Environmental Engineering Reference
In-Depth Information
hazardous facilities near low-income neighborhoods, but rather from market dynamics in
which low-income people are drawn to these locations by lower property values.
22
This
logic would have to be stretched, however, to explain correlations between hazards and
race that persist even after controlling for income.
23
The second hypothesis is that societies with wider power disparities tend to have more
environmental degradation. That is, power disparities a
ect the magnitude of pollution and
resource depletion, as well as their distributional incidence. This hypothesis is based on the
assumption that there is a positive correlation between net bene
ff
π
i
), an
assumption that seems reasonable in that both are likely to be correlated with wealth.
24
Empirical studies of this second hypothesis remain scarce, but support for it can be
drawn from several recent cross-country studies that have investigated the impact of polit-
ical variables on environmental performance. These studies were sparked by research sug-
gesting that environmental degradation - or at least some types of it - is concave in
income, and that high-income countries have passed a turning point beyond which further
income gains are associated with environmental improvements. In an early example, the
Wo r ld Bank (1992, p. 41) reported an inverted U-shaped relationship of this type between
atmospheric sulfur dioxide and per capita income.
This relationship has been dubbed the 'environmental Kuznets curve' (EKC), due to its
likeness to the original Kuznets curve depicting a relationship between income inequality
and per capita income (see Figure 7.2). As in the case of its namesake, the EKC has some-
times been taken to imply that problems that accompany economic growth will be
resolved, more or less automatically, by growth itself. Thus Beckerman (1992) writes, 'in
the end the best - and probably the only - way to attain a decent environment in most
countries is to become rich'.
Notwithstanding the allusion to Kuznets's earlier work on income inequality, few
studies of the EKC have examined the relationship between environmental quality and
inequalities of income, wealth, or power. Yet combining the two inverted-U curves (and
assuming that the income levels at which they reach their turning points are roughly com-
parable), we can infer a positive correlation between environmental degradation and
income inequality, as depicted in Figure 7.2. Such a correlation does not prove causation,
of course, but it is intriguing. And because the curves themselves (when found to exist at
all) are statistical relationships, rather than iron laws, there are many outliers - for
example, countries with relatively low income inequality and low per capita income -
making it possible to attempt to distinguish econometrically between the environmental
impacts of income and inequality.
To investigate the impacts of power disparities on environmental quality, Torras and
Boyce (1998) analyzed cross-country variations in air pollution (ambient concentrations
of sulfur dioxide, smoke and heavy particles), water pollution (concentrations of dis-
solved oxygen and fecal coliform), and the percentages of the population with access to
safe water and sanitation facilities. In addition to per capita income and the Gini ratio of
income distribution, their analysis included two other explanatory variables - adult liter-
acy and an index of political rights and civil liberties - regarded as relevant to the
distribution of power. In low-income countries, the estimated coe
fi
ts (
b
i
) and power (
cients on the rights
and literacy variables had the expected signs in all cases: higher literacy and greater rights
were associated with better environmental quality. These coe
cients were statistically
signi
fi
cant in the majority of cases. Controlling for these other variables, the estimated
