A tale of two elasticities: A general theoretical framework for the environmental Kuznets curve analysis

2013 ◽  
Vol 119 (1) ◽  
pp. 85-88 ◽  
Author(s):  
Eugenio Figueroa B. ◽  
Roberto Pasten

Economies today are relying on coal and other finite sources for their energy needs which has not only resulted in exhaustion of finite resources but also has adversely affected the environment as burning of coal alone is responsible for emission of Green House Gases . As the economy grows the consumption of power also rises and in order to keep pace with the growing demand for power, economies are forced to increase the installed capacity. But in economies like US, China and India dependence on coal has been in rise for last few decades. Simon Kuznet rightly brought this to our notice and established the relationship between carbon emission and GDP which would be positively related initially but growth in GDP would enable the economies to find out some alternatives and reduce the emissions n long run. This paper critically analyses the existence of hypothesized relationship of Environmental Kuznets Curve (EKC) between Gross Domestic Product (GDP) and CO2 emissions of U.S., India and China. In trying to prove the theoretical framework that economic growth (GDP) in terms of purchasing power parity and environmental deterioration are strongly related, the paper used the data of developed and developing countries mentioned above. The main aim of the paper is to check the applicability of Environmental Kuznets Curve (EKC) on the economic growth of U.S., China and India. The researcher used regression for time series analysis in analyzing the data from 1999-2018. The paper is divided into three sections with the first section covering the introduction; the second section is theoretical framework. Data analysis and presentation of findings formed the third section. The researcher finally concluded the paper by giving some suggestions in lieu of the findings.


2020 ◽  
Vol 28 (3) ◽  
pp. 3421-3433
Author(s):  
You-How Go ◽  
Lin-Sea Lau ◽  
Feng-Mei Liew ◽  
Abdelhak Senadjki

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