Exploring the Environmental Kuznets Curve Hypothesis: Deforestation, Trade, and Economic Growth in Pakistan

Abstract

This study investigates the intricate relationship among deforestation, energy consumption, population dynamics, international trade, and economic growth, with a particular focus on Pakistan from 1980 to 2020. It seeks to reexamine both the short-term and long-term dynamics and validate the Environmental Kuznets Curve hypothesis concerning deforestation, international trade, and economic growth in Pakistan. Employing the autoregressive distributed lag bounds testing approach to cointegration, this study rigorously analyzes the relationships among the variables over the specified time period. The results reveal the presence of cointegration among the variables in the long term, indicating stable relationships that persist over time. One notable finding of this study is the diminishing negative impact of economic growth and international trade on deforestation in the long term. This observation aligns with the Environmental Kuznets Curve hypothesis, suggesting that as economies develop and incomes rise, there is initially an increase in environmental degradation, including deforestation. However, beyond a certain income threshold, further economic growth leads to environmental improvement, resulting in a decline in deforestation rates. This finding underscores the potential for sustainable development policies to mitigate deforestation in Pakistan. Additionally, the study finds that population density has a negative effect on deforestation. This implies that as population density increases, there may be greater pressure on forest resources, leading to efforts to conserve and manage forests more effectively. Understanding the relationship between population dynamics and deforestation is crucial for developing targeted policies to address environmental challenges while accommodating population growth. Furthermore, this study employs various diagnostic tests to ensure the reliability of the results for policy development. By conducting robustness checks and sensitivity analyses, the study enhances the validity and credibility of its findings, providing policymakers with valuable insights for informed decision-making.