead of sustainable timber harvesting.

This dissertation is structured as follows. Section 1.2 contains background

information about the Maya Biosphere Reserve as well as the buffer zone. It describes

how the reserve was created, the different areas of the MBR, and how households are

granted access to a forest concession.

The second chapter assesses the impact of being a member of a community forest

concession on income. In this chapter, I examine whether being a concession member

increases annual household income and whether the income effect varies by community.

The dataset used contains information on household income and various demographic

3

characteristics from concession member and nonmember households in 2012. To find the

impact of concession membership on annual income, I first use matching to preprocess

the sample. Then, I use an ordinary least squares regression (OLS) and compare the

results to a doubly robust, average treatment effect, and average treatment effect on the

treated estimators. The results show that, overall, being a concession member leads to

increased annual household income, however the magnitude of the results varies by

community. For example, for households in recently-inhabited communities, which are

comprised of households with backgrounds in agriculture and cattle ranching, being a

concession member has no statistically significant effect on annual household income

earnings. However, in nonresident communities, which are comprised of households that

frequently use forestry as a supplemental source of income, the impact of being a

concession member on annual household income is positive and significant.

Chapter 3 examines the private and social benefits of the community forest

concessions and whether there are trade-offs between conservation and development in

the MBR. I then use this information to develop methods to determine if the benefits of

implementing community forest concessions in the MBR outweigh the costs. This

chapter begins by assessing whether households that participate in a concession earn

more annual income than similar households that do not participate in a concession and

whether the effect is stable over time. I use a two-stage least squares instrumental

variable approach (2SLS) and data from household surveys of MBR concession members

and nonmembers in 2012 and 2017 to determine if concession members earn higher

annual incomes than similar nonmembers. The results show that, on average, being a

4

concession member leads to higher annual household incomes and the effect of

concession membership on income increased from 2012 to 2017.

To quantify the environmental benefits, I first determine whether concessions

decrease deforestation. I use satellite imagery data and a fixed effects panel estimator to

determine if forest concessions decrease deforestation from 2012 to 2017 and find that

the forest concessions decrease deforestation. I then use the deforestation results to find

the impact of concession membership on carbon storage and use the social cost of carbon

to determine the monetary value of the additional carbon stored by the concessions.

Finally, I compare the conservation and income benefits to an estimate of the costs of

implementing the concessions and find that, on average; the benefits of the community

forest concessions outweigh the costs. In addition, in two of the three concession

communities, concessions both reduce deforestation and increase livelihoods, which

implies that there are complementarities between conservation and development.

Chapter 4 examines the willingness to accept of households in communities in the

MBR to conserve forests that sequester carbon through strict conservation efforts instead

of through sustainable timber harvesting. This chapter has two objectives. One objective

is to determine which attributes of a Payments for Ecosystem Services contract (PES) are

most valued by the households that would be required to abide by the contract. The

second objective is to determine whether forest-dwelling households prefer to engage in

sustainable timber harvesting or receive payments for carbon sequestration through strict

conservation and restricted access to the forest. I assess the households’ preferences

through a discrete choice experiment conducted in communities in the MBR and find that

5

households on average prefer to receive payments for carbon storage instead of

sustainable timber harvesting, but most prefer to continue to use forest resources for non-

timber forest product harvesting and ecotourism.

1.2 Maya Biosphere Reserve Background

The MBR was created in 1990 and covers about 2 million hectares of the Petén

department, which is about one-fifth the size of Guatemala. The reserve provides habitat

for numerous important species, such as Macaw (Ara ararauna) and Jaguars (Panthera

onca), and they contain significant cultural resources as the region is the ancestral center

of Maya civilization. The MBR is divided into three zones: the core zone, buffer zone,

and multiple-use zone. The core zone is 36% of the reserve and consists of national

parks and biotopes. It is generally reserved only for low impact tourism and scientific

investigation and receives strict protection. The buffer zone is 24% of the MBR and

forms a “buffer” around the southern border of the MBR. It was created to divert land-

use change pressure away from the core zone. The multiple-use zone is 40% of the

MBR, but unlike the core zone, it is not strictly protected. Within the multiple-use zone,

sustainable timber harvesting is permitted by forest concessions. The forest concessions

in this region were developed in the late 1990s to provide property rights to local groups

who would use the forest for sustainable (Forest Stewardship Council certified) timber

harvesting, non-timber forest product harvesting, and ecotourism. In return the groups

work to ensure that deforestation does not occur within their boundaries. Forest

concessions were encouraged with financial support from USAID after the command-

and-control approach by the government failed to adequately protect the MBR. To apply

6

for a concession, households within communities organize themselves into concession

member groups and apply for a concession through the National Council for Protected

Areas, or CONAP. To be granted a concession, community organizations need to

demonstrate that they can manage the forest resources sustainably. The concession

members within the communities had to partner with a non-governmental organization of

their choice that helped them develop a sustainable forest management plan and obtain

forest management certification from the Forest Stewardship Council (FSC) within three

years of being granted the concession. Upon approval by CONAP, the concession

members were granted exclusive, renewable land use rights to their forested area for 25

years (Radachowsky et al., 2012).

The other activities that are currently permitted within the concessions in the

MBR are ecotourism and non-timber forest product harvesting. These activities require a

separate certification from CONAP and the Forest Stewardship Council, but are generally

granted along with the sustainable timber harvesting rights. From 1994 to 2002, CONAP

granted twelve communities and two companies forest concessions. However, since

2009, three of these concessions have been cancelled or suspended because they did not

abide by FSC standards (Radachowsky et al, 2012).

In the MBR context, communities that manage the forest concessions fall into

three distinct classifications: nonresident, recently-inhabited, and long-inhabited.

Households in nonresident concession communities reside outside of the multiple-use

zone (MUZ) boundaries in larger towns and cities. Many have jobs outside of forestry

and agriculture and use forest concessions as a supplemental source of income. Recently-

7

inhabited households typically have backgrounds in agriculture and cattle ranching and

moved into the MUZ communities around the time the MBR was established. Long-

inhabited households have lived within the MUZ for multiple generations. Households

within these communities have historically depended on harvesting timber and non-

timber forest products for their livelihoods. There are also industrial concessions, which

are managed by private companies, but still need to abide by the restrictions on timber

harvesting set by the Forest Stewardship Council (Radachowsky et al., 2012; Fortmann et

al., 2017). Figure 1 shows a map of the Maya Biosphere Reserve and the location of

nonresident, recently-inhabited, long-inhabited, and industrial concessions. Table 1

shows information about the established and canceled concessions.

8

Figure 1. Maya Biosphere Reserve

Table 4 highlights the differences in income-earning activities of the forest

concession communities. The main income-earning activity in long-inhabited

communities is forestry while in recently-inhabited concessions, agricultural activities

such as cattle ranching and farming, are major income-earning activities. In nonresident

communities, the number of workers and the amount of income earned from working in

businesses or professional activities comprises a larger share of the average household

income than in long-inhabited or recently-inhabited communities.

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Table 1. Community Concessions in the Maya Biosphere Reserve

Concession

Classification

Management

Unit Organization Name

Size

(ha)

Year

Formed

No. of

Members

Long-inhabited

Carmelita Cooperativa

Carmelita 53,797 1997 174

Uaxactún

Sociedad Civil

Organización,

Manejo y

Conservación

Uaxactún (OMYC)

83,558 2000 280

Recently-

inhabited

Cruce a la

Colorada

Asociación Forestal

Cruce a la Colorada 20,469 2001 65

Canceled/

suspended

San Miguel la

Palotada

Asociación Forestal

San Miguel La

Palotada

7,039 1994 39

La Pasadita

Asociación de

Productores La

Pasadita

18,817 1997 122

La Colorada Asociación Forestal

La Colorada 27,067 2001 48

Nonresident

Río Chanchich

Sociedad Civil

Impulsores

Suchitecos

12,117 1998 22

Chosquitán

Sociedad Civil

Laborantes del

Bosque

19,390 2000 74

San Andrés Asociación Forestal

Integral San Andrés 51,940 2000 170

Las Ventanas Sociedad Árbol

Verde 64,973 2001 309

La Unión

Sociedad Civil

Custodios de la

Selva (CUSTOSEL)

21,177 2002 85

Yaloch Sociedad Civil El

Esfuerzo 25,386 2002 39

Industrial

Paxbán GIBOR, S.A. 65,755 1999 N/A

La Gloria Baren Comercial

Ltda. 66,548 1999 N/A

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Chapter 2. The Impact of Forest Concessions on Income1

2.1 Introduction

Many of the world’s most valuable forests are located in developing countries

where individuals in local communities often depend on forests for their livelihood.

Although protection policies may exist, many governments do not, or cannot, devote

enough resources to enforce forest protection to prevent over-exploitation in the form of

unsustainable timber harvesting or conversion to agriculture. This issue is a common

property resource (CPR) overexploitation problem, where the forest resources are

rivalrous and nonexcludable, even when the government claims control. Because

resources ultimately are limited, land rents will be dissipated (Gordon, 1954; Besley,

1995; Galiani and Schargrodsky, 2010; Arágon et al, 2015). The solution in many cases

is to provide for property rights, either individually or in groups.

In the case of natural resource management, communal property rights have been

used widely and have encouraged sustainable resource use (Ostrom 1990; Schlager and

Ostrom, 1992). Where it is difficult to exert property rights over large areas of forests,

particularly in developing countries, many governments have opted for community-

managed common property resource systems. In these systems, local communities are

1 A version of this chapter was published in World Development in July 2018.

11

granted property rights to manage large forest estates in exchange for adopting

sustainable forest management practices. With the proper incentive (e.g., sustainable

livelihoods through avoided rent dissipation), the idea is that individuals in groups will

work together to protect the resource to ensure they can benefit from the resource in the

long run. There is evidence that community-based forest concession policies have

succeeded in decreasing deforestation (Primack et al, 1998; Kumar 2002; Nittler and

Tschinkel, 2005; Agrawl and Chhatre, 2006; Bray et al, 2008; García-Amado et al, 2012;

Blackman, 2015; Fortmann et al, 2017). However, other studies suggest that, although

community forest management may reduce forest degradation or increase tree density

and basal area, it does not always succeed in reducing deforestation (Bowler et al, 2012;

Samii et al, 2014; Pelletier et al, 2016).

Questions remain about whether community forest management can be sustained.

Sustainability requires an incentive, and while forest concession policies appear to have

had an impact on observable deforestation, it is not obvious that the rural populations

they serve have benefited with higher income. For example, Meilby et al. (2014) finds

mixed results with forest-dependent communities in Nepal. Primack et al. (1998) find that

the ejidos (communal pieces of farmland) in the Calakmul Biosphere Reserve decrease

deforestation and provide a sustainable source of income for community families. Kumar

(2002) finds that Joint Forest Management (JFM) systems in India have been successful

at reducing deforestation, but resulting benefits have only gone to the rural elite.

Adhikari et al, (2004) and Adhikari, (2005) report similar findings in Nepal, but also

12

show that socioeconomic characteristics of community groups affect individual

outcomes.

One reason for the mixed results may be free riders (Holmstrom, 1982). Although

free-riders may dissipate rents, Rotemberg (1994) suggests that efficient production and

cooperation can occur if altruism exists among team members. For example, when goods

are produced jointly by teams, an increase in a team member’s compensation can benefit

an individual if it has a positive effect on his/her own future earnings through increased

productivity of a team member. The theory outlined in Rotemberg (1994) depends on

workers knowing that their team members display similar patterns of trust and altruism.

If trust is not present, members will behave more selfishly and exert a suboptimal level of

effort if they are paid as a function of total team output alone (Holmstrom, 1982). In

some cases, however, teamwork and cooperation have been shown empirically to

increase productivity (Hamilton et al, 2003). Thus, with the right incentives and if

altruism is present, teams may increase productivity.

In this paper, we assess whether a communal property rights system in the Maya

Biosphere Reserve in Guatemala increases household income among rural households

involved in the community systems versus similar households that are not involved in

them. The systems we examine are community-based forest concessions, which provide

concession members with land-use rights to extract timber and non-timber forest products

sustainably on forestland within the reserve. For our analysis, we compare household

income levels among community concession members and neighboring non-members

using data from a household survey conducted in 2012. This region is unique because

13

there are three types of concessions that differ along socio-economic and cultural

backgrounds (Maas and Cabrera, 2008; Radachowsky et al, 2012). These differences

allow us to assess whether trust and cohesive group formation influence the effect of

concession membership on household income. Fortmann et al. (2017) show that these

differences do influence deforestation rates, but they do not investigate effects on

household welfare, although there may be other factors that contribute to the

effectiveness of being a concession member on household income,

The paper begins with a household labor allocation model where households in

the reserve allocate labor between agricultural activities and forest harvesting activities. If

forest harvesting activities are relatively more productive under the concession, this leads

to higher income levels for member households. This result relies on the relatively higher

forest product harvesting productivity of group membership. If groups are not more

productive than individuals, because, for instance, they lack trust and cohesiveness, then

group members will not necessarily have higher income.

Although we assume in the theory model that households are more productive at

forest harvesting as concession members, in the case of the Maya Biosphere Reserve,

being part of a team may be more of a burden on some households than others. For

example, if individuals who did not previously know each other came together simply to

obtain a land-use right through the formation of a concession, it may be hard for

individuals to trust each other. As a result, they will be more likely to dissolve the

contract and treat the concession land as open access. To test for this, we assess income

differentials empirically across individuals inside and out of concessions and compare

14

our results for different classes of concessions. There is also the possibility of selection

bias since unobservable factors about the households may lead to increases in income.

Also, being wealthier may lead to a higher likelihood of being a concession member

(reverse causality). To control for the possibility of selection bias, we employ matching

techniques.

The “Model of Optimal Household Labor Allocation” section of the paper

illustrates theoretically why joint production in the forest setting can lead to greater

income than individual production, and the “Results” section presents our regression

results. Our findings suggest that the effect of concession membership on annual income

is positive, but there is heterogeneity among communities in the Maya Biosphere

Reserve. Members of recently inhabited concessions, composed of many individuals

who have recently migrated to the area, do not gain income relative to non-concession

members, while the non-inhabited concessions, composed of individuals with stronger

ties to the region and those engaged largely in forestry, gain income. These results are

robust across several tests for selection effects.

2.2 Model of Household Labor Allocation

We start by assuming that households can be members of a concession in the

MBR, or work individually. Concessions in turn are given community land-use rights to

the land on which they reside, through which the group, not individuals, decides how to

manage the land. As long as benefits to the individuals in the groups are large enough,

this arrangement can remedy the problem of overexploitation described by Gordon

(1954), Scott (1955), and Hardin (1968). Each household earns wages and/or dividends

15

from forest production (including both timber and non-timber products), and in return

concession members must manage the forest in a way that avoids overexploitation and

allows the resource to regenerate for future use. Harvesting forest resources, however, is

not the only land-use option households in and around the MBR have for generating

income; they can also illegally clear forestland to use for agricultural production2. For

both concession members and non-members, there exists a tradeoff between labor

allocated to forest-related production and labor allocated to agricultural production.

We start by assuming that utility is gained from income and that income is based

on two activities: agricultural production and harvesting timber and non-timber forest

products. Other activities could be substituted for the agricultural production function

included in the model and the same results would apply although we focus on a tradeoff

between an activity that requires the conversion of forestland to pasture (agriculture) and

an activity meant to harvest resources sustainably and reduce deforestation (forestry). We

assume in this model that external factors such as corruption, illegal land speculation, and

organized crime that have been ongoing issues in the MBR and may affect household

labor decisions (Radachowsky et al, 2012), are equally as likely to affect each

concession.

Each household in our sample is classified as either a concession member or

non-member. Concession membership is voluntary, but membership is limited only to

those who applied for the sustainable land use rights. (Radachowsky et al, 2012). The

2 Although clearing the forest within in MBR is illegal, we assume that without being subject to a

protection regime, there is no protection for the forests and households can clear land for agriculture with

no consequences.

16

households maximize expected utility by choosing labor allocated to agriculture or

forestry, La and Lf, but income generated from each activity is dependent on membership

status. Concession members have communal rights to a section of forestland but must

manage the forest collectively. Profits earned from forest production, thus, depend on the

cooperation of other concession members (Radachowsky et al, 2012).

Households who are concession members maximize the following utility

function:

( ) ( ( ) ( , ) (L ))

. . L L

0

0

0

i j

i

j

i i i a i a f i f f a f

a f

a

f

f

U I U P A L P F L L w L

s t L

L

L

L

(1)

In (1), L represents the total labor force of household i. La and Lf represent the amount of

labor the household allocates to agriculture and forest production respectively. In this

model, the wage of agricultural and forest-related labor is the same per unit and is

represented by w. 𝐴𝑖(𝐿𝑎𝑖) is household i’s agricultural production function. Because

forest concessions are managed at the community level, each household’s forest resource

harvesting productivity is dependent on their individual production function, as well as

the labor and cooperation of other members. Concession household i’s production

function for timber and non-timber forest products is expressed as 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

), where 𝐿𝑓𝑗

is the amount of labor other member households (j) allocate to forest-related activities.

Both 𝐴𝑖(𝐿𝑎𝑖) and 𝐹𝑖 (𝐿𝑓𝑖

, 𝐿𝑓𝑗) have decreasing returns to scale. Pa and Pf are the market

price per unit of agriculture and forest output respectively. Because the community is

17

given land rights to the property and training on how to successfully manage the forest

from a partner forest management organization, individuals who are members of the team

are relatively more productive at harvesting forest resources than if they are not part of

the concession. Thus, the production function for concession membership is relatively

more productive for all households at each level of Lf, or 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) > 𝐹𝑖(𝐿𝑓𝑖) for all i

and j3. Given their different backgrounds, households in the Petén have different levels

of agricultural and forest harvesting productivity. For example, residents of long-

inhabited community concessions will likely be more productive at harvesting forest

products than households in a recently inhabited or nonresident concession because they

or their families have lived in the MBR for multiple generations and have depended on

the forest for their livelihood.

The Lagrangian the concession members maximize is shown by equation (2) and

the first order conditions with respect to La, L, 𝐿𝑓𝑖 and 𝐿𝑓𝑗

are shown by equation (3).

( ( ) ( ,L ) ( )) ( )i i j i i i im i a i a f i f f a f i a fU P A L P F L w L L L L L (2)

'

'

'

: * ( ( ) ) 0

: * (P F ( ,L ) ) 0

: * ( ( , )) 0

L : w 0

i

i i j

j i j

a a a i a

f f f i f f

f f f i f f

L MU P A L w

L MU L w

L MU P F L L

(3)

One result is that the market wage, w, is equal to the shadow price of labor, or ʎ.

Additionally, household i’s utility is maximized when the marginal utility gained from

3 We are assuming that there is perfect information among concession households so each concession

member knows how much labor and effort is contributed by all other concession members.

18

allocating one additional unit of labor to agriculture is equal to the marginal utility gained

from allocating one additional unit of labor to forest related activities. This is shown by

equation (4) below

( , )

( )

i j

i

f i f fa

f a i a

P F L L wMU

MU P A L w

(4)

As shown by equation (4), the amount of labor each household will allocate to forestry

and agricultural production to maximize their utility will depend on 𝐴𝑖(𝐿𝑎𝑖) and

𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) .

Concession policies aim to enhance welfare through the production function

𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) . If the concession is managed successfully, 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) will yield more

marginal income for every unit of labor allocated to forest production than the non-

member production function. This is due to the added benefit of management training and

land-use rights as well as the gains from cooperation (i.e. labor allocated to forest

production from all other member households in the community, or 𝐿𝑓𝑗 ). The forest

production function assumes households who are members comply with the rules

associated with the concession and are aware that violating these rules will result in

membership termination. The added benefit (if successful) from the production function

𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) is therefore dependent on household i and all other concession member

households abiding by the rules of the concession.

The effect of concession membership on income in the MBR ultimately depends

on the characteristics of the households in the concession communities. To assess the

19

implications of these characteristics on whether concession policies may be successful,

we examine different scenarios involving 𝐴𝑖(𝐿𝑎𝑖) and 𝐹𝑖 (𝐿𝑓𝑖

, 𝐿𝑓𝑗) , as well as the possible

income effects concession membership would have in each scenario. For simplicity, we

only examine the cases where the concession policy encourages 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) > 𝐹𝑖(𝐿𝑓𝑖) for

each unit of labor household i allocates to forest resource harvesting. Also, we assume

that the possible reallocation of labor does not have an impact on market prices for

agricultural products or forest resources. In what follows, we consider three cases based

on this model that are relevant for our analysis.

Case 1: 𝐴𝑖(𝐿𝑎𝑖) > 𝐹𝑖 (𝐿𝑓𝑖

, 𝐿𝑓𝑗) > 𝐹𝑖(𝐿𝑓𝑖

) for all levels of labor allocated to agricultural

production and forest resource harvesting

In this scenario household i is relatively more productive at agricultural

production than forest resource harvesting both with and without concession

membership. Although concession membership results in higher productivity of forest

labor, household i is still relatively more productive at agriculture than forest resource

harvesting. Even if household i were to become a member of a forest concession, they

would keep the labor allocation the same, or they may reallocate some labor to forest

harvesting. As a result, concession membership would lead to an increase in income for

household i, or would have no effect on income. We suspect that Case 1 could represent

nonresident concession members because they appear to use forestry primarily as a

supplement to their wage-earning jobs in larger towns and cities. It is not clear whether

they are relatively more productive at agriculture or forestry since these activities are not

20

typically their primary source of income. Nevertheless, the results suggest that

concession membership has a positive effect on income for nonresident concession

members, which implies that concession membership is increasing their household labor

productivity.

Case 2: 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) > 𝐹𝑖(𝐿𝑓𝑖) > 𝐴𝑖(𝐿𝑎𝑖

) for all levels of labor allocated to agricultural

production and forest resource harvesting

Case 2 represents a scenario where being a member of a community forest

concession leads to a higher level of productivity for each unit of labor allocated to

forestry for household i. Under this scenario, household i would likely reallocate labor

from agricultural production to forestry. Since there is added productivity from forest

resource harvesting and agricultural productivity for household i does not change under

the concession membership, the membership would raise income for household i.

We suspect that Case 2 applies best to long-inhabited concession members, but it

may also apply to nonresident concession members. As mentioned previously, long-

inhabited concession communities have traditionally depended on harvesting timber and

non-timber forest products for their livelihood. This implies that they were relatively

more productive at forest product harvesting than agriculture before the concession

policy was implemented. The concession would, therefore, increase the income level of

the member households since they can be more productive at forest resource harvesting.

Similarly, nonresident concession members in this case may re-allocate labor to forestry

if concession membership makes them more productive.

21

Case 3: 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) > 𝐴𝑖(𝐿𝑎𝑖) > 𝐹𝑖(𝐿𝑓𝑖

) for all levels of labor allocated to agricultural

production and forest resource harvesting

Case 3 shows that even if individuals are more productive individually at

agriculture than forestry, if team production is more productive than both, households

would reallocate labor to forest resource harvesting and concession membership would

have a positive effect on income. This case could apply to recently inhabited concessions

that successfully cooperative to increase forest productivity. Case 3 may also apply to

nonresident concessions because the concession may have improved these members’

forestry productivity function to a large enough extent that they are now relatively more

productive at forestry than agricultural production.

It is also, of course, possible that being a concession member in a recently

inhabited community has a negative impact on household income, in part because

individuals do not gain from joint production (e.g., as suggested by Maas and Cabrera,

2008 and Radachowsky et al, 2012). In this case, agricultural production is greater than

all forms of forestry production, i.e., 𝐴𝑖(𝐿𝑎𝑖) > 𝐹𝑖(𝐿𝑓𝑖

) > 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

). In this example,

individuals will devote more labor to the agricultural activity. Other examples, including

cases where 𝐹𝑖 (𝐿𝑓𝑖, 𝐿𝑓𝑗

) < 𝐹𝑖(𝐿𝑓𝑖), are shown in Appendix A.1.4

4 For all cases where 𝐹𝑖 (𝐿𝑓𝑖

, 𝐿𝑓𝑗) = 𝐹𝑖(𝐿𝑓𝑖

), concession membership would likely have no effect on

income or labor allocation.

22

2.3 Data

The data we use is from a household survey of members of communities in the

Maya Biosphere reserve (Fortmann, 2014). Our sample consists of 432 concession

members and non-members in 22 villages in the Petén. Each of the 22 villages surveyed

is either associated with a community forest concession or has residents who are

members of a particular forest concession. Membership in each concession ranges from

22 to more than 300 members (Table 1). To measure the impact of the concession

membership on household income, we took several steps to sample non-member and

member populations that are as similar as possible. The members included in our sample

were selected from a member list provided by the 12 community concession groups.5

Around 25 percent of the members were randomly selected to be participants in our

study. Because we could not obtain a list of the residents who were not members of the

concession associated with each town/village, we surveyed the closest neighbors of each

selected concession member household to obtain the non-members sample. This strategy

is based on the assumption that non-members who live in close proximity to concession

members have the same job opportunities and educational backgrounds and will be

similar with regards to other unobservable, community-based factors that may affect

income generating potential. Survey participants were asked to provide a variety of

income, demographic, and forest experience questions as well as their opinions and

5 Members of La Colorada had been removed from the concession at the time of the survey and could not

be interviewed.

23

perceptions about the community forest concessions. As a result of our sampling

strategy, concession members and non-members are similar across a number of

observable characteristics except for age, whether the household depends on the forest for

their livelihood, and if the respondent was born in the Petén (Table 2).

Table 2. Member and Non-member Sample Statistics

Members Non-members

Variable Obs Mean Std. Dev. Obs Mean Std. Dev.

Number of children

under 12 in household 219 1.489 1.447 211 1.701

1.679

Number of females in

household 221 2.570 1.599 211 2.578

1.594

Spouse education level

(years of formal

education)

221 3.344 3.274 211 2.417

10.344

Household head age 220 49.377 *** 15.006 208 44.077 *** 14.080

Household head

education level (years of

formal education)

220 4.614 3.274 211 4.171

3.213

Variable Obs Freq. "Yes" Freq. "No" Obs Freq. "Yes" Freq. "No"

Household head male 221 195 26 211 176 35

Household has a loan 220 72 148 210 70 140

Household owns land 221 116 105 211 105 106

Household head is

married 221 174 67 211 164 47

Household head born in

the Petén 221 132 * 89 * 211 98 * 108 *

Household depends on

the forest for their

livelihood

221 144 *** 77 *** 218 71 *** 139 ***

Note: sample statistics are based on 432 observations. 19 observations are excluded because they reported

incomes below 0 or above 150,000Q and 43 observations are excluded because they are from cancelled

concession communities. *,**,*** denote significant mean difference at the 10, 5, and 1 percent levels. The

variable “household depends on the forest for their livelihood” was measured with a Likert Scale from 1 to 5.

