Big data

Quantile regression

World Wide Web

Digital library

Statistics

Poetry

Panel data

Literature

China

Archaeology

Economics

Data mining

Computer science

Business

Mathematics

Estimator

Geography

Political science

Econometrics

Data science

Finance

Digital transformation

Web crawler

Technological Forecasting and Social Change

This study examines the influence of digital finance on green growth using China's city-level data from 2008 to 2019. Web crawler technology and a super-efficiency SBM model are employed to measure inclusive digital finance and green growth. For mechanism analysis, it innovatively quantifies the enterprise digital transformation using Big Data text and factor analysis techniques from the unique perspective of disclosing textual information about “enterprise digital transformation”. The results exhibit that inclusive digital finance significantly promotes green growth, and these results are consistent using robust standard error estimation, bootstrap sampling, endogenous estimators, and alternative proxies. The regional samples demonstrate heterogeneous outcomes, suggesting that the influence of digital finance is more pronounced in eastern and central regions than in the western region. Moreover, the asymmetric effect of digital finance is documented through panel quantile regression. It displays that the influence of digital finance turns stronger from the 3rd to 7th quantile and decreases hereafter. Manifestly, the mechanism analysis discovers that digital finance encourages green growth by supporting the digital transformation of enterprises and addressing energy poverty. These findings offer valuable policy recommendations for legislators.

Digital finance and green growth in China: Appraising inclusive digital finance using web crawler technology and big data