Artikel
Investigating the influence of green credit on operational efficiency and financial performance based on hybrid econometric models
To understand the role of green credit in maintaining economic sustainability, we develop theoretical hypotheses including expectation, supervision and capital allocation channels to explain the impacts of green credit. Then, we use hybrid econometric models by using Chinese-listed enterprises in the energy-saving and environmental sectors from 2007 to 2015 as the research sample to verify the above hypotheses. The empirical results show that: (1) the average value of financial performance and operational efficiency is relatively low, and the endogenous abilities of those enterprises have not yet been established; (2) the issuance of green loans does not improve public expectations of enterprises in the green industry, thus the expectation channel is not supported; (3) the issuance of green loans does not necessarily improve the enterprise's operational efficiency and financial performance, thus the supervision channel hypotheses are not supported; and (4) green loans lead to an increase in financing costs, management costs, operation costs, and expenditure on R&D, thus, the capital allocation hypothesis is partly supported. Based on the empirical analysis, we also provide some countermeasures to strengthen the roles of green credit to support the development of energy-saving and environmental enterprises.
- Sprache
-
Englisch
- Erschienen in
-
Journal: International Journal of Financial Studies ; ISSN: 2227-7072 ; Volume: 5 ; Year: 2017 ; Issue: 4 ; Pages: 1-19 ; Basel: MDPI
- Klassifikation
-
Wirtschaft
Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- Thema
-
green credit
energy-saving
environmental protection
financial performance
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Luo, Changqing
Fan, Siyuan
Zhang, Qi
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2017
- DOI
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doi:10.3390/ijfs5040027
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Luo, Changqing
- Fan, Siyuan
- Zhang, Qi
- MDPI
Entstanden
- 2017
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