“1” indicates that the household responded “strongly disagree” and “5” indicates the household responded

“strongly agree.” The response is considered a “yes” if the household responded “4” or “5” to the statement “I

depend on the forest resources for my livelihood.”

24

Household characteristics also differ by community type (Table 3). For example,

members and non-members in nonresident concession communities are, on average, more

educated than members and non-members located in recently inhabited concession

communities. For the most part, however, means of a number of demographic

characteristics are not statistically different between concession members and non-

members in recently inhabited communities (with the exception of age). The results for

the nonresident concession members and non-members, however, show that there are

several covariates that are statistically different between the two groups including

household head age, household head male, household head married, household owns

land, and household depends on the forest for their livelihood6, which could be a source

of selection bias. We take several measures outlined in the results section to address the

potential selection bias in the data.

6 Household head age, household head male, household head married, household owns land, and household

depends on the forest for their livelihood represents the average age, number of heads of households who

are male, number of households who are married, number of households that own land, and whether or not

the household depends on the forest respectively.

25

Table 3. Recently inhabited and Nonresident Member and Non-Member Sample

Statistics

Recently inhabited Nonresident

Members Non-members Members Non-members

Variable Mean Std.

Dev. Mean

Std.

Dev. Mean

Std.

Dev. Mean

Std.

Dev.

Number of

children under

12 in household

1.857 1.406 1.845 1.518 1.386 1.4 1.626 1.762

Number of

females in

household

3.000 1.617 2.563 1.471 2.653 1.577 2.597 1.658

Spouse

education level

(years of formal

education)

2.000 2.353 0.915 12.082 3.673 3.346 3.899 3.715

Household head

age 52.143 ** 20.587 42.873 ** 14.144 49.986 *** 13.68 44.58 *** 14.04

Household head

education level

(years of formal

education)

2.429 2.138 2.789 2.366 5.048 3.405 4.884 3.371

Variable Freq.

"Yes"

Freq.

"No"

Freq.

"Yes"

Freq.

"No"

Freq.

"Yes"

Freq.

"No"

Freq.

"Yes"

Freq.

"No"

Household head

male 14 0 63 8 132 ** 15 ** 112 ** 27 **

Household has a

loan 1 13 19 51 53 93 51 88

Household owns

land 9 40 15 64 83 * 64 * 92 * 47 *

Household head

is married 11 3 60 11 87 ** 60 ** 63 ** 76 **

Household head

born in the

Petén

5 9 22 48 66 81 60 75

Household

depends on the

forest for their

livelihood

5 *** 9 *** 11 *** 60 *** 92 *** 55 *** 60 *** 79 ***

Note: sample statistics are based on 128 observations for recently inhabited concessions and 286 observations

for nonresident concessions. 18 observations are excluded because they reported incomes below 0 or above

150,000Q and 43 observations are excluded because they are from cancelled concession communities.

*,**,*** denote significant mean difference at the 10, 5, and 1 percent levels. Statistics divided by

membership status are not available for long-inhabited communities due to lack of statistics on non-members.

The variable “household depends on the forest for their livelihood” was measured with a Likert Scale from 1

to 5. “1” indicates that the household responded “strongly disagree” and “5” indicates the household

responded “strongly agree.” The response is considered a “yes” if the household responded “4” or “5” to the

statement “I depend on the forest resources for my livelihood.”

26

The dependent variable in our analysis, household income, is constructed from

components of the 2012 survey focused on income earned from agricultural activities,

cattle ranching, forest harvesting activities, wage earning activities, activities associated

with the forest concessions, and other income generating activities (Table 4). The average

earnings from each source are shown for concession members and non-members in each

concession type for all households that reported positive earnings from that activity in the

past twelve months. Recently inhabited concession members earn more income from

agricultural activities as a proportion of their total income on average than long-inhabited

and nonresident concession members. In nonresident concessions, members earn more

income on average from forestry than non-members, and these communities earn more of

their income, on average, from activities not related to forestry or agriculture than

households in recently and long-inhabited concession communities.

27

Table 4. Income activities by concession classification

Concession Members Non-members

Average income Std. Dev. Average income Std. Dev.

Long-inhabited

Agriculture 1709.84 6874.66 N/A N/A

Cattle Ranching 0.00 0.00 N/A N/A

Forestry 9222.95 19284.36 N/A N/A

Tourism 278.89 1654.60 N/A N/A

Government/NGO 6330.69 16495.99 60000.00 N/A

Small Business 3844.26 10196.64 N/A N/A

Other 8468.85 16035.45 N/A N/A

Recently inhabited

Agriculture 12464.29 23306.11 15365.15 21899.78

Cattle Ranching 0.00 0.00 0.00 0.00

Forestry 0.00 0.00 197.53 1777.78

Tourism 0.00 0.00 64.81 583.33

Government/NGO 0.00 0.00 2926.54 10192.56

Small Business 3944.90 9671.52 7313.58 22788.40

Other 5173.67 9821.88 7190.99 28983.14

Nonresident

Agriculture 3316.03 14470.64 4882.48 11342.58

Cattle Ranching 30.77 384.31 850.69 6119.62

Forestry 3086.54 27290.87 168.97 1561.50

Tourism 521.79 3847.65 1055.17 9054.64

Government/NGO 9904.62 25139.49 9448.35 27406.65

Small Business 8007.05 28310.69 12698.62 45960.34

Other 15689.50 29379.02 22440.96 62000.64

Results for average income depict the average annual income earned by concession

members and non-members for each concession classification only for households that

reported positive earnings for the particular activity. Results are in quetzals. One USD is

equal to about 7.64 quetzals.

28

2.4 Empirical Methods

To examine the effect of concession membership on income we start with

ordinary least squares (OLS) models with village fixed effects. We estimate one model

for the combination of the three different classifications of community concessions

(equation (5)) and then estimate a model with only the recently inhabited community

members (equation (6)) and a model with only the nonresident community members

(equation (7)). We are unable to estimate the income effect in the long-inhabited

communities because there is only one individual in the long-inhabited communities that

is not a concession member in our sample. Also, since La Pasadita, San Miguel, and La

Colorada were cancelled or suspended in 2009, we do not include observations from

these concession communities in our analysis.

𝐼𝑛𝑐𝑜𝑚𝑒𝑖 = 𝛽0 + 𝛽𝐶𝑖 + 𝑋𝑖′𝛽𝑥 + 𝛼 + 𝛾 + ʎ + 𝜀𝑖 (5)

𝐼𝑛𝑐𝑜𝑚𝑒𝑖 = 𝛽0 + 𝛽𝐶𝑖 + 𝑋𝑖′𝛽𝑥 + ʎ + 𝜀𝑖 𝑖𝑓 𝛼 = 1 (6)

𝐼𝑛𝑐𝑜𝑚𝑒𝑖 = 𝛽0 + 𝛽𝐶𝑖 + 𝑋𝑖′𝛽𝑥 + ʎ + 𝜀𝑖 𝑖𝑓 𝛾 = 1 (7)

In equations (5) to (7), 𝐶𝑖 is a binary variable that equals 1 if observation i is a

concession member, 𝛽0 is a constant, ʎ represents village fixed effects, and 𝑋𝑖 is a

vector of demographic and socioeconomic control variables7. In equation (5), α

7 The control variables included are whether or not the respondent was born in the Petén , number of

females in the household , education level of the household head , education level of the spouse of the

household head , whether or not the household owns land , gender of the household head , age of household

head , whether or not the household depends on the forest for their livelihood , whether or not the

household has taken out a loan , number of household residents under 12 , the extent to which the

respondent trusts others , and whether or not the household head is married .

29

represents a dummy variable for recently inhabited concession communities and γ

represents a dummy variable for nonresident communities. We include α, γ, and ʎ to

control for income effects associated with unobserved community and village

characteristics8.

There is a potential selection bias problem with the OLS models (with village

fixed effects) since it is possible that certain characteristics may influence an individual’s

decision to join a concession and their potential for income generation (i.e., their

productivity). To account for observable characteristics that may lead to selection bias,

we use a matched OLS model (also with village fixed effects). The matched OLS model

estimates a standard OLS model on only those observations that fulfill the common

support requirement (also known as the overlap condition). This model uses the predicted

probabilities of being a concession member to match observations that are concession

members (treated observations) to observations that are not concession members (control

observations) that are most similar to the treated observations. Observations are matched

based on their propensity scores, which are estimated using the latent values of a logit

model (Pirracchio et al, 2013). Specifically, 𝑝𝑖 is the probability that household i is a

member of a concession based on covariates 𝑋𝑖. The model we use to estimate the

propensity scores for each household i is shown in equation (8).

𝑝𝑖 = Pr(𝐶𝑖 = 1|𝑋𝑖) =exp (𝑥𝑖

′𝛽+𝜀)

(1+exp(𝑥𝑖′𝛽+𝜀))

(8)

8 We tested for multicollinearity with a Variance of Inflation Factor (VIF) test. The results show that only

the dummy variable for being a member of a recently inhabited community is collinear. However, the

results for the concession membership coefficient do not change with this variable removed from the

analysis.

30

The covariates used in equation (8) control for factors that may lead households to join a

forest concession9. The results of the logit model used to calculate the propensity scores

are show in Appendix A.2.

In addition to comparing the results of the OLS model with village fixed effects to

the results of the matched OLS model with common support, we estimate the average

treatment effect (ATE), average treatment effect of the treated (ATT), and a doubly-

robust (DR) estimator model as robustness checks. Like the matched OLS model, these

estimators use the predicted probability of being a concession member to control for

observable characteristics of the households that are possible sources of selection bias.

However, unlike the matched OLS model, the ATE, ATT, and DR estimator models use

the inverse probability weights to account for the predicted probability of being a

concession member for each household i,

𝐴𝑇𝐸 =1

475 ∑ 𝐶𝑖𝑌𝑖 (

1

𝑝𝑖) − (1 − 𝐶𝑖)𝑌𝑖 (

1

(1−𝑝𝑖))475

𝑖=1 (9)

𝐴𝑇𝑇 =1

256∑ 𝐶𝑖𝑌𝑖 − (1 − 𝐶𝑖)𝑌𝑖 (

𝑝𝑖

(1−𝑝𝑖))475

𝑖=1 (10)

𝐷𝑅 = 1

475∑ [

𝐶𝑖𝑌𝑖−(𝐶𝑖−𝑝𝑖)𝑚1(𝑋𝑖)

𝑝𝑖]475

𝑖=1 −1

475∑ [

(1−𝐶𝑖)𝑌𝑖+(𝐶𝑖−𝑝𝑖)𝑚0(𝑋𝑖)

(1−𝑝𝑖)]475

𝑖=1 (11)

Equation (9) uses the probabilities obtained from equation (8) to estimate the

average treatment effect (ATE) of concession membership on income, or in other words,

the amount by which being a concession member changes income on average for

9 The covariates used to predict pi are the head of household’s education level, head of household’s age, the

respondent is married, education level of respondent’s spouse, whether or not the respondent was born in

the Petén, number of family members in the household, the extent to which the household trusts others,

whether or not the household has savings, and whether or not the household reports that they depend on the

forest for their livelihood.

31

concession members and non-members. Equation (10) estimates the average treatment

effect on the treated (ATT), which can be interpreted as the average effect that being a

concession member has on income, relative to what their income would have been had

they not been part of a concession (Imbens and Angrist, 1994; Pirracchio, 2013).

Equation (11) is the DR model and uses inverse probability weights and regression

adjustment to determine the effect of concession membership on income (Emsley et al,

2008; Funk et al, 2007). The inverse probability weights adjust the treatment (concession

membership) for selection bias. Additionally, 𝑚1(𝑋𝑖) and 𝑚0(𝑋𝑖) are the predicted

values from the OLS regressions of income on the covariates used in equation (5)10 for

concession members and non-members respectively.

2.5 Results

The results of the combined OLS11 model show that concession membership has a

positive and significant overall effect (at the 5% significance level) on annual income

(Table 5)12. These results suggest that concession membership, on average, increases

income by about 7,436 quetzals per year (about 1000 USD). However, we suspect the

majority of this effect is due to the strong income effect in the nonresident concession

10 The covariates are whether or not the respondent was born in the Petén , number of females in the

household , education level of the household head , education level of the spouse of the household head ,

whether or not the household owns land , gender of the household head , age of household head , whether

or not the household depends on the forest for their livelihood , whether or not the household has taken out

a loan , number of household residents under 12 , the extent to which the respondent trusts others , and

whether or not the household head is married . 11 “Combined OLS” refers to equation (1), which is the model representing the average effect of concession

membership on income for all concession types. 12 The concession membership coefficients of the Combined OLS, Recently Inhabited, and Nonresident

regressions with control variables are similar to the membership coefficient in a simple, linear regression of

concession membership on income.

32

communities. In general, being a household in a nonresident community is associated

with an increase in income of about 17,520 quetzals (about 2,335 USD) per year when

compared to long-inhabited community concessions. This may indicate that concessions

have a greater, positive effect on household livelihoods when forest harvesting activities

are meant to supplement income rather than serve as the primary source of income.

In the nonresident concession model, the results indicate that being a concession

member leads, on average, to an increase in income of about 7,634 quetzals (about 1,000

USD) per year, compared to the recently inhabited model, where concession membership

results in an increase in income of 1,416 quetzals, though the coefficient is not

significant. One explanation for this difference between concessions is that almost all

nonresident concession members receive annual dividends in addition to the wages they

earn from working in the concession, while the majority of the recently inhabited

concessions are not allowed to receive dividend payments and instead receive benefits in-

kind.

While the insignificant results for the recently inhabited concessions could be due

to the limited number of observations and a high level of variability in the annual income

levels of the respondents, it also plausible that the concession policy does not benefit

members in those concession communities. That is, it may make forest product

harvesting less productive for the concession members (see Appendix A.1 for more

details). Evidence suggests that this may be the case, as many of the recently inhabited

concessions were cancelled in 2009 because the forests were not being managed

33

sustainably13. Additionally, respondents from these concessions reported earning a higher

proportion of their income from agricultural activities than nonresident and long-

inhabited concession types on the 2012 survey, though they earned less income overall

than individuals surveyed from the other two community types14. Another reason the

concession model might not provide benefits to households in recently inhabited

communities is the lack of trust and altruism among households. Unlike in the

nonresident and the combined OLS models, the coefficient for trust for the recently

inhabited model is negative, indicating that being more trusting of your neighbors in a

recently inhabited concession decreases household income.

13 Interestingly, we ran a regression with the observations for the three concessions that were cancelled in

2009 and the parameter on concession membership was negative and insignificant, suggesting to us that it

is entirely plausible that concession membership does not increase income in these recently inhabited areas. 14 The t-test statistic for the mean difference in total revenue earned from agricultural activities between

recently-inhabited and all other communities is -6.189. “Total revenue earned from agricultural activities”

is comprised of income earned from the production of corn, beans, chile, squash, other crops and cattle

ranching The mean revenue earned from agricultural activities for recently inhabited communities is

5,659.75Q and the mean for all other communities is 1,001.432Q. The t-test statistic for the mean

difference in overall income between recently-inhabited and all other communities is 4.976 and the mean

overall income for the communities is 23,305.700Q and 37,816.52Q respectively.

34

Table 5. Regression results for effect on income

Combined

OLS

Matched

Combined

OLS

Recently

inhabited Nonresident

Household has a concession member

(1=”yes”) 7435.979 ** 11148.32 *** 1415.558 7634.098 **

(3116.051) 3600.465 8033.235 (2825.283)

Household head born in the Petén

(1= “yes”) -2578.861 -3699.814 -7936.032 -937.0821

(3150.765) 4007.789 5814.182 (3585.369)

Number of females in household 978.932 146.2342 -1328.887 820.169 (1024.098) 1239.538 3297.407 (1003.886)

Spouse education level (years of

formal education) 457.101 1665.874 *** 3158.167 * 367.6459 *

(283.141) 645.1523 1659.907 (249.056)

Household owns land (1= “yes”) 8818.022 *** 7394.074 ** 5508.813 10971.8 *** (3055.445) 3463.263 5728.447 (3232.208)

Household head is married -1140.885 -320.9769 128.8726 -1158.306 (1190.980) 1415.258 2823.039 (1383.642)

Household head gender (1=female) -6046.643 * -7533.129 12581.62 -9393.216 * (4128.200) 5081.483 11792.47 (4971.599)

Household head age 148.962 86.68688 581.4513 * 128.2831 (99.538) 126.8493 180.5271 (119.690)

Household head education level

(years of formal education) 2743.959 *** 2217.589 *** 2411.026 2562.006 ***

(518.811) 640.2843 1468.496 (583.484)

Household depends on the forest for

their livelihood 1597.796 1230.92 -367.0058 2128.494

(1326.600) 1565.302 2902.366 (2277.736)

Household has a loan (1= “yes”) -8514.288 *** -6420.709 * -6634.568 -11672.54 *** (3016.270) 3586.664 7280.478 (3831.879)

Number of children under 12 in

household -345.807 196.9151 3231.399 -659.0319

(1117.190) 1313.201 3668.124 (1222.583)

Trust 1788.117 2464.209 -2087.745 1898.948 (1209.267) 1534.836 1965.69 (1244.238)

Nonresident concession community

resident (1= “yes”) 17519.670 *** 18722.02 ***

(5972.205) 6180.63

Recently inhabited concession

community resident (1= “yes”) 2969.035 17568.29 **

(7205.686) 7653.704

35

We note that concession members may also get in-kind benefits, including

scholarships for school supplies, medical attention, life insurance, funeral benefits,

community improvements, and assistance with social programs such as programs to

support women and church organizations. We do not include the value of in-kind benefits

in our income variable, although many households indicated in the survey that in-kind

benefits are an important aspect of concession membership and some even prefer to

receive in-kind benefits to dividends15. Moreover, forest concession policies also give

members priority at wage earning jobs (Radachowsky et al, 2012). This not only provides

concession members with a reliable source of income, but also removes some of the

income variation and uncertainty associated with jobs in the forest product industry16.

15 49.61% of respondents prefer in-kind benefits to cash dividends. Of the 281 concession member

respondents, 77 listed in-kind benefits as one of the primary benefits for joining a concession. Of the non-

member respondents, in-kind benefits were collectively ranked as one of the most important potential

benefits. 16 Of the total sample surveyed, about 60% of non-members said their income either "varied a little" or "did

not vary" while about 67% said their income either "varied a little" or "did not vary." Of the concession

Table 5 (cont.)

Combined

OLS

Matched

Combined

OLS

Recently

inhabited Nonresident

Constant 14792.260 ** 10211.85 -29926.38 40597.280 (11625.100) 15473.65 25649.58 (9204.961)

Village fixed effects Yes Yes No Yes

Observations 411 304 81 273

R-squared 0.3326 0.3455 0.3550 0.3376

Note: *,**,*** denote significance at the 10, 5, and 1 percent levels. Clustered, robust standard errors are

denoted inside parenthesis. Results are in Quetzales. One USD is worth about 7.64Q. Some observations

are excluded because they reported incomes below 0 or above 150,000Q. 43 observations are excluded

because they are from cancelled concession communities. The variable “household depends on the forest

for their livelihood” was measured with a Likert Scale from 1 to 5. “1” indicates that the household

responded “strongly disagree” and “5” indicates the household responded “strongly agree.” The variable

“trust” indicates the participant’s answer to the question “Do you think you can trust the majority of

people?” Each participant chose responses on a Likert Scale from 1 to 5. “1” indicates that the participant

thinks they cannot trust anyone. “5” indicates that the participant thinks they can trust the majority of

people.

36

Members of forest concessions also have access to equipment such as sawmills and kilns

that non-members do not have. The opportunity to use this equipment and collectively

market their products gives concession members valuable experience, which could prove

advantageous in selling forest products. Hence, we suspect that the value of being a

concession member may be underestimated by our current income measure since we are

unable to include the value of these in-kind benefits and risk reduction in the household

income variable. Additionally, since concessions provide work opportunities for

concession members, there may be spillovers within the community. If, for example, the

concession provides more jobs than are able to be filled by concession members,

nonmembers may be given these jobs.

The matched OLS model, which controls for potential selection bias, also has a

positive and significant parameter for the concession membership dummy (Table 5).

ATE, ATT, and DR models also control for potential selection bias (Table 6). In the

model with the three concession types combined, the results are not significant and the r-

squared values are low. This is likely due to the limited number of observations and the

high level of variability in the income levels of the respondents. The magnitudes of the

results, however, are in line with the combined OLS results (7435.979 in the combined

OLS compared to 3855.798, 3640.789, and 3571.510). This suggests that, although

selection bias may influence the results, there is evidence that the effect of concession

membership on income is positive and this result holds across several robustness checks.

members, about 17% said they were "very worried" about their income while about 23% of non-members

said they were "very worried."

37

Table 6. ATE/ATT/DR Results for effect on income

Recently inhabited, Long-inhabited, and Nonresident Combined

ATE ATT DR

Household has a

concession member

(1=”yes)

3855.798

3640.789

3571.510

(3011.736)

(3114.432)

(3141.170)

Constant 33469.650 *** 35318.750 ***

(2032.843)

(2369.805)

Observations 419

419

432

R-squared 0.005 0.004

Recently Inhabited

ATE ATT DR

Household has a

concession member

(1=”yes)

-14870.900 *** -14718.600 *** -10183.500

(4970.855) (5825.556) (89571.630)

Constant 27976.960 *** 30869.470 ***

(3167.806) (3886.764)

Observations 84 84 85

R-squared 0.074 0.071

Nonresident

ATE ATT DR

Household has a

concession member

(1=”yes)

10637.040 *** 10796.880 *** 6954.712 **

(3694.395) (3657.362) (3554.323)

Constant 34272.730 *** 34426.500 ***

(2398.353) (2516.904)

Observations 276 276 286

R-squared 0.031 0.034

Note: *,**,*** denote significance at the 10, 5, and 1 percent levels. Robust standard errors are

denoted inside parenthesis. Results are in quetzals. One USD is worth about 7.64Q.

38

The concession membership coefficients for the ATE, ATT, and DR models for

nonresident concessions are significant, and similar to the membership coefficient in the

nonresident OLS regression. The results for the recently inhabited concession

membership coefficients for the ATE and ATT models are negative and significant while

the OLS coefficient is positive and insignificant. These results help confirm that

concessions in recently inhabited areas concessions do not raise the productivity of

members significantly in forestry activities, and may actually reduce productivity and be

worse.

2.6 Conclusion

This paper examines the role of community based forest concessions on income

generation in the Maya Biosphere Reserve of northern Guatemala. Concessions were

instituted in the late 1990s to early 2000s to provide land use rights to groups that agreed

to sustainably manage timber resources and harvest non-timber forest products. In return

for rights, the groups are not allowed to convert land to agricultural uses. Three types of

groups have obtained rights: groups that have inhabited the forests in the region for long

periods of time (long-inhabited concessions), groups that have lived in the area, but were

primarily composed of individuals or families that moved to the region around the time

the MBR was created (recently inhabited concessions), and groups that do not live in the

concessions and reside in the buffer zone of the MBR (nonresident concessions).

To analyze the impact of concession formation on income, we start with a

theoretical model of household labor allocation. One key dynamic of the forest

39

concessions is that usage rights are given to groups, rather than to individuals, and groups

are provided with training in resource and financial management from participating

NGOs. Groups are then expected to work together to produce the outputs of the

concession. Although free-riding may occur, as suggested by Rotemberg (1982) and

Hamilton et al. (2003), it is possible for group management to increase productivity, and

other studies have shown this for common property resource systems like the MBR

(Ostrom 1990; Schlager and Ostrom, 1992; Primack et al, 1998; Meilby et al, 2014). One

issue less widely addressed in earlier literature is whether certain types of groups, i.e.

those that are better able to cooperate, would gain more from common property resource

systems. The theory model illustrates the conditions under which certain communities

can take advantage of group management strategies to protect the forest and increase

their income. For example, we show that when forest productivity is greater under

concession group management with land use rights than individual exploitation of an

open-access resource, income will be greater for concession members than non-members.

This theoretical approach fits the model of forest concessions in the MBR, which

encourages cooperation among members. We test the model using data from a survey of

concession members and non-members conducted in 2012. The survey provides

information on households that were part of the community-based concessions as well as

neighboring households in the same communities that were not part of the concessions.

Surveys were obtained for all three types of forest concessions in the Maya Biosphere

Reserve: recently inhabited residential, long-inhabited residential, and nonresidential.

The results show that incomes among individuals engaged in concession activity in

40

nonresidential concessions were around 7600 quetzals (about $1,000) per year higher.

The results also suggest that members in recently inhabited concessions have the same or

less income than their non-member neighbors. Interestingly, deforestation for

subsistence agriculture also appears to have continued in the area of the recently

inhabited concessions (Maas and Cabrera, 2008, Radachowsky et al, 2012; Fortmann et

al, 2017), suggesting that the benefits of devoting labor to agriculture are robust.

Alternatively, for nonresident concession members, there are gains to the group

management associated with concession membership and incomes appear to have

increased as a result.

These results suggest that sustainable forestry, if done correctly, can provide

concession members with a steady source of income in the long-run. If nonresident

concessions consistently implemented and enforced their sustainable forest management

plans since their concessions were granted, then deforestation rates should remain low

and sustainable forest extraction can continue to serve as a source of revenue for

concession members. If, as we suspect is the case in the recently inhabited concessions,

the management plan was not successfully implemented, then the concession essentially

converts to an open access resource. According to Gordon (1954), when a resource is

open access, land rents dissipate and the resource becomes degraded. Hence, households

are unable to make a profit from sustainable resource extraction and overexploit the

resource. Of course, the forest may have also been degraded before the concessions were

granted to recently inhabited communities, implying that sustainable resource extraction

was not profitable from the beginning.

41

The results of our analysis have several additional implications. First, it is

possible to create a sustainable forest management plan that serves the dual purpose of

benefiting community members and curbing deforestation. Although this analysis only

examines a small, cross-sectional sample of community members in the Petén, the results

indicate that community forest concession policies are beneficial to certain communities.

Second, the effect of community forest concession policies on income is heterogeneous.

The effect of concession membership on income among members in nonresident

concession communities varies greatly from the effect of membership on income among

recently inhabited concession communities as well as the combination of all types of

concession communities. This indicates that concession plans should be tailored to the

specific needs of the community to best promote community development. All in all,

community forest concessions in the MBR provide a variety of benefits to local

communities and play a positive role in community development.

