Decentralization and Water Pollution Spillovers : Evidence from the Redrawing of County Boundaries in Brazil

Decentralization and Water Pollution Spillovers:
Evidence from the Re-drawing of County Boundaries in Brazil

Molly Lipscomb
Department of Economics, University of Colorado at Boulder

Ahmed Mushfiq Mobarak
Yale University, School of Management


Correspondence: Mushfiq Mobarak, ahmed.mobarak@yale.edu

Preliminary Draft: 11/30/2007, Comments Welcome

Abstract

We examine the effect of political decentralization on pollution spillovers across jurisdictional boundaries.
Upstream water use has spillover effects on downstream jurisdictions, and greater decentralization (i.e. a
larger number of political jurisdictions managing the same river) may exacerbate these spillovers, as
upstream communities have fewer incentives to restrain their members from polluting the river at the
border. We use GIS to combine a panel dataset of 9,000 water quality measures collected at 321
monitoring stations across Brazil with maps of the evolving boundaries of the 5500 Brazilian counties to
study (a) whether water quality degrades across jurisdictional boundaries due to increases in pollution close
a river’s exit point out of a jurisdiction, and (b) what the net effect of a decentralization initiative on water
quality is, once the opposing impacts of inter-jurisdictional pollution spillovers and increased local
government budgets for cleaning up the water are taken into account. We take advantage of the fact that
Brazil changes county boundaries at every election cycle, so that the same river segment may cross
different numbers of counties in different years. We find evidence of strategic enforcement of water
pollution regulations; there is a significant increase in pollution close to the river’s exit point from the
upstream county, and conversely a significant decrease in pollution when the measure is taken farther
downstream from the point of entrance. Pollution increases by 2.3% for every kilometer closer a river gets
to the exiting border, but in the stretch within 5 kilometers of the border this increase jumps to 18.6% per
kilometer. Thus the greatest polluting activity appears to be very close to the exiting border. Our
theoretical model coupled with the empirical results are strongly suggestive that these results are evidence
of strategic spillovers rather than spurious correlation between county splits and pollution stemming from
changing population density. Even in the presence of such negative externalities, the net effect of
decentralization on water quality is essentially zero, since some other beneficial by-products of
decentralization (in particular, increased local government budgets) offsets the negative pollution spillover
effects.



We thank Marianne Bertrand, Erin Mansur, Bernardo Mueller, numerous water management
practitioners at the federal and various state water agencies in Brazil, and seminar participants at
the University of Colorado at Boulder, Yale University, University of Michigan, Harvard
University, Wesleyan University, the 2007 NBER Summer Institute in Environmental
Economics, 2007 BREAD conference and the 2006 ISNIE conference for helpful discussions and
comments. All errors are our own.

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1. Introduction
Water is a publicly provided good of fundamental importance. Over one billion
people in the world lack sufficient water, and over 90 percent of sewage and 70 percent
of industrial wastes are dumped into surface water untreated (Revenga 2000). Diarrhea,
whose incidence is related to the lack of access to clean water, kills 1.3 million children
every year and accounts for 12 percent of under-5 mortality (WHO 2003).
The hundreds of international and intra-national conflicts over water sharing
throughout history (Wolf 2002) are symptomatic of the microeconomics of water
quantity and quality degradation. The flow of rivers creates ‘upstream’ and
‘downstream’ regions, and water conflicts are often related to the opening of a diversion
gate upstream or the discharge of pollutants into the water as it flows downstream. With
negative spillovers on downstream users, water use may be ‘inefficient’ from a societal
perspective in the absence of inter-jurisdictional coordination.
Decentralization initiatives promoted by international organizations as a way to
improve public service delivery (World Bank 2003, Bardhan 2002) may actually
exacerbate cross-border spillovers once jurisdictions start making unilateral decisions.
For example, a reduced role for the central authority in favor of sub-national (e.g. state or
county) government management could lead to upstream water policy that promotes
over-usage and over-pollution, as costs to downstream communities are not considered
during planning processes. On the other hand, if decentralization increases local
government budgets or otherwise reallocates resources toward environmental or
sanitation spending, it has the potential to improve water quality. These issues are not
unique to water quality, and are relevant for any publicly provided good with spillovers.

