Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economies

The role of a reliable resource consumption measurement is essential for devising a relevant climate policy. The consumption-based material footprint is trade-adjusted domestic resource consumption that presents an accurate picture of the domestic material footprint. Pursuing the same, this study draws asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint (MF) in the top 11 highly material-consuming countries. Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is quantile-dependent, which may disclose misleading results in previous studies using linear methodologies. In compliance, a novel empirical estimation technique popularized as Method of Moments Quantile Regression is employed that simultaneously deal with non-normality and structural changes in data. The results exhibit that infrastructure development (green innovation) significantly increases (decreases) MF mainly across medium to higher quantiles (medium-higher level of MF). Interestingly, the resource-depleting effect of infrastructure is highest for higher quantiles and lowest for lower quantiles of MF. Economic growth (globalization) increase MF, and their resource-depleting effect is higher (lowest) for lower quantiles and lowest (highest) for higher quantiles. Lastly, population exhibits an inverted-U shape relationship with MF across lower to higher quantiles. These results suggest pertinent policy recommendations.

Automated summary

Reliable resource consumption measurement is crucial for climate policy, with this study examining the linkages between infrastructure development, green innovation, and consumption-based material footprint in highly material-consuming countries. The study rejects data normality and uses Method of Moments Quantile Regression to handle non-normal data, revealing varying effects of infrastructure development and economic growth on resource consumption across different quantiles. Population shows an inverted-U relationship with material footprint.