Decentralized Governance and Krister Andersson ...ifri/Publications/R07I-2 Andersson...addition to...

Krister Andersson Clark C. Gibson

Decentralized Governance andEnvironmental Change: LocalInstitutional Moderation ofDeforestation in Bolivia

Journal of Policy Analysis and Management, Vol. 26, No. 1, 99–123 (2006)© 2006 by the Association for Public Policy Analysis and Management Published by Wiley Periodicals, Inc. Published online in Wiley InterScience(www.interscience.wiley.com)DOI: 10.1002/pam.20229

Abstract

Dozens of countries have decentralized at least part of their natural resource policiesover the last two decades. Despite the length of time that these policy experiments havebeen in force, there is little agreement about their effectiveness. We argue that part ofthis ambivalence stems from three limitations of extant studies, suggesting that futurestudies of decentralized natural resource governance should consider a combinationof 1) variation in the local institutional context, 2) the fit between the reform andother public policies, and 3) more adequate outcome measures for decentralizedresource governance. After developing such an approach, we posit that varying forestconditions depend on the moderating effects that local institutions have on the socioe-conomic and biophysical drivers of environmental change. Analyzing data from inter-views and remotely sensed images from 30 municipalities in the Bolivian lowlands,we find that the local institutional performance affects unauthorized deforestationdirectly and indirectly, but detect no effects on either permitted or total deforestation.© 2006 by the Association for Public Policy Analysis and Management

INTRODUCTION

Two decades of decentralization reforms in nonindustrial nations have spurred aninterest among public policy analysts to examine the extent to which decentraliza-tion has delivered on its promise to improve public sector performance. Studies ofdecentralization generally explore how changes in the political power of local gov-ernments shape public policy outcomes (for example, Ferejohn & Weingast, 1997;Inman & Rubinfeld, 1996; Rondinelli, McCulloch, & Jonson, 1989). A small subsetof these studies empirically examines the effect of decentralization on the supply ofpublic goods and services. This work generally seeks to adjudicate between twohypotheses. Proponents of decentralization argue several reasons why it shouldincrease accountability. Local governments are more accountable than distant cen-tral governments. Local governments compete for citizens in a market-like arenaand citizens sort themselves according to their preferences for public goods in rela-tion to tax expenditures by voting with their feet (Ostrom, Tiebout, & Warren, 1961;Tiebout, 1956). Others suggest that local governments necessarily have better infor-mation about local conditions and preferences, and therefore make better deci-sions regarding the provision of collective goods (Blair, 2000; Hayek, 1945; Wunsch& Olowu, 1990). Opponents of decentralization provide counterarguments. Decen-tralization may reduce local provision of public services because local elites can

100 / Local Institutional Moderation of Deforestation in Bolivia

divert public funds more easily through a decentralized system than a centralizedone.1 Evidence exists to support both views—even within the same locality(Galiani, Gertler, & Schargrodsky, 2005; Galasso & Ravallion, 2005; Reinikka &Svensson, 2004).

These approaches have been borrowed by researchers to examine decentralizedenvironmental policies. Revesz (1999), for example, argues that interjurisdictionalcompetition between local governments in a decentralized regime is healthy andlikely to lead to efficient environmental governance (see also Oyono, 2005; Ribot,2002). Other scholars are more skeptical. They see decentralization of naturalresource policy leading to a race to the bottom as local governments engage in adownward spiral of competition to have the lowest, least costly regulations in orderto maximize capital investments from the outside (Oates, 2001; Peterson, 1995).Applying this logic to the forestry sector, decentralization may lead to increaseddepletion of forest resources as local politicians will favor short-term private bene-fits such as receiving payments from timber concessions and agriculture industriesover long-term public goods such as protection of soil fertility, controlling soil ero-sion, safeguarding water supplies, and ensuring a stable source of forest products.In Central Kalimantan of Indonesia, for example, McCarthy (2004) finds that decen-tralization has produced a race to the bottom in the forestry sector due to the ambi-guity in rights and rules over forests, which have shortened actors’ time horizons andled them to a “race to make the most of current opportunities without regard tofuture operations” (p. 1215). Existing empirical studies about decentralized forestrypolicy thus appear as ambivalent as the more general literature on decentralization.

We believe that the weakness of current studies regarding decentralized forestrypolicy stems from their exclusion of the scope and fit of forestry decentralization, aswell as the definition of appropriate outcome measures in their analyses. While thereis a growing literature on the role of local institutions in decentralized forestry pol-icy, which we argue is the appropriate scope of these investigations, such work gen-erally fails to consider how this role is conditioned by the scope of the forestrydecentralization and the fit between the decentralization reform and other macro-economic policies. Institutional studies also rarely include robust measures of for-est condition as outcome variables, focusing instead on intermediate variables suchas levels of citizen participation, local capacity, or the degree of implementation ofspecific activities. Some of the existing case studies of decentralized forestry policyexplicitly address the fit of the decentralization reform by discussing the relation-ship of the reform to other macroeconomic policies, but they too do not have robustmeasures for the policy outcomes. By including the appropriate scope, fit, and out-come measures in our analysis, we seek to improve our understanding of environ-mental change within the decentralized regime.

ANALYZING DECENTRALIZED FORESTRY POLICY

In our review of forestry-related decentralization studies, we found only three stud-ies that analyze the relationships between decentralized governance and forest con-ditions. One of these studies, by Klepeis (2003), compares the influence of gover-nance structures on deforestation rates in southern Yucatan in Mexico under twodistinct institutional regimes: the centralized governance structure under President

Journal of Policy Analysis and Management DOI: 10.1002/pamPublished on behalf of the Association for Public Policy Analysis and Management

1 See Bardhan (2002), Bardhan and Mookherjee (2005a), and Bardhan and Mookherjee (2005b) for acomprehensive summary of this debate.

Local Institutional Moderation of Deforestation in Bolivia / 101

Diaz (1876–1910) and the decentralized decision-making structure under PresidentCardenas (1934–40). The comparative analysis finds that total deforestation wassignificantly higher under the centralized era. Klepeis concludes that the decen-tralized decision-making was more effective in protecting the forest. In anotherstudy, Curran et al. (2004) used satellite imagery to study deforestation patterns ina protected area in Indonesia. They found that during the 1985–2001 period, thestudy area lost 56 percent of its forest cover due mostly to timber logging and oil-palm plantations. Curran and colleagues attribute the accelerating deforestationrates to the forestry decentralization reform and describe how the reform allowedlocal governments (districts) to issue small logging permits that caused “unautho-rized harvest of remaining accessible lowlands” (p. 1002).

