Decentralization and Deforestation: The Local Politics of
Environmental Policy
Glenn D. Wright
University of Alaska, Southeast, [email protected]
Krister P. Andersson
University of Colorado, [email protected]
Tom Evans
Indiana University, [email protected]
Clark C. Gibson
University of California, San Diego, [email protected]
Abstract
Policymakers and scholars often tout decentralization as an effective tool in the management of
natural resources such as forests. We argue that the mere existence of a decentralization policy –
even one which actually gives real powers and resources to local governments – does not mean
that local politicians will take an interest in its execution. We argue that politicians, such as the
mayors of Bolivia and Peru in this study, have limited attention and resources at their disposal
and will prioritize actions that will serve their short-term political interests. We hypothesize that
only when community organizations engage with local officials and pressure them to prioritize
forestry-sector activities can decentralized forest policy be successful. We test this argument
using longitudinal field data on social and biophysical characteristics in a large number of local
government territories in Bolivia (a country with a decentralized forestry policy), and Peru
(which has a more centralized forestry policy). We find that decentralization has a small and
positive effect on forest-cover change, and this effect is amplified when community engagement
with local government is high. We attribute these results to the potential positive effects of
community engagement on local political incentives as well as improved information flows.
Key words: Bolivia, Peru, Decentralization, Governance, Natural Resources, Environmental
Policy, Forestry
2
Decentralization and Deforestation
Introduction
Scholars and policymakers continue to debate about the appropriate locus of control
over environmental resources. One of the central topics in this discussion concerns the efficacy
of the decentralizing control over natural resources to lower levels of government and/or the
affected communities themselves. Many argue that decentralization can promote better
governance outcomes, especially in developing countries, (Agrawal & Ribot, 1999; Faguet,
2004; 2009; Faguet & Sanchez, 2008; Ferejohn & Weingast, 1997; Treisman, 2007; Veron,
Williams, Corbridge, & Srivastava, 2006). This argument has been used widely by interactional
organizations who have actively promoted and funded decentralization reforms in developing
countries (FAO, 2001; UNDP, 2000; OECD, 2009) However, some scholars have raised
concerns about the effectiveness of decentralized governance, suggesting that decentralization
reforms may result in worse outcomes, or at best, outcomes will be no better than under
centralization (Atkinson, Rolim Medeiros, Lima Oliveira, & Dias de Almeida, 2010; Boone,
2003; Donahue, 1997; Lambright, 2010a; Transparency International, 2009; Treisman, 2007).
For example, local governments, their argument goes, may lack the financial resources to
implement and maintain policies, or local communities -- even those with a large stake in the
effective management of a particular resource - may fail to organize themselves to advocate for
or support such policies. Some empirical evidence for the effectiveness of decentralized
environmental policy exists, but has been hampered by research designs that do not employ
comparable longitudinal data related to local governments, communities, and resource outcomes
(Faguet, 2004; 2009; Treisman, 2007). Even so, and despite the dearth of scientific evidence on
its effectiveness, decentralization reforms have never been more popular as a solution to
mounting social and environmental problems (Rodden, 2006; Campbell, 2001; Faguet, 2014;
World Resources Institute, 2005).
Here, we argue that the local politics of decentralized environmental policy are critical to its
success. More specifically, community engagement with local governments is pivotal for good
policy outcomes. The mere existence of a decentralized policy does not mean that local
politicians are interested in its execution. But politicians, such as the mayors of Bolivia and Peru
in this study, have limited attention and resources at their disposal. In general, elected officials
will prefer to pursue policies that their electorate signals is important to them. A decentralized
policy alone may not affect the condition of a natural resource; we hypothesize it is far more
likely to have positive effects if local community organizations are engaged with a local
government about their forests. Thus, it is the interaction between decentralization and local
political incentives that augurs better environmental outcomes than decentralization alone.
We collected empirical data to construct a cross-national database that allows for the testing
of the relationship between decentralization policy, local politics, and forest cover in Bolivia and
Peru. While sharing a number of biophysical and cultural factors, Bolivia ‘s central government,
starting in 1996 devolved municipalities given substantial rights, responsibilities, and resources
to govern their forested areas; over the same time period, Peru kept most powers over forests
under the purview of their central government. We compiled four major data sets in this study:
original surveys of local governance actors in 2000 and 2007, census/archive data (2000, 2007),
3
Landsat TM satellite imagery and aerial photography from 1993, 2000, and 2007, and digital
elevation models to derive surface slope measures (topography) for all the localities in each
country. We use matching techniques to compare 200 municipalities in a decentralized setting to
municipalities which share similar demographic and biophysical characteristics in a centralized
regime. With these data, we evaluate the effect of community organization’s interactions with
local officials using GEE regression analysis.
To preview our results, we find that de jure decentralization has a positive association with
forest cover stability: Bolivian municipalities enjoy more forest cover stability than their
matched Peruvian municipalities. But this difference between centralized and decentralized
localities holds only when community engagement with local government is high. Our results
suggest that ability of decentralization to usher in better forest outcomes depends directly on how
local user groups and politicians interact with one another.
