Exploring environment sensitivity to fiscal and monetary policies in China: using ecological footprints as a...

This paper is a pioneer attempt using ecological footprints, the latest environment sensitivity proxy to be regressed, contributing to the scarce literature concerning one of the most burning global dilemmas of the era. For econometric analysis, fiscal and monetary tools, green energy consumption, and economic growth have been chosen as a set of regressors data spanning 1990-2020 in China facing the highest total ecological footpaths. And giving priority to the relevancy, reliability, and robustness autoregressive distributed lag (ARDL), fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) have been applied for instant and eternal sensitivities, followed by the widely used stationarity tests (augmented Dicky-Fuller and Phillips-Perron tests) and bounds test. Granger's ordeal has also noticed causal inferences. Cointegrating findings are robust across all techniques, and ARDL results remain consistent regardless of short and prolonged duration. We witness positive and statistically significant (at 10%) responsiveness of ecological footprints (EFP) to China's rapid gross domestic output (GDP) growth per capita fueled by fossil fuels (primarily coal). Contrarily, negative/inverse sensitivity to expansionary fiscal (higher government expenditures, GEx), contractionary monetary policies (higher policy rate, DR), and green energy use (REnC). Besides, EFP demonstrates statistically significant reciprocal interconnection with GDP and REnC but a unidirectional connection with DR (DR → EFP). GDP has effective collaboration with REnC and GEx whereas single-sided relationship DR as (GDP → DR). Finally, some policy choices are endorsed.