Urbanization, Democracy, Bureaucratic Quality, and Environmental Degradation Abstract The study examines the relationship between urbanization and environment degradation while controlling for political environment in 38 African countries over the period 1970-2011. Using panel cointegration and causality analyses; the findings of the study show that urbanization, environmental degradation and political economy variables (democracy and bureaucratic quality) are cointegrated. Second, democracy and bureaucratic quality are effective in reducing environmental degradation in the long-run. Third, there are positive bi-directional relationships between CO2 emissions and Affluence and CO2 emissions and population as shown by panel vector autoregressive and impulse response functions. However, a negative unidirectional relationship runs from CO2 to bureaucratic quality. These results suggest that political economy variables (democracy and bureaucratic quality) are important in explaining the relationship between urbanization and environmental degradation. 1
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Urbanization, Democracy, Bureaucratic Quality, and Environmental Degradation
Abstract
The study examines the relationship between urbanization and environment degradation while
controlling for political environment in 38 African countries over the period 1970-2011. Using
panel cointegration and causality analyses; the findings of the study show that urbanization,
environmental degradation and political economy variables (democracy and bureaucratic quality)
are cointegrated. Second, democracy and bureaucratic quality are effective in reducing
environmental degradation in the long-run. Third, there are positive bi-directional relationships
between CO2 emissions and Affluence and CO2 emissions and population as shown by panel
vector autoregressive and impulse response functions. However, a negative unidirectional
relationship runs from CO2 to bureaucratic quality. These results suggest that political economy
variables (democracy and bureaucratic quality) are important in explaining the relationship
between urbanization and environmental degradation.
Madagascar, Morocco, Mozambique, South Africa, Swaziland, Tunisia, Zambia documented
averages below the full sample’s average (15.553). Ghana recorded the highest affluence
(growth) value (8.931) and Mali the least (5.459). The sample had an annual affluence (growth)
average of 6.623. Algeria, Botswana, Cameroon, Cote D’Ivoire, Niger, South Africa, Togo,
Tunisia and Zimbabwe, however, had annual averages greater than 7.0 over the entire period
(1970-2011). Equally, Ghana recorded highest on technology (4.052) and Comoros the least
(2.635). About half of the countries in the study recorded an annual average of technology above
3. Urbanization ranges from a low of 2.062 (Burundi) to a high of 4.158 (Ghana). Apart from
Burundi, Burkina Faso, Liberia, Mali, Mauritania, Rwanda, and Seychelles, each recorded
2 Available at: http://www.systemicpeace.org/inscrdata.html.17
Urbanization values less than 3. The sample had an annual average urbanization of 3.374. South
Africa experienced the highest polity (7.0) with negative polity values recorded for about half of
the sample. Similarly, annual averages for democracy range from a high of 7 (South Africa) to a
low -7.049 (Zambia). More than half of the countries in the sample had negative averages for
democracy. Cameroon had the highest bureaucratic quality (0.750) and Morocco the least
(0.000) from 1985 to 2011. The average bureaucratic quality was 0.366 with Botswana,
Cameroon, Gabon, Ghana, Guinea-Bissau, Liberia, Togo and Tunisia documenting averages
more than 5.0.
[Table 1 here]
Correlations are presented in Table 2. CO2 is highly correlated with Affluence (0.912),
followed by Urbanization (0.700), Technology (0.632) and Bureaucratic quality (0.499).
However, CO2 has low correlations with Polity2 (0.028), Democracy (0.028) and Population
(0.171). This indicates a plausible association among the variables in the study.
[Table 2 here]
3.6 Empirical results
3.6.1 Panel unit root results
The unit root tests depicted in both levels and first differences are depicted in Table 3. The null
hypothesis of existence of a unit root cannot be rejected for LLC (in all instances) and IPS (all
but Population, Urbanization and Democracy). However, Hadri rejects the null hypothesis of
existence of unit root for all the series at 1% level for the series in level form. Under the first
difference condition, all the three tests (LLC, IPS and Hadri) reject the null hypothesis at the 1%
18
level of significance. As a result, there is strong evidence that all the series are integrated with
order one.
[Table 3 here]
3.6.2 Panel cointegration results
The relationships between the variables are investigated using a Pedroni cointegration technique.
Each cointegration test is distinguished by the political economy variables (Polity2 [1], demo [2]
and bur [3]) (Table 4). Majority of the test provide sufficient evidence of cointegration in the
panel data by rejecting the null hypothesis of no cointegration. Specifically, 6 out of 7 tests reject
the null hypothesis in [1] and [3] and all in [2].
[Table 4 here]
Table 5 reports DOLS estimates. Similarly, each DOLS estimates is distinguished by the
political economy variables (Polity2 [1], demo [2] and bur [3]). The coefficients of Affluence are
significant in all the three equations ([1], [2] and [3]). These results substantiate the short run
findings of Poumanyvong and Kaneko (2010), Sharma (2011), Leitao and Shahbaz (2013) and
Sadorsky (2014b). Precisely, affluence coefficient ranges between -12% and 2%. Consequently,
the negative coefficient of affluence (see [3]) is in line with Marcotullio and Lee’s (2003)
reasoning that negative effects of environmental degradation could be realized by appropriate
environmental regulations that are energy efficient. This suggests that the bureaucratic quality is
one of the most important channels for reducing environmental degradation in the long-run in
Africa. Whereas population coefficient is negative throughout, those of technology and
urbanization are mixed. The lack of access to energy by many countries in the region might
19
explain why the urbanization estimates are not robust. Also, the International Energy Agency
(IEA) report (2014) documents that more than 620 million people (two-thirds) in SSA remain
without access to electricity. The negative coefficients of democracy and bureaucratic quality
imply that democracy and bureaucratic quality tend to reduce environmental degradation in the
long-run.
