Towards a sustainable development: econometric analysis of energy use, economic factors, and CO2 emission in Pakistan during 1975–2018

• Published in: Environmental monitoring and assessment 2022-02, Vol.194 (2), p.73-73, Article 73
• Main Author: Raza, Muhammad Yousaf
• Format: Article
• Language: English
• Subjects: Atmospheric Protection/Air Quality Control/Air Pollution; Autoregressive models; Carbon dioxide; Carbon dioxide emissions; Causality; Clean technology; Coefficients; Earth and Environmental Science; Ecology; Econometrics; Economic analysis; Economic conditions; Economic development; Economic factors; Economic growth; Economics; Ecotoxicology; Emission analysis; Emissions; Empirical analysis; Energy; Energy consumption; Energy industry; Energy policy; Environment; Environmental Management; Environmental monitoring; Environmental science; Fossil fuels; Impact analysis; Imports; Industry; Manufacturing industry; Monitoring/Environmental Analysis; Renewable energy technologies; Sustainability; Sustainable development; Unemployment; Urban populations
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-021-09713-8

Many studies have computed the carbon dioxide emissions (CO 2 Es) associated with energy consumption, overall population, imports, manufacturing industries, and financial development in various countries. However, past studies have ignored the impact of CO 2 Es on fossil fuel energy, domestic economy, rural–urban unemployment, rural–urban population, services value-added, and fiscal deficit, especially in the context of Pakistan. Thus, to avoid the problems of mis-specification, sustainable growth, and carbon reduction simultaneously, it is necessary to study how to accomplish the time-varying relationship between factors. The present study applied autoregressive distributed lag (ARDL) model for cointegration between CO 2 Es and its determinants to test long-run and short-run effects from 1975 to 2018. The findings are as follows: first, in the short run, CO 2 Es, fossil fuel, and services value added show the unidirectional causality, while CO 2 Es, economic growth, rural–urban population, rural–urban unemployment, and fiscal deficit have bidirectional causality among them. Second, in the long run, we found bidirectional causality between CO 2 Es and its determinants. Finally, the diagnostic estimations, cumulative sum, and cumulative sum of squares check the long-run association between the selected variables and present the constancy of coefficients. The empirical outcomes give new insights for policymakers to regulate renewable technology investment in the energy sector for the improvement of environmental excellence. Related to the key results, the focused policies are presented below.