Decentralization and Natural Resource Governance
A substantial and growing literature demonstrates that it is possible for small communities to
develop effective systems of resource governance without much help from outside actors such as
central governments (Agrawal, 2005; Chhatre & Agrawal, 2008; Ostrom, 1990; Van Laerhoven,
2010). If such decentralized local governance is possible, is it superior to centralized policy
making about forests? Scholars have forwarded a large number of arguments suggesting that
decentralization may be better than centralized decision making. First, some argue that
decentralization is more efficient than centralized governance, suggesting that decentralized
regimes will be able to do more with less and effectively govern forests with fewer fiscal
resources (Oates, 1972). Second, local governments may be able to more easily gather
information about local conditions, crafting policies that better suit local wants and needs, and
carrying out policy experiments which, if successful, can be adopted by other jurisdictions
(Hayek, 1945; Litvack et al 1998; Manor, 1999; Brandeis, n.d.). Finally, decentralized
governance may generate better outcomes because under decentralization, decisions can be made
closer to the citizenry, in a more democratic manner (Agrawal & Ribot, 1999; Ribot, 2003).
At the same time, many of these same scholars express skepticism that the theoretical benefits of
decentralization will come to fruition because of a range of countervailing pressures and
problems with the way decentralization reforms are carried out. For example, it is easier for
wealthy people to participate in governance than poor people, which means that decentralization
may lead to policies which harm the poor and disproportionately help the wealthy (Agrawal &
Gupta, 2005; Andersson and Persha, 2014). Of course, decentralization may fail to be
democratic, lacking “downward accountability,” which some have pointed to as the keystone of
effective decentralized resource governance (Ribot, 2003). And decentralization may also lead
to inequitable outcomes because of existing power asymmetries that allow elites to capture
newly-empowered local institutions (Poteete & Ribot, 2010). Much ink has also been spilled
debating the merits of the so-called “race to the bottom” hypothesis, in which decentralization
encourages resource degradation as local governments compete to attract industry by lowering
taxes and loosening regulation (Revesz, 1997), although some have argued that such a dynamic
can also lead to a beneficial “race to the top” (Donahue, 1997; Howell-Moroney, 2008; Tiebout,
1956). In addition, decentralization my fail to provide sufficient resources to local governments
to carry out the tasks delegated to them, leading to a situation where local governments lack the
capacity to carry out effective policy (Ribot, 2003). Finally, “decentralization” may be a
4
smokescreen for political efforts to undercut political leaders’ rivals, or “theater pieces” designed
to improve outside actors, and may contain little real substantive policy change (Agrawal &
Ribot, 1999; Lambright, 2010b; Ribot, Agrawal, & Larson, 2006).
Studies assessing the general effects of decentralization have generated contradictory
evidence. Faguet, (2004) for example, finds that decentralization is associated with greater
government responsiveness in Bolivia, and Faguet and Sanchez (2008) find the same for
Colombia. On the other hand, using a set of formal models to examine the internal consistency
of arguments for and against decentralization, Treisman (2007) finds no evidence that
decentralization should produce either better or worse outcomes. Lambright (2010) suggests that
decentralization is often associated with poor outcomes. Poteete and Ribot (2010) lays out a
theoretical proposition that questions many of the existing assumptions about the nature of
decentralization and argue that decentralization is better understood as a conflict-laden process
between central governments, NGOs, and sub-national governments in which different actors
jockey for power, rather than a clear-cut set of reforms that automatically devolve authority to
local or regional government.
That said, most of the recent empirical studies on forest governance and decentralization in
developing countries find decentralization to have had a positive effect on forest conditions. For
example, Somanathan et al. (2009) find that decentralization is associated with forest
conservation in the Indian Himalayas. The authors compare forests controlled by village councils
with state-controlled forests and describe forests that have been conserved at least as well and
possibly better under decentralized management and at much lower cost (Somanathan,
Prabhakar, & Singh Mehta, 2009). Also in the Indian Himalayas, Baland et al. (2010) find that
local governance of forest resources generally outperforms central government management in a
variety of areas (Baland, Bardhan, Das, & Mookherjee, 2010).
Cross national research also show a positive relationship between decentralized user
governance and desired biophysical outcomes. Hayes (2006) uses data from 163 forests in 13
countries and shows that community-managed areas boast higher levels of overall vegetation
than government-managed forest areas. These findings are consistent with Porter-Bolland et
al.’s meta-analysis of 73 published case studies on centralized and decentralized forest
conservation approaches in a wide variety of contexts (2012). The authors find that decentralized
conservation approaches generally yield more stable forest cover.
The research designs of current work, however, limit the inferences that may be drawn from
these studies about local governance and forest outcomes. Most analyses focus on a very small
sample of local units within a single geographic area (e.g. Agrawal and Ribot 1999; Crook and
Manor 1998). Studies using large-n samples, on the other hand, tend to feature community-level
resource user groups as the unit of analysis and not local, multipurpose governments, the most
common target of decentralization reforms (Agrawal & Chhatre, 2006; Chhatre & Agrawal,
2009). Few comparative decentralization studies use longitudinal data to test the causal
processes that might drive variations in local government performance, primarily because
longitudinal data on local government units in decentralized or centralized regimes is rare. Even
what might be considered the best empirical studies of decentralized forest governance regimes
rely exclusively on cross-sectional data for one time period (Chhatre & Agrawal, 2008; Gibson,
Williams, & Ostrom, 2005). Finally, very few studies examine actual biophysical outcomes on
resources such as forest cover change, our key outcome variable in the analysis (though see
Chhatre and Agrawal 2009 for a counter-example). Instead, most focus on policy outcomes and
5
human activities such as government expenditures (Andersson, Gibson, & Lehoucq, 2006),
forest-related conflict (Ravikumar, Andersson, & Larson, 2012), inequality (Andersson &
Agrawal, 2011; Persha & Andersson, 2014), and collective action (Barnes & Van Laerhoven,
2014; Naidu, 2009). A number of excellent studies use large-n, statistical analysis, crossnational data, longitudinal data, data on municipal governments or biophysical data. Here we
seek to build on these previous efforts to combine all of these methodological features into one
study.
