Air pollution and environmental tax: Exploring the dynamics in developed nations

Abstract

Air pollution, particularly fine particulate matter (PM2.5), remains a serious concern in developed countries due to its adverse effects on health and the environment. Environmental taxation has emerged as a key policy tool to curb pollution and encourage cleaner practices. This study investigates the heterogeneous distribution of PM2.5 exposure across 39 developed countries from 1995 to 2020, focusing on environmental taxation, renewable energy consumption, per capita GDP, forest cover, and demographic structure. The study uses the Method of Moments Quantile Regression (MMQR) to assess differential impacts across the pollution distribution. A sensitivity analysis was carried out on sub-samples of low- and high-pollution countries to examine sample heterogeneity. For long-run relationships and causality, the study employs the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model and the Dumitrescu-Hurlin panel causality test, both accounting for cross-sectional dependence and parameter heterogeneity. Results consistently show that environmental taxation significantly reduces PM2.5 pollution across all quantiles, with stronger effects in cleaner environments (e.g., −0.146 at Q5 vs. −0.106 at Q95). Renewable energy consumption exhibits a stable and robust negative association with pollution levels (−0.164 across quantiles), while forest cover also contributes positively to air quality. In low-pollution countries, short-run dynamics confirm the significant role of environmental taxes (−0.136), and both long-run relationships and causality with PM2.5 are established. These findings highlight the varying effectiveness of environmental policies under different pollution conditions and underscore the importance of fiscal tools, renewable energy adoption, and forest conservation in addressing air pollution in developed economies.