42

Chapter 3: Assessing the private and social benefits of forest concessions in the Maya

Biosphere Reserve

3.1 Introduction

In many developing regions, property rights for forests are not well defined and

information on forestland values is not widely available. This lack of information applies

both to market and non-market values for the many ecosystem services that forests

provide (e.g., Bowes and Krutilla, 1989; Miteva, 2019). One problem with undervaluing

the benefits that forests provide in developing regions is that local households often

depend heavily upon the resource or the land on which the resource exists. This

dependency, coupled with a disregard for the value of forestland as an amenity, weak

formal institutions and governance to enforce land use restrictions, and few incentives for

effective forest conservation could lead to households overexploiting the resource (e.g.,

Vincent, 2016; Sills & Jones, 2018). Forests are thus susceptible to common-pool

resource concerns, where over-extraction occurs to the point where land rents converge to

zero and neither low-income households nor the rest of society can benefit from the

resource (e.g., Gordon, 1954; Scott, 1955).

To promote local conservation of forest stocks, some developing country

governments have provided local community groups with property or land-use rights to

manage forest resources sustainably. Community-based common property resource

43

(CPR) management systems follow the advice of Gordon (1954) and Scott (1955), who

recommended privatizing the resource to reduce over-extraction, but rights are vested

with groups rather than single individuals or entities. Many studies have now presented

empirical evidence showing how community-based forest management systems affect

deforestation (e.g., Miteva et al, 2012; Agrawl & Chhatre, 2006; Blackman, 2015;

Fortmann et al., 2017; Alix-Garcia, 2007, Rasolofoson et al., 2015; Takahashi & Otsuka,

2016; Robinson et al., 2017). No studies to our knowledge, however, have attempted to

quantify the value of common-pool forest management systems. Common-pool systems

avoid the dissipation of rent and thus increase the value of land in forests, but there is

little empirical evidence about the benefits such systems provide. This is a critical

problem because common property systems are fairly widespread globally (Ostrom,

2009), and are increasingly used by policy makers, but to be sustainable, they need to

generate enough revenue to ensure the continued participation of their members.

Aside from the private benefits that provide members with an incentive to

participate, community systems often also support important public benefits, such as

carbon sequestration or protection of important biological or cultural resources. In

practice, there are likely to be trade-offs between the public and private benefits of

ecosystem services. For instance, more carbon sequestration may require less timber

harvesting, resulting in lower timber revenues but greater carbon services. These trade-

offs are critical to acknowledge and examine when considering whether community

systems are successful. If households that benefit financially from forest access are not

adequately preserving forests, other ecosystem services, like carbon or the provision of

44

biodiversity, may suffer. Alternatively, if a forest management system significantly

increases carbon storage, but participating households are made worse off by harvesting

fewer trees, the household-level costs of participating in the system may be too high, and

conservation efforts may ultimately fail.

This study assesses the trade-offs between welfare gains individuals receive from

harvesting trees and the public conservation benefits of community-based tropical forest

concessions. We examine these trade-offs in the context of the Maya Biosphere Reserve

(MBR) of Guatemala, where common property reserves were established starting in the

mid-1990s and early 2000s. Welfare gains are quantified using rigorous quasi-

experimental approaches and a combination of a panel household survey and geospatial

data from the MBR. Public benefits are valued by measuring the additional carbon

sequestered resulting from avoided deforestation. The analysis finds that private and

public benefits are complements, which indicates that efforts to increase income by

providing property rights also increase the provision of public goods. This outcome has

been observed in long-standing common property systems such as communal tenure

rights in Torbel, Switzerland (Ostrom, 2009), but has not been shown for common

property systems that have been established explicitly to protect lands that were formerly

open access. In the case of the MBR, this outcome results from the establishment of

property rights in the region, which avoids significant forest loss, thereby retaining forest

stocks and allowing for sustainable income generation through timber harvesting. The

results suggest that both income and conservation are compatible outcomes through the

distribution of exclusive land use rights.

45

This is one of the first studies to assess the trade-offs and complementarities

inherent in common property systems deployed to protect public resources like forests.

Some studies have examined whether community management systems benefit local

households, finding both positive and negative effects (e.g., Primack et al., 1998; Sims,

2010; Richardson et al., 2011; Bocci et al., 2018; Kumar, 2002; Adhikari et al., 2004;

Adhikari, 2005; Meilby et al., 2014). All of these studies, however, consider only a single

point in time, making it difficult to assess the sustainability of the property right regimes.

This study innovates by carefully measuring both income and public benefits over time.

We estimate the benefits of the community concessions through a counterfactual

analysis of what “would have happened” if the concessions did not exist, using an

approach that is similar to studies that have examined the welfare effects of establishing

property rights for agriculture in developing countries (e.g. Aragón, 2015; Banerjee and

Weyer, 2005; Besley, 1995; Field, 2007; Galiani and Schargrodsky, 2010; Goldstein and

Udry, 2008; Hornbeck, 2010; Johnson et al., 2002). To help control for potential selection

effects (i.e., the selection of more productive individuals into concessions), we compare

the income of concession members to non-concession neighbors using data from two

survey periods (2012 and 2017). To value avoided deforestation, we use data on

deforestation rates in the concessions and in matched parcels outside the concessions, but

within the Maya Biosphere Reserve, to show the effect of the concessions on

deforestation rates. We then estimate the societal benefits using the social cost of carbon

from Nordhaus (2017). Although there are other benefits due to common property

46

resource management (e.g., Foley et al. 2005; Pimm et al. 2014), we have not valued

these resources in this analysis.

This approach to valuing the benefits of a common property system, which uses

income gains and the marginal increase in carbon sequestration differs from approaches

that value resource rents by valuing flows of timber and non-timber forest products (e.g.,

Peters et al, 1989; Gray et al., 2015). Resource rents do not capture all the productivity

gains that accrue to households in CPR systems when common-pool resources are

managed to prevent overexploitation. For example, the results show that the concessions

increase annual household income by about 2,204 USD per concession member

household, which suggests there are local labor productivity gains. The concessions also

decreased deforestation rates by about 4.2% from 2012 to 2017. As a result, the net value

of the community-based, CPR management system in the MBR is about $5,495,900,

which is about $2.18 per hectare per year. This estimate, while positive, is likely an

underestimate given that the forest concessions also have a positive effect on many types

of wildlife. Other benefits for concession members also are not completely captured in

the income estimate17.

17 Many concession communities reinvest profits into in-kind benefits such as improved schools,

scholarships, donations to church groups, and infrastructure (Radachowsky et al., 2012; Fortmann et al.,

2017; Bocci et al., 2018).

47

3.2 Data

3.2.1 Household Survey Data Collection

Table 7 highlights the differences in income-earning activities of the forest

concession communities.

Table 7. Income and wage-earning Activities

Nonresident

2017 2012

Income Jobs Income Jobs

Forestry 33,130.00 90 14,631.25 8

Agriculture 16,575.41 96 21,346.30 65

Tourism 34,575.00 9 11,991.43 7

Business 33,994.73 201 25,151.08 96

Professional 50,202.54 111 47,811.42 75

Other 36,634.67 136 22,025.60 153

Average annual income per job 34,637.41 107.17 27,125.68 67.33

Average income per household 48,172.35 --- 45,878.35 ---

Recently-inhabited

2017 2012

Income Jobs Income Jobs

Forestry 21,034.50 58 48,000.00 1

Agriculture 33773.36 63 8,647.28 47

Tourism N/A 0 63,000.00 1

Business 9,900.00 12 18,022.67 24

Professional 22,392.00 3 23,408.75 8

Other 33,953.25 12 12,665.00 30

Average annual income per job 26,629.31 24.67 13,668.34 18.5

Average annual income per

household 36,176.18 --- 23,346.88 ---

48

The main income-earning activity in long-inhabited communities is forestry while

in recently-inhabited concessions, agricultural activities such as cattle ranching and

farming, are major income-earning activities. In nonresident communities, the number of

workers and the amount of income earned from working in businesses or professional

activities comprises a larger share of the average household income than in long-

inhabited or recently-inhabited communities.

Table 7 (cont.)

Long-inhabited

2017 2012

Income Jobs Income Jobs

Forestry 36,782.55 125 10,288.47 17

Agriculture 34,965.33 26 572.00 4

Tourism 52,747.96 25 6,000.00 2

Business 27,565.30 38 16,969.23 13

Professional 41,509.14 37 37,358.36 11

Other 35,121.39 53 8,627.75 20

Average annual income per job 37,073.58 50.67 14,825.21 11.17

Average annual income per

household 46,660.50 --- 31,601.98 ---

All Communities

2017 2012

Forestry 32,170.35 273 13,075.15 26

Agriculture 24,249.93 185 15,484.65 116

Tourism 47,734.73 34 15,894.00 10

Business 31,683.12 251 23,065.02 133

Professional 47,938.63 151 44,511.37 94

Other 35,419.30 201 19,322.27 203

Average annual income per job 33,974.61 182.5 23,143.04 97

Average annual income per

household 44,826.22 --- 39,981.97 ---

Income values are in quetzals. Average income is the average, nominal income for each job type

weighted by the number of annual jobs in each category. Average income per household is the

average annual income per household, which often includes income from more than one person

working.

49

To test whether participating in community forest management in the MBR

benefits households, we use a rotating panel survey dataset constructed from 2012 and

2017 household surveys in communities in the MBR that are associated with a

concession. Using enumerators from MBR communities, 494 households were

interviewed in 2012 and 716 households in 2017. We collected a larger sample of

households in 2017 because the population of communities increased. The 2012 sample

was constructed by first taking a random sample of 20% of the households from a

comprehensive list of active concession members in the MBR provided by CONAP.

Once the households were selected, local guides were hired from each concession to take

the enumerators to concession-member households in the sample. Then, to collect data

from nonmember households that were similar to concession households, the

enumerators administered the survey to a next door neighbor who was not a member of

the concession (Fortmann, 2014). For the 2017 survey, local guides were asked to take

the enumerators to households from the list of members and nonmembers from the 2012

survey. If the guides were unable to locate a household, the enumerators either randomly

selected an alternative concession member household using an updated comprehensive

list of active concession members or surveyed a nonmember household located near a

randomly-sampled active concession member.

50

Table 8. Concession members and nonmember characteristics by community type

All Households

2017 2012

Concession Members Nonmembers Concession members Nonmembers

Household Head

Age 50.45 *** 42.46 *** 49.64 *** 44.27 ***

Household Head

Education 6.54 ** 7.07 ** 4.37 4.27

Born in the Petén

(%) 63%

63.33%

53.18% 49.57

Land owned

(manzanas) 11.15 *** 5.85 *** 20.66 16.4

Forest dependent 0.80 *** 0.60 *** 0.53 *** 0.26 ***

Household head

gender 1.20 ** 1.26 ** 1.12 * 1.17 *

Savings 1.84 1.85 1.82 1.82

Spouse education 5.98 ** 6.40 ** 4.65 * 4.26 *

Married 0.82 * 0.78 * 0.76 * 0.81 *

Under 12 1.04 *** 1.33 *** 1.49 * 1.69 *

Trust 0.31 0.34 0.09 0.11

Observations 356 360 267 226 Nonresident

2017 2012

Concession Members Nonmembers Concession members Nonmembers Age 54 *** 44.97 *** 49.63 *** 44.57 *** Education 6.91 ** 7.62 ** 5.14 5.07 Born in the Petén

(%) 57 * 65.79 * 59.73 58.33

Land owned

(manzanas) 12.43 *** 3.51 *** 15.17 *** 8.63 ***

Forest dependent 0.72 *** 0.48 *** 0.53 *** 0.32 *** Household head

gender 1.16 *** 1.31 *** 1.10

** 1.20 **

Savings 1.81 1.80 1.76 1.79 Spouse education 6.13 ** 6.82 *** 4.80 4.57 Married 0.85 *** 0.71 *** 0.74 0.80 Under 12 0.87 *** 1.18 *** 1.36 * 1.60 * Trust 0.31 0.27 0.08 0.12 Observations 209 190 149 144

51

Table 8 (cont.)

Recently-inhabited

2017 2012

Concession Members Nonmembers Concession members Nonmembers

Age 38.94 42.92 49.17 *** 36.41 ***

Education 6.26 * 5.5 * 3.51 3.55

Born in the

Petén (%) 61.70% ** 35.90% ** 49.06% 50.00%

Land owned

(manzanas) 12.77 9.18 36.92 28.36

Forest

dependent 0.94 0.87 0.26 0.36

Household head

gender 1.26 *** 1.03 *** 1.10 1.09

Savings 1.94 1.97 1.94 * 1.77 *

Spouse

education 5.50 5.09 4.88 4.72

Married 0.85 ** 1.00 ** 0.74 0.82

Under 12 1.17 ** 1.87 ** 1.52 * 2.27 *

Trust 0.34 * 0.54 * 0.10 0.09

Observations 47 39 31 22 Long-inhabited

2017 2012

Concession Members Nonmembers Concession members Nonmembers

Age 48.51 *** 35.43 *** 48 N/A Education 5.94 *** 7.26 *** 4.12 N/A

Born in the

Petén (%) 74.75% * 86.96% * 46.38%

N/A

Land owned

(manzanas) 7.58 6.41 9.09

N/A

Forest

dependent 0.93 0.91 0.79

N/A

Household head

gender 1.25 1.30 1.18

N/A

Savings 1.87 1.88 1.90 N/A

Spouse

education 5.91 * 6.62 * 4.45

N/A

Married 0.75 0.80 0.79 N/A

Under 12 1.34 1.42 1.66 N/A

Trust 0.38 0.34 0.11 N/A

Observations 99 69 61 0

52

Table 8 (cont.)

Non-concession

2017 2012

Concession Members Nonmembers Concession members Nonmembers

Age N/A 41.77 N/A N/A Education N/A 6.13 N/A N/A Born in the

Petén (%) N/A

46.67%

N/A

N/A

Land owned

(manzanas) N/A

9.13

N/A

N/A

Forest

dependent N/A 0.58 N/A

N/A

Household head

gender N/A 1.2 N/A

N/A

Savings N/A 1.92 N/A N/A

Spouse

education N/A 5.68 N/A

N/A

Married N/A 0.82 N/A N/A

Under 12 N/A 1.23 N/A N/A

Trust N/A 0.23 N/A N/A

Observations 0 60 N/A N/A Note, *,**,*** indicate that the t-test result is statistically different across members and nonmembers at

the 90%,95%, and 99% confidence levels respectively. T-test results are not shown for long-inhabited

communities in 2012 due to the lack of nonmember observations. For non-concession communities, the

only data available is for 2017 nonmembers. For a detailed description of each variable, see Table 9.

The panel dataset consists of 113 households surveyed both in 2012 and 2017,

104 of which are concession members and 18 of which are nonmembers18. The

characteristics of the concession members and nonmembers surveyed are shown in Table

8 above.

3.2.2 Biophysical Dara

To estimate the environmental benefits of the concessions, we construct a panel

dataset to estimate the effects of concession status on deforestation and CO2 storage from

2012 to 2017. The forest loss variable is constructed using satellite imagery data of

18 We suspect that nonmembers were more likely to leave their communities than members from 2012 to

2017 because they did not have a guaranteed source of income like the concession members.

53

annual forest loss from 2012 to 2017 and percent tree cover from the year 2000 (Hansen

et al., 2013)19. To quantify the additional amount of CO2 stored by the forest conserved

by the concessions, we use the forest loss data from Hansen et al. (2013) and

aboveground woody biomass density described in Baccini et al. (2012)20. Because the

forest loss data only depicts areas of forest lost and does not detect reforestation, we

assume that once an area is deforested, it remains deforested and the aboveground woody

biomass density is negligible. We acknowledge that the effects on CO2 storage are likely

an overestimate since trees store carbon throughout their growth cycle at different rates.

3.3 Theory

The common theoretical justification for decentralizing forest governance to local

communities is that these communities have an incentive to protect forests since their

livelihoods depend on the long-term viability of the forest stocks, thus mitigating the

CPR overexploitation problem (e.g., Baland & Platteau 1996; McKean 2000).21 If

successful, CPR management systems can serve conservation and development purposes

by increasing the value of forests as an amenity, and increasing household incomes

through exclusion. Governments may also avoid costly protection if the group property

right is strong enough so that the benefits of working together to protect the resource are

greater than the costs (Ostrom, 1990).

19 Following Sexton et al. (2015), we use the year 2000 percentage tree cover data and set a 25% tree cover

threshold for what is considered forest. This process eliminates deforestation events post 2012 that do not

coincide with forest in 2012. 20 For a more detailed explanation of the covariates and data sources, see Table 6. 21 Many community-based CPR management policies are implemented with restrictions on harvesting. In

the Maya Biosphere Reserve case, this restriction is based on FSC certification standards.

54

If common property resources are exploited as open access systems, the ability for

any local household to earn income from the forest resource is greatly reduced (Gordon,

1954; Scott, 1955). A CPR management system, such as the MBR forest concessions,

can then benefit local households that have access to the forest if sustainable management

efforts are successful since the resource will be preserved for future use and households

can earn higher incomes from the resource relative to an open access situation. This

increases the value of the land under concession management in the MBR relative to

similar MBR forest not under concession management.

One way to value land rents is to assess timber and non-timber forest product

flows and value those at observed prices. While useful, in a common property resource

management system, this approach may not capture all of the gains in productivity that

occur. For example, individuals may become more productive when they are part of a

group, and the group effort can generate benefits (Holmstrom, 1982). Also, the

concessions provide an opportunity to earn income from the reserve that would not have

otherwise existed, such as value-added jobs in timber mills. By creating a stable, wage-

earning forest industry, households who are concession members no longer have to rely

on exploiting the resource illegally from areas with weaker governance. Forestry then

becomes more productive and households that are relatively more productive in forestry

can benefit by switching into forestry from other, less productive jobs. It is important to

recognize that simply being a concession member does not guarantee an increase in

income. If concession members fail to cooperate with their sustainable forest

management plan or if they cannot effectively monitor and enforce harvesting

55

restrictions, then it is possible that the concession will have a negative or no effect on

member household income (e.g., Alix-Garcia et al. 2005; Ostrom 1990; Baland &

Plattaneu 1996)22.

3.4 Estimation

3.4.1 Effect of concession membership on income

To estimate the effect of concession membership on annual income, we use a two-

stage least squares (2SLS) instrumental variable approach since it is possible that

concession membership may not be exogenous. For example, concession members likely

have connections within the community that are correlated both with the likelihood the

household is a concession member and with household income. Also, while concession

membership may affect income, it is possible that income may impact the likelihood that

a household is a concession member. Wealthier households may be more likely to be

concession members since wealthier households are typically the leaders within a

community. Alternatively, households that did not earn high incomes may be more likely

to join a concession for the opportunity to have a steady job. To mitigate the effects of

reverse causality and unobserved characteristics, we use an instrumental variable

approach. We construct an instrumental variable by matching households from the 2017

survey to households from the 2012 survey using coarsened exact matching methods.

22 We suspect this is the case with the recently-inhabited concession community group since they reside

within the forest and are unable to keep their land unless they are granted a concession. However, few of

the households have backgrounds in forestry and many prefer to rely on subsistence agriculture to make a

living so the people who go into forestry are likely less productive.

56

Matched households from the 2012 survey are a good predictor of concession

membership status for households in the 2017 survey because the households from the

2012 survey are located in the same communities as the 2017 households and have

similar opportunities to earn income. This instrumental variable mitigates the possibility

of reverse causality because the incomes of the matched 2012 households are unlikely to

determine the membership status of 2017 households. Similarly, it is unlikely that the

unobserved characteristics of the 2012 matched households are going to predict the

membership status or household incomes of the 2017 households in the survey. The

household characteristics we use for matching are household head age, household head

education, household head gender, whether the household depends on the forest for their

livelihood, number of individuals under 12 in the household, whether the household head

was born in the Petén, and level of trust23.

The coarsened exact matching method divides the 2017 data into strata. Each

stratum is comprised of observations that are exact matches based on the observable

covariates specified (Mishra, 2016; David et al, 2013; Hausman, 1996). All observations

from which any 2017 observation does not have at least one match from the 2012 data set

were dropped from the stratum. From the matched strata, we take the means of

concession membership status per stratum for the 2012 sample and code this average as 1

(indicating the household is a member) if it is greater than 0.5 and 0 (indicating the

household is not a member), if it is less than or equal to 0.5. This variable based on 2012

23 For a description of each variable used in the income effect analysis, see Table 4.

57

concession membership status is the instrument for the 2017 concession membership

status.

The instrument is valid if it is highly correlated with the variable for which it is

instrumenting and is not directly correlated with the dependent variable. In this study, the

matched 2012 concession membership status average must be correlated with 2017

membership status and the matched 2012 membership status must not be correlated with

household income. To see whether these conditions are met, we examine the first stage of

the 2SLS model. The results show that the instrument is highly correlated with

concession status due to the F-statistic being greater than 10 (Table 23)24. We cannot

directly test whether matched 2012 membership status is correlated with 2017 household

income, or the exogeneity assumption, since we only have one instrument. However, we

conduct a falsification test by estimating the effect of the instrument on income for

observations that were excluded from the analysis, which are the households in

communities whose concession was canceled or suspended and the non-concession

communities. The results indicate that the instrument is not a significant predictor of

income for the subsample. The results of the first stage of the 2SLS model and the

falsification test are in Appendix B.1.

Using the instrument described above, we estimate the 2SLS results for

concession membership on income for all concession communities as well as

24 The exception to this is for the recently-inhabited community group, which has an F-statistic of 9.73.

This could be due to the relatively small number of observations compared to the nonresident and long-

inhabited groups.

58

nonresident, recently-inhabited, and long-inhabited communities separately using

equation (12) and equation (13).

𝐼𝑛𝑐𝑜𝑚𝑒𝑖 = 𝛼 + 𝜃𝐶𝑖 + 𝑋𝑖′𝛽 + 𝛾 + 𝜀𝑖 (12)

𝐶𝑖 = 𝜃𝐶𝑗 + 𝑋𝑖′𝛽 + 𝛾 + 𝜀𝑖 (13)

In equation (12) above, the annual income of household 𝑖 is a function of 𝐶𝑖,

which is the membership status of household 𝑖, 𝑋𝑖′, which represents the household-level

covariates for household 𝑖, 𝛾, which represents village fixed effects, 𝛼, which represents a

constant, and the error term 𝜀𝑖 . Equation (13) is a function for the instrument used for

concession membership. In equation (13), 𝐶𝑗 represents the concession membership

status of household 𝑗 where household 𝑗 is the match of household 𝑖. We control for

variables that impact income including the age, gender, marital status, and education

level of the household head as well as the amount of land owned by the household,

whether the household has savings, the number of children under 12 in the household,

and the education level of the spouse of the head of the household. Married participants

are more likely to earn higher household incomes because more than one individual may

contribute to annual income within the household. Older and more educated participants

will likely have more employment opportunities because they are more likely to have

more skills and experience. The number of children under 12 is a proxy for family

dependents. Households with more dependents will likely have lower incomes because

more time needs to be spent on caring for the dependents, which means less time can be

devoted to working. Households with savings or land in this area are more likely to have

higher incomes because they have more investment opportunities due to having assets

59

Additionally, we control for whether the household depends on the forest and the level of

trust of the respondent, which are variables that affect income in forest-dwelling

communities in the Petén. Being dependent on the forest and having a higher level of

trust imply that the respondent will be more willing to cooperate with other community

members and the rules outlined in a sustainable forest management plan, which

ultimately impacts household income. More detailed descriptions of the variables used to

estimate the income effect of concession membership are shown in Table 9.

60

Table 9. Variable Descriptions for Income Analysis

Variable name Description

Household income The total amount of reported income earned by the household in quetzals.

This includes income earned from forestry and non-forestry activities as

well as dividends earned from forest concessions.

Concession

membership

Indicates whether the household is a member of a community forest

concession in the Maya Biosphere Reserve. This variable is equal to 1 if

the household is a member of a community forest concession and 0 if it is

not

Household head age Represents the age of the household head of the survey participant.

Household head

education

Represents the highest level of education obtained by the household head.

Forest dependent Constructed from a Likert scale question on the 2012 and 2017 surveys

that asked to what extent the respondent agrees with the statement “We

depend on the forest resources for our livelihood.” This variable is equal to

1 if the participant responded “agree” or “strongly agree” and 0 if the

participant responded “strongly disagree,” “disagree,” or “neutral.”

Household head

gender

Observed based on the observed gender of the participant and their

relationship to the head of the household. This variable is equal to 1 if the

participant is a male and 2 if they are a female.

Savings Indicates whether the household has savings. This variable is equal to 1 if

the household has savings and 0 if it does not.

Born Petén Indicates whether the participant was born in the Petén. This variable is

equal to 1 if the participant was born in the Petén and 0 if they were not.

Spouse education Represents the highest level of education obtained by the spouse of the

household head.

Married Indicates whether the household head has a spouse or long-term partner.

This variable is equal to 1 if the participant responded “married” or

“unified” and 0 if the participant responded “divorced,” “single,” or

“widowed.”

Under 12 Indicates the number of children under 12 that live in the household.

Trust Indicates the participant’s response to the question “Do you think that you

can trust the majority of people?” This variable is equal to 1 is the

participant responded “You can trust some people” or “You can trust the

majority of the people.” This variable is equal to 0 is the participant

responded “You need to be very careful with everyone,” “You have to be

somewhat careful with everyone,” “It’s possible that you should be

careful,” “We don’t know,” or if the participant refused to answer.

Own Land Indicates the amount of land in manzanas owned by the household.

The data were collected from 2012 and 2017 household-level surveys in MBR communities.

61

3.4.2 Effect of concession management on conservation outcomes

The value of concessions as a standing forest is comprised of several ecosystem

services such as carbon sequestered from the atmosphere. We focus on carbon

sequestration as an ecosystem service as it is a global public good, can be measured using

available datasets (e.g., Baccini et al., 2012), and can be valued using the social cost of

carbon (Nordhaus, 2017). While other ecosystem services provided by the forest in the

MBR may also be important, they often exhibit high spatial dependence, cannot easily be

measured, and/or do not have an estimated marginal value.

