Abstract
The investigation of economic sides of Greenhouse Gas (GHG) emissions and its penalties is very important, particularly in terms of its volume at the present increasing trend. Carbon dioxide (CO2) emissions account for the largest proportion of total greenhouse gas emissions produced mainly by human activities. So, the prediction of air pollution due to emissions of CO2 can give the right way to policies accepted. In the economics literature of the last decades, the relationship between emissions of CO2 and financial progress is of great interest. This study aimed at modeling and forecasting some environmental and economic variables and investigating the existence of long-run equilibrium relationship between major GHG emissions and economic growth in eight SAARC countries—Bangladesh, India, Pakistan, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. Time series data from 1990 to 2018 was collected from World Bank data archive. Autoregressive Integrated Moving Average (ARIMA) Models and cointegration theory was applied to analyze the data. While forest areas in most of the countries showed decreasing trend, GHG and CO2 emission showed increasing trend in majority of the countries. Industrial and GDP growth in the region was slowly growing over time. ARIMA models fitted well to the data except the cases where data did not show any variability. Mix results were obtained regarding the existence of coingration between CO2 emission and industrial growth and that between CO2 emission and GDP growth. These findings would enable the environmental authorities to understand the environmental impacts of economic development on degradation and to use time series approaches to handle environmental problems.
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