the impact of rural electrification on deforestation and

Tanner_MPP_EssayThe Impact of Rural Electrification on Deforestation and Soil Fertility
By
Master of Public Policy
Presented November 16, 2015
Master of Public Policy essay of Andrew M. Tanner presented November 16, 2015
2
3
Abstract Deforestation and loss of soil fertility are two forms of environmental degradation with global importance. Theories of environmental degradation commonly cited in public and academic discourse have historically emphasized the role of human populations and national economic development as being the primary drivers of environmental damage. This thesis utilizes quantitative techniques and a dataset with global scope to assess evidence supporting a different hypothesis: that lack of access to basic electric services in rural areas is a key explanatory factor in assessing deforestation and soil fertility loss. This hypothesis is drawn from the intellectual tradition of political ecology, which emphasizes the material conditions faced by people constrained by exploitative political economic systems, siting the penultimate driver of environmental destruction under the purview of global systems of power, economic and cultural in nature. This thesis seeks to meld the insights of political ecology with contemporary research standards in comparative politics to identify an alternative to environmental policies, which focus on market expansion or population control as means to mitigate environmental degradation.
4
Competing Theoretical Explanations for Environmental Degradation.........................................10
A Missing Link?: Political Ecology and Environmental Degradation...........................................14
Rural Electrification as a Proxy for Human-Needs Focused Rural Development.........................18
Methods..........................................................................................................................................20
Analytical Results..........................................................................................................................24
Discussion......................................................................................................................................33
Contemporary explanations for environmental degradation tend to emphasize one of two explanations -
either the problem is rooted in overpopulation, which causes increased resource demand in order to sustain
populations, or it is due to the natural progress of economic development, which requires increasing environmental
use until populations become sufficiently wealthy that they can afford to pay the high costs of environmental
protection. Even explanations that accept multi-causal processes such as the popular "IPAT" formulation (Impact =
Population + Affluence + Technology) accept overpopulation and economic development as being at the core of
environmental degradation.
However, since the 1980s an increasing number of scholars have contributed to the burgeoning field of
political ecology, an interdisciplinary area which has sought to counter over-simplified causal explanations of
environmental degradation that fail to address what political ecologists view as a crucial explanatory factor: the
social and economic structural conditions that mediate local people's use of the environment in order to meet basic
human needs. This thesis seeks to apply a broadly political ecological understanding to a quantitative dataset,
controlling for oft-cited degradation factors of population and economic wealth to assess on a comparative basis
these factors against one that broadly impacts local people's need for direct consumption of environmental resources
- rural electrification.
It is the intent of this work to examine the effect of rural electrification in determining levels of
deforestation and soil fertility loss observed at a country level, utilizing a World Bank dataset with global coverage.
It will make the case that rural electrification can serve as a proxy for a mode of rural governance emphasizing
people's access to basic public services, a particular political-economic relationship which reduces material demands
on landscapes and decreases resistance to state policies promoting environmental protection. Governance is a key
factor affecting environmental degradation as the implementation of policy measures often have material impacts on
the natural world, directly or indirectly limiting - or enabling - exploitation of natural resources. By applying
quantitative methods more commonly associated with evaluations of environmental degradation that emphasize
economic and demographic effects, it is argued that local political-economic conditions mediate land user reliance
on local landscapes and so are an important and under-examined causal factor in environmental degradation.
6
Conceptualizing Environmental Degradation: Deforestation and Soil Fertility Loss
The rapid uptake and spread of industrial manufacturing processes, beginning in 19th Century Europe and
moving to encompass most of the rest of the world within the next hundred years, dramatically accelerated forest
loss - to the point that upwards of 70% of original temperate zone forest cover was gone by the time the 21st
Century began (Goudie, 2006). Tropical forests now face the fastest rates of degradation and the bleakest future,
with more than half anticipated to be gone by the mid 21st Century (Goudie, 2006; United Nations, 2005). The
social welfare implications of this ongoing degradation are clear:
Deforestation is not only a serious threat to achieving
sustainability, but also to progress towards hunger and
poverty reduction and sustainable livelihoods, as forests
provide food, water, wood, fuel and other services used by
millions of the world’s poorest people." (United Nations, 2000)
Perhaps surprisingly, 'Deforestation' is not always a clearly defined concept, although the term is widely
used (Brown & Zarin, 2013). When speaking at a regional national level, as is often done in the literature, there
arises a problem that Brown and Zarin (Brown & Zarin, 2013) identify as being tied to notions of 'gross'
deforestation or 'net' deforestation. Basically, this problem comes down to one of clustering observations into a
statistic: if one counts all 'untouched' forest observations as forests, then any modification to these is 'deforestation'
in a 'gross' sense. But if one also counts reforested or afforested areas as being forest as well, this then refers to
deforestation in a 'net' sense. This distinction is important because most statistics available at a national level report
net deforestation.(Brown & Zarin, 2013). This work by necessity adopts a 'net' deforestation definition - that is, if its
total forest area decreases between years it experienced deforestation, and vice-versa - as using country-level data
obfuscates dynamics within a country, leaving only the reported total change in forest area observed.
Soil fertility loss is a potentially devastating form of degradation, but harder to characterize than
deforestation, given the effectively invisible nature of shifts in chemical constituents within soil. Unlike forest loss,
which can be observed in a fairly straightforward manner via satellite based remote sensing, measuring soil fertility
requires physical samples to be obtained and analyzed in multiple locations and, if one seeks to understand change
in soil fertility, at multiple points in time as well (Benjaminson et al, 2010; Manlay et al, 2007; Poudel et al, 2002;
7
Zingore et al, 2011). An indirect measure of soil fertility loss can be made by examining the rate of application of
inorganic fertilizers to cropland, as these are typically applied to either replace nutrients which have been lost over
time or to enhance existing soils beyond their natural capacity for agricultural production (Taddese, 2001; Zingore et
al, 2011).
Deforestation and Soil Fertility Loss: Drivers and Consequences
Deforestation causes have been widely examined in the literature, from a variety of perspectives. Economic
drivers play a role in deforestation, and illegal logging has been identified as one of the biggest drivers of
deforestation in the tropics (Burgess et al, 2012; Lynch et al, 2013). Legal logging is certainly driven by similar, if
not the same, price and cost pressures (Celentano et al, 2011). The boom-bust pattern observed in frontier regions of
the Amazon appears to follow economic logic fairly closely, with deforestation at the frontier improving the welfare
of local people proximate to it, at least up to a point at which point further logging exhibits a negative effect on
welfare (Celentano et al, 2011). International investment is also tied to deforestation, both through timber prices and
the increasing demand for agricultural commodities, which promote deforestation in order to increase the stock of
agricultural land available for productive use (Celentano et al, 2011; Angelsen, 2009). Agriculture is widely seen as
a major contributor to deforestation, with land clearance in order to meet the global demand for commodities
dominating the narrative in recent years (Ryan et al, 2012).
A strategy of creating forest preserves free from human use has been widely employed over time, but may
itself promote deforestation. The 'preserves' strategy emphasizes the importance of forests in providing vital
ecosystem services and identifies the threat to them as fundamentally anthropogenic. This strategy's intellectual
roots emphasize the role of people in general, of the idea of inevitable pressures that human populations exert on
resources, as the underlying culprit behind deforestation (Goudie, 2006; Ryan et al, 2012; Schaeffer and Rodrigues,
2005; Harris et al, 2012). An exclusionary policy is popular in much of the world, but less so in areas that are
officially protected. The reason is fairly clear: more than half of these 'parks' are, in fact, home to people (Almudi &
Berkes, 2010; Rayn & Sutherland, 2011). And, as the UN makes clear in its Millenium Goals and Ecosystem
Assessment, people who live on or near forest lands very often rely on them to preserve their livelihoods.
Preservation efforts have historically stimulated serious resistance on the part of affected locals (Hecht, 2011).
Despite the danger of prosecution, locals in sufficiently desperate circumstances will defy such places' protected
8
status, and deforest them anyway (Pfaff et al, 2014). In examining the effectiveness of establishing forest reserves in
Brazil and Mexico, empirical works have found limited benefits to protection mandates (Almudi & Berkes, 2010;
Pfaff et al, 2014; Rayn & Sutherland, 2011). While certainly having some effect, the magnitude was not found to be
as great as predicted.