The present social value of the MBR forest on concession land is the discounted

sum of private and public benefits. While forest concessions in the MBR increase

household income, it is important to assess the quantity and quality of the forest

conserved by the concession when considering the value of the community-based, CPR

management policy. Before estimating the effect of the concessions on deforestation, we

take several measures to control for the possibility that concessions were not randomly

sited. First, we take a random sample of points over the entire Maya Biosphere Reserve

using a grid with 100m by 100m cells and overlaying the grid with the reserve boundaries

in ARCGIS. The purpose of the grid sampling is to help control for spatial

autocorrelation by ensuring that we are not matching non-concession plots that are too

close to concession plots (Blackman, 2015). Then, we drop plots that are in a core zone

or in the MBR buffer zone because they are under different management systems. There

are four different land classifications in the MBR: core zone, buffer zone, multiple-use

zone under concession management, and multiple-use zone not under concession

62

management. For our analysis, we focus on the multiple-use zone of the MBR because

the core zone areas typically receive more conservation funding from the government and

are not managed by communities, and the buffer zone contains titled land where clearing

forest is a legal option for households. Within the multiple-use zone, there are tracts of

land that, while still within the MBR boundaries, are not managed as a concession or core

zone area.

Matching typically produces regression coefficients that are more accurate and

robust to misspecification than only using a regression model (Imbens and Wooldridge,

2009; Ho et al., 2007). To match concession area pixels with pixels that are in the

multiple-use zone of the reserve, but are not part of a concession, we use a propensity

score, nearest neighbor matching model and drop plots that are unmatched before using a

panel estimator with year and concession fixed effects for the impact of concession

management on deforestation. The logistic regression results used for matching are in

Appendix B.1.

We restrict the matching analysis to areas of the multiple-use zone not under

concession management because they are the closest counterfactual to the forest

concessions. Both land areas are within a nature reserve created with the intent to

conserve the forest resources, but the concessions are managed by a community-based

common property resource management system while the other areas within the multiple-

use zone are just given the classification of being protected under the reserve without any

actual resources devoted to guarding the land like in the core zone. However, since the

MBR is technically a nature reserve, this status may be a deterrent to clear forest land that

63

does not exist in other areas of Guatemala. Land in the non-concession multiple-use zone

is covered with the same type of forest and is under similar deforestation threats, such as

illegal logging and slash and burn agriculture, as land under concession management

(Radachowsky et al., 2012). In other words, these areas most closely represent what

“would have happened” to the forest under concession management if the concession was

never implemented. We estimate the effect of being under concession management on

deforestation using the fixed effects panel estimator with year and concession-level fixed

effects shown in the equation (14) below.

𝑦𝑖 = 𝛼 + 𝜃𝐶𝑖 + 𝑋𝑖′𝛽 + 𝑇 + 𝛾 + 𝜀𝑖 (14)

In equation (14), 𝑦𝑖 is equal to 1 if pixel 𝑖 is deforested, 𝐶𝑖 equals 1 if the pixel is under

concession management, T represents the year fixed-effects, 𝛼 represents a constant,

𝑋𝑖 represents the characteristics of the forest land area 𝑖, 𝛾 represents the concession-level

fixed effects, and 𝜀𝑖 is an error term. In addition to whether the pixel is under concession

management, we control for distance to the nearest road, distance to the nearest

archaeological site, soil nutrients, elevation and precipitation levels. More detailed

descriptions of each of the covariates and dependent variables used to estimate the effect

of concession management on conservation are shown in Table 10.

64

Table 10. Variable descriptions for conservation analysis

To calculate the amount of CO2 stored by the additional hectares of forest

conserved, we convert the woody biomass layer described in Baccini et al. (2012) into

CO2. Although the households that participate in community forest management are

required to manage the forest sustainably, there is concern that concession logging

practices may degrade the quality of the forest even if they are reducing deforestation

overall (Frost & Bond, 2008). If, for example, concessions are selectively extracting

Variable name Description

Forest loss Represents the forest loss in each year from 2012 to 2017. The variable is

equal to 1 if the 100m by 100m pixel was deforested in a given year. A pixel

is “deforested” if the amount of forest on the pixel drops below 25%.

Carbon This variable is constructed from the Aboveground live woody biomass

density layer from Global Forest Watch. The data is at a 30-meter resolution

for the year 2000. The CO2 value per hectare is estimated from this layer as

50 percent of biomass density values multiplied by the ratio of the molecular

weight of carbon and CO2 (44/12) (Baccini et al., 2012; GlobalForestWatch,

2018).

Current Concession This variable is equal to 1 if the 100m by 100m pixel is under concession

management and 0 if it is not. The separate variables for each type of

concession are nonresident, long-inhabited, recently-inhabited, and

industrial.

Distance to road Indicates the distance of each pixel to the nearest road in meters.

Distance to

archaeological site

Indicates the distance of each pixel to the nearest archaeological site in

meters. The archaeological sites considered are el Mirador, Tikal, and

Yaxha-Nakum-Naranjo, which are the three most visited archaeological sites

in the Maya Biosphere Reserve.

Soil Nutrients An index for the amount of nutrients in the soil ranging from 1, meaning no

or few limitations, to 7, meaning water bodies, or non-soil areas

Elevation Taken from the Advanced Spaceborne Thermal Emission and Reflection

Radiometer (ASTER) Global Digital Elevation Model (GDEM), which is a

product of METWe and NASA. The resolution is 70m and the unit is meters

with 0 meters being at sea level.

Precipitation Represents the average rainfall in millimeters for each pixel for each year

from 2012 to 2017.

Unless otherwise mentioned, the data are at the 30 by 30-meter pixel resolution.

65

forest on the areas that sequester large amounts of carbon dioxide, then their social value

may be less than the average amount calculated from the woody biomass layer. To

address this issue, we compare the tons of CO2 per hectare of just the forest lost within

concession boundaries to the tons of CO2 values per hectare lost in areas outside of the

concession boundaries using a matched panel model with year fixed effects from 2012 to

201725. By comparing the CO2 values on just the areas deforested between 2012 and

2017, we determine whether the pixels lost within concession boundaries sequester

less CO2 than pixels lost outside of the concession boundaries.

3.5 Results

3.5.1 Income effect

The results of the 2SLS model for the effect of concession membership on income

are shown in Table 11. The results show that, on average, concession members earn

about 16,500 more quetzals (about $2,20426) per year than nonmembers in the same area.

This result varies by community type with nonresident and long-inhabited concession

members earning 21,490 (about $2,865) and 19,043 (about $2,539) more quetzals per

year than nonmembers in the same communities respectively. When comparing to the

average incomes for each concession type and the average income for all of the

concession types combined (Table 7), this value implies that being a concession member

increases annual household income between 40 and 50% on average. While this is a

25 We construct the variable for CO2 on pixels with forest loss by interacting the annual forest loss variable

by the carbon values calculated from the woody biomass layer (Baccini et al., 2012) 26 The dollar to quetzal exchange rate used is 7.5.

66

large increase, without access to a forest concession, many of these households would

lack a steady source of income. Additionally, concession members not only benefit from

a higher-than-average daily wage, but also receive annual dividends from the concession

profits. For example, in one of the long-inhabited concessions, Carmelita, the net profits

in 2016 were about 3 million quetzals (about $400,000). About 30% of the profits were

paid to concession members in dividends (about 5,000 quetzals per member) regardless if

they harvested timber or non-timber forest products. Concession members also get first

priority for jobs harvesting timber in the concession. These jobs pay between 200 and

300 quetzals per day, which amounts to between 21,000 and 37,000 quetzals per year per

forestry job that would not have existed if the concessions were not established27.

27 The net concession profits are from “Formato Para La Actualización del Plan de Manejo Integrado de

recursos” provided by the Cooperative Carmelita concession board members. The wage and dividend

information is taken from our 2012 and 2017 household panel of concession members and nonmembers.

67

Table 11. Two-stage least squares results for the effect of concession membership on

income

As a robustness check, we test whether concession membership affects income

using a matched, ordinary least squares (OLS) regression for households surveyed in

2017. To match concession member to nonmember households, we first use a logistic

All Communities

Long-

inhabited

Recently-

inhabited Nonresident

Concession membership 16,533*** 19,043*** -10,538 21,490***

(6,173) (4,341) (15,468) (6,954)

Household head age -25.43 -294.0*** 283.9 38.36

(123.5) (43.8) (343.6) (167.4)

Household head education 879.7 1,402 -1,339 1,330**

(586.6) (1,486) (1,845) (678.8)

Forest Dependent 675.0 11,681*** -7,156 -157.7

(4,673) (731.8) (15,064) (6,007)

Household Head Gender 6,132 10,297*** -12,630 11,605***

(4,279) (2,253) (14,022) (3,652)

Savings -8,211* -18,600*** 5,628 -7,394

(4,249) (4,721) (20,888) (4,704)

Born Petén -1,746 -9,429** 18,609 -1,720

(3,922) (4,620) (12,751) (5,431)

Spouse education 1,624*** 2,055* 1,620 1,295*

(642.7) (1,228) (2,413) (773.3)

Married 11,910*** 6,385 1,397 17,082***

(11,910) (11,213) (17,653) (4,257)

Under 12 2,043* 4,618*** -940.6 8.350

(1,097) (243.5) (3,538) (1,557)

Trust -7,197** -2,836** 3,773 -13,448***

(3,597) (1,360) (10,270) (2,865)

Own Land 260.2*** 335.7*** 351.9** 189.4

(77.3) (23.8) (175.4) (137.3)

Constant 12,624 34,074 22,655 -1,801

(13,619) (35,863) (53,171) (14,932)

Observations 642 166 86 390

R-squared 0.110 0.211 0.104 0.132

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors clustered at the village level are inside the

parenthesis. All values are adjusted for inflation. Results include village fixed effects. Observations

that were unmatched and that reported income above 300,000 quetzals a year were dropped from the

analysis. The first stage results are in Appendix B.1.

68

regression to calculate the probability of being a concession member based on observable

characteristics28. Then, we drop observations that were not matched and regress

concession membership on income using an OLS regression. The results of the matched

OLS regression are shown in Appendix B.1. For all concession types as well as

nonresident and long-inhabited communities separately, the results shown in Appendix

B.1 are similar to the results from the 2SLS model shown in Table 11. While the

magnitudes for the matched OLS regression are smaller than those in the 2SLS models,

the results of each model show that concession membership has a positive and significant

effect on income for most concession communities.

Unlike the effect on nonresident and long-inhabited concession member

households, the effect of concession membership on income for recently-inhabited

households is negative and insignificant in the 2SLS model, but positive and significant

in the matched, OLS regression. We suspect that the effect of concession membership on

income in recently-inhabited concessions is inconclusive because recently-inhabited

communities do not have backgrounds in forestry and most of the jobs are in agriculture

as shown in Table 2. It is possible that the concession members in recently-inhabited

communities do not actually want to participate in sustainable forest management or find

it difficult to cooperate with each other because they have more of an incentive to

illegally convert the forest land to agriculture due to their limited forest-based histories.

Recently-inhabited communities, however, are located within the MBR boundaries and

28 The results of the logistic regression used to find the predicted probability of being a concession member

are shown in Appendix B.1.

69

do not have titles to their land (Radachowsky et al., 2012). Thus, if they want a legal,

land-use right to the forest land, they are required to be granted a forest concession.

Additionally, three out of the four recently-inhabited concession groups that were granted

a forest management contract through CONAP have since been canceled or suspended

because they did not abide by the rules of the sustainable forest management plan

(Radachowsky et al., 2012). This suggests that they are not benefiting from the system

and have less of an incentive to sustainably manage the forest to protect their land-use

rights.

We also examine the effect of concession membership on income over time using

the panel of 113 households. The results of the fixed-effects panel model for concession

membership on income are shown in Appendix B.1. Although the results are

insignificant, the magnitude of the effect of concession membership on income is

positive, which further suggests concession membership has a positive effect on annual

household income and this effect remains positive over time29.

3.5.2 Conservation effect

The results show that all concession types reduce deforestation, although some

reduce deforestation by a greater extent than others (Table 12). On average, long-

inhabited concessions reduced deforestation by 3.8% from 2012 to 2017 relative to how

much the land would have been deforested if it was not under concession management.

29 We suspect the effect is insignificant due to the small amount of nonmember observations in the sample.

We was unable to estimate the income effect with a panel for recently-inhabited households due to an

insufficient number of nonmember, recently-inhabited households that were surveyed in 2012 and 2017.

70

Table 12. Effect of concession management on deforestation

Similarly, recently-inhabited, nonresident, and industrial concessions reduced

deforestation by 4.86%, 4.23%, and 5.61% respectively. We use the deforestation effects

for each type to calculate the hectares of forest conserved over the five-year time span of

this analysis. We first use the 2000 tree cover data described in Hansen et al. (2013) and

the average annual deforestation rate for the control group from 2001 to 2017 (about

1.7%) to determine what the tree cover reduction would have been if the concessions did

not exist. Then, we use the deforestation coefficients to determine how many of the

deforested hectares were conserved because the land was under concession

All

Concessions

Long-

inhabited

Recently-

inhabited Nonresident Industrial

Current Concession -0.0420*** -0.0379*** -0.0486*** -0.0423*** -0.0561***

(0.000253) (0.000506) (0.00127) (0.000355) (0.000517)

Distance to road -2.29e-06*** -3.87e-06*** -7.38e-06*** -3.25e-06*** -6.34e-06***

(4.09e-08) (7.99e-08) (1.42e-07) (6.59e-08) (1.01e-07)

Distance to

archaeological site 9.56e-08*** 1.00e-07*** 3.70e-07*** 3.10e-07*** 3.18e-07***

(9.74e-09) (1.88e-08) (2.49e-08) (1.42e-08) (1.84e-08)

Soil Nutrients 0.00675** 0.00817* -0.00059 0.01140*** -0.00370

(0.00312) (0.00440) (0.00537) (0.00381) (0.00432)

Elevation 6.07e-05*** 0.000139*** 0.000213*** 0.000169*** 0.000123***

(1.89e-06) (4.06e-06) (6.50e-06) (3.50e-06) (3.73e-06)

Precipitation 3.03e-06*** 5.10e-06*** -3.40e-07 3.35e-06*** -1.73e-06***

(2.60e-07) (5.84e-07) (7.52e-07) (3.38e-07) (5.66e-07)

Constant 0.0142*** -0.0115** -0.0147** -0.0190*** 0.0173***

(0.00326) (0.00481) (0.00605) (0.00408) (0.00472)

Observations 4,208,562 1,997,364 1,311,114 2,504,610 1,961,778

Number of Pixels 701,427 332,894 218,519 417,435 326,963

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are inside the parenthesis. The “number of

pixels” represents the number of land parcels in the analysis and the “observations” row represents the

total number of observations over the entire time period. For a description of each variable used, see

Table 10.

71

management. The results in Appendix B.2 show that the concessions collectively saved

about 1,514 hectares from deforestation from 2012 to 2017.

The results in Table 13 show that, on average, the areas of forest lost in the

concessions contain about 24 tons of CO2 per hectare less than areas outside of the

concession boundaries.

Table 13. Effect of concession management on CO2 sequestered on lost forest

This suggests that the area of forest lost within the concession boundaries released

less CO2 into the atmosphere on average than the forest loss outside of the concession

boundaries. The exception to this result is the nonresident concessions. On average, the

forest areas lost within nonresident concessions had about 9.5 more tons of CO2 per

All Concession

Types

Long-

inhabited

Recently-

inhabited Nonresident Industrial

Current Concession -24.10*** -50.84*** -14.51*** 9.505*** -40.58***

(0.464) (0.900) (0.578) (1.901) (2.122)

Distance to road 0.00374*** 0.00437*** 0.00483*** 0.00465*** 0.00478***

(0.00013) (0.00013) (0.000134) (0.000135) (0.000136)

Distance to

archaeological site 0.000112*** 3.76e-05*** -1.28e-05 -4.86e-06 -5.16e-06

(1.21e-05) (1.27e-05) (1.28e-05) (1.28e-05) (1.29e-05)

Soil Nutrients -28.08*** -28.44*** -28.70*** -28.84*** -28.66***

(2.266) (2.277) (2.273) (2.286) (2.285)

Elevation 0.460*** 0.461*** 0.454*** 0.455*** 0.455***

(0.00269) (0.00277) (0.00276) (0.00280) (0.00280)

Precipitation -0.0137*** -0.0140*** -0.0138*** -0.0139*** -0.0138***

(0.000333) (0.000338) (0.000338) (0.000339) (0.000338)

Constant 272.20*** 273.40*** 275.30*** 275.30*** 274.90***

(2.527) (2.547) (2.542) (2.559) (2.558)

Observations 233,147 215,837 225,531 211,604 211,369

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are inside the parenthesis. Coefficients are in

tons of CO2 per hectare. The observations used are the pixels that were deforested from 2012 to 2017 within concession boundaries. For a description of each variable used, see Table 10.

72

hectare than similar areas, which suggests that the areas of forest being protected by the

nonresident concessions store less CO2 on average than areas that were lost. The results

for the carbon sequestration benefits adjusted for the specific carbon values of lost forest

areas are shown in Appendix B.2.

The effect of concession management on deforestation reduction from 2012 to

2017 is the smallest for long-inhabited concessions and the largest for industrial

concessions. However, when we estimate the CO2 losses on the deforested areas, there is

a smaller amount of CO2 emitted from forest loss within the long-inhabited concession

boundaries than within the other concessions.

3.5.3 Conservation and income trade-offs

For long-inhabited and nonresident concessions, community forest management

in the MBR increases income for households without increasing deforestation. The long-

inhabited concessions increased annual household income for concession members by

about $2,539 per year and prevented about 335 hectares of forest loss with high carbon

values. Similarly, nonresident concessions decreased deforestation by 622 hectares from

2012 to 2017, and increased annual household incomes for concession members by about

$2,865.

The long-inhabited and nonresident concessions in the MBR show that

community forest management increases income for households without increasing

deforestation. However, there appears to be a trade-off between forest quality and

household income. The impact of forest concession membership on household income in

73

long-inhabited concessions is about $300 less per year than the impact in the nonresident

concessions. However as shown in Table 13, the areas protected by the nonresident

concessions have lower carbon values than the forest lost within the nonresident

concessions. This suggests that nonresident households may be exploiting the higher

quality forest, which leads to higher private benefits at the expense of additional carbon

sequestration.

Not all concessions types succeeded at providing a sustainable source of income

for households while reducing deforestation. Recently-inhabited concessions reduced

deforestation by about 4.9% from 2012 to 2017. While this avoided about 66 hectares of

deforestation, there is little statistical evidence that recently-inhabited concession

members benefited from concession membership. This suggests that there is a trade-off

between deforestation reduction and livelihood benefits in recently-inhabited

communities in the MBR. This outcome may relate to the typical background of

households in recently-inhabited concessions, which are comprised more heavily of

recent migrants to the MBR. Unlike the long-inhabited concession communities that are

comprised of households with forest-based histories and lived within the reserve

boundaries for multiple generations, many households in recently-inhabited communities

settled within the MBR boundaries around the time it was created and had little

experience with forestry.

74

3.5.4 Concession valuation

The value of the land under concession management in the MBR is the value of

the increased carbon sequestration and the additional household income concession

member households receive. To calculate the private benefits of the concessions, we

assume the annual household income impact shown in Table 11 is the same for each year

from 2012 to 2017. We calculate the value of the increased carbon sequestration due to

prevented deforestation by estimating the cumulative sequestered carbon rental value

from 2012 to 2017. To estimate the carbon rental value, we first find the asset value of

the carbon sequestered due to prevented deforestation from 2012 to 2017 using $31 as the

social cost of carbon. As shown in Table 14, this value is $15,714,443. Then, we use a

5% discount rate to calculate the average annual rental value of the carbon sequestered

over the five-year period.

75

Table 14. Cumulative value of land under concession management from 2012 to 2017

As shown in Table 14 above, the cumulative value of household income and

carbon sequestration benefits from forest concession management in the MBR from 2012

to 2017 is $17,166,005, which equates to about $34.05 per hectare. When estimated

separately, the per hectare values of long-inhabited, recently-inhabited, nonresident, and

industrial concession management separately are about $48.87, $8.27, $32.94, and $9.82

per hectare respectively.

All Community

Types

Long-

inhabited

Recently-

inhabited Nonresident Industrial

Average annual income

effect per household $2,204.42 $2,539.04 - $2,865.29 N/A

Concession member

households 1,218 454 65 699 N/A

Cumulative Income effect

(2012-2017) $13,424,947 $5,763,615 - $10,014,191 N/A

Asset value of carbon

sequestered (2012-2017) $15,712,443 $3,496,149 $710,520 $6,176,316 $5,329,458

Cumulative carbon rents

(2012-2017) $3,741,058 $832,416 $169,171 $1,470,551 $1,268,919

Hectares 504,108 134,978 20,445 348,686 129,164

Cumulative value

(income and carbon

rents) $17,166,005 $6,596,031 $169,171 $11,484,742 $1,268,919

Cumulative value per

hectare $34.05 $48.87 $8.27 $32.94 $9.82

Annual Value per hectare $6.81

External Funding $11,670,105

Total net value $5,495,900 Total net value per

hectare $10.59 Total annual net value per

hectare $2.18 The income in the "All community types" column is calculated using the income effects regression

coefficient for the entire sample. All income values are adjusted for inflation. The quetzal to USD

exchange rate used is 7.5. The carbon sequestration rental value is calculated using a 5% discount rate as

shown in Nordhaus (2017). The values for cumulative carbon rents are the sum of the annual carbon

rental values for each year from 2012 to 2017. The values for all community types represent the average

values among the concessions. The income effect for recently-inhabited concessions is not statistically

different from 0. Due to limited information on external funding, we cannot accurately report the

external funding for each concession classification.

76

The organization that oversees the concessions is the Association of Forest

Communities in the Petén (ACOFOP). ACOFOP receives grant funding from

organizations such as the Inter-American Foundation, Margaret A. Cargill Foundation,

Ford Foundation, ClimateWorks Foundation, and USAID and partners to foster

conservation efforts and economic development of surrounding communities. ACOFOP

uses these grants to manage the concessions and provide the initial investments in

equipment to add value to the harvested forest products. As shown in Table 14, the

amount these organizations contributed to concession management from 2012 to 2017 is

approximately $11,670,10530. When considering these costs, the annual net value of

concession management from 2012 to 2017 is about $2.18 per hectare.

3.6 Conclusion

This paper develops methods to evaluate the benefits of a community-based,

common property resource management system. Ostrom (2009) has observed that

common property systems that manage resources effectively, provide benefits to

community members, and protect public goods like forests or water have long existed. As

a result, policy makers have been encouraged in recent years to implement common

property systems as a way to protect natural resources in tropical forest regions where

property rights are insecure, and open access exists. Few studies, however, have

examined whether benefits of establishing such systems exceeds the costs, in part

because it is difficult to quantify the benefits. Thus, while many assessments have now

30 This value reflects the values reported in Gray et al. (2015).

77

established that CPR management systems can reduce externalities, and in particular

deforestation, no studies to our knowledge have estimated the private and public benefits

of a CPR management system. We address this issue by developing methods to calculate

the benefits of land tenure and forest management in a CPR management system in the

Maya Biosphere Reserve in northern Guatemala.

To accomplish this, we use a survey of members of the MBR forest concessions,

and nonmembers in communities in and around the reserve in two different time periods.

We use a novel instrumental variable approach to control for selectivity to estimate the

effect of membership on income and use this measure as an estimate of the productivity

gains associated with the concessions. To complete the analysis, we calculate the value of

the gains in carbon due to the concession management system using the social cost of

carbon.

The results demonstrate that community-based CPR management can have

significant welfare benefits from an environmental conservation and development

perspective. These benefits vary by concession classification. For example, Long-

inhabited concessions are the most valuable per hectare and recently-inhabited

concessions are the least31. In long-inhabited and nonresident concessions, the value

added from the increase in household incomes attributed to concession membership is

greater than the carbon sequestration values. This suggests that community-based CPR

management policies can improve livelihoods in countries with common property

resources.

31 Note that the income effect for recently-inhabited concessions is not statistically different from 0.

78

Our estimate is likely to be a lower bound for their actual values. The income

effect is likely underestimated because industrial concessions provide job opportunities to

households not associated with a community concession in communities around the

Petén. Although they are still required to manage the forest sustainably and, as shown in

Table 12, have succeeded in reducing deforestation, industrial concessions are not

managed collectively by local households, but are instead managed by private companies.

Since workers do not have a direct stake in concession profits nor in protecting the forest

like in the community concessions, if industrial concession workers are in our dataset,

they are considered to be nonmembers. Additionally, there are several in-kind benefits

concession members receive that are not quantified in the dataset including life insurance

and scholarships. Also, as shown in Appendix B.2, concession management has a

positive effect on preserving wildlife habitat, however this effect is not quantified in the

valuation.

Like many community-based resource management policies in developing

countries, MBR concessions are partially funded through international conservation and

development organizations (Gray et al., 2015). This study shows that the value of the

MBR concessions outweighs the costs. Although this estimate is a lower bound for their

actual value, in all cases, the community-based CPR management system succeeds in

reducing deforestation, which resulted in a carbon sequestration rental value of about

$3,741,058 million from 2012 to 2017. However, the conservation benefits of increasing

CO2 sequestration comprise less than half of the value of the forest concessions. The

results in Table 14 show that, without considering the private benefits, the net benefit of

79

implementing the forest concessions is negative versus about $2.18 per hectare when

considering the community development impacts. This suggests that if households were

not able to profit from the forest resources and were only compensated for the

environmental benefits of the system, their incentive to protect the forest would be

significantly reduced.

When implementing a CPR management system, it is important to consider the

implications on the local communities as well as the environment. Our results suggest

that involving local households in CPR management can result in significant societal

welfare gains. Additionally, our results show that while conservation and development

objectives can be simultaneously achieved, but there may be a small trade-off between

household income and exploiting areas with high carbon values. For example, the

nonresident concession member households benefit the most from concession

membership, but they are likely exploiting areas with high carbon values to gain more

income.

When managing common property resources, allowing local communities to take

part in the management process raises the land value of the resource area and incentivizes

households to effectively manage the forest to maximize their earnings from the resource.

These findings are especially relevant in a developing country context where households

that live near resources frequently depend on extracting the resources or using the land

for their livelihoods. All in all, if successful, community CPR management has the

potential to generate public and private benefits through conservation and economic

development.

80

Chapter 4: Timber or Carbon? Evaluating forest conservation strategies through a

discrete choice experiment

4.1 Introduction

Conserving tropical forests in developing countries is not an easy task because

property rights are often insecure, and communities located in the forest may depend on

converting forested land to agriculture or extracting forest resources as a source of

income. Conversion of forests to agriculture currently accounts for 15 to 20% of the

world’s annual carbon emissions (IPCC, 2014). Although timber management in the

tropics and elsewhere can be done sustainably to reduce emissions (e.g. Roopsind et al.,

2018; Tian et al., 2018), there is concern that even sustainable timber production leads to

forest degradation, carbon emissions, and biodiversity losses in the tropics (Schulze et al.,

2008; Ahrends et al., 2010; Brandt et al., 2016). Forest degradation in the tropics is

especially problematic because there is often significant damage done when logging

occurs (Putz et al. 2012; Martin et al. 2015). Currently, around 20.5 million hectares of

forests in developing countries are managed in FSC certified timber reserves (FSC Global

Development, 2019), however, shifting these forests to carbon reserves could increase

carbon sequestration.

