Agricultural carbon footprints, renewable energy and sustainable development in Asia

There is a growing concern over environmental degradation and climate change in rapidly developing Asian nations. However, little research has been conducted on the impact of agricultural carbon emissions and renewable energy use on sustainable development outcomes in Asia. This research looks at the relationship between agricultural carbon footprints (ACF), renewable energy consumption (RE), and sustainable development (SD) in nine Asian nations from 2000 to 2022. The study employed the Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL), Method of Moments Quantile Regression (MM-QR), and Dumitrescu-Hurlin (DH) panel causality techniques to examine the connection. The findings reveal that the relationships vary significantly across the SD distribution. The findings of DH causality indicate bidirectional causality between agricultural carbon footprints and SD, with economic growth primarily driving agricultural emission patterns rather than the reverse. MMQR results demonstrate that agricultural carbon footprints positively impact SD, with effects strongest at lower sustainability levels but diminishing at higher quantiles, suggesting a nonlinear relationship. Trade openness consistently demonstrates negative relationships with SD across all quantiles, while renewable energy shows positive but statistically insignificant effects. Significant country-level heterogeneity emerges, with China and India demonstrating strong Granger causality from agricultural carbon footprints to SD, while other sampled countries show weaker or insignificant relationships. These findings accentuate the need for contextually appropriate policies that recognize the stage-specific relationship between agricultural practices, renewable energy adoption, and sustainable development outcomes in diverse Asian economies.