Finally, in his study of local villages in Cameroon’s tropical forest region, Oyono(2005) notes very mixed results in the environmental outcomes among the villagesthat were recently given increased formal governance responsibilities in theforestry sector. The author presents detailed case study material with examples ofhow forest degradation continues in many places in the decentralized regime,arguing that the mixed results are partly due to discrepancies in local and centralrule-making as well as a lack of effective central government interventions in thelocal communities.

These studies illustrate one of the main difficulties in using biophysical indicatorsto evaluate the performance of decentralized regimes: isolating the effect of decen-tralized governance from other policies that may have also affected, or even over-whelmed, the effect of decentralization. For instance, Klepeis (2003) finds that cen-tralized policy under President Diaz failed to protect the forest. However, inaddition to being heavily centralized, the Diaz regime pursued an agricultural pol-icy that was highly destructive to the forest. This raises the possibility that it wasthe agricultural policy that caused the forest loss rather than the centralized deci-sion making. It is entirely possible that a decentralized approach to implement thesame agricultural policy may have been even more destructive to the forests of theYucatan. In the case of Indonesia, Curran et al. (2004) recognize that the observedacceleration of deforestation in West Kalimantan was fueled by a combination ofdecentralization and macroeconomic policies that promote agro-industry estab-lishments. Because of the tax breaks and subsidized loans promoted by central gov-ernment policies, and the effect these had on local land users, it is possible thatdecentralization, in and of itself, had little effect on the observed deforestation pat-terns. It may be that in the absence of the macroeconomic policies, local farmerswould find forest conversions unprofitable, and as a result, they would not ask localgovernments to issue the logging permits in the first place. Hence, the observedresults are not necessarily explained by decentralized governance per se, but morelikely by a combination of factors.

The three studies make different predictions about the effects of decentralizedgovernance on forests, but their research designs do not allow them to separate outthe effect of their main independent variable from other potential influences. Totease out the effect of decentralized governance, an analysis needs to account forthe influences of other policies, as well as location-specific biophysical and socioe-conomic characteristics. This can be tricky to do, as these exogenous processesoften operate simultaneously to, and even interact with, local governance institu-tions. Next we lay out an approach that will help policy analysts gain a betterunderstanding of when local institutional arrangements are likely to dampen,enhance, or perhaps have no discernible effect on the exogenous drivers of envi-ronmental change.



An Institutional Interaction Approach

We propose an institutional approach by which the analyst develops the researchdesign for decentralized environmental policy in three stages. The purpose of ourinstitutional analysis is to sort out the complex mechanisms by which national poli-cies, biophysical attributes, socioeconomic conditions, and local institutions affectthe changing condition of the natural resources in a decentralized regime.

Our approach emphasizes the interactive properties of local institutions. Itfocuses on the crucial processes in the middle of a causal chain linking socioeco-nomic and biophysical characteristics with policies and changing natural resourceconditions. We argue that the effects of documented drivers of deforestation (thatis, the local density of roads and population growth) depend on the strength of spe-cific institutional arrangements that may either dampen or enhance these effects.Hence, we view local institutional arrangements as playing a moderating role inexplaining variations in outcomes on the landscape.

Following this approach, the researcher starts the inquiry by carrying out a pol-icy diagnosis that seeks to characterize the scope of decentralization reforms in theparticular sector of interest. In this first stage, the researcher documents thedecentralization policy with regards to its targeted actors (that is, to whom areresources, power, and responsibilities devolved?), the administrative mandate (thetasks and responsibilities that the local actors are asked to perform), the degree oflocal political authority (what specific decision-making powers are devolved to thetarget actors?), and the extent of local fiscal powers (what authority does the localgovernment have to levy local taxes in a particular sector?). By drawing out theconceptual boundaries of the decentralization reform in terms of the local juris-diction, it is possible to establish the most appropriate unit of analysis for theempirical inquiry. For instance, a study of a decentralization policy that targetsregional government officials may require a different unit of analysis (that is,regions) than when decentralization targets democratically elected municipal offi-cials (that is, municipalities).

Many recent studies on decentralized forest governance have begun to featurelocal institutions as their analytical scope. Such works generally analyze how localinstitutional arrangements influence the local governments’ administrative per-formance, such as public participation (Blair, 2000; Fiszbein, 1997; Larson, 2002;O’Neill, 2003), downward accountability (Agrawal & Ribot, 1999; Crook & Manor,1998; Smoke, 2003), resource user satisfaction with local governments (Andersson,2004; Gordillo & Andersson, 2004), and fiscal revenues and expenditures in munic-ipal resource governance (Andersson, Gibson, & Lehoucq, 2004; Kaimowitz et al.,2000; Pacheco, 2000). There is no doubt that these studies have increased ourknowledge about the conditions under which the decentralized regime produceseffective local governments. Yet, it is still an open question whether local govern-ments’ administrative effectiveness necessarily translates into better resource con-ditions on the ground, and thus their findings beg questions such as: Are local gov-ernments that are effective in mobilizing financial resources, public participation,and creating mechanisms for downward accountability also effective in preservingthe environment? Or are they equally effective in supporting activities that are detri-mental to the environment? These are questions that are impossible to answer with-out specifying the process by which local governance actors influence the changingconditions of natural resources. This approach stresses the importance for the ana-lyst to describe in some detail the specific decisions and actions in the local arenathat are likely to affect the condition of the locality’s natural resource base (for a



more detailed description of this stage of the analytical process, see Andersson2004, 2006).

In the second stage of the analysis, the researcher addresses the fit of the decen-tralization reform in relationship to the broader set of public policies that concerna particular sector. Here, the goal is to situate the decentralization policy within thenational-level political economy and document to what extent the decentralizationpolicy complements, enhances, detracts, or even contradicts any of the macro-levelpolicies that the national government considers high priority.

The existing studies of decentralization policy that examine the role of local insti-tutions generally do not systematically include the other, more macroeconomic fac-tors into their analysis; they tend to look at one organization and one policy at atime (that is, Blair, 2000; Contreras-Hermosilla & Vargas Rios, 2002; Fiszbein, 1997;but see Hecht, 2005; and Swallow, 2005). Among the studies that do focus on howthe effectiveness of the forestry decentralization policy is influenced by other poli-cies, few analyze how local institutions affect varying resource conditions.

The second step includes an analysis of alternative explanations to the observedpolicy outcomes. The identification of these alternative causal factors may bederived from existing studies or previous empirical observations. The importantthing is to control for their influence in the subsequent analysis of outcomes.When analyzing the drivers of deforestation, it would be crucial to consider factorsthat previous studies have found to be robust determinants, such as the density ofroads, forest dependency, and public policies (for example, Deacon, 1999; Hecht &Cockburn, 1989; Hecht, 2005; Kaimowitz and Angelsen, 1998; Moran, 1982). Andsince the macroeconomic and social policies in many countries often take prece-dence over environmental protection, it would be particularly important that theresearcher documents how conservation-related reforms fit into the broader pol-icy framework.