The impacts of deforestation are increasingly felt at a global level. In terms of impact on climate,
deforestation is one of the biggest contributors to emission of carbon dioxide and other greenhouse gases into the
atmosphere (Goudie, 2006; United Nations, 2005). It is estimated that illegal logging alone may contribute up to
20% of the total anthropogenic greenhouse gas emission budget (Burgess et al, 2012), and between 1-2 petagrams of
anthropogenic carbon totaling 7%-14% of total annual anthropogenic carbon emissions (Harris et al, 2012; Lynch et
al, 2013). This contribution to the global problem of climate change has resulted in the widespread push for the
reduction of emissions from deforestation in developing countries (REDD), which serves as a mechanism for
channeling money from the developed world to the developing in hopes of promoting a development path that does
not require the destruction of native forests, as it did in Europe.
Like deforestation, degradation of soils is widely cited as a major anthropogenic impact on the
environment, but there is no single overarching cause that explains it. Unlike deforestation, however, observing and
characterizing soil degradation presents serious difficulties (Zingore et al, 2011; Blaikie & Brookfield,1987), which
are compounded by there being multiple dimensions of soil degradation which make it important to specify what,
exactly, one is talking about when referring to it.
Two major themes emerge from the literature when seeking to define soil degradation's key components.
First, there is the physical presence of the soil itself - soil being the thin, topmost layer of the ground, under which,
at some depth, the ground transitions to bedrock (Goudie, 2006). Ultimately, the soil represents the substrate of the
biosphere, a source of physical space for plants to take root, anchoring life on Earth. Second, there is the constitution
of the soil itself: what chemical elements are present that sustain the growth of plant life, and in what relative
proportions?
Both the physical presence of soil and its fertility are threatened by degradation in much of the world, but
the developing world is particularly vulnerable. Soil erosion involves the physical displacementof soil between
locations, which often results in its deposition in places where it is of no good to living things. This can occur via
9
natural or human processes, or, as is typical, a combination of both. Given that soil takes millenia to generate
(Goudie, 2006) its loss is effectively permanent. In the worst case, erosion losses can become total, and in Ethiopia,
for example, formerly productive landscapes have eroded all the way to bare rock(Taddese, 2001), likely as a
combined result of human disturbance of natural soil structures via agriculture, and as a natural effect of rain and
wind acting on the soil surface. Erosion is implicated in the process of desertification(Geist & Lambin, 2004).
The proximate cause of soil fertility loss is usually over-use of soils by humans trying to grow crops for
their consumption or for the market. Economics clearly plays a role, as prices set for agricultural commodities and
the costs associated with agricultural production interact to create pressures to intensify and specialize productive
use of a given plot of land.
Agriculturalists have long understood that crop rotation can mitigate fertility loss even without added
inorganic fertilizers because different plants absorb different nutrients at different rates, and their residues can leave
behind enriched sources of nutrients which can be ploughed back into a field to preserve its fertility (Benjaminson et
al, 2010; Sheldrick et al, 2003; Haileslassi et al, 2005; Tittonell et al, 2005; Zingore et al, 2011). However,
competitive pressures can make healthy crop rotations too expensive to maintain (Poudel et al, 2002), forcing
farmers to grow as many cash crops as they can. Such pressures seem to rise as population wealth increases
(Emadodin et al, 2012; Sheldrick et al, 2003), implicating economic growth in affecting farmer ability to practice
healthy soil management.
The interplay between soil degradation and forest degradation must be mentioned. The need for access to
more agricultural land is a notable driver of deforestation, and one reason more land is needed is the exhaustion of
fertility in existing soils (Taddese, 2001). In turn, deforestation can unsettle local hydrological systems and
biological habitat patterns, creating rebounding impacts on soils. The DPSIR model - integrating variables classed as
Drivers, Pressures, State, Impacts, Response - emphasizes the complex interactions between different ecological
sub-systems (Emadodin et al, 2012). It is becoming increasingly clear that damaging soil fertility can cause
feedbacks, spreading damage across the environment.
10
Competing Theoretical Explanations for Environmental Degradation
One of the oldest and most commonly cited causes of environmental degradation is overpopulation. The
core logic behind this proposed causal relationship is simple: humans have needs, which can only be satisfied by
placing demands on the environment. And, in a gross sense, this logic is irrefutable: there is a fixed limit to the
amount of energy the human species can remove from the earth’s natural system (Pimentel, 2009). If, as Malthus
argued, if populations grow faster than the systems of goods production that support them, inevitable conflict
between supply and demand of resources results. Neo-malthusians such as Erlich (1970) and Garret Hardin (1968)
tap this logic to argue that overpopulation is the greatest threat to the planet (Hardin, 1968; Koshland 1993; Alper,
1991; Pimentel, 2009).
Hardin's work has been highly influential, likely because Tragedy of the Commons unites both neo-
malthusian thinking and ideas of economic rationality in an explanation for broad-scale environmental degradation.
His argument is that where private property institutions are lacking, unowned resources are exploited by individuals
who seek to maximize their own resource extraction activities (Hardin, 1968). Without the bounds of property rights
to decide who can take what without paying a price, all users of the commons over-utilize, ultimately degrading,
exhausting, and destroying it, to the detriment of all (Hardin, 1968).
Although the logic behind Tragedy of the Commons was initially applied to explain why public goods, in
the economic sense, are under-produced and over-exploited, underlying the concept is the argument that population
increase is the fundamental driver of over-exploitation (Hardin, 1968). Indeed in a later piece for the journal
Science, Hardin further argued that overpopulation is effectively a disease upon a living planet, which must be
treated to prevent the death of the organism (Hardin, 1971). He is far from alone in making similar arguments. In the
1990s neo-Malthusian arguments again were made by scholars, this time claiming to speak for environmentalists as
a whole in arguing that overpopulation is the greatest threat to humanity (Alper, 1991; Koshland 1993), and that
efforts to introduce affordable family planning are essential in mitigating the issue (Alper, 1991). Counter-
arguments that public demand in markets is the real issue, and the efforts by corporations to stimulate consumption,
were countered (Koshland 1993). And in recent years, predictions of global populations topping out at more than 9
billion by the mid 21st Century were coupled with fear that climate change would damage an already insufficient
food production system (Pimentel, 2009).
11
Numerous issue-specific works that address environmental degradation specifically single out large and/or
growing populations as a causal driver of both deforestation (Celentano et al, 2011; Tacconi, 2011, Goudie, 2006)
and soil degradation/fertility loss (Emadodin et al, 2012; Sheldrick et al, 2003; Taddese, 2001). The impact of
population is explicitly included in the IPAT model, which argues that impacts on the environment (I) are a function
of Population (P), Affluence (A), and Technology (T) (Goudie, 2006). This formulation and its wide use in
sustainability studies is indicative of the impact 'overpopulation' is widely thought to have on the environment.
If overpopulation arguments are accepted at face value, there are few options available to policy makers.
Family planning is one policy option explicitly considered (Alper, 1991), and options such as China's one-child
policy have been tried, even if their effects are not immediately apparent (Pimentel, 2009). In truth, however,
overpopulation arguments are generally presented as if they are undeniably factually correct, without offering
explicit solutions. Hardin himself seems to offer no palliatives, save for humans being willing to give up the right to
have children as part of a wider moral shift in society (Hardin, 1968). Given, however, that it is in developing
countries that the majority of population growth is now observed, it is difficult to conceive how western academics
can bring such a moral shift about. And can be easily observed that it predominantly has been white, affluent,
western scholars who decry population growth that takes place in typically, non-white, poor, non-western contexts.