Our Approach
Decentralizing authority over forests can put new powers and resources into the hands of
officials at the local level. But bringing natural resource governance closer to the communities
that depend on them does not automatically mean that local governments will invest their scarce
time and resources into this policy area. A foundational assumption in political science is that a
politician must first and foremost worry about winning elections; even the most policy-driven
individual must gain office before pursuing their policy goals. A politician’s decision to invest
her time or resources into any activity will always be made with at least one eye on its electoral
consequences.
Consequently, even if it is assumed that a decentralized policy actually bequeaths new
powers and financial resources to an elected official (and is not just an unfunded mandate as
many decentralized natural resource policies are1), there is no a priori reason to believe that this
new clout will result in any change of her activities, or at least not in any activity that may help
produce better natural resource management. Citizens of developing countries infrequently
mention their forests as an issue that is important to them. Instead, individuals are generally
concerned with more tangible concerns, like employment, health, education, and infrastructure
such as roads and housing (Inglehart, 1995).
In this view, a decentralized forestry policy would more likely have an effect on outcomes
when individuals engage with local officials about forests. By communicating with officials,
community members signal their concern, which in turn makes the issue more electorally salient
than before. We do not claim that such communication is necessarily conservation-oriented. In
fact, individuals could be discussing a variety of things with their leaders that could vary from
wanting more access to forest products, to disputes about where the formal boundaries of the
forests are in relation to private land to complaints about outsiders poaching timber. Rather, we
assume that in total, more engagement increases the likelihood that officials will use their powers
and or resources of the decentralized policy to govern this sector more actively, which would
lead to more stable forest cover on the landscape. We hypothesize that decentralization will be
positively correlated with forest cover change (that is, will be correlated with lower rates of
deforestation and higher rates of afforestation) where members of local communities engage
more frequently with local officials about forests.
Forest Policy in Bolivia and Peru
The cases of Bolivia and Peru provide an excellent comparison through which to examine the
effects of decentralization and community engagement in the forest sector. While these
1
For useful discussions of the conflict-laden process of decentralization, see Agawal and Ribot
1999; Ribot, Agrawal and Larson 2006, and Poteete and Ribot 2010.
6
neighboring countries share a number of essential biophysical, socio-economic, historical and
cultural characteristics, they differ on the variable of theoretical interest to this study:
decentralization. Starting in 1996, Bolivian local governments were given substantial rights,
responsibilities and resources from the central government to govern forest areas within their
territories, while Peruvian local governments have no formal mandate for governing forests
(Andersson et al., 2009; Jaramillo and Wright, 2014; Kauneckis & Andersson, 2009).
Bolivia and Peru are both located along the Andean spine of South America, and both
include high mountain environments, and lowland Amazon jungle. The two countries both have
large indigenous populations, including Quechua- and Aymara-speaking highland indigenous
peoples as well as multiple lowland indigenous groups. Both are middle income countries with
high levels of inequality and a great deal of rural poverty. Both countries share a history of
Spanish colonial domination and unstable, authoritarian regimes in the post-independence
period. More recently, both countries have experienced similar waves of neoclassical or
“neoliberal” economic liberalization. And both countries have recently emerged from periods of
authoritarian rule and now host vibrant, contentious, though often corrupt democratic national
governments. However, in forest governance, Bolivia and Peru differ on their level of
decentralization. This makes it possible to compare municipalities on the Peruvian side of the
border to similar municipalities on the Bolivian side to examine the effects of decentralization.
In addition, longitudinal data makes it possible to compare pre-decentralization Bolivian
municipalities to similar municipalities after decentralization was imposed.
Like most other Latin American countries, Bolivia was long organized as a de facto unitary
state. This de facto centralization changed dramatically in the mid-1990s, when the Congress of
Bolivia passed the 1994 Ley Participación Popular, the “Popular Participation Law”—
essentially a package of decentralization reforms which granted substantial authority and 20% of
national tax revenues to municipal governments (Andersson, 2003; CIFOR, 2007; Oemer,
Oemer, & Oemer, 2004; Pacheco, 2006; Wil de Jong, 2004). These municipal governments are
similar to most municipal governments in the United States, with a municipal council (elected
through proportional representation) and a separately elected mayor. Bolivian governments also
have a third elected institution called the Comité de Vigilancia, Oversight Committee, which
consists of elected representatives of community organizations and which has the power to
oversee the mayor’s office and municipal council and to stop the flow of federal transfers to the
municipal government if they believe the municipal government is acting in a corrupt or
inappropriate way.
Decentralization in the forestry sector has been less dramatic, but the 1996 Ley Forestal
1700, Forestry Law 1700, was designed to encourage sustainability in the forestry sector by
lengthening the tenure of government leases to forestry firms for timber exploitation, making
these leases renewable, and improving the security of tenure for the forest-dependent poor by
creating new jurisdictions for the communal management of local forest resources. (ContrerasHermosilla & Vargas Ríos, 2002; Pacheco, 2006). Under the new decentralized forestry regime,
municipalities have the power to monitor forestry leases and enforce forestry rules and
regulations within their territory (Andersson, 2003; Andersson et al., 2006).
Fiscal decentralization in Bolivia has primarily taken the form of transfers of funding from
the central government to municipal governments. In general, funds are not linked to the
implementation of any particular policies (Contreras-Hermosilla & Vargas Ríos, 2002; Pacheco,
2006; Wil de Jong, 2004). Transfers from forestry sources are provided annually to
7
municipalities based on the size of the municipal territory currently under management as
forestry concessions.
