THE INTERACTION OF AGRICULTURE AND ECONOMIC FACTORS IN SHAPING EMISSIONS: INSIGHTS FROM SOUTHEAST ASIA USING PANEL QUANTILE REGRESSION
DOI:
https://doi.org/10.21837/pm.v23i39.1912Keywords:
Agriculture, Panel Quantile Regression, Pollution, EnvironmentalAbstract
Environmental degradation remains a critical concern in Southeast Asia, driven by rapid economic expansion, agricultural activity, population growth and trade liberalization. This study examines the heterogeneous impact of key agricultural and economic factors, namely, trade openness, Gross Domestic Product (GDP), population growth, technology, and agricultural land use, on CO₂ emissions across Southeast Asia countries from 1996 to 2021. We employ panel quantile regression (PQR) to capture variations in emissions across different quantiles. All variables are transformed into natural logarithmic form to address skewness, ensure consistency and interpret elasticities effectively. We address cross-sectional dependence and non-stationarity using Pesaran’s CD test, CADF unit root test, and Westerlund cointegration analysis. The findings reveal that trade openness significantly increases emissions across all quantiles, while GDP shows a negative association with emissions, in line with the Environmental Kuznets Curve (EKC) hypothesis. In addition, population growth, technology and agricultural land use are found to be statistically insignificant across the emission distribution. These insights offer important implications for policy formulation aimed at balancing economic growth with environmental protection in Southeast Asia.
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