Another highly influential theory positing causal mechanisms for environmental degradation emerges from
economics, in the form of the Environmental Kuznets Curve. The original Kuznets curve was conceptualized and
demonstrated by Simon Kuznets in the 1950s as an explanation for inequality in developed societies (Chowdhury
& Moran, 2012). In later years there was an explosion of scholarly research positing that a similar Kuznets curve
could be applied to explain environmental degradation over time (Boucekkine et al, 2012; Chowdhury & Moran,
2012). This followed from the observation that, in the experience of the most developed countries - located primarily
in Europe, but with Canada, the United States, Australia, and New Zealand also included - environmental
degradation increased with economic development, then reached a point where extensive effort was applied to
reverse the damage caused, even as economies continued to grow. The Environmental Kuznets Curve literature
posits a specific pattern for this phenomenon: as wealth increases in a country, so does demand - which can only be
met by increased utilization of natural resources. However the externalities caused by this damage accumulate and
begin to have serious impacts on productivity. At a certain point, it becomes economically rational to invest in
12
mitigation efforts, policies, and technologies that keep degradation under control and reverse it, leading to
decreasing rates of degradation over time (Boucekkine et al, 2012; Choumert et al, 2013; Chowdhury & Moran,
2012; Culas, 2012; Angelsen, 2009; Tacconi, 2011).
The causal mechanism behind the Environmental Kuznets Curve is increased wealth, which first boosts
demand and later accords populations the income flexibility needed to pay for mitigation (Chowdhury & Moran,
2012; Choumert et al, 2013). Significant attention is paid in empirical literature to the 'turning point' in terms of per
capita income associated with the moment degradation begins to decrease (Chowdhury & Moran, 2012; Boucekkine
et al, 2012; Culas, 2012). This is connected with potential thresholds where policy intervention may be necessary in
order to mitigate damages in cases where a threshold of irreversible ecological damage may be crossed (Boucekkine
et al, 2012), intervention that was termed by Culas as being akin to 'tunneling through' the otherwise probable curve
in order to begin the shift to lower degradation rates earlier than might be otherwise observed in a purely lassez-faire
regulatory system (Culas, 2012).
However, empirical results testing the Environmental Kuznets Curve concept have been mixed, with
studies conducted in more recent years tending not to find evidence supporting its relevance (Chowdhury & Moran,
2012; Choumert et al, 2013; Boucekkine et al, 2012). Part of this is due to the many types of degradation that have
been examined, which range from particulate emissions to physical degradation of forests and soils. Typically, the
expected curve has been observed when dealing with certain kinds of pollutant emissions into the air or water, but
not so much for broader, more complex forms of degradation such as deforestation (Choumert et al, 2013).
Choumert et al recently conducted a meta-analysis of many if not most pieces of empirical Environmental Kuznets
Curve literature dealing with deforestation published in the past 20 years (Choumert et al, 2013), and discovered that
more recent studies do tend to lack support for the theory. Other works have found that, with respect to deforestation
in particular, results are similarly mixed, with a tendency not to confirm the theory (Boucekkine et al, 2012;
Choumert et al, 2013; Chowdhury & Moran, 2012; Culas, 2012).
There appear to be significant caveats even in those studies which fail to find an Environmental Kuznets
Curve. First and foremost is the presence of regional effects - it appears that a curve may only be present if an
empirical study is restricted to certain regions, particularly Asia (Culas, 2012). Model specification is also extremely
important, with most models utilizing a quadratic relationship, but some looking at a cubic relationship, between
13
wealth and degradation (Choumert et al, 2013). The regression analysis employed can also affect results, with cross-
section OLS models being less likely to find the expected inverted U shape, but panel models being more likely to
find it - time-invariant factors appear to strongly influence findings with respect to deforestation (Choumert et al,
2013).
Despite the mixed empirical evidence, the Environmental Kuznets Curve is still a widely regarded as an
explanation for environmental degradation with policy implications that have implicitly or explicitly driven applied
efforts to combat destruction of the environment. The 1987 Brundtland report 'Our Common Future', a publication
stemming from a United Nations Commission assembled to identify sustainable development pathways that take
into account environmental protection objectives, popularized the perception of sustainability as ensuring that
humans living presently do not undermine the ability of humans in the future to meet their needs, implicitly accepts
the poverty = degradation hypothesis emerging from Kuznets Curve literature (Chowdhury & Moran, 2012;
Choumert et al, 2013). The REDD framework that has been under construction at the United Nations since 2005,
REDD being an acronym for 'Reducing Emissions from Deforestation and Forest Degradation, also emphasizes
using redirected wealth to fight environmental degradation, effectively promoting paying for development that does
not degrade the environment in developing countries in order to avoid the predicted degradation as a society moves
towards the inflection point in the inverted U curve (Culas, 2012). Assertions that developed countries have simply
exported pollution to developing countries have not managed to derail these efforts (Kearsley & Riddel, 2009).
Unlike Tragedy of the Commons, at least with respect to the supposed overpopulation crisis, the Environmental
Kuznets Curve presents policy makers with viable options.
Even though the neo-Classical approach embodied by the Environmental Kuznets Curve can inform policy,
the sort of policies promoted remain constrained by the near-teleological argument of the Environmental Kuznets
Curve: given that degradation will increase until a high level of development is achieved, and development is
inevitable or that current levels require environmental degradation, degradation is inevitable until all populations are
fully developed. But given the findings by Rockstrom et al (2009), human civilization may not be able to sustain the
degradation needed to develop the entire world. This presents a paradox, which may rectified by identifying an
alternative theoretical approach offering alternative policy prescriptions.
14
A Missing Link?: Political Ecology and Environmental Degradation
Political ecology emerged in large part as a counter to the neo-Malthusian ideas expressed by Hardin and
others in the 1970s, but eventually included critiques of prevailing economic arguments then and after, including
those of the Environmental Kuznets Curve. Political ecology is widely considered to have as its origins in the work
of Piers Blaikie (1985) (Robbins, 2004; Peet & Watts, 2004; Simon, 2008; Walker, 2006). This work was intended
as a counter to then-dominant narratives explaining degradation of soils, particularly in sub-Saharan Africa and the
Himalayas, which emphasized the role of population, ineffective states, and insufficient access to markets in driving
the problem (Blaikie, 1985). However, detailed field work across the spectrum of developing country contexts
presented a complicated set of factors underpinning degradation. Both this work and his next key contribution, a
collaboration with Harold Brookfield (Blaikie and Brookfield,1987) presented an alternative perspective on
degradation - rooted in the idea that "the social relations of production under which land is used is a key and
pervasive element in the explanation of soil erosion" (Blaikie, 1985).
Blaikie and Brookfield essentially argue that land managers - any individual using the land, primarily for
the purposes of sustaining a livelihood - degrade not through ignorance, overpopulation, or lack of technology, but
because of the political economic system in which they are embedded restricts their production options, controls
their access to land, and systematically privileges certain groups in society in such a way that the majority of basic
land users have little to no voice in matters of policy that determine their ability to sustain their livelihood (Blaikie,
1985; Blaikie & Brookfield, 1987). Degradation of what lands they can access ensues, because they are artificially
forced to intensify use in the interest of basic economic survival, even when they are aware of the damage they are
causing (Blaikie & Brookfield, 1987).
This initial push to ascertain the causes of land degradation from the perspective of local-level individuals
was rapidly joined by other scholars, whose work over the next decade created the corpus of works now seen in
Political Ecology circles as foundational (Robbins, 2004; Peet & Watts, 2004). Hecht and Cockburn's "Fate of the
Forest" took a similar local-scale, almost anthropological approach to understand the roots of the destruction of the
Amazon, and determined that the social relations of production forced upon local people by the demands of Brazil's
colonial then military governments were heavily implicated in the Amazon's destruction (Hecht & Cockburn, 1990).
Similar findings emerged from Nancy Peluso's examination of deforestation and forest access in Indonesia,
15
"Rich Forests, Poor People", which saw similar patterns of colonization, military government, and the struggle for
access to livelihood resources as defining the land change patterns seen in Indonesia (Peluso, 1994). A similar
approach, with broadly similar findings, emerged from Roderick Neumann's work "Imposing Wilderness", which
examined the effects of establishing nature preserves in Africa, which also featured the effects of colonialism, but
paid special attention to the role of people's imagining of nature in places perceived as 'wild' by westerners, which
has often led to establishment of preserves intended to either exclude people, or force them into social relations of
production that match externally held images of how they are supposed to interact with landscapes (Neumann,
1998).