Because no forest policy in any country (that we are aware of) aims to protect allforests at all times and at all costs, it is important that the research design capturesthese tradeoffs between development and conservation. In many Latin Americancountries, forestry policy objectives are secondary to the policy goals related totrade, agriculture, and social sectors (Angelsen & Kaimowitz, 1999; Repetto &Gillis, 1998). Simply put, outcomes in the forestry sector depend on how other pub-lic policies influence forestry-related decisions and actions. A thorough examina-tion of the decentralization fit can help the researcher to clarify what constitutesthe most realistic expected outcomes of decentralized governance. The definition ofappropriate outcome measures is the objective of the next stage in the institutionalanalysis.

The third and final stage of analyzing the consequences of decentralized forestpolicy requires creating measures of governance outcomes that make it possible tolink local actions and decisions to resulting changes on the landscape. To evaluatea set of public policies that aim to control indiscriminate deforestation, it makessense to employ performance indicators that are related to changing resource con-ditions, such as forest cover change.

However, rather than employing variables that measure only total changes in for-est cover, deforestation rate, or degree of spatial forest cover fragmentation, it maybe more productive for studies interested in decentralization to construct measuresbased on the limited scope of forestry decentralization. For example, to evaluate adecentralization policy that authorizes local governments to issue forest user log-ging permits for coniferous forests only, researchers would want to include specificmeasurements of changing forest conditions in the coniferous forests. Likewise, if




Figure 1. Deforestation as a Measure of Policy Effectiveness Before Decentralization Policy.

Figure 2. Deforestation as a Measure of Policy Effectiveness After Decentralization Policy.


local governments are asked by the central government to help enforce rules thatprotect forestlands within specific land use categories and the national policy aimsto boost exports of agricultural cash crops from all other land use categories—including some forested lands—it would make sense for analysts to include meas-ures of changing forest conditions within land use zones where forests are supposedto be protected according to public policies. Figures 1 and 2 illustrate this argument.

If public policies allow for no conversion from forestry land uses to other landuses, an appropriate indicator of the effectiveness of public policies seeking to curbdeforestation may be a straightforward measure of total deforestation, such as theannual rate during a specified period of time, or the ratio of forest cut to total for-est for the entire country. Within any municipality like the one represented in Fig-ure 1, this would be the ratio of the polygon area labeled “Cut forest” to the area ofthe circle labeled “Forest.”

However, to evaluate the effectiveness of a set of policies that prohibit forestfelling in some areas but allow it in other areas, total deforestation is no longer anadequate measure. In Figure 2, for example, the municipality’s forest area has twoparts, one of which is protected, and the other of which is not. If the reform tar-geted only the protected zone of the total forest, then the amount of total defor-estation may be the wrong measure of the policy’s success. That is, the sum of thepolygons A and B divided by the area of the entire forest circle is not appropriate.Instead, a better measure of policy effectiveness would be the ratio of A to C, thatis the amount of cut area C within the protected zone A. Cut forest outside of theprotected zone, polygon B, may have occurred by policy design and is therefore nota good indicator of policy performance. By constructing the dependent variables inthis way, the researcher is in a better position to assess if, and to what extent, decen-tralized governance strategies and actions have actually contributed to changingforest conditions. In the next section, we attempt to account for these central com-ponents of the institutional interaction approach in an analysis of Bolivia’s decen-tralized forestry policy.

DECENTRALIZED FOREST GOVERNANCE IN BOLIVIA

We study decentralized forest governance in Bolivia because it is a country whoseforest decentralization policy is considered to be on the cutting edge of policyreforms (FAO, 1999; UNDP, 1997). It is also a country where the reforms have actu-ally been implemented, in contrast to many other countries in which the reformshave remained mere rhetoric (Andersson, 2003; Agrawal & Ribot, 1999). Municipalgovernments in Bolivia have received substantial resources and political power con-cerning decisions over the forestlands within their jurisdiction (Contreras-Her-mosilla & Vargas Rios, 2002; Pacheco & Kaimowitz, 1998).

The Scope of Forestry Decentralization

Prior to 1994, municipal governments in Bolivia were essentially small, voluntaryurban organizations without much political power, financial resources, or a clearlydefined jurisdiction. In 1994, the government of President Sanchez de Lozadalaunched a decentralization reform that fundamentally changed the role of munic-ipal governments in public affairs. Through the reforms, many municipal govern-ments’ annual operating budgets increased by as much as 1,000 percent, and sev-eral went from a zero budget to tens of thousands of dollars in available resources,practically overnight. In addition to the intragovernmental financial transfers, each



municipality was authorized to levy taxes on motor vehicles, urban property, andrural properties larger than 50 hectacres. In relation to transfers from the centralgovernment, however, the contribution of local taxes to the municipal governmentbudget is quite limited in most Bolivian municipalities (Urioste & Pacheco, 2001).

In the forestry sector, municipal governments are asked to enforce the nationalforestry law and assist local forest users in acquiring formal forest property rights.In order to acquire such rights, users must demonstrate that an official forest man-agement plan has been developed. The municipal government is to assist forestusers in developing such a management plan and is then responsible for monitor-ing and enforcing the compliance with the new forest property rights regime. Table1 lays out these and other parts of the municipal government forestry mandate, cod-ified in the 1996 Forestry Law (Government of Bolivia, 1996). Because of their piv-otal role in the implementation of the decentralized forestry regime, the munici-pality represents an adequate unit of analysis for observing how decentralizedgovernance affects environmental change in Bolivia.

The Fit of Forestry Decentralization

The decentralization reform’s influence on the forest condition in Bolivia is likely todepend on how this reform fits into the broader set of macroeconomic policies. Oneof the central pieces of the country’s free-market-oriented macroeconomic policies,which has predominated public policies since the structural reforms in the mid-1980s, is the active promotion of industrial agriculture as a source for export earn-ings (Pacheco, 1998). The Bolivian national government promotion of agribusinesshas included a variety of macroeconomic interventions, such as the removal ofprice controls on soybeans, devaluation of the Bolivian currency, and infrastructure


Table 1. Municipal forestry mandates in Bolivia.

Mandate Tasks

Regulatory • Assist central government to monitor and enforce national forestry law.

• Propose municipal forest reserves for community use on up to 20 percent of the total forested public land within the municipality.

• Report transgressions of the forestry law to the central government.

Fiscal • Receive 25 percent of commercial logging royalties collected by the central government (USD 1 per hectare of managed forest).

