Economics at your fingertips  

Green Credit Policy and Corporate Productivity: Evidence from a Quasi-natural Experiment in China

Xin Cui, Panpan Wang, Ahmet Sensoy, Duc Khuong Nguyen and Yuying Pan

Technological Forecasting and Social Change, 2022, vol. 177, issue C

Abstract: Taking the implementation of the “Green Credit Guidelines” in China in 2012 as an exogenous shock, we adopt the difference-in-differences (DIDs) method to explore the influence of the green credit policy on total factor productivity (TFP). We show evidence of a significant and positive correlation between green credit and corporate total factor productivity, and this result is robust to a series of robustness tests. In addition, the improvement is particularly evident for non-SOEs, small-scale firms, firms with weak external supervision, and firms in developed areas of eastern China. Moreover, the green credit policy mainly affects corporate total factor productivity through promoting technological innovation and enhancing resource allocation efficiency. Overall, green credit promotes the win-win development of the environment and the economy.

Keywords: Green credit policy; Total factor productivity; Technological innovation; Resource allocation efficiency (search for similar items in EconPapers)
JEL-codes: G18 G38 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.techfore.2022.121516

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

Page updated 2023-01-28
Handle: RePEc:eee:tefoso:v:177:y:2022:i:c:s0040162522000488