Unlike Bolivia, decentralization had not yet touched the forestry sector in Peru at the time of
our last wave of data collection in 2009. Unlike many Latin American countries which
implemented decentralization reforms in the 1980s and 1990s, the Peruvian national government
only truly began to devolve power in the early 2000s, during the presidency of Alejandro Toledo
(Vega Castro, 2008). Peruvian decentralization reforms granted a broad mandate to Peruvian
municipal and regional governments. These government are structured much like local
governments in the United States and Bolivia, with independently elected executives (mayors)
and separately elected legislatures (city councils) (Jaramillo, 2009). These governments are
generally funded largely by transfers from the national government, following a complex
formula incorporating measures of poverty, population, and estimates of local and regional
hydrocarbon and mineral revenues (Ahmad & García-Escribano, 2006).
Data
There are four major data sources for this study: (1) surveys of local governance actors
(2000 and 2007), (2) census/archive data (2000, 2007), (3) satellite images (1993, 2000, and
2007), and (4) digital elevation models of Peru and Bolivia. In each of the 200 selected
municipalities, we interviewed the elected mayor in two waves: 2000/1 and again in 2007/8. In
addition, we interviewed municipal forestry officials and community leaders in order to
triangulate responses in 2007/8. Each face-to-face interview took approximately 1.5-2 hours.
The survey instrument (258 questions) was designed to elicit information regarding the
interviewee’s policy priorities, staff, relationship with central and nongovernmental agencies,
and relationship with citizens. It uses a variety of techniques to understand political incentives
and behaviors. We checked several interview responses with archival data and found the survey
instrument to be highly reliable. We also use government statistics from both countries for some
of our key variables (as noted below).
Our biophysical data was generated from two sources: (1) digital elevation models to create
topographic data, and (2) forest cover data that were generated using remote sensing techniques
(Landsat TM satellite imagery and aerial photography). We use digital elevation models to
generate estimates of altitude and the percentage of land in each municipality above a 12%
grade—that is, the slope above which commercial, large-scale agricultural production is not
feasible. We also hired remote-sensing analysts in Peru and Bolivia to estimate forest cover
change for our sample of 100 local government territories in Bolivia for the period 1993-2008,
and for 35 Peruvian municipalities in the period 1990-2008. Table 1 presents the descriptive
statistics of the main variables included in the empirical analysis.
[Table 1 about here]
We present two independent variables of interest: de jure decentralization reforms and degree
of community engagement on forest cover change (deforestation) over time. De jure
decentralization is a dummy variable that identifies whether the municipality was located in a
formally decentralized regime, therefore this variable is coded 0 in both time periods for Peru,
and 0 in period 1 for Bolivia (2001), and 1 in the second time point for Bolivia (2008).
Decentralization was coded in this way because we believe that the 1996 decentralization
reforms would not have had a substantial impact on policy and forest cover by 2001, but would
8
have begun to have an effect by 2008. However, to ensure the robustness of our results, we
tested all of the models presented here with an alternative coding, in which Bolivia is coded 1 in
both time periods. Although this changed the balance of our matching sample significantly, the
direction and significance of our results did not vary when using this alternate coding.
Community engagement is a variable that denotes the degree to which a local government is
connected through frequent interactions about forestry with community-based organizations.
This variable is drawn from our survey question that asks respondents how often community
organizations expressed opinions regarding forestry to municipal government officials on a range
from 1 (“never”) to 5 (“very frequently”). We averaged the responses from surveys with
mayors, local forestry officials, and community organization leaders to generate an overall
measure of the degree of community engagement in a municipality.
Quantitative Estimation Techniques
Our empirical tests employ two multivariate techniques: (a) Mahalanobis matching with
propensity scores, and (b) GEE regression using Mahalanobis matching with propensity scores
as a pre-processing technique to eliminate non-comparable observations.
Ideally, to test the effects of decentralization on forest-related outcomes such as
deforestation, we would use a randomized, controlled experimental approach, in which
decentralization reforms would be applied to randomly selected jurisdictions such as
municipalities, while other jurisdictions would not receive the decentralization “treatment”. If
decentralization were applied randomly to municipalities in Bolivia and/or Peru, for example, it
would be possible to examine the effects of decentralization, by comparing the average changes
in forest cover in decentralized municipalities to changes in forest cover in cases which have not
been “treated“ with decentralization.
Such an approach is not possible, however, and although decentralization reforms in forest
policy have been applied to municipalities in Bolivia and not in Peru, a simple comparison
between Bolivian and Peruvian municipalities in terms of land cover change and other forestryrelated outcomes (the so-called difference in difference approach) is not appropriate. This is
because we are likely to confuse differences between Peru and Bolivia with the effects of
decentralization (Fisher, 1966; Rubin, 1990; Splawa-Neyman, 1990).
Instead, we use multivariate matching techniques to examine the effects of decentralization.
Specifically, we use a matched sample in which municipalities in a decentralized setting are
matched with non-decentralized municipalities which share several key characteristics.