• Not allowed to charge user fees, charge any taxes in the forestry sector.

Technical • Give technical advice to local forest users to acquire formal management rights and to prepare forest management plans.

• Support the National Forestry Registry (database of forest resources).

Socioeconomic • Organize training for user groups, as well as to facilitate and promote commercial undertakings and private-sector participation in the municipality.

Source: Forestry Law (1996) and Popular Participation Law (1994).


improvements, as well as the introduction of tax breaks and export credits for soy-bean producers (Kaimowitz et al., 2000). The explicit goal of these policies was toreach 1 million hectares of soybean plantations by the year 2000 (Urioste &Pacheco, 2001). As a direct result of this policy, agro-industries deforested largeareas of dry tropical forest in the lowlands, especially around the city of Santa Cruz.It is important to note, however, that there was nothing illegal about this defor-estation. In fact, Bolivia’s official land use plan determined that the area where thesoybean plantations are located outside Santa Cruz is an area designated to, andappropriate for, extensive agriculture (Government of Bolivia, 1995).

Both agricultural and forestry policies in Bolivia allow for deforestation to takeplace in certain areas under specific circumstances. For Bolivian forestry policy,deforestation per se is not a bad thing. Rather, it is the unauthorized deforestation—the deforestation that takes place in areas that, according to the national govern-ment land use plan, should only be used for forestry (Government of Bolivia, 1995).Municipal governments are asked to enforce this land use plan in their respectiveterritories. Municipal governments also have the authority to develop a moredetailed municipal land use plan, as long as this is in broad accordance with thenational plan. The land use plan divides the municipal territory into land use zonecategories, and each category contains a set of acceptable land use activities. Whendeforestation takes place in zoning categories that allow for conversion to otherland uses, municipal governments may not intervene. On the other hand, they areexpected to stop the unauthorized deforestation occurring in prescribed forestryzones. Given the limited mandate of municipal governments and the country’smacroeconomic policies, it would be unreasonable to expect that even the mostmotivated and capable municipal governments—the reform’s targeted actors—would act to conserve all forests at all costs.

Apart from municipal governance performance as a potential determinant ofvarying deforestation rates, there are several alternative explanations. For instance,previous studies have shown that the effectiveness of local forest governance insti-tutions is fundamentally a function of the biophysical, socioeconomic, and policyenvironment in which the local institutions operate (Ostrom, 2005; Poteete &Ostrom, forthcoming; Varughese, 1999). Related to the biophysical drivers of defor-estation, previous studies have demonstrated that deforestation is more likely tooccur in areas that have relatively well developed road infrastructure (Laurance,Albernaz, Fearnside, Vasconcelos, & Ferreira, 2004; Moran, 1982, 1984), high pop-ulation growth (Meyer, & Turner, 1992; Rudel, 1989) and in areas with a history ofhigh forest-to-agriculture conversion rates (Chu & Yu, 2002; Liverman, Moran,Rindfuss, & Stern, 1998). In the policy realm, several studies point to the indirectinfluence of public policies, such as land use, agricultural and trade policies ondeforestation rates (Andersson, 2002; Hecht, 2005; Contreras-Hermosilla, 2000;Kaimowitz & Angelsen, 1998). Our subsequent empirical tests of the influence ofdecentralized governance performance on deforestation will take these alternativeexplanations of deforestation into account. The next section further unpacks thefactors that are likely influences of the decisions for local governments to takeaction in the forestry sector.

Local Context, Institutions, and Actions

Even though the municipal mandate in the forestry sector is uniform throughoutthe country, the importance that local people place on forestry sector activities arelikely to vary from one place to another. The actors in the local context—including



citizens, interest groups, municipal officials, and central government agents—arelikely to be highly selective regarding which portions of the reform would be in theirinterest to implement. Supporting this notion of selective implementation of themunicipal mandate, Andersson (2003) finds that municipal governments in eventhe forest-rich lowlands of Bolivia are unlikely to take any action in the forestry sec-tor unless both community-based organizations and central government agentsexerted pressure on the municipal administration to do so. Pacheco (2000) notesthat only about 10 percent of all municipal governments have sufficient resourcesto carry out their mandate in the forestry sector. The observed variation in Bolivianmunicipalities’ interest and capacity to take action in the forestry sector suggeststhat their effectiveness in protecting forest resources is likely to vary a great dealtoo. We propose that the variable influence of municipal governance efforts on envi-ronmental outcomes depends in part on how the local institutional arrangementsinteract with the local environment. Municipal forest governance institutionschoose to respond in different ways to the factors that affect environmental changein the area. And since municipal governments in Bolivia are asked to assist forestusers in acquiring formal forest property rights, preparing forest managementplans, as well as monitoring local user compliance with the formal rules of theregime, one possible way of assessing municipalities’ forest governance perform-ance would be to measure the extent to which municipal-level actors actually carryout these activities on a regular basis.

Defining Adequate Outcome Measures

A recent forest resource assessment in Bolivia estimates that more than 3 millionhectares of lowland forests have now been cleared (Camacho, Cordero, Martinez,& Rojas, 2001). 1.4 million hectares, or 45 percent of that total, was deforestedin the Department of Santa Cruz during the seven years between 1993 and 2000(Pacheco, 2000). Spatially explicit analyses show that the deforestation in thisarea was primarily associated with large, industrial soybean plantations (Hecht,2005; Steininger et al., 2001). After agriculture, the second most important driverof forest loss was urbanization, accounting for about 25 percent of the deforestedareas during the period (Camacho et al., 2001). According to Steininger et al., 87percent of the forest clearings for agriculture during this period were carried outby about 3,000 industrial farmers, including the Mennonite colonies, while thealmost 100,000 small-scale farmers accounted for about 13 percent of the agri-cultural conversions. Overlaying the central government’s land use plan on the1993–2000 deforestation map, Rojas, Martinez, Cordero, & Contreras (2003) findthat about 26 percent of all deforestation in Bolivia occurred in areas wheredeforestation was not allowed by the government’s land use plan. Within theDepartment of Santa Cruz, there is a great deal of variation in deforestation dur-ing the 1993–2000 period. Among the 30 randomly selected municipal govern-ments in our sample: 8 experienced a 0 percent deforestation rate, 4 of them hada rate between 0 and 1 percent, 10 had a rate between 1 and 5 percent, andanother 5 had a deforestation rate above 10 percent for the period. The distribu-tion of unauthorized deforestation was equally varied, but as may be observedfrom the map in Figure 3, the municipalities with the highest rates are clusteredjust east of the city of Santa Cruz.

