COMPONENTE BIÓTICO

A number of empirical models of how EKC relationship may exist have presented. Especially in recent decades, lots of domestic and foreign scholars make considerable empirical studies on the degradation of environmental quality caused by the economic growing process. These studies have the prominent commonness that they use one single pollutant represented the pollution pressure in their

Pre-industrial economies

Income Pollution

(a) Scale Effect

Industrial economies Income Pollution (b) Structural Effect Post-industrial economies Income Pollution (c) Abatement Effect

Figure 3.3: Three Effects between Pollution Pressure and Income

study. they adopt the basic model from Grossman and Krueger (1991) which is to make regression on the relationship between environmental pressure P and national income per capita Y .

Pit= α + β1Yit+ β2Yit2+ β3Yit3+ Xit+ uit (3.27)

where Pitis pollution pressure per capita in country i at year t. Yitmeans GDP per capita in country

i in year t. X is the vector of other control variables. α is the intercept of abscissas. β ≡ (β1, β2, β3)

is the parameter vector and uit is an error term. If the coefficient on GDP per capita, β1 is positive

and the coefficient on GDP per capita squared, β2is negative, the relationship between GDP per capita

and pollution emissions is not monotonic but displays an inverse-U shaped.

The equation (3.27) enables to test the various relationships between pollution emission and the income per capita as follows 7 conditions:

(i)β1> 0, β2= 0 and β3= 0 implies a monotonic increasing linear relationship. It means that when

income rises, environmental degradation also increases.

(ii)β1> 0, β2< 0 and β3= 0 implies that the inverted U-shaped EKC relationship exist.

(iii)β1> 0, β2< 0 and β3> 0 implies a N-shaped relationship. It means once the the pollution

emission dropped to the ground as income increase, it increase again as the further increase in income level.

(iv)β1= 0, β2= 0 and β3= 0 implies a horizontal line or no relationship. It means that income level

does not affect environmental degradation at all.

(v)β1< 0, β2= 0 and β3= 0 implies monotonic decreasing linear relationship. It means that as the

income increase, the environmental degradation is decreasing. (vi)β1< 0, β2> 0 and β3= 0 implies an U-shaped relationship.

Therefore, the inverted U-shaped EKC is only one of the seven results from the equation (3.27) and an EKC results from β1> 0, β2< 0 and β3= 0.

There is a way to find the turning point if the EKC curve exist. The turning point or threshold level of income, where the pollution emission is at maximum can be calculated by taking the First Order Condition of Pit) in equation (3.27) with respect to Yit and solving for Yit, then we have the

turning point as,

Y∗= − β1 2β2

(3.28)

or if every variable is in a logarithm form in equation (3.27), we need to use equation (3.29) instead of equation (3.28) to calculate the turning point.

Y∗= exp(− β1 2β2

) (3.29)

The turning point measures the maximum relationship between pollution emissions and the income per capita if the inverted U-shaped EKC present. It explains that when the income reaches a certain level for individuals, the environment degradation will reach its limit and needs to be recovered in order to reach to a long-run sustainable equilibrium.

After the breakthrough studies of EKC hypothesis from Grossman and Krueger (1991), (1993), Panayotou (1993) and Shafik and Bandyopadhyay (1992), an extensive amount of research has been conducted to study the EKC hypothesis. However, these studies have a major commonness which they used one single pollutant as an indicator of the environmental degradation. The main disadvantage of using one pollutant as pollution indicator is to generate inconsistent results. Grossman and Krueger (1991) and (1993) test the EKC relationship between income per capita and several different pollutants individually. The results are different from individual pollutants. Grossman and Krueger (1995) studied the relationship between urban air pollution and GDP per capita by using a single pollutant, SO2.

The data are tested by the Global Environmental Monitoring System (GEMS) that is designed by the World Health Organization and the United Nations Environment Programme in 42 countries from 1977 to 1993. They found a N-shape relationship instead of an inverted U relationship between SO2 and

GDP per capita. However, Shafik (1992) and Panayotou (1993), concluded an inverted-U relationship between these two in same study. They found a turn point of income per capita around 3,700 US dollars and 10,000 US dollars respectively. Li (2011) studied the relationship between CO2 per capita

and GDP per capita of high-emission regions, low-emission regions and medium-emission regions of China from 1995 to 2009. He concluded a N-shaped EKC curve among all three regions. However, He (2014) thought that there is a reverse U-shape relationship between these two and he found a turning

point around 35,000 US dollars in same study. Grossman and Krueger (1995) and Selden and Song (1995) found an inverted-U shape relationship between income per capita and CO per capita and the turning point that they have found are around 22,800 US dollars and 6,200 respectively. Panayotou (1993), Shafik (1994), and Cole, Rayner and Bates (1997)found an inverted-U relationship between Suspended Particulate Matter(SPM) per capita and income per capita. The turning points they found are around 4,500 USD, 3,200 USD, 8,100 USD. Whereas, Grossman and Krueger (1993), Selden and Song (1994), Vincent (1997) and Carson, Jeon and McCubbin (1997) thought there wasn’t an inverted U-shaped relationship between these two. Panayotou (1993), and Cole, Rayner and Bates (1997) got an inverted U-shape relationship between N Ox and income per capita and found turning points of

5,500 USD and 15,100 USD respectively. Grossman and Krueger (1995) found an inverted U-shaped relationship between Biochemical Oxygen Demand (BOD) and income per capita while Shafik and Bandyopadhyay (1992), Shafik (1994) and Cole, Rayner and Bates (1997) all thought there is a linear positive relationship between these two.