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For example, local governments may under-invest in health programs if the positive
spillover benefits of improvements in health status (e.g. Miguel and Kremer 2004) to
those residing outside the jurisdiction are not taken into account.
This paper empirically examines the effect of a particular form of decentralization
- the geographic splitting of counties leading to a larger number of counties managing the
same river segment - on negative water quality spillovers on downstream users in Brazil.
We combine a rich panel dataset of water quality measures collected at monthly intervals
at 321 upstream-downstream pairs of monitoring stations located in all eight major river
basins across Brazil with GIS maps of evolving county boundaries to examine (a)
whether water quality degrades due to increases in pollution close a river’s exit point out
of a jurisdiction, and (b) the net effect of decentralization on water quality, accounting for
both spillovers and budgetary impacts. We find substantial evidence that Brazilian
counties strategically pollute close to the river’s downstream exit point out of the county
(and conversely, remain clean at upstream locations where the river enters the county),
but no evidence that the decentralization initiative causes an overall deterioration in water
quality, suggesting the presence of offsetting budgetary effects.
We can replicate Sigman (2002)’s empirical approach for analyzing pollution in
international rivers to examine whether there are differentially larger drops in quality at
monitoring stations downstream from a jurisdictional boundary (or more generally, when
a river crosses a larger number of boundaries). However, the number of boundary
crossings is likely correlated with other characteristics of the counties through which the
river flows including major economic activities in the county, population heterogeneity,
and environmental spending. Some characteristics correlated with both water quality and

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county size (which in turn is correlated with distances to county borders and boundary
crossings) are not observed in the data and this can introduce bias in estimated spillover
effects.1
We then take advantage of the fact that Brazil redraws county borders (the
number of counties increased from 4492 in 1991 to 5562 in 2001), thereby changing both
the number of boundary crossings and distances to nearest borders for the same river
segment over time. This enables us to more precisely identify the effects of changes in
proximity to borders and decentralization on the inter-temporal change in water quality
deterioration by controlling for fixed effects for each station-pair (or the river segment
defined by that pair). Since each county has some policy-making authority over
environmental regulatory standards and over sanitation spending, the splitting of counties
leads to de facto decentralization in the sense that more separate jurisdictions gain control
over water quality in a river segment.2 Management of water at the baseline is already
somewhat “decentralized” in the usual sense of the word, but examining the effects of
changes in distances to borders and in the number of counties managing the same water is
a particularly useful way of honing in on the inter-jurisdictional spillover effects.
Our dependent variable is the change in Biochemical Oxygen Demand (BOD)
from the upstream to the downstream location in each station pair:
BOD
?
= BOD ? BOD .3 For the same station-pair the county re-districting can change
d
u

1 Sigman (2002) notes the need to include monitoring station fixed effects to account for such
heterogeneity, but is unable to do so since her border variables of interest do not vary over time.
2 Sigman (2004) on the other hand uses variation in which U.S. states are authorized to enforce Clean
Water Act regulations to study the border spillover effects stemming from such authorization. This allows
her to control for a station-fixed effect, but since distances to borders do not vary over time, that variable
remains omitted, which may be of concern if the placement of monitoring stations is not random.
3 Sigman (2002) also uses BOD to study pollution in international rivers. BOD is relatively easily measured
by standard procedures, helping to ensure data quality. BOD tends to travel farther downstream than some
other pollutants, which makes it appropriate for a study on inter-jurisdictional spillovers. We use ?BOD