This study builds on several studies that consider whether payments for

ecosystem services (PES) programs can be deployed in the tropics to conserve resources

81

(e.g., Vorlaufer et al., 2017; Jayachandran et al., 2017; Randrianarison et al., 2017; Duke

et al., 2014; Ortega-Pacheco et al, 2009; Wunder et al, 2008; Wunder and Albán, 2008;

Kosoy et al, 2008; Kosoy et al., 2007). The literature suggests that there is the potential to

lower carbon emissions in the tropics with sustainable and reduced impact logging (e.g.,

Pearson et al., 2014), but few studies have considered whether groups with forest tenure

rights would be willing to give up timber and non-timber forest product (NTFP)

harvesting to sequester carbon. This study addresses this issue by examining the trade-off

between timber production and carbon storage in forest concessions where individuals

have rights to manage forest resources. Specifically, we examine whether individuals

with rights to forest concessions already managed with FSC certification in a developing

country would be willing to further reduce timber production to gain payments for carbon

sequestration. We then determine how much they would be willing to accept to give up

timber harvesting, in conjunction with other important attributes.

Stopping harvesting and reducing emissions, however, may be costly. Tenure

arrangements for groups that allow sustainable timber harvesting link the quality of the

resource to profits and household income (Bocci et al., 2018; Meilby et al., 2014;

Fortmann et al., 2017). These exclusive land use rights provide households with an

incentive to protect forests, which diminishes overexploitation. Thus, more income can

be generated from the common-pool resource (Scott, 1955; Gordon, 1954). If, on the

other hand, households received a payment to stop extracting resources, ensuring that this

is effective would require strict monitoring of forest outcomes and linking the payments

households receive to these outcomes.

82

When deciding whether to participate in decentralized forest management,

households must consider how forest management affects their access to the resource and

income-earning potential. This study puts these household-level decisions into the

context of potential PES contracts in the Maya Biosphere Reserve (MBR) that would

restrict land use and other income-earning activities in exchange for an annual payment.

The MBR is protected through the allotment of concession management agreements to

individual communities who must maintain forest cover in return for exclusive access to

timber and NTFP harvesting. Although this study is conducted in the context of the

MBR, the results of this study can be applied to PES contracts elsewhere. Many

developing countries have decentralized tropical forest management to local community

groups in exchange for exclusive land use rights in a similar way to the MBR (e.g.

Primack et al, 1998; Kumar 2002; Agrawal & Chhatre, 2006; Alix-Garcia, 2007; Miteva

et al, 2012; Meilby et al. 2014; Rasolofoson et al.,2015).

For example, this study considers the role of property rights by examining the

trade-off between carbon storage and timber harvesting. To receive payments for carbon

storage by reducing timber harvesting, communities would have to give up a portion of

their land-use rights and an external agency would have permission to closely monitor

timber flows and carbon in the area. In principle, people should be willing to trade these

rights in return for payments, but the payments for carbon typically come from

government sources (either nationally or internationally). Although timber harvesting

requires more time than conserving the forest to receive payments for carbon

sequestration, it is possible that those with tenure rights will not trust government to pay

83

for the carbon, especially when they may have to give up a fairly secure private stream of

revenue from timber and non-timber forest products.

Communities may also value forest resources for cultural or other economic and

non-economic reasons. For instance, MBR concessions currently manage a portfolio of

income generating activities that includes timber, non-timber forest products, and

tourism. They distribute the economic benefits of their activities to members individually

through wages or dividends, and through in-kind benefits that include public goods such

as schools, medical facilities, and other benefits. These cultural and economic benefits

could have important implications when measuring preferences because a contract for

carbon sequestration could alter access to forests for all purposes. Although not all

households are able to harvest non-timber forest products, NTFP harvesting is a

culturally significant activity in the MBR and it is possible that many households enjoy

having the option to harvest them and want to preserve NTFP harvesting traditions for

future generations (Nesheim & Stølen, 2012; Taylor 2010). Similarly, tourism is a

growing industry in the MBR, which may provide substantial benefits to residents in the

future.

In the MBR concessions, some benefits are distributed to concession members via

individual payments (wages or dividends) or group payments (e.g., provision of public

goods). Carbon sequestration contracts could shift payments either more towards

individuals or more towards the provision of public goods, depending on where the

proceeds are sent. We specifically test individual preferences for the type of payment in

our analysis. We also assess contract length to determine if households prefer to enter a

84

land use contract for a longer period of time. Stable work is scare in the MBR so it is

possible that households prefer a contract that guarantees them a longer-term stable

income (Radachowsky et al., 2012; Bocci et al., 2018). The subsequent sections describe

the attributes, data, and methods of the choice experiment followed by the model

specification. The final sections describe the results of the analysis and provide a brief

discussion of their policy implications.

4.2 Methods and Data

4.2.1 Maya Biosphere Reserve Household Characteristics

We administered a survey to 716 households in communities in and around the

MBR concessions during the summer of 2017. Using lists of community members

obtained from concession leaders, we randomly selected 25% to sample. Local

enumerators then visited each selected household and conducted the survey via an in-

person interview. If no adult members of the household were present, the enumerator

asked when the participant would be returning and set up a time to return. If no adult

members of the household were present when the enumerators returned, the enumerators

surveyed another concession member household we randomly selected from the list.32

While our original protocol called for providing a small remuneration to the survey

participants (around $3), we were asked by the community concession leaders to forgo

32 The overall survey response rate for households asked to take the survey was about 99.6%. There were 2

out of 716 households given the choice experiment that did not want to participate so we selected

alternative households in these cases. We also had to select alternative houses from the concession member

list in about 10% of the cases because we were unable to find the respondent to ask for their participation.

The majority of these cases were in nonresident communities.

85

this remuneration. Instead, we provided participants with cards that contained $3 worth of

airtime for their cell phones.

Our sample includes both members of the community concessions living in 19

communities, and nonmembers who live in the same set of communities. While non-

member households cannot currently receive profits from harvesting timber through a

forest concession, they could experience the impacts of a carbon program if it alters

outputs in timber or non-timber forest products. For example, if non-members work in

one of the mills owned by the concession, lower harvests would affect their livelihoods.

Additionally, they may be affected if the payments provide public goods from which they

can benefit (e.g., better roads, schools, or medical facilities) or if carbon payments are

provided to all households within a community. Despite these potential effects, non-

members do not have land-use rights to the concessions, and thus have less to gain or lose

with a change in how they are managed. This means that they will have different values

for the potential shift in property rights. To obtain the non-member sample, we selected

households neighboring those of the concession members surveyed. We assumed

neighboring non-member households have similar spatial and observable characteristics

to the concession member sample.

The full survey that we administered contained 8 parts with this choice

experiment occurring at the end. The first 7 parts of the survey focused on demographic

characteristics of the household, income generation, attitudes towards forest resources

and the concessions, and migration history. The final section included the choice

experiment elicitation and the follow-up questions. We developed and implemented the

86

script for the choice experiment with the enumerators to help respondents better

understand the consequences of their choices. The full script in English and Spanish is

shown in Appendix A.

Most of the head of households in the sample are males (Table 15), with an

average age of 46 years and about 7 years of education. Average household income

across the groups is around $4,608 USD (34,560Q) per year (Table 15). Concession

members have higher income than non-concession members by about 48% (Bocci et al.,

2019). Around 41% of concession member households have jobs in forest-related

activities.33

Table 15. Maya Biosphere Reserve Household Characteristics

Members Nonmembers

Forest-

dwelling

Non-forest

dwelling All

Male Household Head 80% 75% 77% 78% 77%

Female Household Head 20% 25% 23% 22% 23%

Born in the Petén 63% 63% 70% 60% 63%

Born outside of the Petén 37% 37% 30% 40% 37%

Average Age 50.45 42.46 42.33 48.69 46.43

Average Education (years in school) 6.54 7.07 6.28 7.10 6.81

Median Annual Household Income $5,493 $3,933 $4,597 $4,624 $4,608

Average Annual Household income

from forest harvesting activities $1,772 $595 $2,075 $688 $1,180

Percentage of households with a job

in a forest harvesting activity 41% 14% 49% 16% 28%

One dollar is equal to about 7.5 quetzals. The average annual income from forest activities includes

households that earn $0 from forestry.

The survey contained Likert-scale questions that examined the respondents’

attitudes towards environmental issues in the MBR (Table 16). The results suggest a large

level of interest in and concern about maintaining the forest resources of the Petén. The

33 The proportion of income earned from forest-related activities is derived from a 2017 household survey

of concession members and non-members. Table 2 shows the average income earned from forest-related

activities for the combined sample of concession members and non-members.

87

respondents seem largely aligned with the current policy that limits access to a large

amount of nearby forests in that a large portion disagree or strongly disagree that anyone

should be able to access the forests to cut trees or to harvest non-timber forest products.

The respondents are also somewhat neutral about whether agriculture threatens forest

resources. To assess whether individuals discerned a difference between cattle ranching

and other types of farming, we included a question specifically asking if cattle are

threatening the forests in the final 242 of the surveys collected. The results suggest that

our respondents do distinguish between these two types of production. The results of the

Likert scale questions also indicate the importance of non-timber forest products locally.

There is stronger support for harvesting non-timber forest products and engaging in

tourism than harvesting timber among all the individuals and among the subgroups of

individuals.

Table 16. Likert Scale questions on attitudes towards various environmental and

concession related issues in the MBR (1=strongly disagree; 5=strongly agree)

All

communities

Concession

Members Nonmembers

Forest-

dwelling

Non-forest

dwelling

Statement Avg n Avg n Avg n Avg n Avg n

I depend on the forest

resources for my livelihood 3.71 713 3.98 355 3.44 358 4.28 254 3.40 459

I am very worried about the

future of the forests in the

Petén

4.58 714 4.61 355 4.55 359 4.58 254 4.58 460

Anyone should be able to cut

wood from the Maya

Biosphere Reserve

1.72 709 1.70 352 1.73 357 1.75 254 1.69 455

Anyone should be able to

harvest non-timber forest

products from the Maya

Biosphere Reserve

1.79 714 1.76 355 1.82 359 1.83 254 1.77 460

Cattle ranching is threatening

the forests in the Petén 4.52 242 4.50 105 4.55 137 N/A 0 4.52 242

88

Table 16 (cont.)

All

communities

Concession

Members Nonmembers

Forest-

dwelling

Non-forest

dwelling

Statement Avg n Avg n Avg n Avg n Avg n

Agriculture is threatening the

forests in the Petén 3.19 711 3.16 354 3.22 357 2.98 252 3.31 459

Ecotourism harms the forests

in the Petén 1.83 707 1.78 354 1.88 353 1.78 252 1.85 455

Ecotourism harms the

cultural resources in the

Maya Biosphere Reserve

1.74 712 1.66 354 1.81 358 1.69 254 1.77 458

The forests should receive

strict protection without

being exploited by

concessions or other uses

3.42 712 3.14 354 3.70 358 3.18 254 3.55 458

Protecting the historical and

cultural resources such as

Tikal and el Mirador is

important

4.70 708 4.68 353 4.73 355 4.71 249 4.70 459

Extracting wood from the

Maya Biosphere Reserve is

an important source of

income for the region

3.75 702 4.00 351 3.50 351 4.07 251 3.57 451

Extracting wood from the

Maya Biosphere Reserve,

even if done sustainably,

harms the environment

3.22 710 2.86 353 3.58 357 3.04 252 3.32 458

Extracting non-timber forest

products from the forest

(such as chicle and xate) is an

important source of income

for the region

4.31 711 4.49 354 4.14 357 4.56 252 4.18 459

Ecotourism is an important

source of income in the

region

4.26 711 4.32 354 4.21 357 4.24 252 4.28 459

It is necessary that the

government spend more

money on protecting the

forest in the Maya Biosphere

Reserve against illegal

activities

4.52 711 4.54 354 4.50 357 4.53 252 4.52 459

In 20 years, there will be the

same amount of forest in the

Maya Biosphere Reserve

2.71 709 2.96 352 2.47 357 3.14 251 2.48 458

Only 242 respondents were asked whether cattle ranching is threatening the forests in the Petén.

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4.3.2 The Choice Experiment Instrument

Following recommendations outlined in Johnston et al. (2017), we used our findings

from several focus groups conducted in summer 2016 to identify important attributes of the

decision to enter a carbon contract. The focus groups consisted of concession members and

non-members invited from MBR communities. We invited the non-members to complete the

survey to help ensure that the results reflect an accurate valuation for all households in the

area, not just those directly involved in current concession activities (Wilson and Howarth,

2002). During the focus groups, we presented participants with lists of attributes they would

like included in a concession contract under the assumption that similar attributes would be

valued in a contract to store carbon. We chose to present this in the context of the

concessions because member and non-member households were already familiar with the

concession contract structure and the strengths and weaknesses of the current concession

contracts.

The important attributes we identified were payment size, whether non-timber and

tourism activities could continue, and contract length. Using these attributes, we developed

an initial design that asked participants to choose between one of two contracts to store

carbon or the status quo (no contract option). The two carbon storage contracts contained

different levels of the attributes that we identified as important in the focus groups. After

developing an initial design, we had it reviewed by several individuals working at NGOs in

the region who are familiar with the concession activities. To select the pictures used for the

choice experiment, we intercepted individuals in Petén communities, presented several

pictures to them, asked them what they thought the picture described, and then selected

pictures based on these perceptions. We developed a design to minimize D-error and began

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testing the instrument in the field, following the recommendation in Johnston et al. (2017).

The instrument was blocked into 6 blocks of 6 choice occasions. After obtaining the first 25

responses in a test community, we estimated a Random Utility Model (RUM), used the

resulting parameter estimates to rerun the design to further minimize D-error, and

implemented the new design. We updated the design for approximately one week with new

data from responses obtained each day. Based on the findings from the focus groups and the

results from the test community, we used five attributes in the final instrument for this

analysis: level of carbon storage, contract length, payment per year of the contract, whether

NTFP harvesting or ecotourism is permitted, and whether the payment is at the community or

individual level (Table 17).

Table 17. Choice experiment levels and attributes

Attribute Levels

Carbon storage Increase carbon storage by 30% and decrease timber harvesting by 30%

Decrease carbon storage by 30% and increase timber harvesting by 30%

Keep timber harvesting levels the same and get paid for carbon storage

Contract length 5, 10, or 20 years

Other permitted activities Only permit NTFP harvesting

Only permit tourism

Permit both NTFP harvesting and tourism

Prohibit NTFP harvesting and tourism

Payment level Individual

Group

Payment amount 800, 2000, 3200, 4800, 10000, or 20000 quetzals

One U.S. dollar equals about 7.50 quetzals. The average annual income for MBR households is about

28,000 quetzals so the payment amounts ranged from 2.86% to 71.43% of the average income. Each

level of carbon storage is represented by a binary variable that equals 1 if the contract has that

attribute and 0 if it does not.

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Following Johnston et al. (2017), the enumerators were instructed to clearly

describe to households how the MBR was formed, what MBR residents are currently

doing to help sequester carbon in the reserve, and ask the respondents several questions

while describing the scenario to help ensure that the respondent stayed focused and

understood the scenarios. To enhance policy consequentiality, the enumerators told

respondents to think carefully about their choices because their choices would be

considered when policy makers offered a price for carbon in future carbon sequestration

programs in the MBR. Enumerators also described the status quo option as the household

being permitted to participate in ecotourism and NTFP harvesting, not receiving a

payment to store carbon, and not receiving an additional payment. The choice experiment

script that was administered to MBR households in 2017 is in Appendix C.1.

The three levels of the carbon storage attribute represent the range of decisions

that individuals can plausibly undertake. First, as shown in Fortmann et al. (2017) the

concessions have already reduced carbon emissions because they are measurably

reducing deforestation, however, the concessions have not been explicitly remunerated

for the carbon they have stored to date (Guzman, 2019). Thus, one option would be for

the communities to receive payment for the carbon benefit they are already providing.

Second, the concessions can reduce their timber harvesting activities, which would

further increase carbon storage in the region (see Pearson et al., 2014). This would

reduce their timber revenues, but they would be compensated via carbon payments.

Alternatively, the concessions could increase their timber harvesting activities, which

would also increase their revenues, but reduce the carbon stored in the concession.

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The contract length attribute describes the number of years the household would

have to agree to abide by the restrictions in the contract. Participants were told they

would receive the payment shown for each year of the contract and be subjected to strict

enforcement and monitoring of the carbon program. We conveyed that the monitoring

that would occur as part of the carbon program would be significantly more intensive

than current monitoring activities on the current set of programs. We also conveyed that

the concessions could lose the carbon payments if they do not abide by the restrictions.

The payment attribute shows how much the household would be compensated for

each year of the contract. Households were instructed in the survey script that the

payment is the net effect of all of the possible changes to their salaries, dividend

payments, and direct or in-kind carbon payments that result from making the adjustments

described within the contract. For example, if a household selected a contract that

required them to increase carbon storage by 30% by decreasing timber harvesting for

10,000 quetzals per year, the household should expect their net income to change by

10,000 quetzals per year after taking into account the payment and all possible changes to

their annual income.

4.3 Model Specification

To analyze the choice experiment data, we start with the typical expression of

indirect utility Vj for individual i represented by equation (15),

𝑉𝑖𝑗 = 𝑣𝑖𝑗 + 𝜀𝑖𝑗 (15)

where Vij represents the observable utility component respondent i receives by choosing

alternative j and ɛij represents the random error component. We assume the respondent

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maximizes their utility when making a choice among the alternatives presented to them.

Hence, if respondent i chooses alternative j over another alternative (k), we assume

Vij>Vik. The probability of respondent i choosing alternative j over alternative k in choice

set c is shown in equation (16).

𝑝𝑖 (𝑗

𝑐) = 𝑝(𝑉𝑖𝑗 > 𝑉𝑖𝑘) = 𝑝[(𝑣𝑖𝑗 + 𝜀𝑖𝑗) > (𝑣𝑖𝑘 + 𝜀𝑖𝑘)], 𝑗 ≠ 𝑘 (16)

We estimate the probability of individual i choosing an alternative in the choice set c

(equation (16)) with a mixed logit. A mixed logit is more flexible than a standard logit

because it allows for random taste variation, unrestricted substitution patterns, and

correlation in unobserved factors over time (McFadden and Train, 2000). Equation (17)

shows the estimation of pij based on observable covariates of the individual (Zi) and

observable characteristics of the choice set from which individual i chooses alternative j

(Xij).

𝑝𝑖𝑗 = ∫exp(𝛽𝑖𝑋𝑖𝑗+𝛾𝑍𝑖)

∑ exp(𝛽𝑖𝑋𝑖𝑗+𝛾𝑍𝑖)𝐾𝑘=1

𝑓(𝛽|𝜃)𝑑𝛽 (17)

From equation (17), we estimate the respondent’s willingness to accept for each attribute

described in Table 19. This value represents the amount of money that must be given to a

person for them to be just as well off as they were before changing their behavior (Haab

and McConnell, 2002, Casey et al, 2008). If the respondent, for example, engages in 1%

more sustainable timber harvesting, they are changing their behavior by exerting

additional effort to harvest more timber and must be compensated accordingly. Assuming

Vij is linear and additive, we estimate the indirect utility function for the entire sample of

concession communities with equation (18).

94

𝑉𝐴𝑖𝑗 = 𝛽𝐴𝑋𝐴𝑖𝑗+ 𝛾𝐴𝑍𝐴𝑖

+ 𝜀𝐴𝑖𝑗 (18)

where the subscript A refers to “all” the sample. Due to the different backgrounds of

individuals in the sample, the attributes that maximize utility are likely not the same

across groups. For example, groups that reside within the forest would likely receive

more utility from being allowed to harvest non-timber forest products because

households have used NTFP harvesting as a stable source of income for multiple

generations and harvesting these products is culturally important to forest-dwelling

communities (Radachowsky et al., 2012; Plotkin & Famolare, 1992). Also, households

that are concession members will likely receive less utility from a carbon contract since

they have grown accustomed to earning a stable income from sustainable timber

harvesting. Because of these differences, we estimate separate indirect utility models for

concession members (equation (19)), nonmembers (equation (20)), forest-dwelling

households (equation (21)), and non-forest dwelling households (equation (22)). The

willingness to accept can then be represented as the ratio of each β for each attribute over

the β for the payment attribute (equation (23)).

𝑉𝐶𝑖𝑗 = 𝛽𝑐𝑋𝐶𝑖𝑗+ 𝛾𝐶𝑍𝐶𝑖

+ 𝜀𝐶𝑖𝑗 (19)

𝑉𝑁𝐶𝑖𝑗 = 𝛽𝑁𝐶𝑋𝑁𝐶𝑖𝑗+ 𝛾𝑁𝐶𝑍𝑁𝐶𝑖

+ 𝜀𝑁𝐶𝑖𝑗 (20)

𝑉𝐹𝑖𝑗 = 𝛽𝐹𝑋𝐹𝑖𝑗+ 𝛾𝐹𝑍𝐹𝑖

+ 𝜀𝐹𝑖𝑗 (21)

𝑉𝑁𝐹𝑖𝑗 = 𝛽𝑁𝐹𝑋𝑁𝐹𝑖𝑗+ 𝛾𝑁𝐹𝑍𝑁𝐹𝑖

+ 𝜀𝑁𝐹𝑖𝑗 (22)

𝑊𝑇𝐴 = −1 (𝛽𝑎𝑡𝑡𝑟𝑖𝑏𝑢𝑡𝑒

𝛽𝑝𝑎𝑦𝑚𝑒𝑛𝑡) (23)

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4.4 Results and Discussion

The results for the mixed logit model for all communities combined, communities

within the forest, communities outside of the forest, concession members, and

nonmembers are shown in Table 18. The results across the full sample show that

households prefer to sign a PES contract that sells carbon rather than remain in the status

quo. Households also show preference for contracts that are longer, allow for NTFP

harvesting, allow for ecotourism, and provide household-level payments instead of

community-level or group payments. There are also several household characteristics

that affect the likelihood that a household selects the status quo. The results for the full

sample and nonmembers show that residing within a forest-dwelling community and

having a female household head makes the respondent less likely to select the status quo.

For non-forest dwelling households, having an older household head makes the

respondent less likely to select the status quo.

For forest-dwelling communities, the results for households preferring carbon or

timber harvesting are insignificant, suggesting that households living in forest

communities do not strictly prefer carbon or timber payments. Forest-dwelling

households, however, have strong preferences for NTFP harvesting and ecotourism. In

long-inhabited communities, for instance, households have traditionally depended on

harvesting non-timber forest products for their livelihoods, and harvesting non-timber

forest products like xate is a culturally important activity (Radachowsky et al., 2012;

Plotkin & Famolare, 1992). Although income from xate is lower on average than income

96

earned from timber harvesting activities34, harvesting non-timber forest products such as

xate provides a stable source of income for the region and requires almost no initial time

or capital investment since it grows naturally in the MBR and there is no expensive

equipment needed to harvest the leaves. Additionally, xate harvesting gives women and

children the opportunity to participate in the labor force with flexible schedules since xate

harvesters are typically paid per bundle of leaves and can be harvested after doing

household chores or attending school (Nesheim & Stølen, 2012). We suspect that

households residing within forested areas selected contracts heavily based on having

access to the forest and NTFP harvesting.

In contrast, households that reside outside of the forest within the MBR buffer

zone show preferences for storing carbon over increasing timber harvesting. Although

these households also prefer to have access to the forest for NTFP harvesting and

ecotourism, the parameter estimates on these attributes are smaller than the same

parameters for the forest-dwelling communities that reside within the multiple use zone.

One possible reason why households that reside outside of the forest would like to store

carbon is that many households within these communities are not concession members,

but still would like to receive compensation for protecting the forest.

34 The results from a 2017 survey of MBR communities show that the average income for a NTFP

harvester is between 50 to 100 quetzals ($6.67 to $13.33) per day while the average income for a timber

harvester or tourism worker is between 200 and 300 quetzals ($26.67 to $40) per day.

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Table 18. Mixed logit results for contract attributes

The willingness to accept estimates calculated using equation (23) are shown in

Table 19. The attributes with positive coefficients are those for which households would

All

communities

Concession

Members

Nonmembers

Forest-

dwelling

Non-forest

dwelling

Payment amount (in

1000 Q) 0.0420 *** 0.0521 *** 0.0339 *** 0.0368 *** 0.0478 ***

(0.000004) (0.000007) (0.000006) (0.000008) (0.000006)

Store more carbon 449.57 *** 307.42 ** 593.57 *** 44.54 715.58 ***

(0.07697) (0.12372) (0.09822) (0.12188) (0.09944)

Keep the same

carbon storage 300.76 648.76 ** 6.79 586.51 372.07

(0.20227) (0.33387) (0.24680) (0.37521) (0.232.74)

Contract length 20.05 *** 23.32 *** 17.53 *** 17.05 ** 20.98 ***

(0.0041) (0.00686) (0.00514) (0.00714) (0.00509)

NTFP harvesting 1,252.72 *** 1,711.97 *** 946.37 *** 1,928.81 *** 919.15 ***

(0.08955) (0.16309) (0.10299) (0.17449) (0.09732)

Tourism 830.56 *** 1,142.67 *** 633.70 *** 1,211.49 *** 648.56 ***

(0.07180) (0.12412) (0.08731) (0.12880) (0.08670)

Group payment -225.93 *** -119.11 -289.57 *** -345.30 *** -163.88 *

(0.07082) (0.11480) (0.08962) (0.12225) (0.08774)

Status quo -2,694.18 *** -2,430.03 * -2,721.36 *** -3,939.65 *** -971.53

(0.85266) (1.2881) (1.0153) (1.31140) (0.71050)

Gender*status quo -1,076.00 ** -1,004.14 -1,133.51 ** -690.70 -744.55

(0.50039) (0.985.83) (0.56487) (0.76007) (0.62146)

Age*status quo 12.94 -32.38 17.27 -29.19 -31.63 **

(0.01643) (0.01793) (0.01847) (0.02048) (0.01549)

Education*status

quo -11.60 2.86 -8.00 0.21 -15.80

(0.00850) (0.01099) (0.01108) (0.01270) (0.01229)

Concession

member*status quo -606.81 --- --- 695.04 -823.53

(0.47606) --- --- (0.67611) (0.66121)

Forest-dwelling*

status quo -1,275 ** -951.17 -1,599.09 ** --- ---

(0.60653) (0.86106) (0.71645) --- ---

Number of

households 716 355 361 254 462

Observations 12,912 6,399 6,513 4,620 8,292

*** p<0.01, ** p<0.05, * p<0.1. Standard errors are in parenthesis. The results were divided by 1,000 to report

the coefficient values more concisely.