To tease out the extent to which the actions of decentralized governance actorshave influenced these observed changes on the landscape, we analyze whether thereis any discernible and systematic relationship between the performance of the local



governments and the observed pattern of forest cover change. If our multivariateanalysis detects a systematic relationship, this would support our hypothesis thatlocal institutional performance helps determine forest conditions in the decentral-ized regime. Considering the scope and fit of Bolivia’s decentralization reform, wewould expect that Bolivian municipalities with strong municipal forestry institu-tions experience less deforestation on lands where the government’s land use planprohibits this. However, we do not expect to find any statistically significant effectsof municipal government performance on either the permitted or the total amountof deforestation because the decentralized regime does not prohibit all types ofdeforestation. To test these hypotheses empirically, we analyze data from 30 ran-domly selected municipalities in the Department of Santa Cruz, Bolivia.


Figure 3. Permitted and Unauthorized Deforestation in the Municipalities ofthe Department of Santa Cruz, Bolivia, 1993–2000 (Lines Represent MunicipalBoundaries).


EMPIRICAL ANALYSIS

For our empirical analysis we use data collected through personal interviews withthree different forestry sector actors in each of the selected municipalities (a totalof 90 interviews), as well as national census data and satellite imagery products offorest cover change and land uses. The interviews in each municipality were car-ried out with the mayor who held office during the 1996-2000 period, the munici-pal staff member in charge of forestry issues, as well as the president of the Munic-ipal Oversight Committee.2 We gathered this data for a random sample of 30municipalities in the Lowland Department of Santa Cruz. A total of 13 Landsat 5Thematic Mapper (TM) images from 1993 and 13 Landsat 7 Enhanced ThematicMapper (ETM) images from 1999–2000 were processed and converted to a Geo-graphic Information System (GIS) by an expert team working for the Bolivian For-est Service (Camacho et al., 2001). We generated the spatial data for our sampledmunicipalities by using the GIS data provided by that team, combining it with theinterview and census data, and analyzing it using Two-Stage Least Squares (2SLS)multiple regression techniques.

Dependent Variables

We employ three different, but complementary, dependent variables (DVs) as proxymeasures for changing forest conditions in the Department of Santa Cruz. All threeDVs are related to different types of deforestation and were derived from satelliteimagery. In the first model, the DV is the proportion of all forest cut between 1993and 2000. We call this variable Total Deforestation 1993-2000. In the second model,the DV is the proportion of deforestation between 1993 and 2000 that occurred onland that the central government’s Land Use Policy declared conversion fromforestry to other land uses allowable. We call this DV Permitted Deforestation 1993-2000. Finally, the third model’s DV consists of the proportion of deforestation occur-ring between 1993 and 2000 on land that was formally protected by the nationalland use policy. We call this variable Unauthorized Deforestation 1993–2000. Weuse the digital map produced by Camacho et al. (2001) that overlays the 1995 gov-ernment land use map with the 1993–2000 deforestation map for Santa Cruz. Wethen combine this map with the INE (2001) municipal boundary map to calculatethe areas of the polygons representing the three measures of deforested areas ineach municipality. Because the 1995 land use plan assigned land use categoriesbased on the existing land uses in 1995, all forestlands that were assigned forestland use categories were actually forested in 1995 (Government of Bolivia, 1995).This means that the unauthorized deforestation variable effectively indicates theproportion of such deforestation that occurred between 1995 and 2000—roughlycoinciding with the implementation of the forestry decentralization reforms in1996. The results of the GIS analysis are presented in Table 2 and in Figure 3.

Independent Variables

We include a total of eight independent variables and one interaction product in ourempirical analysis. Below we describe how each of these were operationalized.


2 The Municipal Oversight Committee (Comité de Vigilancia) is an association of local community rep-resentatives, empowered by the 1994 Popular Participation Law to monitor the performance of themunicipal government.


Municipal Forest Governance (MFG) Index: We construct a four-level ordinal vari-able (0-3) as a proxy measure for the de facto performance of the municipal insti-tutions for forest governance. This is an additive index comprising three comple-mentary components of municipal forest governance performance: (1) propertyrights facilitation, (2) field presence, and (3) technical capacity. Each of these com-ponents of the MFG index is described below.

1. Forest property rights issued to previously excluded user groups.The forestry decentralization reforms provided indigenous groups, rural com-munities of smallholder farmers, as well as private individuals with theopportunity to acquire formal forest property rights. It is part of the munici-pal government forestry mandate to assist these previously excluded forestusers in acquiring such rights. Several studies underscore the importance offorest tenure security for resource user motivation to invest in resourceimprovements (that is, Arnold, 1999; Bruce, 1998; Thomson, 1992) and thisfirst component of the MFG Index reflects the extent to which the municipalgovernance authorities help these user groups to acquire such securitythrough formal property rights. Municipal governments that assisted previ-ously excluded groups to acquire formal property rights between 1996 and2000 are coded as 1, otherwise 0.

2. Field presence to assist local resource users and to monitor compliance.Formal property rights may be necessary to motivate long-term thinkingamong forest users, but is hardly sufficient for achieving sustainable forestmanagement. Several institutional scholars have emphasized the importanceof moving beyond the analysis of formal rules to consider the degree to which


Table 2. Descriptive statistics of dependent and independent variables (n 5 30).

Type Variable Mean St. Dev. Min. Max.

Dependent Total deforestation 1993–2000 (%) 0.1627 0.1550 –0.0049 0.6281 Permitted deforestation 1993–2000 (%) 0.1492 0.0468 0.0000 1.0000Unauthorized deforestation 1993–2000 (%) 0.0237 0.0381 0.0000 0.1323

Independent Local institutionsMunicipal governance index (ord) 1.8077 0.7494 0 3

National PolicyLand use policy-defined ag areas (%) 0.2847 0.3069 0.0000 0.9726Central government monitoring 2.6154 1.2985 1 7 Instrumental variable for central monitoring

(timber royalties in 100,000s of Bolivianos) 0.4302 0.5985 0.0000 2.2837

Socioeconomic ContextFirewood dependency 0.6642 0.2423 0.0556 0.9533

Biophysical ContextDeforestation before 1993 (100 km2) 0.4522 0.6013 0.0000 2.0745Density of roads (km/ km2) 0.1169 0.0694 0.0185 0.2777Population growth 1991–2001 (%) 0.3287 0.2382 –0.1306 0.7988Municipal area (1,000 km2) 7.7910 15.4754 0.0417 7.1408

Source: Data from Camacho et al. (2001), CIPEC (2001), INE (2001), and SIF (2001).


such rules are actually used, applied, and respected among natural resourceusers (Andersson & Pacheco, 2006; Auer, 2006; Heikkila, 2004; Lubell, 2004).For formal property rights to have an effect on resource user behavior, activemonitoring and enforcement is necessary (Gibson, Williams, & Ostrom, 2005;Meinzen-Dick, Knox, Place, & Swallow, 2002; Ostrom, 1999). In this case, weconsider the number of field visits that the municipal staff makes each weekas a proxy indicator of the municipality’s monitoring and enforcement activ-ities. If a given municipality made at least one visit to the field per weekbetween 1996 and 2000, we assign a 1 to the municipality, otherwise 0.