This use of local-level, highly contextualized methodological approaches has also generated results
demonstrating alternative relationships between local livelihoods and centers of power, with positive results. In post
civil-war El Salvador, forests have been observed to be resurgent, in large part because of increased rural
governance autonomy, land redistribution, and the emergence of collective institutions at the local level which have
pushed for more sustainable modes of management (Hecht, 2004). In Himalayan India, the successes of the Chipko
movement and granting of statehood - in federal India a key means of retaining local autonomy - of Uttaranchal
State, reconstructed state-local relationships to more closely connect governance with local needs, resulting in
improved local land management (Rangan, 2004).
The emphasis on local cases and the effects of the 'constructivist turn' in the social sciences have, however,
largely taken contemporary political ecology far from its roots as a policy-focused critical assessment of how land
users respond to the pressures of power in sustaining their lives. Many constructivist scholars have critiqued classic
works in Political Ecology as insufficiently addressing its 'political' component (Peet & Watts, 2004; Blaikie, 2011;
Robbins & Bishop, 2008, Walker, 2006). And the local-level focus inherent in studies inspired by anthropological
methods have made it difficult to more broadly generalize findings in specific studies, which have trended towards
being so interested in the production of local identities that broader contexts are ignored (Robbins & Bishop, 2008;
Simon, 2008). This path of intellectual development has led others to describe Political Ecology as insufficiently
attentive to its roots in critiquing policy (Walker, 2007; Blaikie, 2008; Blaikie, 2011). Additionally, Political
ecology is increasingly assuming a global view, and rather than focus on the developing world exclusively is
exporting lessons learned and focus on material impacts of the social aspects of production to the developed world
16
(Schroeder et al, 2006). 'Classic' patterns of environmental degradation and constrained livelihood options have been
observed in US Appalachia (Nesbitt & Weiner, 2001) and in the Exurban US West (Walker, 2003; Walker &
Fortmann, 2003). Recent debates have called for Political Ecology that directly engages policy makers and local
governance by explaining environmental degradation's roots in local resource users being unable to secure their
livelihoods in an increasingly globalized world.
One of the most significant challenges Political Ecology faces, however, in ensuring its relevance lies in
reconciling its epistemological viewpoint with that of more broadly understood bodies of theory, such as those that
have given rise to the Environmental Kuznets Curve and overpopulation. Although rooted in post-positivist thinking
- albeit with a heavy dose of critical theory derived from Marxist thought - Political Ecology tends to emphasize
individual cases and constructivism. This makes the creation of broadly applicable general theory quite difficult, as
noted by Robbins and Bishop (2008), and Political Ecology scholars appear common in their reluctance to make
global-level theory backed by universalist arguments.
This work attempts to address the aforementioned global arguments for environmental degradation on their
own terms: identifying omitted variables in statistical analysis of the determinants of environmental degradation.
Given the limited attention paid to local-level measures of livelihood in global datasets, it is necessary to look for an
indicator of livelihoods despite its probable imperfection. The World Bank reported proportion of rural residents
with access to electricity is a promising indicator, as it serves a measure of the level of basic services offered to what
are most likely among the poorest, least well-represented people. In terms of the functional connection between rural
electrification and environmental degradation, lack of access to electricity means needing alternative means of
securing fuel for heat and lighting. The deforestation literature indicates that a significant driver is need for fuel,
manure and charcoal, all of which can be obtained by forest clearance (Hecht, 2011; Pfaff et al, 2014; Tacconi,
2011).
This indicator is not without its problems. A logical connection exists between level of development and
rural access to electricity, and it appears widely accepted that electric access underpins development (Gomez &
Silveira, 2010; Matsika et al, 2013; Narula et al, 2012). Controlling for the effect of increased development on rural
electrification is necessary if rural electrification itself is to be an acceptable explanatory variable for environmental
degradation. However, even given the probable connection, there are logical reasons to believe that rural
17
electrification is not predominantly an indicator of a country's development. Income disparities within even a more
developed country may lead to markets failing to see a benefit in providing electricity to rural residents, and power
disparities may lead to political systems failing to ensure services are provided. Relative poverty in rural areas is
identified as a reason for continued lack of electric access, even in rapidly developing economies like Brazil, India,
and South Africa (Gomez & Silveira, 2010; Matsika et al, 2013; Narula et al, 2012). By contrast, rapidly developing
China has achieved nearly 100% rural electrification, but not according to a typical neo-Classical model where
markets expand as incomes rise: China has instead embarked on an explicit rural electrification policy backed by the
state, and achieved almost complete success (Bhattacharyya & Ohiare, 2012). Given these authors' arguments, it
seems reasonable to believe that while development does affect rural electrification, it does not fully explain it.
There is likely to be a reverse-causal relationship in cases, as improved rural electric access itself stimulates growth.
Political Ecology focuses on the artificial nature of resource scarcity forced on the most vulnerable by poor
systems of governance and the unequal distribution of power in a society. It claims that population is not necessarily
a negative driver of impacts on the environment - high populations have historically been sustained even on
vulnerable landscapes, because of the phenomenon of 'landesque capital'. This is a form of human-constructed
environmental degradation prevention systems that can be and often have been sustained for centuries because
sufficient labor was available for the job (Blaikie & Brookfield, 1987). Political Ecology has traditionally
emphasized that populations whose survival depends on their natural environment are often seen carefully managing
it to ensure long-term sustainability, and will often incorporate important knowledge about proper management into
long-standing cultural traditions (Zimmerer, 1997). Clearly there are situations where this fails - consider the cases
of Easter Island and the Maya as noted by Jared Diamond (2005), but even early Political Ecology noted cases
where populations had sustained the natural environment for millenia (Blaikie, 1985; Blaikie & Brookfield, 1987).
Political Ecology ultimately argues that most local land managers degrading vulnerable lands would
choose a different option if systems of political and economic power did not constrain them (Blaikie, 1985, Blaikie
& Brookfield, 1987; Robbins, 2004; Peet & Watts, 2004). Even if wealth increases as a consequence of
development, its concentration in the hands of the powerful interests who are typically better placed to take
advantage of new markets will leave poor residents in largely the same situation as they were before - unable to pay
for the accoutrements of development such as electrification, but now increasingly susceptible to global market
18
pressures which often force them to make painful decisions in order to survive - including destroying the natural
world they historically have relied upon for their livelihoods (Blaikie, 1985, Blaikie & Brookfield, 1987; Robbins,
2004; Peet & Watts, 2004; Peluso, 1994; Hecht & Cockburn, 1990).
This is where neo-classical theorist derived policy prescriptions that emphasize development as a solution
to environmental degradation fail: in a political-economic system riven by structural economic inequality, where
land users are bound in "relational webs shot through with power" (Rocheleau & Roth, 2007), development in and
of itself is no guarantee of mitigating environmental degradation. Directly meeting the basic needs of people
inhabiting landscapes - and here rural areas are emphasized due to their spatial proximity to the natural environment
- is a more reliable means of addressing environmental degradation.
Rural Electrification as a Proxy for Human-Needs Focused Rural Development
Drawing on a political ecology emphasis on power relations provides a connection between theory and this
data: given structural inequalities that privilege the interests of wealth accumulators over the livelihoods of typical
rural resource users - who are assumed to be lower income and more reliant on physical labor productivity to meet
basic needs - under capitalist political-economic conditions, increased national wealth will not automatically result
in improved access to electricity. Only if responsive governance mechanisms are sufficiently robust that rural
residents are able to successfully demand national investment in infrastructure development that benefits primarily
rural areas, will improved electrification rates be observed.
This theoretical prediction is supported by a basic fact of most rural electrification, so implicit in the
literature that it is not often directly stated: rural electricity provision is typically a result of mandates by government
entities - not private markets (Narula et al, 2012; Bhattacharyya & Ohiare, 2012; Gomez & Silveira, 2010; Oda &
Tsujita, 2011). The root of this fact resides in the cost of expanding electricity infrastructure to universally or even
partially bring rural communities onto the grid - costs of electrification rapidly increase with distance
(Bhattacharyya & Ohiare, 2012; Gomez & Silveira, 2010; Narula et al, 2012; Zahnd & Kimber, 2009), to the point
that for some more distant communities, grid extension may form the bulk of costs, surpassing even generation
costs. Given the well-established connection between rural life and increased poverty rates, it almost goes without
saying that rural communities are often incapable of bearing the cost of grid extension without significant
19
government intervention.
