Abstract:
This study examines the dynamic relationship between the emission of carbon dioxide (CO₂) and some of the important macro-economic, structural, and demographic factors in Pakistan from 1970 to 2023 using Autoregressive Distributed Lag (ARDL) bounds testing approach. The analysis includes three structural specifications industry, agriculture and services as this captures sectoral heterogeneity in emissions behavior. The results confirm the existence of long-run cointegration betweenCO₂ emissions, GDP, GDP, energy consumption, trade openness and population density. The long-run coefficients are estimated and reveal that the GDP has a positive relationship with the emission and the squared term of the GDP has a negative relationship with the emission which validates the Environmental Kuznets Curve hypothesis. Energy consumption is the single biggest driver of emissions in all models and industrial and agricultural activities increase environmental degradation. However, the services sector has the lowest emission elasticity, indicating its potential for facilitating decarbonization in the long run. Trade openness does not have a clear impact but rather mixed effects on emissions, since in the industrial model emissions are lowered, while in the agricultural and services sectors emissions rise. Error correction terms are negative and significant under all models and suggest stable adjustment to equilibrium. The results highlight the importance of clean energy transitions, sustainable industrial restructuring and environmental policies that are ecosystem-specific in order to balance economic growth and sustainability in Pakistan.