3. Technical capacity of the decentralized regime.Arguably the most prominent explanations for mixed local government per-formance in Bolivia’s forestry sector are related to the level of financial andtechnical resources within the local government administrations (for exam-ple, Contreras-Hermosilla & Vargas Rios, 2002; Ferroukhi, 2003; Pacheco,1998). We incorporate this aspect of municipal forest governance perform-ance by measuring whether a municipal administration has a professionalforester on its payroll. If it did during at least half of the time between 1996and 2000, we coded the municipality as 1, otherwise 0.

By adding these three components together for each municipality, we get an ordi-nal index score ranging from 0 to 3 that captures the de facto level of performanceof the municipal governance system with respect to the forestry sector. We expectthat forest users who live in municipalities that score high on this index willincrease their net benefits from forest use because of the higher quality of munici-pal services related to forest management that are offered to them. Receiving highernet benefits will strengthen people’s incentives to engage in forest managementrather than clearing forests for agriculture or cattle pastures. Hence one wouldexpect that there would be less unauthorized deforestation in such municipalities.Because of the particular municipal mandate and existing land use policies inBolivia, we do not expect this variable to have any significant effect upon the pro-portion of total or permitted deforestation during the period.

Public Policies

Land use policy prescriptions: The 1995 National Land Use Policy delineates accept-able land uses according to a detailed zoning approach, which contains 19 differentland use prescriptions (Government of Bolivia, 1995). According to this policy, landuse within certain forestland polygons is restricted to forestry activities, while con-version to different types of agriculture is prescribed as acceptable usage in others.This variable measures the land area in each municipality that the land use policyhas designated to different forms of agriculture (in thousands of hectares). Weexpect that the greater the proportion of prescribed agricultural land area, thegreater the proportion of total and permitted deforestation. We would not, however,expect that this policy prescription would increase the likelihood of observinghigher proportions of unauthorized deforestation. Reflecting our earlier discussionof institutional fit, it is plausible that the more lenient the land use policy is towardsagriculture—that is, the larger the area designated to agricultural use in a givenmunicipality—the less unauthorized deforestation one is likely to observe.

Central government monitoring: This variable measures the number of unan-nounced visits per year by the central government forestry service, La Superinten-dencia Forestal (SIF). SIF officials informed us that they strive to be strategic in the



allocation of resources to monitoring activities, targeting those areas that have previ-ously experienced high rates of unauthorized deforestation. This poses an endogene-ity problem for our analysis. To deal with this problem, we select an instrumentalvariable for central government monitoring and employ two-stage least squares(2SLS) regression estimation techniques in our analysis. In the first stage of all threeregression models, we regress the central government monitoring variable on itsinstrument—the cumulative amount of timber-related royalties that each municipal-ity received during 1999 and 2000. The amount allocated to each municipality isequivalent of 25 percent of total timber royalties collected by the central governmentfrom resource users within each municipal territory (each timber concession holderpays $1.00 per hectare). The instrumental variable, which is derived from SIFs annualreports for 2000 and 2001, is significantly correlated with the intensity of central gov-ernment monitoring but is unaffected by a municipality’s rate of deforestation. Allother things equal, we expect that frequent central government monitoring is associ-ated with lower unauthorized deforestation rates because the public policy actionsspecifically seek to limit this. For the same reason we would not expect any signifi-cant effect of this variable on our other two measures of deforestation.

Socioeconomic Conditions

As proxy for socioeconomic conditions, we employ the percentage of the populationin each municipality that depends on firewood as its primary source of energy forcooking and heating. This variable, which is derived from the 2001 census, not onlyprovides information about the importance of forest goods to satisfy basic subsis-tence needs among the population in each municipal territory, but it also gives agood indication of the general level of development. Previous studies have linkedboth resource dependency and the degree of modernization to resource degradation(Cropper & Griffiths, 1994; Gibson & Becker, 2000; Rock, 1996). We hypothesizethat the larger the proportion of the population that depends on firewood, the morepressure there will be on the forest, and the higher the rates of all three types ofdeforestation.

Biophysical Conditions

As outlined under the discussion of alternative explanations, it is necessary to con-trol for at least four biophysical variables in our analysis of how municipal forestgovernance relates to changing forest conditions. All four factors are included ascontinuous control variables in the 2SLS regressions.

Deforestation before 1993: Except for one or two urban municipalities, all lowlandmunicipalities still have high proportions of their land covered by forests. Evenafter years of deforestation, it is very rare that a municipality has less than 50 per-cent forest cover. Because of this abundance of forests, we assume that deforesta-tion rates are strongly path-dependent and expect that municipalities with highdeforestation rates prior to 1993 are likely to continue to experience relatively highrates in subsequent time periods.

Population growth is another alternative explanation of deforestation. It is meas-ured as the percent change in total municipal population between 1991 and 2001(INE, 1992, 2002)

Density of roads (km/km2) is a continuous variable that was calculated by divid-ing the total length of primary roads (calculated in a GIS) with the total area ofeach municipality (Government of Bolivia, 1995). The theoretical expectation is



that if a municipality has low road density, it will also have lower rates of all threetypes of deforestation.

Municipal Area: It is important to control for the size of the land area for whichthe municipal government is responsible. Municipalities of considerable spatialextent will have a more difficult task to create an effective forest governance sys-tem than those municipalities with relatively small areas, regardless of the size oftheir forests.

Institutional Interactions

Two-way Interaction Product: To test our main theoretical argument that municipalforest governance institutions moderate the exogenous drivers of unauthorizeddeforestation, we create a two-way interaction product between the municipal-forest-governance variable and the deforestation-prior-to-1993 variable. The reasonfor choosing the latter variable as an interaction term is that this is the exogenousvariable that consistently had the strongest and most significant effect on all threemeasures of deforestation in the main-effects-only regression models.

To avoid problems of multicollinearity and to facilitate the interpretation of bothsimple and interaction effects in subsequent regressions, we follow the approachlaid out in Jaccard and Turrisi (2003) and transform all independent variables sothat they are mean-centered. After examining the data for outliers, we are forced todrop one observation. The municipality of Montero is an outlier case for our sam-ple because it cut all its forest prior to 1993, causing a severe overestimation of thepredicted ratios of deforestation in all three models.