The next-best solution for communities is typically installation of some sort of decentralized electricity
generation system (Gomez & Silveira, 2010; Narula et al, 2012; Oda & Tsujita, 2011), but even this can be cost
prohibitive for a typical rural community. The rapid increase in rural electrification observed in rapidly developing
nations like Brazil, India, and China is not considered directly attributable to simple increases in per capita GDP,
rather it is a result of direct government intervention to ensure rural electric access (Assuncai et al, 2014;
Bhattacharyya & Ohiare, 2012; Gomez & Silveira, 2010; Oda & Tsujita, 2011) - something that reflects the western
experience with rural electrification as well, where grid connections are largely taken for granted even in most
remote locations.
This is not to say that there is no wealth effect on rural electrification, given that a wealthy household in a
rural area may pay for its own generator system, or that a wealthier country may be more willing to pay for universal
rural electric access. However, there is equally no guarantee that increased national wealth will inevitably result in
greater rural investment - if rural areas are politically marginalized, the state may have little incentive to pursue rural
electrification investments. Additionally, though a connection is observable between increased wealth and increased
rural electric access, a good number of scholars and development professionals would argue that rural electrification
is itself a prerequisite to widespread economic development, rather than the reverse (Bhattacharyya & Ohiare, 2012;
Gomez & Silveira, 2010; Matsika et al, 2013; Oda & Tsujita,2011 ).
Aside from being connected to broadly conceived human well-being and economic development, rural
electrification is a crucial component of environmental degradation. Even when lacking access to electricity, human
populations still require access to some form of energy to use in household cooking, heating, and lighting - likely
part of the reason it is an official UN Millenium Goal to provide universal electric access (Narula et al, 2012). And
so it can be readily observed virtually wherever rural residents have insufficient access to electricity that they are
forced to rely on environmental sources of fuel - all too often forest and agricultural sources, leading to deforestation
and insufficient natural organic fertilizer supply (Cai & Jiang, 2010; Matsika et al, 2013; Zahnd & Kimber, 2009). It
is important to note, however, that rural electrification can potentially itself be associated with environmental
degradation, For example, farmers with access to cheap electricity tend to be more likely to irrigate their fields,
which can contribute to soil fertility loss due to increased crop yields. In places where irrigation greatly improve
20
agricultural performance, farmers often have an incentive to cut down nearby forests in order to expand their
cropping areas. The process of electrification itself may devastate large areas of existing farm and forest land due to
the construction of dams. However, this thesis hypothesizes that the net direction of rural electrification effects on
environmental degradation is negative - that is, increased rural electric access has a net reducing effect on
degradation.
Which leads to the overarching hypothesis here derived from an application of political ecology insights to
empirical case study evidence from major developing countries: environmental degradation is significantly
connected to rates of rural electrification, which is at least as important as population and economic development in
explaining deforestation and soil fertility loss. And this hypothesis is directly linked to a particular argument: given
that rural electrification is largely a matter of government policy, a governance strategy for mitigating
environmental degradation is the promotion of rural electrification in developing regions where 100% electric
access is not guaranteed.
Methods
To assess this hypothesis, OLS multivariate regression was employed for a panel of 162 countries from the
period 2002-20121. All data originated from the World Bank (2015). In order to estimate the significance and
magnitude of the effect of rural populations having access to electricity on environmental degradation, the modeled
effects of this indicator were assessed against indicators connected to the more typically utilized approaches to
explaining environmental degradation as outlined above, specifically rural population.and national wealth. Rural
population is considered, as opposed to total national population, because individuals in rural areas are the ones who
must directly and materially engage in environmentally degrading activities in their physical location, and often by
necessity as part of pursuing their livelihoods. Those living in urban areas are separated from the site of degradation
by the intervening effects of distance and markets, and often have multiple sourcing options for material goods, so
they are not inherently tied to environmental degradation in one particular region, complicating meaningful
comparative country level analysis. The fraction of total population living in rural areas was used here as this
eliminates differences in gross population size between countries, and serves as an indication of the relative degree
1 These are the countries for which World Bank data is available for the relevant variables. See Appendix.
21
to which environmental degradation tied to direct population use of the environment is important in each country,
given that a high rural fraction of the population likely indicates increased rural reliance on local natural resources.
The basic model used for analysis was:
Degradation was operationalized using two dependent variables, deforestation rate and kilograms of
fertilizer applied per hectare of farmed land. The latter was a proxy for soil fertility loss, used under the assumption
that fertilizer is applied in accordance with underlying lack of fertility in soils. Deforestation was calculated by
differencing the percent of total forested land area in each country across two sequential years, the reference year -
2002 and 2012 - and the year immediately prior: 2001 and 2011. Taking t1-t2 - so 2001-2002 and 2011-2012 - a
rate of chance was obtained. This resulted in a measure of deforestation between the two years, with positive values
- occurring where t2<t1 - indicating a net loss of forest cover and negative values - occurring where t2>t1) indicating
a net gain in forest cover.
The primary independent variable of interest was the proportion of rural residents with access to electricity,
as outlined above. However, for several models, a modified form of rural electrification was utilized. This
alternative measure of rural electrification was the residual of an OLS regression where rural electrification rates
serves as the dependent variable, run on per capita GDP and rural population proportion as the independent
variables. The logic behind using a residual is that it removes movements in population growth and development
from variation in rural electrification (in other words, the residual encompasses variables other than those controlled
for that lead to changes in rural electrification). The standardized residuals for this model were calculated, and were
used as a robustness check in further analysis, as a control for the significant correlations between rural
electrification and environmental degradation
The competing hypotheses, rural population and economic development, are directly operationalized using
World Bank data for each country. Rural population is expressed by the proportion of the total national population
living in rural areas, while economic development is represented by the measurement of per capita GDP. However,
to use per capita GDP as a measure of wealth affected by the proposed Environmental Kuznets Curve, it was
necessary to employ a non-linear term in the basic regression to capture the predicted non-linear relationship
between degradation at high levels of wealth. A quadratic transformation of the basic per capita GDP value was
employed.
22
To account for omitted variable bias, several further control variables needed to be incorporated into the
model. These included: Land area in square kilometers, to control for the effect of country size and associated
governance difficulties; Arable land in hectares per person, which controls for the relative scarcity of farmlands, an
often cited factor in promoting deforestation, and; average annual precipitation in millimeters, which is an important
control of basic agricultural productivity and forest cover.
In addition, regional effects were assessed by incorporating simple dummy variables signifying whether a
particular observation (country) was located in a particular region. Six regions were created, along broadly
continental lines: North America, Europe, Asia, Africa, Latin America, and Oceania. North America served as the
standard baseline category against which others are assessed, except where the data is restricted to non-OECD
nations, where non-OECD Europe serves as the baseline, due to both nations in the North America region being
OECD members. It should be noted that North America consisted only of the United States and Canada, in order to
isolate these geographically and economically similar, very large countries, while Central America from Mexico to
Panama was grouped along with South America under 'Latin America'. Additionally, Oceania was coded to include
the continent of Australia along New Zealand and the many islands and archipelagos scattered across the Pacific.
To validate the model, both cross section and panel OLS regressions were employed for each dependent
variable of interest. The simple cross-section regressions utilized data from 2002 or 2012, ensuring no time-effects
complicated analysis within individual cross-sections. Sub-models were assessed for each dependent variable in
each year, allowing a comparison of results under different specifications. Sub-models investigated the baseline
model as described above and a semi-log form involving natural-log transformation of all independent variables -
but not the dependent variable, for which observations with negative and zero values would be dropped in a log
transformation. Each of these three sub-models was further evaluated both including all observations in the sample,
and with OECD nations excluded from the sample. This is done to mitigate the potential skew effect inherent in the
more wealthy, developed economies, which tend to have 100% electrification rates and little to no deforestation, as
well as more money to spend mitigating soil fertility loss without necessarily relying on fertilizers. OECD countries
represent a sub-class of observations with common characteristics that may obscure trends inherent only in
contemporary developing countries.
