Determinants of e-waste composition in the EU28 + 2 countries: a panel quantile regression evidence of the STIRPAT model

Abstract Previous studies have examined the relationship between total e-waste generation and its determinants. However, categories not received appropriate attention, thus important information is missing for policymakers. This paper advances state of knowledge by studying individually. Statistical data in EU28 + 2 countries over period 2000–2015 disaggregated into single categories, namely temperature exchange equipment, screens monitors, lamps, large small IT telecommunication equipment. To examine main driving forces each category, STIRPAT model (Stochastic Impacts Regression on Population, Affluence, Technology) environmental Kuznets curve (EKC) hypothesis are applied, using panel quantile regression as method pooled OLS to control robustness findings. Results show that population, renewable energy consumption, trade openness, urbanization positively correlated with all categories. Renewable exploitation a major driver IT. Interestingly, an inverted U-shaped gross domestic product (GDP) per capita quantity was found across most regressions when (28 out 30 quantiles), method. confirms EKC indicates increases GDP up certain level (turning point) but then decreases continues grow.