98

need to be compensated while the attributes with negative coefficients are those for

which households would be willing to give up money. If an attribute with a positive

coefficient were to exist in a contract offered to the average household, that household

would need to be compensated for that attribute and would be willing to accept a value no

less than the coefficient value.

On average, households are likely to choose a contract over the status quo and

these contracts are worth about $8,548 to households. This large value is consistent

across the models, suggesting strong preferences for the combined elements of the

contracts. This value illustrates incredibly strong local values associated with maintaining

forest cover, a result that is consistent with other results in our survey. For instance, a

majority of the respondents indicated that they depend on the forest resources (see Table

16), with 233 out of 254 respondents in forest-dwelling communities indicating that they

either “agree” or “strongly agree” that they depend on the forest resources for their

livelihoods. A majority of households also indicated that they are worried about the

future of the forests in the Petén, and a large majority prefer to maintain strict controls on

who can cut wood from the MBR (Table 16). Although MBR households prefer access

to the forest, the majority prefer that access is restricted via a contract.

For the entire sample, households place a $1,426 per year value on having the

option to receive a payment for increasing carbon storage by 30% and decreasing timber

revenues by 30%. Households that are not members of a concession place more value,

$2,337 per year, on increasing carbon storage by 30% by decreasing timber harvesting by

99

30%, while households that are members of a concession place $787 per year on this

option.

Concession members typically earn a living from harvesting timber, so they are

less willing to give up 30% of their timber harvesting for carbon payments. However,

reducing timber harvesting by 30% would decrease timber income for concession

members by about $532 per person per year on average35. The results show that

concession members on average are willing to take a pay cut of up to $787 per year to

receive payments for storing 30% more carbon instead of harvesting 30% more timber.

Then, after being compensated for a $532 reduction in timber harvesting income,

households would be willing to accept $25536 less per year to earn income from 30%

more carbon storage instead of 30% more timber harvesting. This implies that a payment

for a carbon storage program could result in significant household welfare gains if

implemented with minimal restrictions on NTFP harvesting and tourism.

Households in the MBR value longer contracts. For the entire sample, households

value each additional year of the carbon contract at $64. This value is highest for

nonmembers ($69). One explanation for this difference is that nonmembers do not have a

long-term contract for land use rights through a forest concession and want to experience

the benefits of a long-term contract. Interestingly, the value that forest-dwelling

communities place on longer contracts is similar to that of non-forest dwelling

communities. One potential reason is that stable work is scarce in both areas. Although

35 The average annual timber income is derived from concession financial records. A 30% reduction in

timber harvesting leads to a gain in 10.2 tons of CO2 per year per concession member. 36 -$255 is the net value of the pay cut concession members are willing to take to store carbon over timber

(-$787) and the amount they would be giving up in timber harvesting income ($532).

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some temporary work opportunities provide an above-average income for households,

there is a high degree of risk associated with these activities since employees are not

guaranteed a salary for the entire year. Thus, it is possible that households in this region

may be willing to accept a lower salary if they were given a contract for a stable income

for a longer time period37.

Table 19. Willingness to accept estimates (U.S. dollars)

All

communities

Concession

Members Nonmembers

Forest-

dwelling

Non-forest

dwelling

Store more carbon -1,426 *** -787 *** -2,337 *** -161 -1,998 ***

Keep the same

carbon storage -954 *** -1,660 ** -27 -2,124 -1,039

Contract length -64 *** -60 *** -69 *** -62 ** -59 ***

NTFP harvesting -3,975 *** -4,380 *** -3,727 *** -6,985 *** -2,566 ***

Tourism -2,635 *** -2,924 *** -2,495 *** -4,387 *** -1,811 ***

Group payment 717 *** 305 1,140 *** 1,250 *** 458 *

Status quo 8,548 *** 6,217 * 10,716 *** 14,267 *** 2,712

Gender*status quo 3,414 ** 2,569 4,464 ** 2,501 2,079

Age*status quo -41 83 -68 106 88 **

Education*status quo 37 -7 31 -1 44

Concession

member*status quo 1,925 --- --- -2,517 2,299

Forest-

dwelling*status quo 4,047 *** 2,434 6,297 ** --- ---

*** p<0.01, ** p<0.05, * p<0.1. The exchange rate used is 7.5 quetzals to 1 U.S. Dollar.

37 About 53% of the respondents in a 2017 MBR household survey felt that having access to stable work

opportunities was more important than receiving annual dividends or in-kind benefits from a forest

concession.

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Households have high value for the ability to access forests for ecotourism and

NTFP harvesting (Table 19). In forest-dwelling communities in particular, access to the

forest for tourism and NTFP harvesting is worth $4,387 and $6,985 respectively. These

results confirm the importance of NTFP harvesting and tourism to the region.

Additionally, the amount that the entire sample is willing to accept to take a group

payment over an individual-level payment is about $717 per year. This suggests that

households would be willing to accept less of a payment if there were a way to

compensate each household individually rather than through a group or community

organization. However, for concession members, the group payment coefficient is

insignificant. It is possible that, since they are required to collectively manage the forests

and share the benefits under the current system, concession members are more

accustomed to making decisions for the group, which often yields preferences that differ

from individual-level decisions in ecosystem services valuation (Murphy et al., 2017).

We included several statements to encourage respondents to truthfully state their

preferences, and we include questions to assess their responses. First, respondents were

told that their response would be used to influence future forest management and

conservation policies. Second, several follow-up questions were included in the survey to

determine whether individuals were making choices based on their actual preferences.

Table 20 shows the responses to these questions, which asked why a respondent chose a

contract. The responses in Table 20 confirm that households value contract length, carbon

storage, and NTFP harvesting since these attributes were most frequently reported as one

of the top three attributes households considered when choosing a contract. The

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responses for the least important contract attributes also reaffirm the findings in Table 18

and Table 19 since whether the payment is at the group level was frequently reported as

the least important attribute for households to consider when selecting a contract and the

group payment coefficient is insignificant in two out of the five sets of results.

Importantly, the most frequent response to which attributes are least important was “none

are least important.” This implies that, although some households do not value every

attribute in the proposed contracts, many households considered every attribute when

making their contract selection choice. The results shown in Table 18 and Table 19 also

show that most attributes are highly valued by households since the coefficients are

positive and significant.

To identify why “protest voters,” or participants who only chose the status quo, or

did not want to choose a contract, the enumerators asked participants why they selected

the status quo. The responses in Table 21 show that one of the most frequent reasons

reported were that households did not like the restrictions on harvesting non-timber forest

products. This sentiment is reaffirmed by the results in Table 18 and Table 19 that show

households highly value being able to harvest non-timber forest products. Some

households also indicated that they did not believe they would receive an additional

payment or that they did not want to work for a government. One possible explanation

for this response is that many households in the area have been promised payments for

conservation, but have not yet received them because carbon programs have not yet been

fully implemented (Hodgdon et al, 2012; GuateCarbon, 2014; Guzman, 2019).

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Table 20 Most and least important contract attributes

Top 3 "Most important when choosing a contract"

In top 3 1st 2nd 3rd

The length of the contract 53% 23% 13% 18%

The carbon stored 50% 24% 13% 13%

The level of timber extraction 40% 10% 18% 12%

If the payment is at the individual level 25% 11% 8% 6%

If the payment is at the group level 9% 2% 31% 4%

The payment amount 30% 8% 11% 11%

If you can harvest non-timber forest products 50% 14% 21% 16%

If you can participate in ecotourism 41% 9% 13% 20%

Total responses 479 479 478 475

All are important 4%

None are important 1%

Top 3 "Least important when choosing a contract"

In top 3 1st 2nd 3rd

The length of the contract 34% 17% 8% 13%

The carbon stored 19% 9% 6% 7%

The level of timber extraction 30% 13% 10% 11%

If the payment is at the individual level 40% 16% 16% 14%

If the payment is at the group level 40% 14% 22% 11%

The payment amount 35% 12% 10% 18%

If you can harvest non-timber forest products 30% 8% 15% 13%

If you can participate in ecotourism 32% 11% 12% 14%

Total responses 275 275 230 206

None are least important 74%

All are least important 0%

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Table 21. Reasons why only status quo was chosen

4.5 Conclusion

This paper examines the potential for carbon payments to displace timber harvests

in community forest concessions in Guatemala. This region is rich in cultural resources

and biodiversity. Since the 1990s, significant resources have been extended to protect the

forests and culture in this region. This protection has occurred in the form of national

parks, community-based forest concessions, industrial concessions, and other zones that

are afforded less protection.

Evidence suggests that the community-based concessions have reduced

deforestation and encouraged additional carbon storage (Blackman, 2015 and Fortmann

et al., 2017). The results indicate that households prefer to receive payments for carbon

Response Total indicated (%)

Household does not want to sell carbon 9%

The payment is not sufficient 14%

Household does not like the restrictions on ecotourism 21%

Household does not like the restrictions on harvesting non-timber forest products 44%

Household does not like the restrictions on timber extraction 28%

The contract is too long 2%

The contract is too short 0%

Household does not believe they would receive an additional payment 26%

Household does not want to work for national or foreign governments 9%

Household does not want to answer or is not interested 9%

Household is loyal to the community or current concession system 9%

Total households only choosing the status quo 43

Households were able to select multiple responses. About 6% of survey respondents only selected the status

quo. The “Household does not want to work for national or foreign governments,” “Household does not want

to answer or is not interested,” and “ Household is loyal to the community or current concession system”

responses were compiled from the “other” response category (Appendix 1).

105

storage over timber harvesting. Non-members have the smallest willingness to accept

payments to store more carbon, which is not surprising given that they also have the

lowest opportunity costs. By choosing to get paid for carbon storage, communities must

consider a number of additional factors or attributes including whether the communities

have forest access for harvesting non-timber forest products and tourism, whether they

are willing to undergo intensive monitoring of carbon outcomes, how long the contract

will last, and whether the payments should come to them individually or to a group. To

date, however, the communities have not been compensated for this storage of carbon

(Guzman, 2019), and they have continued to harvest trees to generate income, which

likely leads to carbon emissions.

The choice experiment reveals that allowing groups to harvest non-timber forest

products and to conduct tourism operations in the region is extremely valuable to

households. The magnitudes of the willingness to accept coefficients for these two

attributes are large for all of the regressions over different groups. Evidence from other

studies points to the significant cultural value associated with harvesting non-timber

forest products (e.g., Nesheim & Stølen, 2012; Taylor 2010), and our results provide

additional evidence on this value. If government or NGOs pursue carbon contracts, it

would be important to make sure that these two activities can continue to occur.

The survey results indicate that a large proportion of the group we sampled is

worried about the future of forests in the region, and that nearly everyone was interested

in limiting access to the Maya Biosphere Reserve, regardless of whether they are

concession members. While individuals in our sample were interested in protecting the

106

cultural and ecological resources in the region, they were more divided on the extent of

protection that should be provided, with non-members advocating for modestly more

protections of the forests than members. This is understandable given that members are

more likely to exploit and use the forests for commercial purposes. Nonetheless,

members and non-members alike were interested in seeing NTFP extraction and tourism

continue.

Individuals have preferences for longer contracts, with values from $59 to $69 per

year. On average, households prefer individual contracts over group contracts, but the

results for concession members are insignificant. Concessions already provide some

benefits to concession members through group payments, so it is likely that individuals

who are members have less resistance to the idea of group payments.

The results of this study have several important policy implications. First, since

households prefer to receive payments for increasing carbon storage rather than timber

harvesting, conservation programs should focus on providing households with carbon

payments rather than paying households to harvest timber sustainably. Second, most

households in our sample prefer to receive individual payments to group payments and

providing a direct payment to households could result in significant welfare gains.

Providing households with longer contracts could also benefit households in this area

since households would be guaranteed a stable source of income for a longer time.

Finally, households overwhelmingly preferred contracts that allow for NTFP harvesting

and tourism. Allowing groups to harvest non-timber forest products and to conduct

tourism operations in the region is highly valuable to households. These two activities

107

appear to have important cultural significance in the region. If carbon contracts are to be

implemented it would be important to make sure that these two activities can continue to

occur.

108

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Appendix A.1: Chapter 2

Common-pool resource management strategies may be ineffective at increasing the

welfare of community members if the policy is not tailored to the specific needs of the

community (Ostrom, 1990). In the case of the recently inhabited communities, the effect

of concession membership on income is negative, but insignificant. It is possible that this

policy is not designed to fit the needs of the communities, which could result in non-

members being more productive at forest product harvesting than members, or

. More specifically, it is possible that

(case 4) occurs for the recently inhabited concessions. In

this case, household i is relatively more productive at agricultural production than forest

resource harvesting both with and without the concession membership. Also, in this case,

the concession is not set up properly to yield a higher productivity for each unit of labor

allocated to forest resource harvesting. If household i becomes a concession member,

they would possibly have to reallocate more labor towards agriculture or keep the

allocation of labor between forest resource harvesting and agriculture the same as when

they were not a member. The income effect of concession membership would either be

negative or concession membership would not have an impact on income. The effect

would be negative if the amount of labor reallocated to agriculture or remaining in

( ) ( , )i i ji f i f fF L F L L

( ) ( ) ( , )i i i ji a i f i f fA L F L F L L

123

forestry is less productive than that unit of labor in forestry prior to the concession

membership. In contrast, there would be no effect if the amount of labor reallocated to

agriculture or remaining in forestry is as productive as prior to the concession

membership. This would occur, for example, if the household allocated all of their labor

to agriculture prior to the concession policy.

The following cases describe other possible concession policy income effects that

may occur if the policy is not tailored to the specific needs of a community. We do not

suspect, however, that either of these cases apply to the current concession policies in the

MBR, but they may occur if additional concessions are formed.

Case 5: for all levels of labor allocated to agricultural

production and forest resource harvesting

If household i becomes a concession member in case 5, the effect that membership would

have on income would be negative. In this case, the concession is not set up in a way that

would make forest production more productive. Also, the household is relatively more

productive at forest resource harvesting than agriculture so the allocation of labor would

stay the same, but concession membership would only serve as a restriction to forest

resource production.

Case 6: for all levels of labor allocated to agricultural

production and forest resource harvesting

( ) ( , ) (L )i i j ii f i f f i aF L F L L A

( ) (L ) ( , )i i i ji f i a i f fF L A F L L

124

Case 6 represents a scenario where concession membership decreased the household’s

forest resource harvesting productivity relative to its agricultural productivity. In this

scenario, the household would reallocate labor from forest product harvesting to

agricultural production and concession membership would have a negative effect on

income since the concession is putting a restriction on forest resource harvesting

productivity. Not only would this concession policy design decrease household income,

but it would likely lead to an increase in deforestation since concession members are

shifting labor from forest product harvesting to agriculture.

125

Appendix A.2: Chapter 2

Table 22. Logit model results for likelihood of being a concession member

Coef. Std. Err.

Household head age 0.043 *** 0.008

Household head education level (years of

formal education) 0.043 0.037

Household head is married 0.023 0.082

Spouse education level (years of formal

education) 0.013 0.018

Number of family members 0.019 0.044

Trust -0.120 0.100

Household head born in the Petén 0.524 ** 0.234

Household has savings (1=”no”) 0.096 0.274

Household depends on the forest for their

livelihood -0.570 *** 0.109

Constant -1.248 0.823

Observations 455.000

Log Likelihood -281.499

Note: *,**,*** denote significance at the 10, 5, and 1 percent levels. Robust

standard errors are denoted inside parenthesis. The variable “household

depends on the forest for their livelihood” was measured with a Likert Scale

from 1 to 5. “1” indicates that the household responded “strongly disagree”

and “5” indicates the household responded “strongly agree” to the statement

“I depend on the forest for my livelihood.” The variable “trust” indicates the

participant’s answer to the question “Do you think you can trust the majority

of people?” Each participant chose responses on a Likert Scale from 1 to 5.

“1” indicates that the participant thinks they cannot trust anyone. “5” indicates

that the participant thinks they can trust the majority of people.

126

Appendix B.1: Chapter 3

Table 23. 2SLS first stage results for instrument on concession membership

All Community

Types Long-inhabited

Recently-

inhabited Nonresident

Household head age .00198* .0034372** -.0007313 .0030943**

(.0010421) (.0016409) (.0029711) (.0014465)

Household head education -.0015469 .0017412 .0106537 -.0002937

(.0052684) (.0089562) (.0156759) (.0069655)

Forest Dependent .0620899* -.0091771 .0875065 .0663322*

(.0326653) (.078037) (.1285354) (.0383067)

Household Head Gender .0258014 .015648 .2372176** -.0205991

(.0364279) (.0589938) (.1155193) (.0482929)

Savings -.0551528 -.0413343 -.266616 -.0183232

(.0372151) (.0659855) (.1809424) (.0456959)

Born Petén .0811459** -.0029377 .2395872** .0532374

(.0338238) (.0578347) (.1024261) (.0444288)

Spouse education -.003583 .0030468 -.0168345 -.0009576

(.0057784) (.0096554) (.0212621) (.0074645)

Married .0260778 -.0397788 -.1298929 .0623913

(.0383753) (.0594423) (.1477859) (.0504363)

Under 12 -.0096468 .001789 -.0066814 -.0153684

(.0105877) (.0137944) (.0302241) (.0166224)

Trust .0103392 -.0478751 -.1112285 .0428471

(.0287561) (.0452531) (.0836104) (.0398554)

Own Land .0003596 -.0002579 -.0005975 .0013487

(.00062) (.00106) (.0015215) (.0008568)

Observations 646 167 86 393

F-statistic 33.99 31.57 9.73 21.14

R-squared 0.58 0.73 0.62 0.56

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are inside the parenthesis. For a complete

description of each variable, see Table 9

127

Table 24. Falsification test results for instrument

Coefficient Standard Error

Instrument (matched 2012 membership status) -13,785 16,578

Household head age 149.9 304.7

Household head education 1,837 1,757

Forest Dependent -2,393 9,019

Household Head Gender -3,637 14,874

Savings 5,336 15,857

Born Petén -4,142 9,223

Spouse education 448.3 1,807

Married 13,687 16,440

Under 12 -3,383 3,721

Trust -270.4 9,812

Own Land 1,051*** 130.4

Constant -9,508 43,327

Observations 63

R-squared 0.724

*** p<0.01, ** p<0.05, * p<0.1. For a complete description of each variable, see Table 9

128

Table 25. Logistic regression results for likelihood of being a concession member

Logit results Odds Ratio

Household Head Age 0.0171** 1.017267**

(0.00721) .(007332)

Household head education 0.00669 1.006716

(0.0371) (.0373664)

Born Petén 0.284 1.32832

(0.226) (.3008249)

Constant -0.0726 .9300165

(0.524) (.4875009)

Observations 488

*** p<0.01, ** p<0.05, * p<0.1. Standard errors are in parenthesis.

129

Table 26. Matched ordinary-least squares regression results for the effect of concession

membership on income

All Communities

Long-

inhabited

Recently-

inhabited Nonresident

Concession membership 13,077*** 13,517* 19,348** 15,198**

(4,396) (7,967) (9,376) (6,367)

Household head age -6.918 -210.1 26.19 106.4

(151.5) (233.3) (310.9) (231.5)

Household head education 1,140 684.7 -643.4 1,829

(783.3) (1,336) (1,578) (1,115)

Forest Dependent 1,171 12,084 -28,139** 2,222

(4,929) (12,464) (13,177) (6,253)

Household Head Gender 8,210 13,529 -16,664 12,554

(5,420) (9,211) (11,005) (7,754)

Savings -3,091 -16,476* 10,406 -588.5

(5,363) (9,443) (18,749) (7,181)

Born Petén -2,500 -8,941 -10,660 1,651

(5,047) (8,247) (11,322) (7,252)

Spouse education 1,425* 2,623* 1,206 775.1

(842.5) (1,472) (2,039) (1,162)

Married 14,148** 8,620 2,475 20,492***

(5,579) (9,144) (13,327) (7,880)

Under 12 1,722 4,487** -971.3 -488.3

(1,526) (1,875) (3,081) (2,683)

Trust -5,946 1,039 5,801 -11,617*

(4,196) (6,443) (9,171) (6,301)

Own Land 275.9*** 337.0** 129.5 265.8*

(87.04) (138.8) (151.5) (135.5)

Constant -1,963 14,515 38,165 -25,918

(20,200) (31,038) (45,183) (29,075)

Observations 482 122 66 294

R-squared 0.140 0.221 0.223 0.141

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are inside the parenthesis. 233 households were

unmatched and dropped from the analysis. All values are adjusted for inflation.

130

Table 27. Panel results for effect of concession membership on income

All Communities Nonresident Long-inhabited

Concession membership 12,986 14,055 4,345

(11,452) (16,348) (16,600)

Household head age -260.1 -507.0 -103.2

(215.5) (418.0) (230.9)

Household head education 210.1 19.26 1,886

(1,126) (1,774) (1,464)

Forest Dependent 4,734 14,943 -592.2

(7,640) (12,371) (9,122)

Household Head Gender -2,345 182.3 5,465

(9,796) (14,070) (14,888)

Savings 1,072 5,622 -7,768

(7,461) (10,646) (9,158)

Born Petén 8,432 14,122 1,983

(5,760) (9,362) (6,681)

Spouse education 406.2 -162.5 108.8

(1,054) (1,689) (1,311)

Married -6,214* -7,710 -2,277

(3,339) (5,171) (3,961)

Under 12 2,052 -1,567 4,285***

(1,848) (4,176) (1,590)

Trust -1,561 -10,231 12,947*

(6,694) (10,679) (7,479)

Own Land -53.55 -230.0 142.5

(125.6) (170.0) (215.6)

Constant 19,151 16,319 50,732

(28,884) (47,193) (34,461)

Observations 224 118 83

Number of Households 113 63 46

*** p<0.01, ** p<0.05, * p<0.1. Results include village fixed effects. Observations that were

unmatched and that reported income above 300,000 quetzals a year were dropped from the analysis. All

values are adjusted for inflation.

131

Appendix B.2: Chapter 3

Table 28. Logistic regression results for likelihood of concession placement

Logit results Odds Ratio

Distance to road 0.000191*** 1.00019***

(1.04e-06) (1.04e-06)

Distance to archaeological site -5.05e-05*** .99995***

(2.18e-07) (2.18e-07)

Elevation -0.00106*** .99894***

(4.20e-05) (4.20e-05)

Soil nutrients -0.04450*** .95649***

(0.00036) (0.00036)

Constant 758.00*** ---

(6.05) (6.05)

Observations 783,480 783,480

*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are inside the parenthesis.

132

Table 29. CO2 values adjusted for specific carbon sequestration values

Additional

forest

conserved

(ha)

Average

tons of CO2

per ha

Average tons of

CO2 per ha

(adjusted)

Carbon

gains

(adjusted)

Value of

CO2

(adjusted)

Long-

inhabited 342.05 278.87 329.71 112779 $3,496,149

Recently-

inhabited 65.63 334.72 349.23 22920 $710,520

Nonresident 621.53 330.07 320.56 199236 $6,176,316

Industrial 484.71 314.1 354.68 171918 $5,329,458

Total for

active

concessions 1513.92 506853 $15,712,443

The value of CO2 is calculated using $31 as the social cost of carbon (Nordhaus, 2017). The

average tons of CO2 per hectare are calculated by concession classification (long-inhabited,

recently-inhabited, nonresident, and industrial). All adjusted values are calculated using the

results for the effect of concession management on CO2 in lost forested areas shown in

Table 13.

133

Appendix C.1: Chapter 4

Survey No. ___________

Encuesta Para Hogares de Guatemala

SECCIÓN 1: INTRODUCCIÓN __________________ Encuestador: Pregunte el nombre del encuestado, y llene la información siguiente: Enumerator: Ask for the respondent’s name; fill in the information in the cells below.

1.1 Entrevistado: _________________________ 1.2 Tiempo de Inicio: _____________________ 1.3 Código de Hogar: ______________________ 1.4 Código de Encuestador: _______________ 1.5 ¿Quien es en el entrevistado? What is the relation to the head of the house?

(1)____ Jefe del hogar household head

(2)____ Cónyuge spouse

(3)____ Otro other

Si la persona entrevistada no es el jefe de la casa, conteste las preguntas 1.6 – 1.10 basado en el jefe de la casa. If the survey respondent is NOT the head of house, answer questions 1.6-1.10

based on the head of house (not spouse if interviewing spouse instead).

1.6 Genero del jefe de hogar (observado) Gender of head of house (observed) (1)_____ Hombre Male

(2)_____ Mujer Female

1.7 ¿Cuál es su ocupación principal? (¿o la ocupación del jefe de hogar?)

What is your principal occupation? (or the occupation of the head of house?)

(1)____ Trabajo relacionado con el bosque (como una concesión industrial o PFNM) Job related to forestry (2)____ Agricultor Farmer

(3)____ Jornalero diario en agricultura o ganadería daily laborer in agriculture (4)____ Trabajo doméstico para finqueros u otros patrones Domestic work for ranchers

or landowners (5)____ Empleado en pequeño negocio employee at small business (6) ____ Empleado de ONG o contratado por una ONG employee for NGO or contract

work for NGO (7)____ Empleado de gobierno o magisterio government employee

(8)____ Negocio propio (auto-empleo) self-employed business (9)____ Carpintero o artesano carpenter or wood worker

(10)___ Carrera profesional profesional career

134

(11)___ Turismo relacionado tourism related

(12)___ Ama de casa/domestica housewife/husband

(99)___ Otro, especifique_________________________________ 1.8 ¿Cuántos años tiene? (o tiene el jefe del hogar) ________ (escriba el numero o

marque “No sé”) How old are you? (or how old is the head of the household)?

(98) _____ No sé Don’t know

1.9 ¿Cuál es el grado de escolaridad más alto que ha terminado? (o ha terminado el jefe del hogar) ? What is the highest year of school completed? (Or that the head of household completed?) (1)_____ Primero o menos (no educación formal) (No formal education) (2)_____ Segundo (3)_____ Tercero (4)_____ Cuarto (5)_____ Quinto (6)_____ Sexto (7)_____ Primero Básico (8)_____ Segundo Básico

(9)_____ Tercero Básico (10)____ Diversificado (11)____ Universidad (12)____ Maestría o superior (97)____ No contesta No answer

1.10 Un grupo familiar incluye todas las personas que vive juntas y comparten alimentos diariamente. Incluyéndose usted, ¿cuántas personas viven en su casa? __________ A household is considered all the people living together that share meals on a daily basis. How many people, including yourself, live in your household?

