Green innovation efficiency, green finance, and industrial upgrading in China: A VECM and NARDL analysis

Abstract

The coordination among green finance (GF), industrial upgrading (IS), and green innovation efficiency (GIE) is crucial for sustainability. Few studies focus on the asymmetric impacts of GF. Controlling for the 2009 policy shock, this study examines the dynamic and asymmetric effects of green finance from a city-level perspective. By employing the Vector Error Correction Model (VECM) and the nonlinear autoregressive distributed lag (NARDL) model, we find that GF significantly drives GIE in the long run. The ARDL results reveal that a one-standard-deviation increase in GF significantly improves GIE by 0.35 units. The NARDL model reveals the asymmetric impacts of GF in the short run, showing that credit contraction can lead to a more severe decline in GIE; yet these frictions gradually dissipate in the long term. These findings suggest the necessity for targeted GF policies to smooth short-term frictions during the transformation of manufacturing cities.