RESULTS

The results of three different 2SLS regressions3 and subsequent robustness testsare displayed in Table 3. For the first model, the adjusted R2 is 0.6572, indicatingthat a linear combination of the nine independent variables accounts for about 66percent of the variation in total deforestation rates for the 1993-2000 time period.The same nine independent variables explain about 67 percent of the variation inpermitted deforestation (Adjusted R2 5 0.6722), and 78 percent of the varying lev-els of unauthorized deforestation (Adjusted R2 5 0.7761). Tests for aggregate sig-nificance (F-test), multicollinearity (VIF) heteroskedasticity (Breusch-Pagan), andoutliers (standardized residuals) affirm that the results are robust in all three mod-els.4 The unstandardized regression coefficients for the mean-centered independ-ent variables for the second-stage regressions are listed in Table 3 with t-scores inparentheses.

One of the most important findings is that different sets of factors affect unau-thorized deforestation on the one hand, and permitted and total deforestation onthe other. Consistent with our theoretical expectations, biophysical factors are thestrongest determinants of both total and permitted deforestation between 1993 and2000. A 100 square kilometer increase in deforestation prior to 1993 is associated


3 In the first stage of all three regression models, we regress central government monitoring on timber-related royalties (instrument). The instrument variable is positive and highly significant (p , 0.01). TheAdjusted R2 for the first-stage model in the 2SLS is 0.29. 4 A case-wise listing of all the data points’ standardized residuals in the two models reveals that none ofthem are greater than 2.1—significantly smaller than 3.3, which is the conventional threshold for outliersin OLS regression.


with a 12 percent increase of total deforestation (Model 1), an 11 percent increasein permitted deforestation (Model 2), but only a 3 percent increase in unauthorizeddeforestation (Model 3).

The density of roads has a significantly positive effect on both permitted and totaldeforestation rates but not on unauthorized deforestation. When holding all othervariables constant at their mean values (after mean-centering all independent vari-ables, the mean value is 0), a one unit increase in road density (1.0 km per km2) cor-responds to a 12 percent increase in the total deforestation (Model 1) and a 10 per-cent increase in permitted deforestation (Model 2) for the period. The intercept isstatistically significant and indicates that when all independent variables are heldat their mean values (5 0 in the mean-centered model), the mean total deforesta-tion during the 1993–2000 period equals 16.46 percent for the Department of SantaCruz. The mean permitted deforestation rate for the period was 14.23 percent. Theinteraction term, which is derived by multiplying the variables “MFG” and “Defor-estation prior to 1993,” is not statistically significant at the 95 percent confidencelevel, which indicates that there is no two-way interaction effect present in the firsttwo models. In other words, local institutions do not appear to moderate thestrength of the effect that prior deforestation has on permitted and total deforesta-


Table 3. Two-stage least squares multiple regression results.

Model 1: Model 2: Model 3: Total Permitted Unauthorized

Deforestation Deforestation Deforestation Variable 1993–2000 (%) 1993–2000 (%) 1993–2000 (%)

Local InstitutionsMunicipal forest governance (a) –0.0119 (–0.31) –0.0180 (–0.52) –0.0296 (–3.58)***

National PolicyLand use policy 0.1151 (0.83) 0.1350 (1.08) –0.0539 (–1.79)*

Central monitoring (instrumented) 0.0172 (0.36) 0.0141 (0.33) 0.0134 (1.31)

Socioeconomic ContextFirewood dependency 0.0215 (0.21) 0.0361 (0.38) 0.0121 (0.53)

Biophysical ConditionsMunicipal area –0.0014 (–0.61) -0.0011 (–0.53) –0.0003 (–0.58)Deforestation before 93 (b) 0.1211 (2.08)** 0.1090 (2.08)** 0.0311 (2.47)**

Population growth 0.0257 (0.28) 0.0007 (0.01) –0.0042 (–0.21)Density of roads 0.1216 (2.12)** 0.0986 (1.90)* 0.0153 (1.24)

Two-way-interaction product 0.0761 (1.33) 0.0720 (1.39) –0.0293 (–2.93)**

(a 3 b)Intercept 0.1646 (6.42)*** 0.1423 (6.16)*** 0.0202 (3.65)***

Adjusted R2 0.6572 0.6722 0.7761F (p-value) 6.88 (0.0002) 7.25 (0.0002) 13.07 (0.0003)Avg. variance inflation factor (VIF) 2.143 2.143 2.143Breusch-Pagan: prob . chi2, df 5 9 0.0705 0.0874 0.3728Observations 29 29 29

Note: Coefficients for mean-centered independent variables with t-scores in parentheses. * 5 p , 0.1; **5 p , 0.05; ***5 p , 0.01.


tion. Similarly, when letting road density interact with MFG, the interaction term isnot statistically significant in any of the three models (p . 0.4 in all three models).

The results of the third model suggest that the varying levels of unauthorizeddeforestation are best explained by a combination of variables related to the localinstitutional performance, national policy, and biophysical conditions. The level ofmunicipal forest governance performance has a negative and statistically signifi-cant effect on unauthorized deforestation. Holding all other variables constant attheir means, a one unit increase in the ordinal score of the variable (which meansa municipality increases its performance level in the forestry sector) leads to a 3percent decrease in unauthorized deforestation. Another variable that seems tolower unauthorized deforestation rates is the proportion of land within the munic-ipality that the national land use policy has designated to agricultural use, althoughthe simple effect regression coefficient for this variable is statistically significantonly at the 10 percent level). Consistent with our theoretical expectation, the largerthe proportion of land for recommended agricultural use, the less unauthorizeddeforestation takes place. When other variables are held constant at their mean val-ues, each percent increase in prescribed agricultural land corresponds to about a 5percent decrease in unauthorized deforestation rates.

The interaction variable is a product of the Municipal-Forest-Governance variableand the Deforestation-Prior-to-1993 variable, and its coefficient is highly significant(p 5 0.0085) in the third model. This would suggest that there is a bilinear, two-wayinteraction present in the third model. The strength of this interaction effect, asindexed by the squared semi-partial correlation for the product term, is 0.0607.5This means that the two-way interaction between municipal forest governance anddeforestation prior to 1993 accounts for about six percent of the variance in unau-thorized deforestation between 1993 and 2000. The value of the coefficient for thetwo-way-interaction variable of –0.0293 indicates how the relationship betweenDeforestation before 1993 and Unauthorized Deforestation 1993-2000 is moderatedby the strength of the Municipal Forest Governance performance: For each ordinalscore increase of Municipal Forest Governance (for example, from 0 to 1 or from 2to 3), the slope of Unauthorized Deforestation 1993–2000 on Deforestation before1993 is predicted to decrease by 0.0293 units. In other words, the better the per-formance of a municipal governance system is, the more it dampens the positiveeffect of Prior Deforestation on Unauthorized Deforestation during the 1993-2000period. We depict this institutional moderation effect in Figure 4 for all for levels ofmunicipal forest governance performance.

