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First Author: Ghaffar Ali

Global warming and climate change are the most burning issues nowadays, which have diverted the attention of researchers towards climate change adaptation & mitigation strategies. In the early days, after the formation of Pakistan, its survival and future was under a great deal of skepticism. Therefore, the Government of Pakistan (GOP) took initiatives for agricultural growth and development in the mid-1960’s, which later on became a revolution, commonly known as the Green Revolution. The present study aims to explore the environmental consequences of the Green Revolution by testing a hypothesis. Our H0 states that there is no trade-off between agricultural growth (proxy variable for economic growth) and carbon dioxide emissions in case of Pakistan, based on the annual data on variables (such as GHG emissions and Index of agriculture, GDP, etc.) from 1960 to 1990. Johansen’s method of cointegration has been employed in this study to test H0. This method has an advantage over Phillips-Ouliaris’ and Engle-Granger’s methods of cointegration, in that it has the ability to estimate more than one cointegrating relationship between variables. Results of the present study do not support the existence of EKC hypothesis in relation to the Green Revolution, neither in the short run nor in the long run. None of the factors that led to the Green Revolution significantly contributed to the CO2 emissions; however, the Green Revolution resulted in an increase in the GDP of Pakistan. This shows that the agricultural sector of Pakistan can provide better earning opportunities besides having the potential for climate change mitigation. The present scenario in Pakistan necessitates the need for the government to focus on climate change mitigation and adaptation policies through the agricultural sector. Moreover, effective implementation of such policies using economic instruments, such as charges and subsidies, especially against the polluting industries, should be encouraged.

Contact the author: CUI Shenghui
Page Number: 166-171
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PubYear: 2017
Volume: 77
The full text link: https://doi.org/10.1016/j.envsci.2017.08.019