To ensure the model met additional OLS assumptions, HC3 Robust Standard Errors were utilized to
23
account for heteroskedasticity, VIF scores and pairwise correlation tables were generated and evaluated to account
for multicollinearity, and the tactic of employing different functional forms was utilized to account for model
specification. All metrics were standardized to ensure ease of evaluating relative magnitude of effects.
Time effects were accounted for in two ways: creating a panel by pooling the cross sections from each year,
and in applying first-differences transformation. Panel regressions followed the same pattern as the cross-section
regressions: sub-models were assessed and compared to account for OECD status - making non-OECD European
countries the new baseline category for the regional dummy variables due to all members of the North American
category being OECD members, eliminating this category entirely, natural-log transformations for independent
variables, and a transformation of the rural electrification indicator to compensate for collinearity with GDP and
rural population. All panels utilized GLS random effects, justified by the non-significance of a Hausman test
comparing performance of models using fixed and random effects, with potential fixed effects further controlled for
by use of the n-1 dummy variables, and near-significance of a Durbin-Watson test, indicating a degree of first
degree serial correlation. A binary dummy variable for time was also included to control for time-dependent effects.
Heteroskedastic-robust standard errors were employed in all models2.
2 See Appendix for further model robustness checks, including sample jackknifing
24
Table 1: 2002 cross sections for deforestation 2002 Deforest X-Section
I OECD=yes raw rurelec.
II OECD=yes log transform
III OECD=no raw rurelec.
IV OECD=no log transform
Rural Electric Access fraction
β coeff std.error p-stat
-.488 .498 .329
-.239 .391 .541
-.559 .529 .293
-.009 .556 .987
Constant -.297 -2.17 -.449 -3.10 N 162 161 128 127 R^2 .228 .205 .203 .181
a. *indicates p<.10, 90% significance; **indicates p<.05, 95% significance; ***indicates p<.01, 99% significance b. all values have been standardized or log transformed (models II and IV) c. dummy variables coded as 0/1 binaries, 0 indicating non-applicability d. in models I, II, III, regional dummies are relative to the United States and Canada e. in models IV, V, VI, regional dummies are relative to non-OECD Europe f. observations systematically excluded from all models include countries lacking data or where data is unreliable due to conflict during time period under examination g. observations excluded in non-OECD models include all countries who are members of the OECD h. in log-transformed models (II and IV) the Kuznets effect is omitted due to perfect collinearity
25
Table 2: 2012 cross sections for deforestation 2012 Deforest X-Section
.294
.436
.502 Constant -.114 -1.04 -.308 -1.97 N 162 161 128 127 R^2 .224 .207 .195 .180
26
.374
.357
.294 Constant .291 -1.11 -.006 -1.54 N 324 322 256 254 R^2 .221 .198 .191 .166 chi^2 62.48 62.78 45.25 45.11
27
Table 4: 2002 cross sections for fertilizer use 2002 Fertilizer X-Section
N/I
-.681 1.16 .560
Constant -.201 2.80 -.245 3.41 N 133 132 99 98 R^2 .176 .313 .281 .350
a. *indicates p<.10, 90% significance; **indicates p<.05, 95% significance; ***indicates p<.01, 99% significance b. all values have been standardized or log transformed (models II and IV) c. dummy variables coded as 0/1 binaries, 0 indicating non-applicability d. in models I, II, III, regional dummies are relative to the United States and Canada e. in models IV, V, VI, regional dummies are relative to non-OECD Europe f. observations systematically excluded from all models include countries lacking data or where data is unreliable due to conflict during time period under examination g. observations excluded in non-OECD models include all countries who are members of the OECD
28
Table 5 2012 cross sections for fertilizer use 2012 Fertilizer X-Section
-.071 .678 .916
Constant -.820 4.84 .619 5.15 N 141 140 107 106 R^2 .232 .301 .930 .364
a. *indicates p<.10, 90% significance; **indicates p<.05, 95% significance; ***indicates p<.01, 99% significance b. all values have been standardized or log transformed (models II and IV) c. dummy variables coded as 0/1 binaries, 0 indicating non-applicability d. in models I, II, III, regional dummies are relative to the United States and Canada e. in models IV, V, VI, regional dummies are relative to non-OECD Europe f. observations systematically excluded from all models include countries lacking data or where data is unreliable due to conflict during time period under examination g. observations excluded in non-OECD models include all countries who are members of the OECD
29
-2.92 .276 .291
Constant -.448 4.03 .230 4.60 N 274 272 206 204 R^2 .180 .286 .399 .323 Wald chi^2 30.67 38.31 100.93 26.61
30
Results indicate robustness to the various model specifications applied, however, the independent variable
having the predominant impact on the dependent variable of interest differs depending on the dependent variable's
identity, that is, whether it is deforestation or fertilizer application that is being explained.
The hypothesis that rural electrification has a significant and negative impact on deforestation rates -
negative here in the mathematical sense of its increase being associated with reducing deforestation - is borne out by
the results of the cross section and panel models. In the individual year cross-sections for 2002 and 2012, rural
electrification remains significant across all model specifications, save for log-transformed models in 2002. In these
cross-section models, the other consistently significant variables are precipitation levels, which are positively
associated with deforestation, and rural population fraction of general population, which is also positively associated
with deforestation in some models. In the sample restricted (non-OECD) models, a country being in Asia, Latin
America, or Africa is significantly and positively associated with observed deforestation compared to non-OECD
European countries. However, in the panel models, rural population ceases to remain a significant predictor of
deforestation (the indicate lacks significance in all but one model), with precipitation and location in Asia or Latin
America remaining significantly and positively associated with deforestation.
Given the significance of virtually every model variation addressing deforestation, it becomes necessary to
argue for which should be considered the 'true' model. The most likely 'true' model bearing the most significant
impact for future policy options should be considered to be the panel model that excludes OECD countries from the
sample. This is due to the unique circumstances facing less-developed countries, which are structurally encouraged
by the global market system to emphasize exploitation of local natural resources in pursuit of national comparative
advantage. In addition, practically speaking, less-developed countries are also unique relative to wealthier OECD
countries in that they typically have not achieved full electrification within their jurisdictions. In 2002, for example,
the average rural electrification rate in OECD countries was over 99%, compared to just under 53% in non-OECD
countries. Non-OECD countries had only, by 2012, reached an average rural electrification rate of just over 61%.
This indicates it is in the less wealthy parts of the world where a rural electrification strategy to mitigate
deforestation can have a potentially significant impact.
Restricting the sample to the 128 non-OECD countries for which there is reliable data, a .277 standard
deviation reduction in deforestation rates is observed for a one standard deviation increase in rural electrification
31
rates. Given that the average non-OECD deforestation rate is .087% of total national land area per year as of 2012,
with a standard deviation of .275, and given that one standard deviation in terms of rural electric access in non-
OECD countries is roughly the difference between average rural electrification rates around the world and full
electrification - the norm in OECD countries - these results indicate that successfully achieving full electrification in
rural areas in the non-OECD world can be predicted to reduce average deforestation rates by .079% of average total
national land area per year, a 90% reduction in the deforestation rate observed in 2012 in the non-OECD world.
However, it must be noted that there was a .011% reduction in average total national land area per year lost
to deforestation from 2002 to 2012 in those countries experiencing deforestation rates greater than 0, concurrent
with a 7% increase in rural electrification rates in the non-OECD world countries with deforestation rates greater
than 0 during the same decade. The results above would predict that this approximately .184 standard deviation
improvement in rural electrification rates would result in a .051 standard deviation reduction in deforestation, which
translates to a predicted .013% of land area per year reduction in the affected countries. This discrepancy indicates
that caution should be exercised when applying the model results to the real world.