The four lines in Figure 4 represent the regression lines for Unauthorized Defor-estation on mean-centered scores of Deforestation Prior to 1993 for four differentlevels of MFG performance (MFG 5 0, MFG 5 1, MFG 5 2, and MFG 5 3). If therewere no two-way interaction effects in the model, the four lines would be parallel.When MFG performance is at its lowest (MFG 5 0)6 a one unit increase (100 km2)of Deforestation Prior to 1993 corresponds to a 6.1 percent increase in Unautho-rized Deforestation 1993-2000, but for each unit increase of MFG, this effect isweakened by 2.9 percent. When MFG 5 1, the effect of the biophysical driver onUnauthorized Deforestation 1993-2000 diminishes to b 5 0.0324. When MFG is at


5 This was calculated by subtracting the R2 for the main-effects-only model from the R2 of the interactivemodel (0.8667 – 0.8064 5 0.0603). 6 This refers to the absolute value of the MFG variable, not the mean-centered score. When the mean-centered MFG score equals 0, the coefficient for deforestation prior to 1993, as presented in table 3,equals 0.0311.


its maximum value (MFG 5 3) the coefficient actually becomes negative, as shownin Figure 4.

These results provide support for our moderation hypothesis—that local insti-tutional performance dampens the influence of biophysical drivers on unautho-rized deforestation. The better the performance of the municipal forest gover-nance systems, the lower the impacts of prior total deforestation on currentunauthorized deforestation.

DISCUSSION

Consistent with our theoretical expectations, the empirical results suggest that themunicipal-level institutions matter for strategies to contain unauthorized defor-estation. Municipal institutions, however, do not affect permitted or total defor-estation measures. Comparing the results of the three models displayed in Table 3,we find that different types of variables seem to drive the observed outcomes on thelandscape. In the first and second models, biophysical characteristics—such as theprevious rate of deforestation and road infrastructure—help explain why somemunicipal territories have experienced higher levels of total deforestation than oth-ers. In contrast, unauthorized deforestation is best explained by a combination ofmunicipal forestry institutions, national public policy, and biophysical characteris-tics. These findings underscore the importance of employing multiple measures offorest conditions in the analysis of decentralized forestry policy.

The findings provide empirical support for the notion that municipal governancesystems can mitigate pressures to deforest indiscriminately. Our field observationslead us to believe that the municipal moderation of deforestation is related to themunicipal governments’ potential facilitation of improved forest property rights forlocal forest users. Forest users who live in municipalities where municipal govern-ments perform relatively well enjoy better access to and protection of forest prop-erty rights. And forest users who have more secure forest property rights are more


Figure 4. Local Institutional Moderation of Prior Deforestation’s Influence onUnauthorized Deforestation, 1993–2000.


likely to engage in forest management activities and are less likely to convert forestto competing land uses, such as agricultural and pasture lands. Hence, we see someevidence that high-performing municipal governance systems in Bolivia have beenable to shift local forest user activities toward land use activities that are lessdestructive to protected forest areas.

However, the potentially positive role of the municipal government in mitigatingdeforestation in Bolivia should not be overstated. While there is evidence that localgovernance matters, it is also true that the rates of unauthorized deforestation in SantaCruz remain quite high in absolute terms. Among the 30 surveyed municipalities, 22experienced some degree of deforestation during the 1993–2000 period (resourceusers in one municipality had cut all their forests prior to 1993). On average, aboutone-third of all deforestation occurring in these municipalities was not authorized bythe national land use policy. The sheer magnitude of the current levels of unauthorizeddeforestation should be a concern for policy actors who seek to promote sustainableland use practices in the Bolivian lowlands. It is doubtful that the current levels of per-formance among the municipal governance systems would be sufficient to ensure thecontinued survival of significant stretches of lowland forests in Bolivia.

CONCLUSION

We end our study of Bolivia’s decentralization experiment by highlighting twobroad issues regarding the study of such policies and their impact on environmen-tal governance. First, the Bolivian case illustrates that decentralization can producehighly variable environmental outcomes. Even though the municipal officials oper-ate under the same forestry policy framework—a framework that assigns the samegeneral rights and responsibilities to all municipal governments in the country—wefind that, in reality, there is very large variation in local government responses tothe uniform decentralization policy. Some local government actors seem to see theirincreased authority as an opportunity to serve their constituents, and consequentlydecide to take action in the forestry sector. Other local governments appear to seelittle benefit from their new powers and seem to do just enough to stay out of trou-ble. Yet another group of municipalities seem to ignore completely their new rightsand responsibilities, and take no action at all.

While we do not dwell more deeply in this study on why some municipal systemswould be motivated to do more than others in the forestry sector, the observed vari-ance in performance levels suggests that there is a local dynamic of institutionalmoderation of national policy reforms that researchers and policymakers need tounderstand. We believe that exploring the scope and fit of forestry decentralizationwith local governance arrangements, as well as appropriate outcome measuresrelated to such policies, will help explain the variance in these motivations, andthus improve our knowledge about the factors that generate successful decentral-ized environmental policy.

Second, to improve the performance of public policies in the area of environ-mental management, government officials themselves would benefit from more sys-tematic monitoring of how current public policies, including decentralization, actu-ally influence resource users’ decision-making and activities on the ground. Webelieve our study provides a set of useful indicators which, if gathered over time,may serve to assess the environmental performance of decentralized regimes.Hence, monitoring systems that are based on research designs that consider a com-bination of institutional scope and fit, as well as adequate outcome measures, caninform policy decisions in a more meaningful and nuanced manner.



More specifically, our institutional approach to the study of decentralized gover-nance demonstrates that it is easy to overlook the importance of local institutionswhen analyzing the effects of public policy on natural resources conditions. In fact,had we settled for using the traditional outcome measure of forest conditions in ourstudy—the proportion of forest cut during a given time period—our analysis wouldhave been forced to conclude that local institutional performance does not system-atically affect changing forest conditions. It was only after constructing comple-mentary, more policy-sensitive outcome variables that we were able to test for theinfluence of municipal-level governance institutions. This result reinforces the needfor careful a priori examination of the role of local institutions, conditioned by thescope and fit of decentralization, before designing an empirical analysis.

KRISTER ANDERSSON is Assistant Professor of Political Science and Environmen-tal Studies, University of Colorado at Boulder.

CLARK C. GIBSON is Professor of Political Science in the Department of Political Sci-ence, University of California at San Diego.

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