We use Mahalanobis matching in this study. This approach matches observations (in this
case, several treatment cases for each control) according to the “Mahalanobis distance” between
them. The Mahalanobis distance is the distance between observations in a multi-dimensional
space, in which each dimension is a control variable (a variable upon which the matching is to be
based). By using this technique, it is possible to generate a set of matched cases in which
treatment and control cases are not significantly different on observables, except for the
treatment. In essence, then, the technique, like other matching techniques, generates a
“treatment” and “control” group that are statistically not significantly different on important
observable control variables (Rubin, 1980; Sekhon, 2009)
9
Results
In this section, we first present a comparison between unmatched Bolivian and Peruvian
municipalities to give some ideas of the differences between the two countries in general, and
which begin to illustrate the importance of matching or similar techniques in order to carry out
meaningful comparisons. We then show results from testing the relationship between
decentralization and deforestation without considering community engagement. Finally, we
present results from the GEE regression that tests our hypothesis about the effect of the
interaction of community engagement and decentralization on forest cover change.
Pre-Matching Differences
The box and whisker plots in Figure 1 give a good idea of some of the differences between
municipalities in Peru and Bolivia in terms of our variables of interest. First, in terms of rates of
forest cover change, Bolivia seems to have much better outcomes, as the Bolivian cases are
experiencing much slower rates of deforestation than our Peruvian cases. The median rate of
forest cover change in Bolivia is about -1% (loss of about 1% of forest cover a year). On the
other hand, Peru’s median rate of change is greater than -3%, with extreme values around -14%.
Similarly, Bolivian municipalities in our sample have lower levels of community engagement
(the scales of these variables are explained in “Data,” above).
[Figure 1 here]
In general, then, these naïve comparisons might lead us to conclude that decentralization—
present in Bolivia but absent in Peru in the forestry sector—is associated with lower rates of
deforestation. However, these comparisons fail to take into account some of the systematic
differences between Bolivian and Peruvian municipalities which may be correlated with
community engagement. More specifically, it is possible that these are comparisons of apples in
oranges. To address this concern, we carry out a series of matched comparisons that permit us to
compare apples to apples and conclude with much greater certainty whether decentralization is
associated with differences in community engagement and deforestation.
Decentralization
Our final set of models—in which treatment cases were similar to control cases—showed
significant differences between decentralized and non-decentralized cases, even after including
controls and comparing between cases which do not significantly differ in terms of our control
variables: First, matching results showed that decentralized cases had significantly more positive
rates of forest cover change than non-decentralized cases. This means that observations in
decentralized settings had, on average, higher rates of afforestation and lower rates of
deforestation. In other words, forests were better off in decentralized settings than in nondecentralized ones. The average treatment effect (ATE) associated with decentralization was
about 2.6 percent of more forests per year. Arriving at this result and generating a balanced
sample required trimming our sample down to about 100 observations where propensity score
matches were most dense. These results are shown in table form in Table 2, and in a more
intuitive graphical form in Figure 2, which allows us to easily compare the post-matching
distribution of forest cover change and community engagement in municipalities in centralized
and decentralized settings.
[Table 2 about here]
[Figure 2 about here]
10
Interaction of Community Engagement and Decentralization
We then tested the effects of community engagement regarding forestry on deforestation
across decentralized and centralized municipalities to see if the effect differed. To do so, we
generated an interaction term—the product of “decentralization” and “community
engagement”—and included the interaction term, as well as both base terms, in a GEE model
with the same control variables used above. Where an interaction term is included in a
regression model like the GEE models used here, the significance of coefficients in the table is
not substantively meaningful, therefore, as suggested by methodologists, we show a graph of the
marginal effects of a change from a centralized to a decentralized regime, conditional on the
level of community engagement (Brambor, Clark, & Golder, 2006; Keefer, 2007). The
regression results are presented in the Appendix.
[Figure 3 about here]
The effect of decentralization on forest cover is shown in Figure 3, and provide support for
this study’s central hypothesis: Where community engagement is low i.e., where community
organizations rarely interact with local government officials to express opinions regarding
forestry, there is no significant effect of decentralization on deforestation. However, where
community engagement is greater, decentralization has a positive and significant effect on forest
cover change, leading to lower rates of deforestation.
Discussion and Conclusions
Given some of the past and ongoing unsustainable deforestation rates across the globe,
donors, non-governmental organizations, and governments have suggested the decentralization
of authority over forests to lower levels of government (Andersson & Gibson, 2006; World
Bank, 2003; World Resources Institute, 2005). The reasons behind this proposal were many:
many central government units were corrupt, poorly funded, and/or poorly trained. It was also
thought that local governments and communities would have more knowledge about their forests
and thus create more efficient policy in their locale.
Many countries did indeed pursue decentralization in the forestry sector, although not all
of these efforts devolved any real power to local governments, and others merely created laws
that resulted in unfunded mandates (Agrawal & Ribot, 1999; Poteete & Ribot, 2010; Ribot et al.,
2006). Other countries created programs that skipped local government and worked directly
with non-governmental organizations or other unelected, non-democratic organizations (Ribot,
2003). Results on the landscape from these efforts have been mixed, and the causes of failure
and success have been many (Ribot et al., 2006). In several cases, researchers have noted that
without the support of local governments and the communities they serve, such decentralized
policy will fail (Agrawal & Ribot, 1999).
We also hypothesized this relationship, but sought to contribute to this work by using
clear measures of the dependent and independent variables, data and methods appropriate for
rigorous testing. We built a unique dataset that incorporates individual level survey data, census
and budget data, digital elevation models, and remote sensing. By combining these elements at
the level of municipal government and employing matching and GEE regression techniques, we
provide new evidence in support of the idea that both decentralization and community
engagement are necessary to achieve better forest outcomes. What might explain these results?
