The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Asymmetric impacts of the policy and development of green credit on the debt financing cost and maturity of different types of enterprises in China
Abstract
Abstract Green credit plays an increasingly important role in promoting environmentally friendly enterprises and limiting polluting enterprises by regulating the flow of social capital to strengthen environmental governance and promote green production in society. Taking China as an example, this paper surveys the asymmetric impacts of the policy and development of green credit on the debt financing cost and maturity of different types of enterprises. It uses the fixed effect model based on the Hausman test and the mediating effect analysis method to quantify the panel data of 52 green enterprises and 81 high-pollution and high-emissions (referred to as “two-high”) enterprises in China from 2001 to 2017. The findings are as follows: (1) both green credit policy and green credit development increase the debt financing cost of “two-high” enterprises, but they reduce the debt financing cost of green enterprises; (2) green credit policy and the development of green credit reduce the debt financing maturity of “two-high” enterprises, while they have little impact on the debt financing maturity of green enterprises; (3) the impact of green credit policy on enterprise debt financing cost and maturity occurs partly through the development of green credit; and (4) with respect to the debt financing cost and maturity, enterprises in economically developed regions are more strongly affected by green credit than those in economically underdeveloped regions. The conclusions will help the government, banks and enterprises make their environmental protection and financing decisions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The impact of corporate social responsibility on the cost of bank loans
Goss, A., & Roberts, G. S. (2011) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2010.12.002 · Cited by 2,101
Cited by
Zhang, S., Wu, Z., Wang, Y., & Hao, Y. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113159 · Cited by 659
Green finance, fintech and environmental protection: evidence from China
Muganyi, T., Yan, L., & Sun, H.-P. (2021) · Environmental Science and Ecotechnology · doi:10.1016/j.ese.2021.100107 · Cited by 626
Luo, S., Yu, S., & Zhou, G. (2021) · Energy Economics · doi:10.1016/j.eneco.2021.105335 · Cited by 194
Theoretical framework of sustainable value creation by companies. What do we know so far?
Zioło, M., Bąk, I., & Spoz, A. (2023) · Corporate Social Responsibility and Environmental Management · doi:10.1002/csr.2489 · Cited by 40
Metadata
- Authors
- Xu, X., & Li, J.
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 264
- Pages
- 121574
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W3016723146
- Cited by
- 450
- References
- 1
- FWCI
- 62.07
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.