1.11 ¿De estas personas cuantas son mujeres o niñas? _______ How many of these

people are females?

1.12 ¿Cuántas personas que viven en su casa tienen 12 años o menos? ____ How many people living in your household are less than 12 years old?

1.13 ¿Principalmente, cuál religión está practicada en su casa? What religion is

primarily practiced in your household?_________ (98)____No quiere contestar They don’t want to answer

(99)____No sé

1.14 ¿Va a la iglesia? Do you go to church?

(1)_____Sí (2)_____No (98)____No quiere contestar (99)____No sé

135

SECCIÓN 2: VIVIENDA y BIENES HOUSING AND ASSETS_______________

Ahora, voy a hacerle algunas preguntas sobre su casa, posesiones y tierra que su familia posee. Now, I will ask you some questions about your house, assets, and land that your household possesses.

Conteste las siguientes preguntas basado en observaciones de la vivienda, o pregunte al entrevistado si es necesario. Answer the following questions based on observations of the house or ask if

necessary

2.1 Techo (roof) (1) ___ Lamina iron sheets (2) ___ Guano palm

(3) ___ Madera wood (4) ___ Teja tile

(5) ___ Corozo o manaque

(6) ___ Terraza

2.2 Paredes de la casa (walls)

(1) ___ Madera wood

(2) ___ Cemento cement (3) ___ Bajareque Mud (4) ___ Adobe (5) ___ Blocks

2.3 Piso (floor) (1) ___ Cemento cement (2) ___ Madera wood

(3) ___ Tierra dirt

(4) ___ Cerámico ceramic

2.4 ¿Cuál es la fuente de agua principal en su casa? (what is the main water source ?) (1) ____ Chorro (adentro de la casa) pump inside (2) ____ Pozo comunal community well

(3) ____ Pozo propio prívate

well (4) ____ Chorro comunitario Community pump

(5) ____ Agua comprada buy

wáter

(6) ____ Rio, Nacimiento River or surface water

2.5 Combustible para cocinar principal? (energy for cooking)

(1) ___ Leña firewood (2) ___ Electricidad (3) ___ Carbón charcoal (4) ___ Gas (99)___Otro

2.6 Fuente principal para Iluminación? (lighting

source) (1) ___ Candelas candles

(2) ___ Candiles kerosene (3) ___ Leña firewood (4) ___ Electricidad (99)___Otro

Ahora me gustaría preguntarle sobre algunos artículos que hay en su casa. Now I would like to ask you about the assets your household owns.

2.7 Posee en su casa…. (lea los artículos y marque todos que tienen) Does your

household have? (a) ____ Teléfono celular cell phone

(b) ____ Televisión color television

(c) ____ Refrigerador refridgerator

(d) ____ Servicio de electricidad electricity service

(e) ____ Planta eléctrica electric generator

(f) ____ Motocicleta motorcycle

(h) ____ Carro car

(i) ____ Tractor tractor

136

(j) ____ TV Satelital satellite tv (k) ____ Panel Solar solar panel

Ahora, tengo algunas preguntas sobre tenencia de la tierra y sobre las actividades que usted realiza en su parcela. Now, I have some questions about land tenure and

what activities you are involved in on your land.

2.9 ¿Posee usted alguna tierra? Do you possess any land?

(1) ___ Si ¿cuantas manzanas? __________ how many manazas?

(2) ___ No Pase la siguiente pregunta 2.14 skip to question 2.14

2.10 ¿Dónde se ubica esta tierra? (lea las opciones y marque todas las que aplican)

Where is the location of this land?

(1) ____ Dentro de esta comunidad This community

(2) ____ Fuera de esta comunidad pero en el mismo municipio Outside of this community but in the same municipio

(3) ____ Fuera del municipio pero en el Petén Outside the municipio, but still in the

Petén (4) ____ Fuera del Petén pero en Guatemala Outside the Petén, but still in Guatemala

(5) ____ Fuera de Guatemala Outside Guatemala.

2.11 ¿Alquila alguna parte de esta parcela a otras personas? Do you rent some of this

land to others? (1) _____ Si cuantas manzanas? _________________ how many manzanas?

(2) _____ No Pase a la siguiente pregunta 2.14 skip to question 2.14

2.12 ¿Dónde se ubica esta tierra alquilada? (lea las opciones y marque todas las que aplican)

Where is the location of this rented land?

(1) ____ Dentro de la tierra que usted posee Within the land you possess

(2) ____ Dentro de esta comunidad This community

(3) ____ Fuera de esta comunidad pero en el mismo municipio Outside of this community but in the same municipio

(4) ____ Fuera del municipio pero en el Petén Outside the municipio, but still in the

Petén (5) ____ Fuera del Petén pero en Guatemala Outside the Petén, but still in Guatemala

(6) ____ Fuera de Guatemala Outside Guatemala

2.13 ¿Cuánto le pagan por manzana que usted alquila a otros al año? Q_____________

How much to do you receive per manzana rented per year?

2.14 ¿Alquila usted alguna tierra de otras personas o al municipio? Do you rent any

land from others?

(1) _____ Si cuantas manzanas? ________ how many manazas? (2) _____ No pase a la pregunta 2.17

2.15 ¿Dónde se ubica esta tierra alquilada? (lea las opciones y marque todas las que aplican)

137

Where is the location of this rented land?

(1) ____ Dentro de esta comunidad This community

(2) ____ Fuera de esta comunidad pero en el mismo municipio Outside of this community but in the same municipio

(3) ____ Fuera del municipio pero en el Petén Outside the municipio, but still in the

Petén (4) ____ Fuera del Petén pero en Guatemala Outside the Petén, but still in Guatemala

(5) ____ Fuera de Guatemala Outside Guatemala.

2.16 ¿Cuánto paga usted por alquilar una manzana al año? Q_____________ How much do you pay per manzana to rent land per year?

2.17 ¿Utiliza usted alguna parcela, alquilada, poseída o usado en otra manera, para agricultura? Do you use any land, rented, possessed, or used in another way, for agriculture?

(1) ___ Si ¿Cuántas manzanas son utilizadas para agricultura?______

(2) ___ No pase a la pregunta 2.25

2.18 En la parcela que usó usted el año pasado, cultiva….? (Lea cada opción y pregunte 2.19-2.23 cuándo necesario).

2.19 ¿En cuántas manzanas?

2.20 ¿Qué parte era consumido por su familia? (circulo uno)

2.21 ¿Vendió este producto? (circulo uno)

2.22 ¿Qué era el precio de este producto?

2.23 ¿Cuántas unidades de este producto vendió?

Selecciona la unidad que dice el participante (Escriba el código de la unidad apropiada)

Maiz Sí

<1/2 1/2 >1/2 No Sí

Frijol Sí

<1/2 1/2 >1/2 No Sí

Chile Sí

<1/2 1/2 >1/2 No Sí

Pepitoria Sí

<1/2 1/2 >1/2 No Sí

Otro, Sí Especifique __

<1/2 1/2 >1/2 No Sí

Otro, Sí Especifique ____________

<1/2 1/2 >1/2 No Sí

Otro, Sí Especifique __________

<1/2 1/2 >1/2 No Sí

138

Unidades 1=busheles 2=libras 3=otro

2.24 ¿Qué otras actividades realiza en la parcela aparte de la agricultura? (Marque todas las que aplican) What activities do you do on the land you manage? (Check all

that apply) (a) _____ Ganadería cattle ranching ¿Cuánto ganó en los últimos 12 meses?

Q_____________ (b) _____ Manejo Forestal forest management (c) _____ Guamil fallow land (d) _____ Huerto orchard

(e) _____ Apicultura Bee-keeping

(99) ____ Otro, especifique________________________

2.25 ¿Ha comprado usted alguna parcela en los últimos 10 años? Have you bought any land in the past 10 years?

(1) ____ Si (2) ____ No pase a la pregunta 2.28

2.26 ¿Cuánta tierra compró? _____________ manzanas How much land did you buy?

2.27 ¿Cuánto pagó por esta tierra? Q___________en total o por manzana (circulo uno)

How much did you pay for this land?

2.28 ¿Ha tenido alguna parcela que la vendió parcial o totalmente en los últimos 10 años?

Have you had some land that you sold, either partial or all of it in the last 10 years?

(1) ____ Si (2) ____ No pase a la Sección 3 skip to section 3

2.29 ¿Cuánta tierra vendió? _____________ manzanas How much land did you sell?

2.30 ¿Por cuánto dinero vendió la manzana? Q____________ For how much did you

sell each manzana manzana?

2.31 ¿En qué año vendió la tierra? ____________ What year did you sell the land?

SECCIÓN 3. DINERO Y FINANZAS MONEY AND FINANCES_______________

Ahora, le haré algunas preguntas sobre las fuentes de ingresos de su casa y sobre cómo administra el dinero basado en la contribución económica que hacen todos los miembros de su familia para los gastos de comida, estudios, alquiler, etc. en los últimos 12 meses,

139

Now I will ask you some questions about your household’s sources of income and how you administer your money based on all the members in your household that contribute to household expenses, such as food, rent, etc.. ¿Cuántas personas en su casa, incluyéndose usted, contribuyeron con dinero

para el gasto familiar en los últimos 12 meses? (Escriba la relación con el jefe o el nombre abajo). Si cada de estas personas son socios de una concesión, por favor, solamente incluye sus salarios aquí y no dividendos ni beneficios en especie asociados con la concesión. Vamos a preguntarle a usted sobre estos beneficios más tarde. How many people in your house, including yourself, contribute to family expenses in the past 12 months? Can you give me the first names of these people? (Write the names in the first column of the table below). If any of these people are concession members, please include only their wages here and not any dividends or in-kind benefits associated with the concession. We will ask about those later.

***Hay dos tablas para estas preguntas. Una es para tres personas y la otra es para las ultimas. Llena las líneas como es necesario para cada persona que trabaja en la casa.*****

3.1 Miembro de la casa que trabajó (Escriba la relación con el jefe o el nombre abajo. Si la persona tiene más que uno trabajo, use los espacios con la misma letra de la persona)

3.2 ¿Que trabajo hizo? Utilice el código abajo para llenar el espacio.

3.3 ¿Cuánto tiempo trabajó en los últimos 12 meses?

D/M/S/Q

3.4 ¿Cuánto se le pagó por este trabajo?

(Si la persona no sabe escriba código 98 D/S/Q/M

3.5 ¿Fue este trabajo asociado con una concesión forestal comunitaria? (circulo uno)

3.6 ¿Qué parte de este trabajo fue asociado con una concesión? (circulo uno)

a) Q Sí

No No Sé

Todo Un medio o más

Menos que un medio

No sé

a) (si persona “a” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

140

a) (si persona “a” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

a) (si persona “a” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

b) Q Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

b) (si persona “b” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

b) (si persona “b” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

b) (si persona “b” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

c) Q Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

c) (si persona “c” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

c) (si persona “c” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

c) (si persona “c” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

1 = Trabajo relacionado con el bosque 2 = Jornalero diario en agricultura o ganadería

5 = Empleado de ONG o contratado por una ONG 6 = Empleado de gobierno o magisterio 7 = Negocio propio (auto-empleo) 8 = Carpintero o artesano

11= Vender productos agrícolas 12= Vender ropa/comida 13= Vender otras cosas

D=días M=meses S=semanas Q=quince días

141

3 = Trabajo doméstico para finqueros u otros patrones 4 = Empleado en pequeño negocio

9 = Carrera profesional 10= Turismo relacionado

14= Trabajo temporal 15 = Otro

Use esta tabla para continuar si hay más que tres personas que trabajan en la casa

3.1 Miembro de la casa que trabajó (Escriba la relación con el jefe o el nombre abajo. Si la persona tiene más que uno trabajo, use los espacios con la misma letra de la persona)

3.2 ¿Que trabajo hizo? Utilice el código abajo para llenar el espacio.

3.3 ¿Cuánto tiempo trabajó en los últimos 12 meses?

D/M/S/Q

3.4 ¿Cuánto se le pagó por este trabajo?

(Si la persona no sabe escriba código 98 D/S/Q/M

3.5 ¿Fue este trabajo asociado con una concesión forestal comunitaria? (circulo uno)

3.6 ¿Qué parte de este trabajo fue asociado con una concesión? (circulo uno)

d) Q Sí

No No Sé

Todo Un medio o más

Menos que un medio

No sé

d) (si persona “d” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

d) (si persona “d” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

d) (si persona “d” tiene

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

142

otro trabajo)

e) Q Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

e) (si persona “e” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

e) (si persona “e” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

e) (si persona “e” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

f) Q Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

f) (si persona “f” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

f) (si persona “f” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

c) (si persona “c” tiene otro trabajo)

Sí No No Sé

Todo Un medio o más

Menos que un medio

No sé

1 = Trabajo relacionado con el bosque 2 = Jornalero diario en agricultura o ganadería 3 = Trabajo doméstico para finqueros u otros patrones 4 = Empleado en pequeño negocio

5 = Empleado de ONG o contratado por una ONG 6 = Empleado de gobierno o magisterio 7 = Negocio propio (auto-empleo) 8 = Carpintero o artesano 9 = Carrera profesional 10= Turismo relacionado

11= Vender productos agrícolas 12= Vender ropa/comida 13= Vender otras cosas 14= Trabajo temporal 15 = Otro

D=días M=meses S=semanas Q=quince días

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3.7 Tuvo su casa alguna fuente adicional de ingresos en los últimos 12 meses tales como… (lea las respuestas y marque todas que aplican)

(a) ____ Dinero de otro familiar que no vive en la casa pero vive en Guatemala Cuanto?Q ___________ Money from a family member that lives in

Guatemala (b) ____ Dinero de algún programa del gobierno Cuanto? Q______ Money from a government program (c) ____ Remesas Cuanto? Q ____________ Remittances (from outside

Guatemala) (d) ____ Otro fuente, especifique _________________ Cuanto Q_____ (e) ____ Ninguno 3.8 ¿Actualmente, tiene usted algún ahorro? Do you currently have savings?

(1) ____ Si, ¿Cuánto? _________ (2) ____ No

3.9 ¿Actualmente, tiene usted algún préstamo? Do you currently have any loans? (1) ____ Si ¿Por cuánto dinero for how much money? _______ (2) ____ No pase a la pregunta 3.12 skip to question 3.12

3.10 ¿Dónde consiguió el préstamo? Where did you get the loan?

(1)____ Banco bank

(2)____ Concesión comunitaria community concession

(3)____ Institución microfinanciera microfinance institution

(4)____ Cooperativa cooperative

(5)____ Prestamista de la comunidad community lender

(6)____ Grupo de ahorro savings group

(7)____ Familiar/amigo family/friend

(99)___ Otro, especifique ________________________________________________ 3.11 ¿Aproximadamente cuánto dinero gastó su casa en los siguientes cosas el año pasado?Approximately how much money did you spend on the following last year?

(a) Medicinas y atención médica medicine/medical attention _________Q

(99)___No sé I don’t know

(b) Educación/costo de matrícula education/tuition________Q

(99)___No sé I don’t know

3.12 ¿Usted piensa que se puede confiar en la mayoría de las personas, o que se debe tener muchísimo cuidado al tratar con otras personas? Would you say that most people can be trusted, or that you can’t be too careful in dealing with people? Please tell me what you think, where 1 means you can’t be too careful and 5 means most people can be trusted.

(1)____ Se debe tener muchísimo cuidado Can’t be too careful

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(2)____ Se debe tener algún cuidado Some care should be taken

(3)____ No se debe tener cuidado Do not have to be careful (4)____ Se puede confiar en algunas personas Can trust in some people

(5)____ Se puede confiar en la mayoría de las personas Most people can be

trusted (98)___ No sé Don’t know (97)___ No contesta No answer

SECCIÓN 4. RESPONSIBILIDADES EN SU CASA Responsibilities in your household

Ahora, voy a preguntarle a usted como algunas responsabilidades en su hogar están divididas entre usted y su cónyuge. I will now ask you about how some household

responsibilities are divided among you and your spouse.

4.1 ¿Cuál es su estado civil (o el estado civil del jefe del hogar)? What is your

marital status (or the marital status of the head of household)? (1)_____ Casado/a Married

(2)_____ Unido/a Living together but unmarried

(3) _____Divorciado/a Divorced pase a la sección 5 (4)_____ Soltero/a Single pase a la sección 5 (5)_____ Viudo/a Widowed pase a la sección 5

4.2 ¿Cuántos años tiene su cónyuge o pareja (o tiene el cónyuge o pareja del

jefe de hogar)? What is the age of your spouse or partner (or the head of household’s

spouse/partner?_________ (99)_____No sé

4.3 ¿Cuál es la ocupación principal de su esposa/o (o el esposo/a del jefe del hogar)?

What is the principal occupation of your spouse (or the head of household’s spouse)?

(1)____ Trabajo relacionado con el bosque (como una concesión industrial o PFNM) Job related to forestry (2)____ Agricultor Farmer

(3)____ Jornalero diario en agricultura o ganadería daily laborer in agriculture (4)____ Trabajo doméstico para finqueros u otros patrones Domestic work for

ranchers or landowners (5)____ Empleado en pequeño negocio employee at small business (6) ____ Empleado de ONG o contratado por una ONG employee for NGO or

contract work for NGO (7)____ Empleado de gobierno o magisterio government employee

(8)____ Negocio propio (auto-empleo) self-employed business (9)____ Carpintero o artesano carpenter or wood worker

(10)___ Carrera profesional profesional career

(11)___ Turismo relacionado tourism related

(12)___ Ama de casa/domestica housewife/husband

(99)___ Otro, especifique_____________________________________

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4.4 ¿Cuál es el grado de escolaridad más alto que ha terminado (de la esposa del jefe de hogar)? What is the highest year of school completed? (of the spouse of the

head of the household) (1)_____ Primero o menos (no educación formal) (No formal education) (2)_____ Segundo (3)_____ Tercero (4)_____ Cuarto (5)_____ Quinto (6)_____ Sexto (7)_____ Primero Básico (8)_____ Segundo Básico (9)_____ Tercero Básico (10)____ Diversificado (11)____ Universidad (12)____ Maestría o superior (97)____ No contesta No answer

¿Quién en su hogar hace la decisión final o tiene la responsabilidad primaria para la decisión en relación a las siguientes cosas?

Yo me Mi cónyuge my spouse

Other otro

4.5 Decisiones para gastar dinero Financial decisions

4.6 Decisiones gastos médicos (visitas al doctor, medicación…etc) Medical decisions (doctor visits, medication…etc.)

4.7 Educación para sus hijos Education for your children

4.8 Necesidades (ropa, comida…etc.) Necessities

(clothes, food…etc.)

4.9 Compras grandes (vehículos, aparatos...etc.) Large purchases (vehicles, appliances…etc.)

4.10 Visitas a familia o amigos visits to family and friends

SECCIÓN 5. OPINIONES ACERCA DEL MANEJO FORESTAL Y

CONSERVACIÓN OPINIONS ABOUT FOREST MANAGEMENT AND CONSERVATION

Por favor, ordena las siguientes actividades en términos de sus importancia para asegurar las vida de la gente que viven en dentro de y cerca de la Reserva de Biosfera Maya (lea los objetivos y opciones, y circúlo el numero) Please rank the

following activities in terms of their importance for ensuring the livelihood people who live in and around the forests of the Maya Biosphere reserve (Read the objectives and options and circle the number)

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Cuan de acuerdo está usted con lo siguiente:

Muy en desacuerdo

Desacuerdo

Neutral

De acuerdo

Muy de acuerdo

5.1 “Dependo de los recursos del bosque para mis ingresos económicos.” I depend on

the forest resources for my income

1 2 3 4 5

5.2 “Estoy muy preocupado/a por el futuro de los bosques de Petén” I am very worried

about the future of the Petén’s forests

1 2 3 4 5

5.3 “Cualquier persona debe poder cortar madera de la Reserva Biósfera Maya”. Anyone should be

able to harvest timber from the MBR

1 2 3 4 5

5.4 “Cualquier persona debe poder cortar productos forestales no maderas (e.g., Chicle o Xate) de la Reserva Biósfera Maya”. Anyone should be

able to harvest non-timber forest products from the MBR

1 2 3 4 5

5.5 “La agricultura está amenazando a los bosques en el Petén.” Agriculture (crops or

grazing) is threatening to the forests in the Petén.

1 2 3 4 5

5.6 “El turismo hace daño a los bosques en el Petén.” Tourism is

causing damage to the forests in the Petén

1 2 3 4 5

5.7 El turismo hace daño a los recursos culturales de la reserve. Tourism causes

1 2 3 4 5

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damage to the cultural resources of the Reserve.

5.8 Los bosques debe recibir protección estricta sin aprovechamiento de concesiones u otros. Forests should be strictly protected from any use by concessions or others.

1 2 3 4 5

5.9 Proteger los recursos históricos y culturales como Tikal y Mirador es importante Protecting

historical and cultural resources like Tikal and Mirador is important

1 2 3 4 5

5.10 Cortar madera de la Reserva Biósfera Maya es una fuente de ingreso importante para la región. Timber

harvesting is an important source of income in the region.

1 2 3 4 5

5.11 La extracción de madera de la reserve, aunque completada en una manera sustentable, causa daño al medio ambiente. Timber

harvesting in the reserve, although done sustainably, causes damage to the Reserve

1 2 3 4 5

5.12 Colectar productos no de madera del bosque (como chicle y xate) es una fuente de ingreso importante para la región. Non-

timber forest products like chicle and xate are an important source of income in the region.

1 2 3 4 5

5.13 El turismo es una fuente de ingreso importante en la

1 2 3 4 5

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región. Tourism is an

important source of income in the region.

5.14 Es necesario que el gobierno gaste más dinero en la protección del bosque en el Petén de actividades ilegales. It is necessary for the government to spend more money on the protection of the forest in the Petén from illegal activity

1 2 3 4 5

5.15 En 20 años, habrá la misma cantidad del bosque en la Reserve In 20 years,

there will be the same amount of forest in the Reserve

1 2 3 4 5

SECCIÓN 6. LAS CONCESIONES FORESTALES COMUNITARIAS The forest

concessions

En la próxima sección, voy a hacerle algunas preguntas acerca de las concesiones forestales comunitarias. In this section I will ask you some questions about the community

forest associations. 6.1 ¿Actualmente, es usted socio de alguna concesión? Are you currently a member?

(1) ___ Si pase a la pregunta 6.16 (2) ___ No

6.2 ¿Alguna vez, ha sido socio de alguna concesión forestal comunitaria?

Have you ever been a member of a community forestry association? (1) ___ Si (2) ___ No pase a la pregunta 6.6

6.3 ¿Si alguna vez fue socio, pero ya no, en qué año terminó su afiliación?

___________ If you were a member at one time, what year did you end your membership?

6.4 ¿Vendió usted su membresía? Did you sell your membership?

(1) ___ Si A cuanto la vendió? Q________________ How much did you sell it

for? (2) ___ No 6.5 ¿Cuál fue la principal razón para terminar su afiliación con la concesión?

What was the primary reason for ending your membership in the forest community concession? (1) ____ No ganaba suficiente dinero trabajando en la concesión

Was not earning enough money working in the concession (2) ____ Había un conflicto con otro socio Had a conflict with another member

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(3) ____ Quería centrar su atención en la agricultura Wanted to focus on agriculture (4) ____ Llegó una oportunidad más rentable A more profitable opportunity came along

(5) ______ Fui expulsado (99) ___ Otro, especifique_____________________________________

(Lea esta oración solo si fue socio en el pasado y ya no) Por favor responda las próximas preguntas con base en el tiempo en que fue usted miembro de alguna concesión. (Read this if they were a member in the past but not now.)

Please answer the next questions based on the time you were a member

Pase a la pregunta 6.16 6.6 ¿Ha escuchado algo sobre las concesiones forestales comunitarias?

Have you ever heard about the community forest concessions?

(1)___ Si (2)___ No pase a la Sección 7 skip to section 7

6.7 ¿Cuánto considera usted que sabe acerca de las concesiones forestales? (lea las respuestas) How much would you say you know about them?

(1)____ He oido algo, pero no sé nada acerca de ellas. I’ve heard of them, but I don’t know anything about them

(2)____ Se un poco de ellas. I know a little bit about them (3)____ Se mucho de ellas. I know a lot about them

6.8 ¿Alguna vez tuvo la oportunidad de formar parte de una concesión

forestal, pero no quiso? Did you ever have the opportunity to join an association or cooperative, but

did not want to join?

(1) ____ Si (2) ____ No pase a la pregunta 6.11

6.9 ¿A cuáles podría haberse unido? Which group could you have joined?

(1) _____ San Miguel (8) _____ Las Ventana (Arbol Verde) (2) _____ Uaxactún (OMYC) (9) _____ La Unión (CUSTOSEL) (3) _____ Cruce a la Colorada (AFICC) (10)_____San Andrés (AFISAP) (4) _____ Carmelita (11)_____Rio Chanchich (Suchitecos) (5) _____ La Pasadita (12)_____Chosquitán (Laborantes) (6) _____ La Colorada (AFIC) (13)_____Lechugal (Selva Maya Norte) (7) _____ Yaloch (El Esfuerzo) 6.10 ¿Por qué eligió no unirse a la concesión? Why did you choose not to join the association?

(1) ____ Muy caro Too expensive (2) ____ No está interesado en el sector forestal Not interested in forestry (3) ____ No desea unirse a un grupo comunitario Do not want to join a community

group (4) ____ No tiene tiempo No time

(5) ____ Penso que unirse la asociación no dejaba ganancias. Did not think joining the association would be profitable

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(6) ____ No quería dejar mi trabajo para trabajar en una concesión. Did not want to leave my job to work in concession

(99) ___ Otro, especificar __________________________________

Vaya a Sección 7 Go to Section 7 6.11 Estaría interesado en unirse a una concesión forestal comunitaria si

tuviera la oportunidad? Would you be interested in joining a community forest concession if given

an opportunity?

(1) ____ Si (2) ____ No Vaya a Sección 7

6.12 ¿Cuáles son las razones principales para querer unirse una concesión? (Marque todos los que aplican) What are the main reasons you would want to join a

concession? (Check all that apply) (1) ____ Para tener mejores oportunidades de trabajo For better job opportunities

(2) ____ Quiero tener acceso legal a productos forestales Wanted legal access to

forest products

(3) ____ Tengo familia o amigos en el grupo Had family or friends in the group (4) ____ Para tener beneficios financieros asociados con la calidad de socio Financial benefits associated with membership (5) ____Para tener beneficios en especie asociados con la calidad de socio (6) ____ Todos los demás en la comunidad se estaban convirtiendo en socios Everyone else was becoming a member (7) ____ Proteger los bosques To protect the forests

(99)___ Otro, especifique ________________________________ 6.13 Por favor, clasifica usted los beneficios potenciales por ser un socio de una

concesión en orden de importancia para usted. (Indica lo más importante con

“1,” el segundo más importante con “2,” y el ultimo con “3.”) Please rank the potential

benefits for being a concession member in order of importance.