We suggest there are at least two ways in which community engagement help to make
decentralized governance more effective. First, when community-based organizations interact
11
regularly with local politicians they may affect their political incentives by articulating
preferences and even demands for interventions in the forestry sector. These interactions also
offer opportunities to hold the local officials to account, face to face. Second, community
interactions also present an opportunity for local forest users to provide information about local
circumstances to the local politicians, which may help the latter to devise a more effective policy
response. For example, these interactions may reveal who the individuals are that are responsible
for some of the deforestation activities, and suggest ways in which the problems might be
addressed. Unfortunately, we do not have the data to test these potential causal paths, but hope
that future research will be in a position to investigate the validity of these explanations.
One possible concern with our results is the possibility of and endogenous relationship
between forest cover, decentralization, and community engagement. While we did not run an
experiment in this study, we believe that our use of baselines, longitudinal data, and matched
cases helps support the causal logic of our hypothesis.
Our results lead to a number of additional questions that, while important to those
interested in creating more effective policy, were not part of this study: How is community
engagement generated? Is it a result of community level self-organizing, or do people become
more engaged because the local government facilitates it? What are the best “forms” of
community engagement? What specific powers does a decentralized polity require to be
successful? We currently lack the data to answer these questions here, although we do note that
our observations in the field strongly suggest that communities are unlikely to engage with
municipal governments unless the municipalities are perceived to be at least minimally effective.
12
References
Agrawal, A. (2005). Environmentality: Technologies of Government and the Making of Subjects.
Durham, NC: Duke University Press.
Agrawal, A., & Chhatre, A. (2006). Explaining success on the commons: Community forest
governance in the Indian Himalaya. World Development, 34(1), 149–166.
doi:10.1016/j.worlddev.2005.07.013
Agrawal, A., & Gupta, K. (2005). Decentralization and Participation: The Governance of
Common Pool Resources in Nepal’s Terai. World Development, 33(7), 1101–1114.
doi:10.1016/j.worlddev.2005.04.009
Agrawal, A., & Ribot, J. (1999). Accountability in Decentralization: A Framework with South
Asian and West African Cases. The Journal of Developing Areas, 33, 473–502.
Ahmad, E., & García-Escribano, M. (2006). Fiscal decentralization and public subnational
financial management in Peru. IMF Working Papers. Washington, D.C.
Andersson, K. (2003). What Motivates Municipal Governments? Uncovering the Institutional
Incentives for Municipal Governance of Forest Resources in Bolivia. The Journal of
Environment & Development, 12(1), 5–27. doi:10.1177/1070496502250435
Andersson, K., & Agrawal, A. (2011). Inequalities, institutions, and forest commons. Global
Environmental Change, 21(3), 866–875. doi:10.1016/j.gloenvcha.2011.03.004
Andersson, K., & Gibson, C. C. (2006). Decentralized Governance and Environmental Change.
Journal of Policy Analysis and Management, 26(1), 99–123. doi:10.1002/pam.20229
Andersson, K., & Van Laerhoven, F. (2007). From Local Strongman to Facilitator: Institutional
Incentives for Participatory Municipal Governance in Latin America. Comparative Political
Studies, 40(9), 1085–1111.
Andersson, K., Gibson, C. C., & Lehoucq, F. (2006). Municipal politics and forest governance:
Comparative analysis of decentralization in Bolivia and Guatemala. World Development,
34(3), 576–595. doi:10.1016/j.worlddev.2005.08.009
Atkinson, S., Rolim Medeiros, R. L., Lima Oliveira, P. H., & Dias de Almeida, R. (2010). Going
down to the local: incorporating social organisation and political culture into assessments of
decentralised health care. Social Science & Medicine (1982), 51(4), 619–36.
Baland, J.-M., Bardhan, P., Das, S., & Mookherjee, D. (2010). Forests to the People:
Decentralization and Forest Degradation in the Indian Himalayas. World Development,
38(11), 1642–1656.
Barnes, C., & Van Laerhoven, F. (2014). ScienceDirect. Environmental Science and Policy, 1–
14. doi:10.1016/j.envsci.2014.06.008
Boone, C. (2003). Decentralization as Political Strategy in West Africa. Comparative Political
Studies, 36(4), 355–380.
Brady, H. E., & Mcnulty, J. E. (2011). Turning Out to Vote: The Costs of Finding and Getting to
the Polling Place. American Political Science Review, 105(01), 115–134.
doi:10.1017/S0003055410000596
Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding Interaction Models: Improving
Empirical Analyses. Political Analysis, 14(1), 63–82. doi:10.1093/pan/mpi014
Brandeis, L. D. Dissent on New State Ice Co. v. Liebmann.
Campbell, T. 2001. The quiet revolution: The rise of political participation and leading cities
with decentralization in Latin America and the Caribbean. Pittsburg, PA: University of
Pittsburgh Press.
Chhatre, A., & Agrawal, A. (2008). Forest commons and local enforcement. Proceedings of the
13
National Academy of Sciences, 1–6.
Chhatre, A., & Agrawal, A. (2009). Trade-offs and Synergies Between Carbon Storage and
Livelihood Benefits from Forest Commons. Proceedings of the National Academy of
Sciences, 1–4.
CIFOR, T. C. F. I. F. R. (2007). Toward wellbeing in forest communities: A source book for
local government (pp. 1–96). Bogor, Indonesia: Center for International Forestry Research.
Contreras-Hermosilla, A., & Vargas Ríos, M. T. (2002). Social, Environmental and Economic
Dimensions of Forest Policy Reforms in Bolivia (pp. 1–42). Bogor, Indonesia: Center for
International Forestry Research.
Crook, R. C., & Manor, J. (1998). Democracy and Decentralisation in South Asia and West
Africa. New York: Cambridge University Press.