[Table 5 here]
Afterwards, the causal link between variables is investigated in PVAR framework using
Granger causality test. Results are summarized in Table 6. The most striking results are; bi-
directional relationships between population and CO2 emissions, Affluence and CO2 emissions
and finally unidirectional causality from CO2 emissions to bureaucratic quality. The next step
involves assessing the strength and the impact of the causality using impulse response functions
(IRFs).
[Table 6 here]
Our results from the IRFs indicate that bidirectional relationships between population and CO2
emissions, Affluence and CO2 emissions are positive whereas the unidirectional causality from
CO2 emissions to bureaucratic quality after 10 years of initial shock [Figures 1-3]. Also,
controlling for democracy unravels a unidirectional causality from CO2 to urbanization at 1%
level of significance and a weak unidirectional causality from Democracy to CO2. Such results
lead us to investigate the importance of shocks (impulse) on one variable in explaining changes
in the other using variance decompositions (response). The 10-year horizon of Affluence remains
the one of the highest contributor to CO2 (24.91%), confirming a moderate causality from
energy and Affluence to CO2 in the long run. Additionally, the variance decomposition (VDs)
20
shows that CO2 explains approximately 54.25% of the variations in bureaucratic quality while
bureaucratic quality explains 1.41% of the variation in CO2 in the long run [Table 7 here]
This confirms very strong unidirectional causality from CO2 to bureaucratic quality. This means
environmental degradation give rise to effective policies in Africa.
4.0 Conclusion
The study examines the relationship between urbanization and environment degradation while
controlling for political environment in 38 African countries over the period 1970-2011. The
findings of the study show that environmental degradation, population, affluence, technology,
urbanization and political economy variables (democracy and bureaucratic quality) are
cointegrated. Second, democracy and bureaucratic quality are effective in reducing
environmental degradation in the long-run. Third, there are positive bi-directional relationships
between CO2 emissions and Affluence and CO2 and population. However, a negative
unidirectional relationship runs from CO2 to bureaucratic quality.
The findings provide three main policy implications. First, that urbanization as an
inevitable process has a significant impact on carbon emissions and therefore has to be managed.
With SSA’s urbanization rate at 40% and expected to increase to 60% by 2050 and population to
triple over the period (Freire et al. 2014), Africa does not have a choice but to put in the
necessary steps to reduce the dangers of environmental degradation. This is critical in light of the
fact that Africa’s economy is highly dependent on the primary sector and its abundant natural
resources, is particularly vulnerable to the effects of climate change. The big question for policy
makers is how to harness the positive effects of urbanization in terms of education, health,
manufacturing activity, and infrastructural development) while reducing its negative tendencies.
21
It is worth noting that with the high population growth and urbanization, the SSA region
recorded the lowest human development index (HDI) of 0.502 in 2013 (United Nations
Development Programme [UNDP] 2014).
Second, if indeed, urbanization is not just a subplot but the main policy narrative for SSA
(Freire et al. 2014), then it is indicative that the future of the region is dependent on not just
government policy but the capacity to implement the desired framework necessary for
sustainable development. Even as the countries have embarked on massive economic reforms
they must deepen the political reforms already underway and more importantly improve the
public administrative system to ensure the proper functioning of the bureaucracy to ensure
implementation success. This is consistent with the view that rapid urban growth is likely to be a
greater challenge to states that have low functional capacity because they will be unable to
provide basic services to a burgeoning population (Barnett 2003). A similar argument is made by
Parnell and Walawege (2011) who claim that environmental change is more likely to have
significant consequences for growing African cities with weak management capacity but fast
growing populations. The UN Habitat (2009) report also notes that weak urban management
structures and under capacitated local and regional states set up dynamic global environment
change urbanization dynamics across the developing world but more severe in Africa.
Third, is the problem of fossil fuels and traditional sources of energy other than
electricity which form the bulk of energy supply for many SSA and causes damage to the
environment. The SSA countries must therefore be proactive and invest more in less intensive
energy sources and improve electricity supply to reduce the emission of gases. The IEA (2014)
report notes that more than 620 million people live without electricity and over 730 million
22
people use hazardous, inefficient forms of cooking. The report further notes that SSA has 13% of
the world population, but only 4% of its energy demand. What is at the heart of the energy mix is
bioenergy use (mainly fuel wood and charcoal), which outweighs demand for all other forms of
energy combined. Four out of five people in sub-Saharan Africa rely on the traditional use of
solid biomass, mainly fuel wood, for cooking. No wonder it is described as the epicenter of the
global challenge to overcome the energy poverty. Castellano et al. (2015) have noted that if sub-
Saharan Africa aggressively promotes renewables, it could obtain a 27 percent reduction in CO2
emissions; this would result in a 35 percent higher installed capacity base and 31 percent higher
capital spending (or an additional $153 billion).
Finally, with its rich source of energy and yet low in demand, it is the argument of the
paper based on the review of literature and the findings of the study that urbanization could be a
vehicle to promote sustainable development if it is given the desired attention to harness its
positive effects while reducing the negative effects. This requires strong government support and
the political will to prioritize efforts, keep an eye on the long term, and focus on the regulations
and capabilities of its machinery to maximize the benefits of urbanization.
23
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*,**, and *** indicate significance at the 10%, 5% and 1% level respectively; a-polity equation, b-democracy equation and c- bureaucratic quality equation