In terms of its effect on fertilizer application, assuming this indicator is a sufficient proxy for degradation in
terms of soil fertility, rural electrification rates appear to have no reliable statistical impact, regardless of model
specification. Only in 2012 cross sectional models IV and VI, sample restricted to non-OECD countries, does rural
electrification show as significantly associated with fertilizer application, and there as a positive predictor. This
fleeting effect disappears in the panel data, and given the suspiciously high R-squared of .93 in these models, there
appears to be something external driving the association between 2012 rural electrification and fertilizer application.
In fact, the most reliable predictor of fertilizer application is the control of arable land per person, with a
decidedly negative impact on fertilizer application rates. Second to it in terms of reliable significance across the
cross-section and panel models is the rural population fraction and Kuznets curve effects, which given the
collinearity between GDP per capita and its square term should be interpreted as meaning there is a significant
connection between fertilizer application rates and GDP, with a quadratic relationship occurring at higher levels of
GDP per capita.
Of particular interest here is that both rural population fraction and GDP are negatively associated with
fertilizer application - with the GDP effect reversing as wealth increases, representing an inverse Kuznets curve.
32
This indicates that countries with greater fractions of the population living in rural areas see less incidence of
inorganic fertilizer application, and that increases in wealth contribute to decreased fertilizer use, up to a point, at
which increases in GDP begin to exert a positive influence on fertilizer application. It does appear that the Kuznets
effect only exists in non-OECD countries, perhaps indicating that once a country becomes sufficiently wealthy that
fertilizer application is no longer a function of wealth.
It is important to note that, in accordance with the methods laid out above, additional models utilizing first-
difference regressions were employed exactly as in the cross sections and panels above. However, tables have been
omitted as in no case was any variable in any model statistically significant at even a 90% level. This may mean
that, despite the results reported in full here, time-invariant factors are strongly significant and exhibit collinearity
with the indicators used in this work.
There are other factors which may be influencing these results. With particular respect to fertilizer
application, this indicator may simply be an insufficient proxy for degradation in soil fertility. Unlike deforestation,
which can be fairly readily observed using aerial and satellite remote sensing technologies, soil fertility requires
intensive sampling and analysis. And also unlike deforestation, which involves a fairly clear physical transformation
- trees to no trees - fertilizer application does not necessarily involve a change from no fertility to fertility, and may
occur out of a desire by a land user to enhance existing fertility rather than replace fertility which has been lost. In
addition, unlike in the deforestation case, there is no direct substitution effect possible - electricity itself cannot
physically impact soil fertility, but it can replace heating, cooking, and lighting which can be provided by either
electric appliances or direct use of biomass from trees.
Finally, the use of a country-level unit of analysis is not ideal for land change variables given the spatial
heterogeneity within many, if not most, countries. In many countries, reforestation or managed plantations which
increase forest area in some jurisdictions offsets deforestation of native forests in other areas, so that while overall
deforestation rates are suppressed in a national metric, serious deforestation is actually occurring in ecologically
significant areas.
33
Discussion
In terms of the specific hypothesis put forth above, that rural electrification rates have a significant impact
on deforestation rates, the above analysis indicates that a strong argument can be made that rural electrification does
indeed offer a means of mitigating deforestation, particularly in developing countries who have not adequately
electrified their rural districts.
This accords with the experience of several countries whose recent emphasis on rural electrification has
been observed to exhibit positive impacts on rural use of forest lands as sources of fuel. China has publicly pursued
a policy of 100% rural electrification, achieving its goal by the 2010s, and has observed a marked decrease in rural
people's need for forest fuels (Bhattacharyya & Ohiare, 2012; Cai & Jiang, 2012). India has likewise pursued rural
electrification, albeit less fully, (Narula et al, 2012; Oda & Tsujita, 2011), and has itself maintained negative
deforestation rates throughout the 2000s to the present. In Nepal, a small Himalayan state which has seen a dramatic
improvement in rural electrification, the material benefit of reduced reliance on forests for fuel have been
accompanied by improvements in health and education (Zahnd & Kimber, 2009). Studies of Brazil's rural
electrification efforts and simultaneous reductions in deforestation have additionally posited that rural electrification
is strongly responsible for improved economic conditions, sparking a virtuous cycle of increased wealth, which
further enabled electrification. (Assuncai et al, 2014; Gomez & Silveira, 2010)
This analysis undermines the Malthusian arguments that tie environmental degradation to population
pressures as well as Development arguments which claim a connection between development and environmental
degradation, at least with respect to deforestation. There does indeed appear to be a signal, albeit faint, associating
rural populations with deforestation. However, in the panel models above this signal is only statistically significant
when OECD countries, which tend to be fairly well-developed and urbanized, are included in the sample. This may
indicate that a few highly-developed countries are driving the observed effect. In no case does wealth appear to
have a significant impact on deforestation rates, a surprising result but one that remains robust even when the
potential collinearity between rural electrification and GDP per capita is removed.
Simply examining the raw data, one can see examples of the opposite effect as that argued by the
Malthusian Tragedy of the Commons narrative: the Phillippines, Macedonia, Armenia, and Sri Lanka all
experienced decreases in deforestation rates despite only slight improvements in wealth and significant increases in
34
their rural populations, but while simultaneously improving rural electric access between 2002 and 2012. As
mentioned above, China and India have also sought to improve rural electric access, and are observing increasing
domestic forest coverage despite being home to approximately 1/3 of the global population. Brazil, home to much of
the Amazon, and a focal point in global efforts to reduce deforestation, has seen its rate of forest loss decline
dramatically from the 1990s, when predictions of the Amazon's complete destruction were repeatedly made (Hecht,
20). Path dependency may play a role here, as there are diminishing returns associated with exploiting a given forest,
so that once a forest is reduced in size, there is less physical material to cut in a given future year.However,
significant tracts of Brazilian forest remain and its continued positive rates of deforestation indicate that potential
supply has not been exhausted, so the path dependency may not play a significant role as yet. In all these cases,
improving the access to what is now broadly considered a basic human need has correlated with a reduction in forest
loss, as predicted by the model and significant portions of the literature. This demonstrates the capability of political
ecology to inform policy analysis, and also the utility of quantitative measures to improve results of political
ecology-oriented works.
It therefore seems reasonable to argue that policy efforts to mitigate deforestation should consider investing
time and effort in to further promoting rural electrification efforts. Given that approximately 30% of rural
populations, the people who tend to be proximate to and reliant upon forest resources, lack access to electricity - and
in all likelihood, many more lack reliable electric access - there is a great deal of potential for mitigating
deforestation via electrification of rural areas.
The results do not support the hypothesis that rural electrification is associated with fertilizer application.
What evidence of association that does exist is suspect given the relevant models' apparent over-fitting problem, and
even if legitimate indicate the reverse effect from that predicted - that is, rural electrification is in 2012 associated
with increased fertilizer use. This could well be connected to observations that rural electrification can enable
increased irrigated agriculture, which may require fertilizer investments to bring to full productive fruition. In
addition, soil and electricity are not directly substitutable for one another, while forests and electricity are, to a
degree.
The connection between arable land availability and fertilizer use appears reasonable on its face Increased
availability of arable land likely reduces the need for inorganic fertilizers, as supply of food is sufficient to meet the
35
needs of a country's people. This accords with Malthusian arguments to a degree, but not in any compelling way:
neither competing theoretical approach motivating this study would suggest that if there is no shortage of food - at
least in some context - farmers would still apply fertilizer or, frankly, degrade their soils in the first place. However,
the association between increased rural population and decreased fertilizer use is quite antithetical to a strictly
Malthusian view. One possibility here is that larger rural populations ensure a steady supply of labor for agricultural
works, which can substitute for increased fertilizer inputs and mitigate soil degradation due to the creation of
"landesque capital" - an observation stemming from classic political ecology (Blaikie, 1985; Blaikie & Brookfield,
1987, Peet & Watts, 2004).
However, the inverse Kuznets curve, which appears to be significant for non-OECD countries, does offer
an interesting result, one not easily predicted using typical Kuznets arguments. There appears to be a tendency for
increased wealth to militate against fertilizer application, at least until a certain degree of national wealth is reached.