Donahue, J. D. (1997). Tiebout? Or Not Tiebout? The Market Metaphor and America's
Devolution Debate. The Journal of Economic Perspectives, 11(4), 73–81.
Faguet, J.-P. (2004). Does decentralization increase government responsiveness to local needs?
Evidence from Bolivia. Journal of Public Economics, 88(3-4), 867–893. doi:10.1016/S00472727(02)00185-8
Faguet, J.-P. (2009). Making Reform Work: Institutions, Dispositions, and the Improving Health
of Bangladesh. World Development, 37(1), 208–218.
Faguet, J.-P., & Sanchez, F. (2008). Decentralization’s Effects on Educational Outcomes in
Bolivia and Colombia. World Development, 36(7), 1294–1316.
doi:10.1016/j.worlddev.2007.06.021
Faguet, J. P. (2014). Decentralization and governance. World Development, 53, 2-13.
Ferejohn, J., & Weingast, B. (1997). The New Federalism: Can the States be Trusted? In J.
Ferejohn & B. Weingast, The New Federalism. Stanford, California: Hoover Institution
Press.
Fisher, R. A. (1966). The design of experiments (8 ed.). New York: Hafner.
Frees, E. W. (2004). Longitudinal and Panel Data: Analysis and Applications in the Social
Sciences. New York: Cambridge University Press.
Gibson, C. C., Williams, J. T., & Ostrom, E. (2005). Local Enforcement and Better Forests.
World Development, 33(2), 273–284. doi:10.1016/j.worlddev.2004.07.013
Heinrich, C. J., & Lopez, Y. (2009). Does Community Participation Produce Dividends in Social
Investment Fund Projects? World Development, 1–15. doi:10.1016/j.worlddev.2009.01.009
Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as Nonparametric Preprocessing
for Reducing Model Dependence in Parametric Causal Inference. Political Analysis, 15(3),
199–236. doi:10.1093/pan/mpl013
Howell-Moroney, M. (2008). The Tiebout Hypothesis 50 Years Later: Lessons and Lingering
Challenges for Metropolitan Governance in the 21st Century. Public Administration Review,
1–13.
Inglehart, R. (1995). Public Support for Environmental Protection: Objective Problems and
Subjective Values in 43 Societies. PS: Political Science & Politics, 28(1), 57–72.
Jaramillo, M. (2009). The Pre-Decentraliation Baseline Case. In K. Andersson, G. Gordillo De
Anda, & F. Van Laerhoven, Local Governments and Rural Development (pp. 113–138).
Tucson, Arizona: The University of Arizona Press.
Kauneckis, D., & Andersson, K. (2009). Making Decentralization Work: A Cross-national
Examination of Local Governments and Natural Resource Governance in Latin America.
Studies in Comparative International Development, 44(1), 23–46. doi:10.1007/s12116-00814
9036-6
Keefer, P. (2007). Clientelism, Credibility, and the Policy Choices of Young Democracies.
American Journal of Political Science, 51(4), 804–821.
Lambright, G. M. S. (2010b). Decentralization in Uganda: Explaining Successes and Failures in
Local Governance. Boulder, Colorado: Lynne Rienner.
Litvack, J., J. Ahmad, and R. Bird. 1998. Rethinking Decentralization in Developing Countries.
The World Bank Sector Study Series, Paper No. 21491. Washington, D.C.: The World Bank.
Naidu, S. C. (2009). Heterogeneity and Collective Management: Evidence from Common
Forests in Himachal Pradesh, India. World Development, 37(3), 676–686.
doi:10.1016/j.worlddev.2008.07.001
Oates, W. E. (1972). Fiscal Federalism. New York: Harcourt Brace Jovanovich.
Oemer, C., Oemer, C., & Oemer, C. (2004, September). Living Conditions of Forest-Dependent
People in the Northern Bolivian Amazon: A Case Study of El Sena Municipality. AlbertLudwigs-University Freiburg Faculty of Forestry and Environmental Sciences. Retrieved
from file:///Users/glennwright/Documents/Mendeley Desktop/Oemer - 2004 - Living
Conditions of Forest-Dependent People in the Northern Bolivian Amazon A Case Study of
El Sena Municipality.pdf
Ostrom, E. (1990). Governing the Commons. New York: Cambridge University Press.
Pacheco, P. (2006). Descentralización Forestal en Bolivia: Implicaciones en El Gobierno De
Los Recursos Forestales Y El Bienestar De Los Grupos Marginados (pp. 1–71). La Paz,
Bolivia: CIFOR.
Persha, L., & Andersson, K. (2014). Global Environmental Change. Global Environmental
Change, 24, 265–276. doi:10.1016/j.gloenvcha.2013.12.005
Phelps, J., Webb, E. L., & Agrawal, A. (2010). Does REDD+ Threaten to Recentralize Forest
Governance? Science, 328(5976), 312–313. doi:10.1126/science.1187774
Poteete, A. R., & Ribot, J. C. (2010). Repertoires of Domination: Decentralization as Process in
Botswana and Senegal. World Development, 1–11. doi:10.1016/j.worlddev.2010.09.013
Rabe-Hesketh, S., & Skrondal, A. (2008). Multilevel and Longitudinal Modeling Using Stata.
College Station, Texas: Stata Press.
Ravikumar, A., Andersson, K., & Larson, A. M. (2012). Decentralization and forest-related
conflicts in Latin America. Forest Policy and Economics, 1–7.
doi:10.1016/j.forpol.2012.07.005
Revesz, R. L. (1997). Federalism and Environmental Regulation. In J. Ferejohn & B. R.
