Paper Example on Economic Growth and Environmental Deterioration: Exploring Kuznets Curve

The empirical verification of the relationship between economic growth and the deterioration of the environment has been a subject of intense debate, and most of the research has been carried out within Kuznets Environmental Curve (KEC) framework which states that the relationship between the level of income per capita and the deterioration of the quality of the environment is represented by an inverted U-shaped curve (Stern, 2018; Pineiro, Tamazian & Vadlamannati, 2017), indicating that low levels of income are correlated with a growing deterioration in the environment, but after a certain point of inflection of per capita income, the relationship between the two variables becomes negative. Thus, a higher level of per capita income corresponds to a decrease in environmental degradation (Stern, 2018). In this sense, the KEC is limited to an empirical verification between indicators of environmental degradation and per capita income.

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This hypothesis is supported by the argument that higher levels of development imply a change in the structure of the economy in favor of industry and services, where production processes are based on more efficient technologies that help conserve resources and, in this way, significantly reduce environmental deterioration (Stern, 2018). Similarly, the KEC shows the development of an economy over time. In a first phase, it is an economy based on the agricultural sector with a strong impact on the quality of the environment; in a second phase the industry is developed, which although a higher level of wealth is generated, has as a consequence a greater deterioration in the quality of the environment. After a turning point, the economy supports its growth in efficient and cleaner technologies, mainly in the services sector.

Considering a set of countries, the KEC hypothesis establishes that the developing countries are located on the positive slope of the curve, where their actions and policies in favor of growth generate a deterioration in the environment, but upon reaching a state development, implement policies to improve the quality of the environment and protect natural resources, and eventually degradation begins to diminish . This result could suggest that economic growth is the key to getting out of environmental problems. Every time, when the economy breaks that turning point the indicators of environmental deterioration would have to be reversed.

The Kuznets curve represents a reduced form that conceals other phenomena such as technology, the composition of the product, the environmental regulations or the demands of society (Jha & Murthy, 2003). In this sense, this reduced form does not allow initially identifying the effects of economic policy. However, it is possible to define a parametric form of the KEC hypothesis (Cole, 2004) defined as:

EDit=v0+v1YPit+v2YPit2+v3YPit3+Sj=1ghjXj,it+uit

i=1, 2,...N t=1,2,...T

Figure 1 shows a scatter diagram between the per capita CO 2 and GDP per capita, shows that an increase in GDP per capita is associated with an increase in emissions per person. However, the correlation pattern between the two variables ceases to be linear when going from a per capita GDP value of more than 10 thousand dollars. In effect in values above this level, the CO 2 in some cases remain constant between 5 and 10 tons per person, for other countries emissions rise to values higher than 10 tons per. Levels of GDP per capita above 20 thousand dollars a year, do not correspond with decreased CO2, which would be empirical evidence against an inverted-U shape KEC, and in favor of a non-linear pattern or N-shaped. In other words, developing economies maintain a strong association between economic growth and emissions, showing a growing trajectory. For their part, the more developed countries with higher income levels do not show a reduction in per capita emissions, in fact, they tend to remain constant.

The specifications of fixed effects and random effects in the KEC including the control variables were consistent with the theoretical hypothesis, and in terms of the signs and magnitudes of the estimators. The Hausman statistical test (Cole, 2004) can be used to determine the best specification between fixed and random effects. This test compares the estimators of fixed effects and random effects, and if there is a difference that is statistically significant between both, it indicates that the estimators of random effects are inconsistent, consequently, the best specification for the panel data model corresponds to one of the fixed effects. (Stern, 2018; Cole, 2004).

It is assumed as a null hypothesis that the explanatory variables are not correlated with the unobserved heterogeneity H 0: E (x it ' a i) = 0 and the alternative H 0: E (x it ' a i) 0.

The test statistic is defined based on the difference of the estimators of fixed and random effects q=vFAND-vRAND, and the difference in the value of the variances of the estimators Vtor(q)=Vtor(vFAND)-Vtor(vRAND). Finally, the Hausman statistic is defined as:m=q'[Vtor(q)]-1 q, which is distributed as a chi-square with k degrees of freedom kh 2 ( k ), which is the number of parameters. From the Hausman test, the null hypothesis is rejected, indicating correlation among model variables and the individual effects, so both the best specification in data panel is that of fixed effects.

Results of the Hausman Test

kh 2 (3) = 15.9863 (0.001)

Empirical Investigation

Empirical evidence presented shows that when considering a sample of 144 countries from 1990 to 2010, using a panel data model, the relationship between the per capita CO 2 and GDP per capita is adjusted to a environmental Kuznets curve in the form of N, in which countries with low per capita income tend to raise emissions per capita and with its environmental deterioration, because the exploitation of Natural resources are made with non-efficient technologies and the extraction of natural resources exceeds their conservation. On the other hand, the control variables show that in these countries the structure of the economy is concentrated in agriculture and industry, with high consumption of fossil fuels, low levels of energy efficiency, as well as poor protection of the natural resources and biodiversity.

Countries with high per capita income show a reduction in emission levels with a structure of the economy supported mainly by services, better energy efficiency, moderate levels of consumption of fossil fuels and greater concern for the environmental issues. However, the estimate shows that the KEC curve is N-shaped, therefore in countries with high-income levels the reduction of emissions stops, possibly because the opportunities to reduce emissions are getting smaller, the reduction costs tend to rise because the price of the new technologies is higher. Also, there is a transfer of those from production processes that generate emissions, from higher income countries to countries that do not apply strict regulation on environmental matters.

These results show that there are important implications for achieving sustainable growth over time. In the first place, it cannot be argued that it is possible to "exit" from environmental problems exclusively through economic growth and, consequently, regulatory environment and energy policies play an important role in reversing environmental deterioration. The estimates of the KEC including control variables show that environmental improvements do not depend only on economic growth, energy efficiency is a relevant variable in the design of policies to reduce emissions, as well as the protection of biodiversity and conservation of natural areas. Therefore, the implementation of adequate regulations and maintaining a continuous process of technological innovation is required.

References

Andreoni, J., & Levinson, A. (2001). The simple analytics of the environmental Kuznets curve. Journal of public economics, 80(2), 269-286.

Cole, M. A. (2004). Trade, the pollution haven hypothesis and the environmental Kuznets curve: examining the linkages. Ecological economics, 48(1), 71-81.

Jha, R., & Murthy, K. B. (2003). An inverse global environmental Kuznets curve. Journal of Comparative Economics, 31(2), 352-368.

Pineiro Chousa, J., Tamazian, A., & Vadlamannati, K. C. (2017). Does Higher Economic and Financial Development Lead to Environmental Degradation: Evidence from BRIC Countries.

Stern, D. I. (2018). The environmental Kuznets curve. In Companion to Environmental Studies (Vol. 49, No. 54, pp. 49-54). ROUTLEDGE in association with GSE Research.