(1) ______Beneficios en especie (seguro de vida, atención médica, becas

escolares…etc.) In-kind benefits (life insurance, medical attention, schorships…etc.)

(2) ____Trabajo estable para un salario Stable work for wages

(3) ____Dividendos dividends

6.14 De los siguientes beneficios en especie potenciales para un socio de una concesión, cuales son para usted los tres más importantes. (Lea los beneficios y marque el orden de importancia que dice el entrevistado

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Of the following potential in-kind benefits from being a concession member, which three are the most important to you? (Read the benefits and mark the order of importance that the participant states.)

(a)____mejoramiento a centros de las saludes (b)_____mejoramientos a edificios escolares (c)_____Otros mejoramientos comunidades por ejemplo, dinero a iglesias o apoyo para mujeres

(d) ____ Seguro de vida y gastos funerales life insurance

(e) ____ Medicinas y atención médica medical benefits

(f) ____ Becas escolares y gastos escolares además de servicios ofrecidos por el gobierno scholarships/grants besides services offered by the government

(g) _____ Acceso a créditos Access to loans

6.15 ¿Piensa usted que los socios de una concesión son mejor o peor en términos de sus subsistencias que los no socios? Do you think that members of a

concession are better or worse off in terms of their livelihoods than non-members?

(1)____ Mucho peor Much worse (2)____ Un poco peor A Little worse (3)____ Igual Same (4)____ Un poco mejor A Little better (5)____ Mucho mejor Much better (98)___ No sé Don’t know (97)___ No contesta No answer

Vaya la Sección 7 Go to Section 7

(Las siguientes preguntas son para socios actuales o pasados de una concesión. Salte a la Sección 7 si no es así.) (The following questions are for current and former

concession members. Skip to Section 7 otherwise) 6.16 ¿A qué grupo concesionario pertenece o perteneció? Which concession group

are/were you a member of?

(1) _____ San Miguel (8) _____ Las Ventana (Arbol Verde) (2) _____ Uaxactún (OMYC) (9) _____ La Unión (CUSTOSEL) (3) _____ Cruce a la Colorada (AFICC) (10)_____San Andrés (AFISAP) (4) _____ Carmelita (11)_____Rio Chanchich (Suchitecos) (5) _____ La Pasadita (12)_____Chosquitán (Laborantes) (6) _____ La Colorada (AFIC) (13)_____Lechugal (Selva Maya Norte) (7) _____ Yaloch (El Esfuerzo) 6.17 ¿En qué año se convirtió en socio? _______________ What year did you become

a member?

6.18 ¿Cuáles fueron las razones principales para unirse? (Marque todos los que aplican)

Why did you join? (Check all that apply)

(1) ____ Para tener mejores oportunidades de trabajo For better job opportunities

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(2) ____ ONGs me animaron a convertirme en socio NGO encouraged me to

become member

(3) ____ Quería tener acceso legal a productos forestales Wanted legal access to

forest products

(4) ____ Tenía familia o amigos en el grupo Had family in the group (5) ____ Para tener beneficios financiarios asociados con ser socio

To receive financial benefits associated with membership

(6) ____ Para tener beneficios en especie asociados con ser socio como becas escolares o seguro de vida

To receive inkind benefits associated with being a member such as scholarships or life insurance (7) ____ Todos los demás en la comunidad se estaba convirtiendo en socios Everyone else was becoming a member (8) ____ Se vio obligado a unirse, pero no deseaba convertirse en socio Was forced to join but did not want to become member (99) ___ Otro, especifique __________________

6.19 Tuvo que hacer algún pago para unirse? Did you have to pay to join?

(1) ___ Si ¿Cuánto? Q_____________ (2) ___ No

6.20 Que beneficios recibe o podría recibir usted como socio de una

concesión? (Leas todas las respuestas y Marque todas las que aplican) What types of benefits do you receive or are eligible for as a concession member? (check all that apply) (a) _____ Tener prioridad para trabajar get first priority for jobs

(b) _____ Mejoramiento comunitario community enhancements (c) _____ Seguro de vida life insurance

(d) _____ Medicinas y atención médica medical benefits

(e) _____ Becas escolares/donaciones scholarships/grants

(f) _____ Distribución anual de ganancias annual dividends

(g) _____ Acceso a créditos Access to loans

(h) _____ Ninguno None

6.21 ¿Cómo un socio de una concesión, le prometieron algunos beneficios que no recibió? As a concession member, were you ever promised benefits you didn’t receive?

(1)_____Sí (2)_____No (99)_____No sé 6.22 Por favor, clasifica usted los beneficios por ser un socio de una concesión

en orden de importancia para usted. (Indica lo más importante con “1,” el

segundo más importante con “2,” y el ultimo con “3.”) Please rank the benefits for

being a concession member in order of importance.

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(1) ______Beneficios en especie (seguro de vida, atención médica, becas

escolares…etc.) In-kind benefits (life insurance, medical attention,

schorships…etc.)

(2)____Trabajo estable para un salario Stable work for wages

(3)____Dividendos dividends

6.23 De los siguientes beneficios en especie para un socio de una concesión,

cuales son para usted los tres más importantes. (Lea los beneficios y marque el orden de importancia que dice el entrevistado) Of the following in-kind benefits from being a concession member, which are the most important to you? (Read the benefits and mark the order of importance that the participant states.)

(a) ____ Mejoramiento comunitario community enhancements

(b) ____ Seguro de vida life insurance

(c) ____ Medicinas y atención médica medical benefits

(d) ____ Becas escolares/donaciones scholarships/grants

(e) _____ Acceso a créditos Access to loans

6.24 ¿Piensa usted que los socios de una concesión son mejor o peor en términos de sus subsistencias que los no socios? Do you think that members of a

concession are better or worse off in terms of their livelihoods than non-members?

(1)____ Mucho peor Much worse (2)____ Un poco peor A Little worse (3)____ Igual Same (4)____ Un poco mejor A Little better (5)____ Mucho mejor Much better (98)___ No sé Don’t know (97)___ No contesta No answer

6.25 ¿Alguna vez han sido usted o su cónyuge miembro de la Junta Directiva de la Concesión?

Have you or your spouse ever been a member of the board of directors for your concession?

(1) ____ Si, yo Yes, me (2) ____ Sí, mi cónyuge Yes, my spouse (3) ____ Sí, mi cónyuge y yo Yes my spouse and I

(4) ____ No

6.26 ¿Cuánto tiempo han servido usted y/o su cónyuge en la Junta Directiva? ___________ How many years did you and/or your spouse serve on the board? 6.27 ¿Que tan satisfecho está usted en general con el manejo administrativo

de la concesión? How satisfied are you in general with the management of the concession (by the board of directors)?

(1) ____ Satisfecho satisfied

(2) ____ Neutral (3) ____ Insatisfecho unsatisfied

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(98)____No sé Don’t know

6.28 ¿Cuál fue su trabajo principal antes de unirse a la concesión? What was your primary job before you joined the concession?

(1)____ Trabajo relacionado con el bosque (como una concesión industrial o

contrato de PFNM)

(2)____ Agricultor farmer

(3)____ Ganadero Rancher

(4)____ Jornalero diario en agricultura o ganadería daily laborer in agriculture (5)____ Trabajo Doméstico para finqueros u otros patronos (6)____ Empleado en pequeño negocio employee at small business (7)____ Empleado de ONG o contratado por una ONG employee for NGO or

contract work for NGO (8)____ Empleado de gobierno government employee (9)____ Negocio propio (auto-empleo) self-employed business (10)___ Carpintero o trabajador de la madera carpenter or wood worker (11)___ Carrera profesional profesional career (12)___ Turismo relacionado tourism related (99)___ Otro, especifique ____________________________Other, specify

6.29 ¿Comparado con antes, como siente que es su situación económica

después de haberse unido a la concesión? (lea todas las respuestas) How do you feel your economic situation was after you joined the concession compared to before you joined?

(1)____ Mucho peor Much worse (2)____ Un poco peor A Little worse (3)____ Igual Same (4)____ Un poco mejor A Little better (5)____ Mucho mejor Much better (98)___ No sé Don’t know

6.30 ¿Comparado con las personas que no son miembros de la concesión, diría usted que está mejor o peor que esta gente? Compared with people who are not

members of a concession, would you say that you are better off or worse off than these people?

(1)____ Mucho peor Much worse (2)____ Un poco peor A Little worse (3)____ Igual Same (4)____ Un poco mejor A Little better (5)____ Mucho mejor Much better (98)___ No sé Don’t know (97)___ No contesta No answer

Si no es un socio actualmente, pase a la sección 7 If not currently a member, skip to section7

6.31 ¿Cuántas asambleas se han realizado en la concesión durante los últimos 12 meses? ____

How many assembly meetings have there been in the past 12 months?

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6.32 ¿A cuántas de estas asambleas ha asistido usted en los últimos 12 meses? ____

How many meetings have you attended in the past 12 months?

6.33 ¿Ha recibido usted ganancias por ser socio de una concesión, en los últimos 12 meses? Have you received any dividend payments in the past 12 months?

(1) ___ Si ¿Cuánto? Q_____________ (2) ___ No

6.34 ¿Si pudiera venderlo a otra persona, cuánto cree que vale su derecho a la concesión? Q_________________ o No se ______________ If you had to estimate, how much do you think your membership is currently worth if you were to sell it to another person?

6.35 ¿Se le ha asignado alguna tierra dentro de una concesión para uso

personal como agricultura? Have you been allocated any land from the concession for personal

use such as farming and agriculture? (1) ___ Si ¿Cuánta tierra? _____________ manzanas (2) ___ No

SECCIÓN 7. Migración Migration

En la próxima sección, voy a hacerle algunas preguntas acerca de su residencia y cambios de residencia durante su vida. In this section I will ask you some questions about your

residence and residence changes during your lifetime.

7.1 ¿En qué departamento nacieron sus padres? (marque por los dos padres) In which department were your parents born? (mark for each parent)

(1) ____ Petén (9) ____ Guatemala (17) ____ Sacatepéquez (2) ____ Alta Verapaz (10) ____ Chimaltenango (18) ____ San Marcos (3) ____ Izabal (11) ____ Chiquimula (19) ____ Santa Rosa (4) ____ El Quiché (12) ____ Escuintla (20) ____ Sololá (5) ____ Huehuetenango (13) ____ Jalapa (21) ____ Suchitepéquez (6) ____ Baja Verapaz (14) ____ Jutiapa (22) ____ Totonicapán (7) ____ El Progreso (15) ____ Quetzaltenango (23) ____ Otro país (8) ____ Zacapa (16) ____ Retalhuleu

7.2 ¿Hicieron sus padres trabajos con la agricultura? (1)___ Si (2)___ No 7.3 ¿Nació usted en el Petén? Were you born in the Petén? (1)___ Si Pase a la pregunta 7.5 (2)___ No

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7.4 ¿En qué departamento nació usted? In which department were you born? (1) ____ Alta Verapaz (9) ____ Chimaltenango (16) ____ Sacatepéquez (2) ____ Izabal (10) ____ Chiquimula (17) ____ San Marcos (3) ____ El Quiché (11) ____ Escuintla (18) ____ Santa Rosa (4) ____ Huehuetenango (12) ____ Jalapa (19) ____ Sololá (5) ____ Baja Verapaz (13) ____ Jutiapa (20) ____ Suchitepéquez (6) ____ El Progreso (14) ____ Quetzaltenango (21) ____ Totonicapán (7) ____ Zacapa (15) ____ Retalhuleu (22) ____ Otro país (8) ____ Guatemala Pase a la pregunta 7.6 7.5 ¿Nació usted en esta comunidad? Were you born in this community?

(1)___ Si Pase a la sección 8 (2)___ No 7.6 ¿En qué año se mudó usted a esta comunidad? In what year did you move to this

community?_________ (99)___No sé ****Use las siguientes preguntas por los participantes que han cambiado sus residencias. Repita estas preguntas por casa cambio de residencia.*** Use the following questions for the participants that have changed residency.

7.7 ¿Antes de esta comunidad, dónde vivía usted? Utilice el código abajo para llenar el espacio. Before this community, where did you live? Use the code to fill in the space

7.8 ¿Por cuánto tiempo vivía usted en esta comunidad? How long did you

live in this community?

7.9¿Por qué vivía en esta comunidad? Utilice el código abajo para llenar el espacio. Why did you live in this community? Use the code to fill in the space

a)

b)

c)

d)

e)

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1= La Libertad 8= Melchor de Mencos 2= San Francisco 9= Las Cruces 3= San Andrés 10= Dolores 4= Sayaxché 11= San Benito 5= San José 12= Santa Ana 6= Poptún 13= San Luis 7= Flores 14= Otra comunidad en el Petén 15= Otra comunidad dentro del país 16= Otra comunidad afuera del país

1= Mi familia y/o mis amigos estaban allá 2= Tenía trabajo allá/Había más oportunidades para trabajo allá 3= Iba un socio de una concesión 4= Iba barato a vivir aquí 5= Prefería el ambiente de esa comunidad a otras 6= Nací en esta comunidad 7=Otro

SECCIÓN 8. El Manejo de la Reserva de Biosfera Maya Management of the Maya Biosphere

Reserve Esta sección de la encuesta les pregunta a los residentes adentro y cerca de la Reserva de Biosfera Maya (MBR) a declarar como quieren que la Reserva sea dirigida. La MBR era fundada en 1990 para conservar la biodiversidad, mejorar el turismo, animar el manejo forestal sustentable, mantener el cubierto intacto del bosque, preservar los sitios arqueológicos de los Mayas. Sobre tiempo, la gente se ha dado cuenta de los esfuerzos por las comunidades de la MBR a mantener el cubierto del bosque también ha guardado el carbono en los árboles.Por guardar el carbono afuera del aire, los bosques en la MBR reducen los impactos del cambio del clima. El cambio del clima puede afectar la gente en todas partes y es posible que el cambio del clima cause sequías y fuegos en el Petén. This section of the survey asks residents in and around the Maya Biosphere Reserve to state how they want the Reserve to be managed. The MBR was established in 1990 to conserve biodiversity, enhance tourism, encourage sustainable forest management, maintain intact forest cover, and preserve Mayan archaeological sites. Over time, people have recognized that the efforts by the communities of the MBR to maintain forest cover have also stored carbon in trees. By keeping this carbon out of the air, the forests of the MBR reduce the impacts of climate change. Climate change can affect people everywhere, and may cause droughts and forest fires in the Petén Debido a la importancia de los bosques en la MBR a las comunidades que

habitan la región y los beneficios los bosques en la MBR proveen a los

residentes y gente sobre todo el mundo, Nos gustaría comprender como usted

muestra el manejo los bosques en la MBR. Particularmente, querríamos a

comprender su punto de vista en la extracción de madera y productos no de

madera, vender carbón, y participar en el turismo. Sus respuestas van a

ayudarnos a comprender como usted y sus vecinos quieren la MBR ser dirigida

en el futuro.

Given the importance of forests in the MBR to the communities that inhabit the region, and given the many benefits the

forests in the MBR provide to local residents as well as people all over the world, we would like to understand your views

on management of forests in the MBR. In particular, we are interested in understanding your views on harvesting timber

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and non-timber forest products, selling carbon, and participating in tourism. Your responses will help us understand how

you and your neighbors want the MBR to be managed in the future.

Para hacer esto, vamos a presentarte con una colección de escenarios que

describen las maneras diferentes de dirigir la Reserva. Nos gustaría que escoja

la opción que prefiere usted. Esta opción incluye la posibilidad que prefiere

ninguna opción. La MBR consiste del área en la figura abajo. La Reserva es

dividida en tres zonas. La zona de parques nacionales es amarilla. Esta zona

consiste de áreas de preservación de prioridad alta como monumentos de las

Mayas y parques nacionales como Tikal. La extracción de madera y productos

no de madera como xate y chicle es prohibida en esta zona, aunque, se puede

participar en el turismo. La zona de uso múltiple es mostrada en verde. Las

concesiones comunitarias y dos concesiones industriales manejan esta tierra

para la extracción de madera, la extracción de productos no de madera y

turismo. También, hay áreas en esta zona que no son manejadas. La zona de

amortiguador en anaranjada es una tira de tierra de 15 kilómetros en la frontera

del sur de la Reserva que es dedicada en gran parte a las actividades de

agricultura y hacienda. Mucho de la zona de amortiguador es tierra titulada.

To do this, we will present you with a set of scenarios that describe different ways of managing the Reserve. We would

like you to choose the option you prefer, including the possibility that you prefer no changes. The MBR consists of the

area in the figure below. The reserve is divided into three zones. The core zone is in yellow. It consists of high-priority

preservation areas such as national parks and ancient ruins. Timber harvesting, non-timber forest product extraction

(such as xate and chicle) are prohibited there, although tourism can occur. The multiple use zone is shown in green.

Community based concessions and two industrial concessions manage this land for timber, non-timber forest products,

and tourism. There are also some unmanaged areas in this zone. The buffer zone in orange is a 15-kilometer wide strip

along the southern end of the reserve largely dedicated to agricultural and pastoral activities. Much of the buffer zone is

titled land.

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Los escenarios abajo solamente consideran en el manejo en la zona de uso

múltiple en verde en el mapa arriba. Aunque las preguntas son hipotéticas, le

pregunta a usted a escoger las opciones que están basadas en sus preferencias

personales para como se debe manejar la parte verde de la Reserva. Piensa

usted de su elección como votar para el plan que prefiere. Asuma que las

actividades para que la mayoría de las personas votan será implementado

exitosamente en la zona de uso múltiple en la MBR. Su opinión en el manejo de

esta región es muy importante debido a sus experiencias de vivir aquí.

The scenarios only consider management in the multiple use zone in green in the map above. Although the questions are

hypothetical, I ask that you to make your choices based on your personal preferences for how the green part of the

reserve should be managed. Think of your choice as casting a vote for the plan you prefer. Assume that the activities that

the most people vote for will be implemented and executed successfully in the multiple use zone of the MBR. Your opinion

on the management of this region is very important, given your experiences living here.

Nos gustaría que considere usted las siguientes actividades: The following are the activities we would like you to consider

Guardar el carbono Las concesiones comunitarias en la MBR ya han reducido las emisiones de carbono en la atmosfera por impedir deforestación y practicar el manejo sustentable de los bosques. Los socios de las concesiones pueden recibir pagos para este carbono. Comunidades, también, pueden escoger a aumentar el carbono guardado por extractar menos madera de los bosques en las concesiones y en las áreas envolventes en verde arriba. Esta significa que los ingresos ganan de madera van a disminuir mientras los ingresos del carbono van a aumentar. Alternativamente, las concesiones van a aumentar la extracción de madera para aumentar los ingresos de madera extractada de la Reserva, pero no podrán a recibir los pagos del carbono. Niveles: Statu quo: La extracción de madera y el carbono guardado se quedan los mismos y no hay pagos por carbono. Junta el programa del carbono y recibir un pago por el carbono ya guardado, pero mantener el nivel actual de la extracción de madera. Reduce la extracción de madera por 20% y aumenta el carbono guardado por 20% Aumenta la extracción de madera por 20% y reduce el carbono guardado por 20% Carbon Storage The community concessions in the MBR have already stored carbon and reduced the effects of climate change by preventing deforestation and practicing sustainable forest management. They can be paid for this carbon. Communities can also choose to increase carbon storage by harvesting less timber in the concessions and surrounding areas in green above. This means that timber revenues will decline, while carbon revenues will increase. Alternatively, concessions can increase timber harvesting to increase timber revenues, but they will not be able to receive carbon payments.

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Levels: Status Quo: Timber harvests and carbon storage remain the same as currently and there is no payment for carbon. Join carbon program and get paid for carbon already stored, but keep timber harvesting at current levels. Reduce timber harvests by 20% and increase carbon storage by 20% Increase timber harvests by 20% and reduce carbon storage by 20%.

Las ventas del carbono Si el gobierno vende el carbono a un comprador internacional afirmaría un contrato con el gobierno que garantizaría las actividades requeridas para un periodo de tiempo.. El comprador requería el monitoreo estricto de los recursos de carbono en las concesiones. Si los grupos no obedecen por los contratos, los pagos pararían y es posible que el gobierno recompense alguno o todo el dinero. Niveles: Statu quo: no vende Vende con un contrato de 5 años vende con un contrato de 10 años vende con un contrato de 20 años Carbon Sales If the government sells the carbon to an international buyer, they would sign a contract that would lock in the required activities for a given time period. The buyer would require strict monitoring of the carbon resources in the concessions, and if the groups were not abiding by the contract, then payments would stop, and the government may have to repay some or all of the money. Levels: Status Quo: Do not sell Sell with 5 year contract Sell with 10 year contract Sell with 20 year contract.

Otras actividades

El Turismo y la colección de productos forestales no de madera como chicle y xate son

actividades que ocurren actualmente entre las concesiones. Estas actividades no afectan

la extracción de madera ni el carbono guardado, pero pueden tener otros impactos en el

ecosistema y la biodiversidad que son posiblemente negativos.

Niveles:

Statu quo: Continua en la situación actual con ambas actividades

Solamente permite turismo

Solamente permite la colección de productos no de maderaNo permite ninguno

Other activities Tourism and the collection of non-timber forest products, such as chicle and xate, are also activities that currently occur

within the concessions. These activities do not affect timber harvesting or carbon storage, but they can have other,

potentially negative, impacts on ecosystems and biodiversity.

Levels

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Status Quo: Continue as is with both activities possible in the concessions

Only allow tourism

Only allow collection of Non-timber Forest Productions

Do not allow either activity.

Pago: Por cambiar el manejo de la Reserva, los pagos que va a recibir de su concesion

puede aumentar o disminuir. Esta incluye todos los cambios posibles a sus sueldos y/o

dividendos. Debajo esta alternativa, recibiría___________

Niveles:

Status Quo: 0Q por año

+800Q por año

+2000Q por año

+3200Q por año

+4800Q por año

Payment: By changing management of the reserve, the payments you receive from your concession could increase or

decrease. This includes all possible changes to wages and/or dividends. Under this alternative, you would receive

_________.

Levels:

Status Quo: 0Q per year

+800Q per year +2000Q per year +3200Q per year +4800Q per year

*Lengua alternativa por no socios: Estos cambios en los acuerdos de las concesiones

resultaría en ingresos más grandes o más pequeños en la región, los cuales permitiría los

pagos ser hechos a todos los individuos que viven entre la región.. Debajo de esta

alternativa, recibiría ________

Niveles:

Statu Quo: 0Q por año

+800 por año

+2000Q por año

+3200Q por año

+4800Q por año

*Alternative language for non-concession members: These changes in the concession agreements would result in

larger or smaller revenues in the region, which would allow payments to be made to all individuals living within the region.

Under this alternative you would receive ___________.

Levels:

Status Quo: 0Q per year

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+800Q per year +2000Q per year +3200Q per year +4800Q per year

El vehículo del pago:

Niveles:

El pago le viene a usted

El pago le viene a su concesión (o pueblo por los no socios)

Payment vehicle: Levels: The payment comes to you individually The payment comes to your concessions and is used for concession related efforts *Alternative for non-concession members: The payments comes to your village and is used for community improvements (sewage treatment, water supply, schools, medical clinics, etc.).

Asuma usted, por favor, que el manejo de las opciones que escoge puede ser

ejecutadas exitosamente.

Please assume that the management options you choose can be executed successfully.

Ahora, voy a presentarle a usted con cuatro escenarios. Considera cada

escenario separadamente y asuma que no puede cambiar las opciones de

diferentes escenarios. Piensa de esta actividad como una vota para los

programas que le gustaría implementar en la MBR y cualquieras actividades que

reciben la mayoría de la votas van a ser implementadas. Vamos a darle a usted

un escenario con tres opciones: dos planes propuestos y una opción para el

statu quo. Por votar por la opción de statu quo, está diciendo que prefiere

mantener los niveles actuales del turismo, la extracción de productos de madera,

la extracción de productos no de madera y el cubierto intacto del bosque con no

programa del carbono en la MBR. Por votar de uno de las opciones de los

planes propuestos, está diciendo que preferiría eso plan a la opción de statu quo

y la otra opción para el plan propuesto.

I will now present you with four choice scenarios. Consider each scenario separately and assume you cannot combine

choices from different scenarios. Think of this activity as casting a vote for the programs you would like to see

implemented in the Maya Biosphere Reserve and whichever activities receive the most votes will be implemented. You

will be given a scenario with three options: two proposed plan options and a status quo option. By voting for the status

quo option, you are saying you prefer to keep the current levels of tourism, timber harvesting, non-timber forest product

collection, and intact forest cover with no carbon program in the MBR. By voting for one of the proposed plan options, you

are saying you’d prefer that plan to the status quo and the other proposed plan option.

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Este es el fin de la encuesta. Muchas gracias por su colaboración. Aquí hay 25 Quetzales por su tiempo. ¿Puede por favor firmar la hoja y el recibo de pago? Nuevamente gracias por su colaboración. This is the end of the interview. Thank you very much for your participation. Here is 25 Quetzales to compensate for your time. Can you please sign your name here (hand them form) in receipt of payment? Again, thank you for participating.

Este es el fin de la encuesta. Muchas gracias por su colaboración. Aquí hay 25 Quetzales por su tiempo. ¿Puede por favor firmar la hoja y el recibo de pago? Nuevamente gracias por su colaboración. This is the end of the interview. Thank you very much for your participation. Here is 25 Quetzales to compensate for your time. Can you please sign your name here (hand them form) in receipt of payment? Again, thank you for participating.

* * * * * * * * * * * * * * * PARA EL ENCUESTADOR FOR THE ENUMERATOR * * * * * 9.1 Se mostró la persona entrevistada nerviosa o irritada por las preguntas durante la encuesta?

Was the person who answered the questions irritated or nervous during the interview?

(1)______ Si (2)______ No

9.2 Considera usted que el entrevistado hizo un esfuerzo por decir la verdad? Do you think the respondent made an effort to tell the truth?

(1)______ Si (2)______ No

9.3 Como calificaría en general la calidad de la entrevista?

How would you rate the overall quality of the interview?

(1)______ Buena Good (skip next question) (2)______ Razonable Fair (3)______ Pobre Poor

9.4 Por favor anote comentarios o preocupaciones específicas: Please note specific

concerns or comments:

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