Weingast, The New Federalism (pp. 1–16). Stanford, California: Hoover Institution Press.
Ribot, J. (2008a). Authority over Forests: Negotiating Democratic Decentralization in Senegal.
Representation, Equity & Environment, (January).
Ribot, J. (2008b). Building Local Democracy through Natural Resource Interventions: An
Environmentalist’s Responsibility. Washington, D.C.: World Resources Institute.
Ribot, J. C. (2002). Democratic Decentralization of Natural Resources. Washington, D.C.:
World Resources Institue.
Ribot, J. C. (2003). Democratic decentralisation of natural resources: institutional choice and
discretionary power transfers in Sub-Saharan Africa. Public Administration and
Development, 23(1), 53–65. doi:10.1002/pad.259
Ribot, J., Agrawal, A., & Larson, A. (2006). Recentralizing While Decentralizing: How National
Governments Reappropriate Forest Resources. World Development, 34(11), 1864–1886.
doi:10.1016/j.worlddev.2005.11.020
15
Rodden, J.A. 2006. Hamilton’s paradox: The promise and peril of fiscal federalism. Cambridge,
UK: Cambridge University Press
Rubin, D. B. (1980). Bias Reduction Using Mahalanobis-Metric Matching. Biometrics, 36(2),
293–298.
Rubin, D. B. (1990). Comment: Neyman (1923) and Causal Inference in Experiments and
Observational Studies. Statistical Science, 5, 472–480. doi:10.3102/10769986027004385
Sekhon, J. S. (2009). Opiates for the Matches: Matching Methods for Causal Inference. Annual
Review of Political Science, 12(1), 487–508. doi:10.1146/annurev.polisci.11.060606.135444
Smith, H. L. (1997). Matching with multiple controls to estimate treatment effects in
observational studies. Sociological Methodology, 27, 325–353.
Somanathan, E., Prabhakar, R., & Singh Mehta, B. (2009). Decentralization for Cost-Effective
Conservation. Proceedings of the National Academy of Sciences, 106(11), 4143–4147.
Splawa-Neyman, J. (1990). On the Application of Probability Theory to Agricultural
Experiments. Essay on Principles. Section 9. Statistical Science, 5(4), 465–472.
Tiebout, C. M. (1956). A Pure Theory of Local Expenditures. The Journal of Political Economy,
64(5), 416–424.
Transparency International. (2009). Corruption and Local Government. Education. Berlin:
Transparency International.
Treisman, D. (2007). The architecture of government: rethinking political decentralization (pp.
349–349). Cambridge: Cambridge University Press.
Van Laerhoven, F. (2010). Governing community forests and the challenge of solving two-level
collective action dilemmas--A large-N perspective. Global Environmental Change, 20(3),
539–546. doi:10.1016/j.gloenvcha.2010.04.005
Vega Castro, J. (2008, July). Análisis del Proceso de Descentralización Fiscal en el Perú. Lima,
Peru.
Veron, R., Williams, G., Corbridge, S., & Srivastava, M. (2006). Decentralized Corruption or
Corrupt Decentralization? Community Monitoring of Poverty-Alleviation Schemes in
Eastern India. World Development, 34(11), 1922–1941.
Wil de Jong, M. B. S. R. Y. C. G. (2004). Retos Y Perspectivas Del Nuevo Régimen Forestal en
El Norte Amazónico Boliviano. (W. De Jong) (pp. 1–26). Center for International Forestry
Research (CIFOR).
World Bank. (2003). World Development Report 2004. (World Bank). Washington, D.C.:
Oxford University Press and the World Bank.
World Resources Institute. (2005). World Resources 2005: The Wealth of the Poor. Washington,
D.C.: World Resources Institute.
16
Table 1. Descriptive Statistics
17
Figure 1: Forest cover differences between unmatched (left box) and matched (right box)
Peruvian and Bolivian samples.
.
18
Table 2. The effects of decentralization, matching results.
Matching Results
Treatment Control
Total
Dependent Variable
Cases
Cases
Cases
43
59
102
Annual forest change (pct.)
Community engagement
42
59
101
T-statistics in parentheses
* significant at the p < .05 level; ** significant at the p < .01 level
19
ATE
0.03
-1.03
ATU
0.03
ATT
0.02
(2.47)*
-1.02
-1.05
(-2.43)*
Figure 2: Unmatched sample differences between forest cover change and community
engagement in centralized and decentralized settings.
20
Figure 3. The effects of decentralization, based on the GEE regression models. This graph
shows the marginal effects of decentralization, conditional on community engagement. The
difference between centralized and decentralized municipalities is not significant where
engagement is weak, but the effect of decentralization is strong and significant where community
engagement is stronger. Dashed lines represent 95% confidence intervals.
21
Appendix
GEE results: Effect of community engagement with local officials across
centralized and decentralized regimes.
Note that methodologists suggest that regression tables like these are not helpful in
the case of interaction models (Brambor et al., 2006).
GEE
Regression
Decentralization
0.012
(0.373)
Community engagement
-0.011
(0.000)**
Community engagement * Decentralization
0.003
(0.521)
Slope
0.000
(0.817)
Road density (ln)
-0.003
(0.241)
Population (ln)
0.004
(0.063)+
Municipal size (ha., ln)
0.005
(0.032)*
Budget ($US millions, ln)
0.010
(0.000)**
Forest cover (lagged, ln)
0.000
(0.984)
Constant
-0.099
(0.001)**
Observations
101
Number of geographic identifier: unique across countries
79
p values in parentheses
+ significant at 10%; * significant at 5%; ** significant at 1%
22