This study investigates how industry, agriculture, food production, renewable energy
consumption, consumer price index, and urbanization influence the ecological
footprint across nine Asian countries from 1995 to 2020. Utilizing panel quantile
regression and the system GMM as robustness checks, the analysis draws on
data sourced from the world development indicators and the global footprint
network. The findings from the panel quantile regression reveal that industry has
a significant positive association with the ecological footprint across all quantile
levels, with the effect becoming particularly stronger beyond the 20th and 30th
quantiles. Food production shows a heterogeneous impact; it contributes to
reducing ecological footprint at the lower quantiles (10th, 20th, and 30th). However,
from the 40th to 90th quantiles, food production significantly increases ecological
footprint, indicating that in high-impact scenarios, agricultural intensification
and resource demand worsen environmental pressure. In contrast, renewable
energy consumption demonstrates a statistically significant negative effect on
ecological footprint, particularly evident at the 40th quantile and even more
substantial at the 90th quantile. The effect of the consumer price index varies
across quantiles, with positive impacts in lower quantiles and its negative effect
at higher quantiles. Moreover, agriculture consistently emerges as a significant
contributor to ecological footprint across all quantile levels. Finally, urbanization
exhibits a dual and quantile-dependent effect, notably significant in the 20th and
30th quantiles. Moreover, the study incorporates the system GMM as a robustness
check, which accounts for potential endogeneity, unobserved heterogeneity, and
dynamic relationships among the variables, thereby ensuring more reliable and
consistent estimates. Based on these findings, practical policy implications have
been proposed along with the study’s limitations and directions for future research.
