Analysis Of The EKC Hypothesis

2349 Words5 Pages

Over the past years, numerous studies on the Environmental Kuznets Curve have been in great contention by investigating the income-pollution relationship. In recent times, however, criticism of cross-section estimations of the EKC hypothesis has grown. Consequently, the contribution of this study uses time series data for a developed country with reliable data: Canada. A dynamic analysis is performed in the form of the Vector Error Correction Model to test the short-run and long-run relationship of income and pollution. Using this method it is found that short-run estimations do not support the EKC hypothesis, but only in the long-run does it support the EKC hypothesis.
This literature review is organized in the following manner. The first section gives a brief background on the theory of the EKC and the assumptions behind it. In the second section, literature focused on cross-country analyses is presented. The third section considers studies concerning an individual country approach.
2.1 Theoretical Background of the EKC
There are many assumptions that can explain the inverse U-shape relationship between pollution and income. It has been stated that the EKC is the result of non-homothetic preferences of users of environmental goods within the economy (Lopez, 1994). When individuals have homothetic preferences it implies that when income increases, so does consumption, which by extension causes increased pollution. When individuals have non-homothetic preferences, when income increases they decide to consume less and thus, pollute less. This depends on the relative risk aversion to damaging the environment in order to consume more.
Dasgupta and Laplante (2002) presented assumptions regarding the inverted U-shape relationship betw...

... middle of paper ...

... income, therefore a time trend was added to the static model. Furthermore, the Engel-Granger test revealed no cointegration between the explanatory variables. This result suggests that a long-term relationship between per capita income and the measures of environmental degradation in the study, do not exist.
Day and Grafton tested for causality using a vector autoregression (VAR) approach. The test elicited bidirectional causality and not unidirectional causality, from income to the environment. They conclude that there is little evidence that suggests increases in income per capita will effectively reduce environmental degradation. Day and Grafton (2001), suggest in order to adequately assess the economic-environmental growth relationship, a sectoral analysis is recommended as it will help explain the effects of economic and social progress on the environment.

Open Document