Thus, economic growth does not seem to necessitate environmental degradation, at least of soils. The change in sign
of the GDP per capita and fertilizer use relationship may in fact be better predicted by referring to some of the
classic literature in political ecology. Zimmerer's work in the Andes indicates that class strongly impacts demand for
types of food, with wealthy people often purchasing imported food, which would mitigate the need for local
agricultural productivity (Zimmerer, 1997). However, as a country becomes more integrated in the global economic
system, ensuring continued wealth generation will tend to subject local agricultural lands to global market discipline,
forcing exploitation of soils in order to produce surplus for export.
Policy Implications and Conclusion
This work largely confirms a hypothesis regarding systems with human and natural components:
complexity is guaranteed. Single explanations for any form of environmental degradation are unlikely to be
satisfactory, regardless of the theoretical perspective employed.
However, this work has demonstrated that insights derived from political ecology are at least as relevant for
environmental degradation as those emerging from neo-classical economics and neo-malthusian population
concerns. While environmental degradation may be complex, a key driver is the political-economic status and local-
governance involvement of those living proximate to the natural world: residents of rural areas. Their relationship
36
with their environment is not one of pure exploitation, rather it is contingent on satisfying basic needs of life. Simply
controlling rural population in terms of its size, or pursuing national economic development without ensuring that
benefits accrue to all members of the population - these are insufficient policy prescriptions for mitigating
environmental destruction. It is necessary to understand what specific factors cause local-level over-utilization of the
proximate natural world, and then seek to address them. The causes and remedies will not be the same from place to
place, or across time. This work offers further support to a view that governance which directly addresses local
material needs has a role to play in mitigating environmental degradation. Meeting one of these needs, energy, is
associated with mitigating deforestation, and recent evidence of successful efforts by China, India, and Brazil in
particular to accomplish this is very likely connected to reduction in deforestation rates in each country. Although
direct evidence for policy efforts which can mitigate soil degradation are lacking in this work, the same logic ought
to hold: if local populations are observed to be increasing agricultural output by exhausting soils, understanding the
material connection between this behavior and the results pursued by land users will shed light on policy
prescriptions which may mitigate the consequences. And although this cannot be easily assessed quantitatively, it
seems reasonable to extend this logic to argue that successful policy interventions which mitigate degradation while
helping people meet their needs are likely to have a strong legitimizing effect on further policy efforts in the area.
This can potentially offer a path forward in situations where governance has been previously characterized by local
resistance to policy, such as in cases where environmental preserves have been created, yet are unsuccessful in their
objective.
Deforestation and soil fertility loss have material effects that manifest across spatial levels. It is now
broadly accepted that human impacts on the biosphere constitute a threat to its long-term survival. Innovative policy
is necessary to arrest and reverse these impacts before they further undermine the biosphere's capacity to support
human civilization. However, the roots of these impacts are highly complex and vary in nature from place to place.
A net effect of this complexity and variability is to render them less than amenable to one-size-fits-all policy
prescriptions. Nuanced understanding of human-environmental impacts are needed, allowing for identification of
general principles of mitigation, aiding development of contextualized policy.
37
Almudi, Tiago, Berkes, Fikret. 2010. Barriers to empowerment: fighting eviction for conservation in a southern Brazilian protected area. Local Environment 15(3): 217-232 Alper, Joe. 1991. Environmentalists: ban the (population) bomb; after years of silence on the issue, conservationists urge the United States to lead the fight against population growth. Science 252: 1247 Angelsen, Arild. 2009. Policies for reduced deforestation and their impact on agricultural production. Proceedings of the National Academies of Sciences 107(46): 19639-19644 Assuncai, Juliano, Lipscomb, Molly, Mobarak, Ahmed Mushfiq, Dimitri Szerman. 2014. Electrification, Agricultural Productivity, and Deforestation in Brazil. Working Paper. http://faculty.som.yale.edu/mushfiqmobarak/papers/brazil_elec_agri.pdf Bhattacharyya, Subhes C., and Ohiare, Sanusi. 2012. The Chinese electricity access model for rural electrification: Approach, experience and lessons for others. Energy Policy 49: 676-687 Benjaminson, Tor A., Aune, Jens B., Sidibe, Daouda. 2010. A critical political ecology of cotton and soil fertility in Mali. Geoforum 41: 647-656 Blaikie, Piers. 1985. The Political Economy of Soil Erosion in Developing Countries. Routledge Blaikie, Piers; Brookfield, Harold. 1987. Land Degradation and Society. Routledge Blaikie, Piers. 2008. Epilogue: Towards a future for political ecology that works. Geoforum 39:765-772 Blaikie, Piers 2011. Should some political ecology be useful? The Inaugural Lecture for the Cultural and Political Ecology Specialty Group, Annual Meeting of the Association of American Geographers, April 2010. Geoforum 43 (231-239) Boucekkine, Raouf, Pommeret, Aude, Prieur, Fabien. 2012. Technological vs. Ecological Switch and the Environmental Kuznets Curve. American Journal of Agricultural Economics 95(2): 252-260 Brown, Sandra, Zarin, Daniel. 2013.What Does Zero Deforestation Mean? Science 342: 805-807 United Nations. 1987. Report of the World Commission on Environment and Development: Our Common Future. Burgess, Robin, Hansen, Matthew, Olken, Benjamin A., Potapov, Peter, Sieber, Stefanie .2012. The Political Economy of Deforestation in the Tropics. Quarterly Journal of Economics 1707-1753 Cai, Jing, and Jiang, Zhigang. 2010. Energy consumption patterns by local residents in four nature reserves in the subtropical broadleaved forest zone of China. Renewable and Sustainable Energy Reviews 14: 828-834 Celentano, Danielle, Sills, Erin, Sales, Marcio, Verissimo, Adalberto. 2011. Welfare Outcomes and the Advance of the Deforestation Frontier in the Brazilian Amazon. World Development 40(4): 850-864 Choumert, Johanna, Motel, Pascale Combes, Dakpo, Herve K. 2013. Is the Environmental Kuznets Curve for deforestation a threatened theory? A meta-analysis of the literature. Ecological Economics 90: 19-28 Chowdhury, Rinku Roy, Moran, Emilio F. 2012. Turning the curve: A critical review of Kuznets approaches.
38
Applied Geography 32: 3-11 Culas, Richard J. 2012. REDD and forest transition: Tunneling through the environmental Kuznets curve. Ecological Economics 79: 44-51 Diamond, Jared. 2005. Collapse: How Societies Choose to Fail or Succeed. Penguin Books Erlich, Paul. 1970, The Population Bomb. Ballantine Books Emadodin, Iraj, Narita, Daiju, Rudolf Bork, Hans. 2012. Soil degradation and agricultural sustainability: an overview from Iran. Environmental Development Sustainability 14:611-625 Geist, Helmut J., Lambin, Eric F. 2004. Dynamic Causal Patterns of Desertification. Bioscience 54(9): 817-829 Gomez, Maria F. and Silveira, Semida. 2010. Rural electrification of the Brazilian Amazon - Achievements and lessons. Energy Policy 38: 6251-6260 Goudie, Andrew. 2006. The Human Impact on the Natural Environment. Wiley and Sons Haileslassi, Amare, Priess, Joerg, Veldkamp, Edzo, Teketay, Demil, Lesschen, Jan Peter. 2005. Assessment of soil nutrient depletion and its spatial variability on smallholders’ mixed farming systems in Ethiopia using partial versus full nutrient balances. Agriculture, Ecosystems, and Environment 108: 1-16 Hardin, Garrett. 1968. The Tragedy of the Commons. Science 162: 1243-1248 Hardin, Garrett. 1971. Nobody Ever Dies of Overpopulation. Science. 171: 527 Harris, Nancy L., Brown, Sandra, Hagen, Stephen C., Saatchi, Sassan S., Petrova, Silvia, Salas, William, Hansen, Matthew C., Potapov, Peter V., Lotsch, Alexander.2012. Baseline Map of Carbon Emissions from Deforestation in Tropical Regions. Science 336: 1573-1576 Hecht, Susanna; Cockburn, Alexander. 1989. Fate of the Forest: D

the impact of rural electrification on deforestation and

Documents