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the distance the river traverses in the “upstream county” (i.e. where the upstream station
is located), the distance traversed in the “downstream county”, and the number of county
boundary crossings between the pair of stations. We use variation in all three dimensions
in order to analyze both strategic pollution spillovers and the net effect on water quality
from the decentralization that results from county splitting. The theoretical framework
we develop shows that under strategic behavior, counties shift polluting activity to near
their downstream exit border and remain clean in the upstream part of their own
jurisdiction. Thus pollution level in the upstream county would be greater when
measured closer to the exit border, and conversely, pollution level in the downstream
county should be lower when measured further away from the upstream entering border.
We find strong statistical evidence for both effects, suggesting the presence of spillovers
due to such strategic behavior by counties. Further our theory also suggests that under
strategic pollution shifting, water quality should fall more dramatically in the upstream
county the closer we get to the exiting border, and our regression estimates indicate
precisely this type of dynamic for changes in BOD in Brazilian rivers. When we allow
for non-linear effects of distance to border, we find that BOD increases by 2.3% for every
kilometer closer a river gets to the exiting border, but in the stretch within 5 kilometers of
the border this increase jumps to 18.6% per kilometer. Thus the greatest polluting activity
appears to be very close to the exiting border.
In spite of such clear evidence on cross-boundary spillovers, we find that the net
effect on water quality of having extra boundary crossings induced by county splitting is

(rather than, say, BODd) as the dependent variable since pollution at any point on a river is determined by
the entire “spatial history” of the river (tributary inflows and dumping at any point upstream), and BODu
acts as an effective control variable for the determinants of pollution anywhere upstream of point u. Our
empirical models are then left with the simpler task of explaining the change in pollution from the upstream
point to the downstream point as a function of the characteristics of counties in between the two points.

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statistically indistinguishable from zero. County splitting may be associated with
potentially countervailing benefits from (a) the increased aggregate public services
budgets that accompany decentralization, and (b) the possibly greater homogeneity in
population that results. Each county in Brazil receives a fixed transfer from upper-level
governments in addition to a portion of the taxes collected in their jurisdiction. Thus the
replacement budget for the smaller counties after a split exceeds the original county’s
budget. County fixed effects regressions show that per-capita sanitation spending
increases by 20% in counties that are split, which potentially explains the improvement in
water quality offsetting the negative spillover effects. Further we find that the net effect
of decentralization on water quality is negative when we condition on monitoring stations
located closer to borders (as opposed to the nil effect in the full sample). Close-to-border
is also where spillovers are larger, so this further buttresses the case that there appears to
be a spillovers-budgets tradeoff inherent in this process of decentralization.

A key concern with our estimation strategy is whether factors correlated with
increases in pollution affect a county’s propensity to split. For example, increasing
population density may be correlated with both the propensity to split and with changes
in pollution. It is not obvious that such a story would explain the specific pattern of
strategic pollution shifting we report (that pollution increases non-linearly and more
dramatically in the upstream county the closer we get to the exiting border), but
nonetheless we want to be as careful as possible in differentiating evidence of true
strategic behavior from spurious correlations. We therefore theoretically model this
specific form of endogeneity (where a jurisdictional split occurs endogenously in an area
with high population density), and examine the spatial pattern of pollution both upstream

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and downstream of county borders that would result under scenarios where endogenous
population density-induced pollution is present, and in another scenario where it isn’t.
This yields an empirical test of that particular form of endogeneity (that splits occur in
high density areas), and the data show that the specific spatial pattern of pollution that we
report is not consistent with the hypothesis that endogeneity due to population density is
the main driver of the relationship between decentralization and pollution spillovers.
In the absence of a suitable instrument for county splitting we also adapt the
Altonji, Elder and Taber (2005) methods to assess the potential bias in our estimates from
the possibility that counties split for other unobserved reasons correlated with water
quality. If the selection on county splits due to the set of observed explanatory variables
(e.g. changes in population density or GDP per capita) is any guide, then the bias
stemming from unobservable determinants of county splits is not likely to be very large,
and can explain away only a small portion of our results on spillovers. Finally, we also
conduct sensitivity checks to ensure that these results are not driven either by the
selective addition of new stations in areas where the pollution problems are worsening, or
extreme values of BOD measures, or by changing population density in re-districted
counties.

