TITLE:
Environmental Quality, Governance, and Quality-of-Life: A Cross-National Comparative Analysis
AUTHORS:
Wullianallur Raghupathi, Dongli Zhang
KEYWORDS:
Air Pollution, Environmental Quality, Governance, Quality of Life, Social Indicators, Cross-National Analysis, Between-Within Model, PM2.5
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.14 No.3,
March
30,
2026
ABSTRACT: Environmental quality is increasingly recognized as a fundamental determinant of quality of life, yet comprehensive cross-national studies examining environment-well-being relationships while accounting for governance factors remain scarce. This study examines structural associations between environmental quality indicators—particularly fine particulate matter (PM2.5) air pollution—and quality of life outcomes across 90 countries selected based on data availability and completeness criteria using World Bank data spanning 2005-2014. We employ a between-within (hybrid) regression framework that explicitly decomposes cross-national differences from within-country temporal variation, with cluster-robust standard errors and controls for governance quality (corruption control, political stability) and year effects. Variance decomposition reveals that most of the variation in both pollution exposure and quality of life outcomes is cross-sectional (between-country) rather than longitudinal, making a purely cross-national comparative approach both transparent and appropriate. Countries with higher PM2.5 exposure tend to exhibit higher life-threatening disease incidence and lower labor force participation and electricity access, with these associations concentrated in between-country differences. Governance quality, particularly corruption control, emerges as an important correlate of health and technology access outcomes. Results are robust to log-transformation of PM2.5, inclusion of quadratic terms, leave-one-region-out analysis, and exclusion of power consumption from the models. We interpret all results in terms of coefficient magnitudes and cluster-robust standard errors rather than null hypothesis significance testing, following methodological recommendations for observational studies with purposively selected units. These findings contribute to the social indicators literature by demonstrating that environmental quality and governance quality represent complementary structural dimensions of cross-national quality of life variation.