Modeling the environmental Kuznets Curve: A stochastic approach using economic and climate data

Area of Science:

• Environmental Economics
• Sustainable Development
• Econometrics

Background:

• Economic growth in developing nations often correlates with increased carbon emissions due to industrialization and fossil fuel reliance.
• The Environmental Kuznets Curve (EKC) hypothesis suggests pollution initially rises with economic development then falls.
• Pakistan's economic trajectory from 1960-2023 shows growth with periods of stagnation and decline.

Purpose of the Study:

• To investigate the dynamic relationship between economic expansion and carbon emissions in Pakistan.
• To test the applicability of the Environmental Kuznets Curve (EKC) hypothesis in the Pakistani context.
• To provide insights for aligning economic policies with sustainable development goals.

Main Methods:

• Utilized coupled stochastic differential equations to model the interaction between economic growth and carbon emissions.
• Employed the Differential Evolution Algorithm for model optimization.
• Analyzed time-series data from 1960-2023 for Pakistan's GDP and carbon emissions.

Main Results:

• The study confirms that Pakistan's development path aligns with the Environmental Kuznets Curve (EKC) hypothesis.
• A turning point was identified, indicating that beyond a certain economic development level, emissions are projected to decline.
• The stochastic differential equation model, optimized via Differential Evolution, validated the EKC hypothesis for Pakistan.

Conclusions:

• Pakistan's economic development and carbon emissions exhibit an inverted U-shaped relationship, supporting the EKC.
• Policy interventions are crucial to manage the environmental impact of economic growth and achieve sustainability.
• Findings offer valuable guidance for policymakers to balance economic progress with environmental protection for a sustainable future.