2. The Literature on Decentralization and Water Quality Spillovers
Decentralization has been one of those “buzz-words” promoted by many
development scholars and practitioners as a way to improve public service delivery and
rural development outcomes. The World Bank 2004 World Development Report on
service delivery devotes large sections to the topic, and the World Bank has also made

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loans aimed at localization of projects, technical assistance based on local capacity
building, and conducted budget analyses of inter-governmental transfers necessary for
decentralization to be successful. Many other multi-lateral development institutions have
policies encouraging decentralization. The UNDP’s Decentralized Governance Program
works with national level governments to support the empowerment of local
governments. The FAO has a policy of prioritizing work with local governments and
encouraging rural and local governments to take a leading role in their projects.
However, the relative merits of decentralized versus centralized organization of public
services remains a debated topic in the scholarly literature. At issue is balancing the
objective of improving accountability and responsiveness of the public sector with the
difficulty of providing public goods with benefits or costs that cross jurisdictional
boundaries. Identifying conditions under which decentralization improves the efficiency
of the public sector remains a key policy challenge.
In its early stages, the contribution of the economics literature to the
decentralization debate was primarily theoretical. Oates (1972)’s seminal work on the
topic argues that decentralization improves efficiency if it enables communities to take
advantage of heterogeneity in preferences over public goods provision. However, Oates
(2001) argues that there are two major sources of inefficiency under decentralization. It
allows communities to ignore the externalities that they impose on other regions and it
causes duplication in management bureaucracy. List and Mason (2001) show that as long
as such spillovers are not too high, decentralization will improve efficiency over a
centralized government setting uniform pollution standards under heterogeneity in the
costs of pollution across localities. Coate and Besley (2000), by contrast, note that when

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the budget is shared between localities and there is heterogeneity in preferences within
communities, the optimal allocation of the public good need not be reached as each
community does not pay the full marginal cost of local programs.

Insights from the environmental “race to the bottom” literature are also relevant
for evaluating the merits of decentralization. Cumberland (1981) and others have argued
that competition between jurisdictions to attract business investment may lead to a “race
to the bottom” in environmental quality. In contrast, Oates (2001) suggests that a “race
to the bottom” is unlikely to follow inter-jurisdictional competition, since environmental
damage is capitalized into local property values, and as a result community members face
the implicit shadow price of environmental damage even as they perceive the benefits of
increased economic activity in their region.
The policy-making community has noted the relative paucity of empirical
evidence for the various arguments in favor of and against decentralization (World
Development Report 2000). This lack of empirical evidence is in part due to the
difficulty of accurately measuring spillover effects, and in part a result of the
impossibility of isolating the effect of decentralization when it is combined with a series
of legislative reforms.
Sigman (2002) was the first to examine water pollution spillovers across
jurisdictional boundaries. She finds that stations just upstream of international borders
have higher levels of BOD than similar stations elsewhere. However, this effect is not
robust to the inclusion of country fixed effects, and she herself warns of the dangers of
interpreting correlations that may be driven by cross-country heterogeneity in some other
unmeasured characteristic. Sigman (2005) improves this identification strategy in

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analyzing spillovers across U.S. states following the passage of the Clean Water Act.
She uses variation in the time at which states were authorized to enforce the Clean Water
Act within their boundaries in order to determine the impact of the decentralization of
control over water policy. A key identifying assumption is that authorized states are
comparable to other states at the baseline, and the timing and choice of states to authorize
is essentially as exogenous event. Her estimation strategy requires identifying the
location of monitoring stations relative to borders, and classifying each station as either
upstream, downstream, or bordering a state boundary. Using a fixed 50-mile distance to
the border to classify stations, she finds that a significant number of stations can be
categorized in more than one group (i.e. they are both upstream of one boundary and
downstream of another). The location of stations relative to state borders lacks any time
variation, and empirical identification in the station-fixed-effect regressions comes from
time variation in states’ authorization status.
In contrast, our approach uses pairs of stations (rather than individual monitoring
stations) as the unit of observation to examine changes in water quality from an upstream
station to its nearest downstream station. Classification of “upstream’ and “downstream”
stations using GIS river flow vector maps is therefore natural and unambiguous. In
addition, since our identification strategy takes advantage of the evolving county
boundaries in Brazil over time, we have time variation in each station’s distances to the
nearest county exiting (i.e. downstream) and county-entering (i.e. upstream) borders. We
identify the pollution effect of distance to border solely from changes in that distance
over time for the same monitoring station due to a change in the county boundary. This
reduces concerns about the strategic or non-random placement of monitoring stations

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