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Cited by 553

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Green credit policy, credit allocation efficiency and upgrade of energy-intensive enterprises

Wen, Huwei, Lee, Chien-Chiang, Zhou, Fengxiu·2021·Energy Economics
DOI 10.1016/j.eneco.2021.105099
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Abstract

Abstract Using the quasi-experimental method, this research investigates the impact of green credit policy on the upgrade of energy-intensive enterprises from the perspective of credit allocation efficiency. Through the panel data of listed companies in China, this study finds that the green credit policy under the Green Credit Guidelines in 2012 (GCG2012) has a significantly negative effect on the research and development (R&D) intensity and the total factor productivity (TFP) of treated firms. Empirical evidence also shows that the GCG2012 significantly reduces bank credit but increases trade credit. Consequently, the substitution hypothesis is established. Furthermore, GCG2012 has reduced the allocation efficiency of bank credit within energy-intensive industries. As an improved green credit policy to encourage enterprises to invest in energy efficiency, the Energy Efficiency Credit Guidelines in 2015 (EECG2015) increases both the bank credit and the fixed asset investment, whereas no increase in R&D intensity or TFP is found. These findings are enlightening for designing better green credit policies.

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Citations

Cites

Show all 36 references

Research works printed but not linked: 10

  1. Guo, 2014, Financial policy innovation for social change: a case study of China’s green credit policy, Int. Rev. Sociol., 24, 69, 10.1080/03906701.2014.894347 · doi:10.1080/03906701.2014.894347
  2. Hao, 2020, The role of internet development on energy intensity in China: evidence from a spatial econometric analysis, Asian Econ. Lett., 1, 10.46557/001c.17194 · doi:10.46557/001c.17194
  3. Hao, 2019, De-capacity policy effect on China’s coal industry, Energies, 12, 2331, 10.3390/en12122331 · doi:10.3390/en12122331
  4. Liu, 2020, Convergence of the world’s energy use, Resour. Energy Econ., 62, 101199, 10.1016/j.reseneeco.2020.101199 · doi:10.1016/j.reseneeco.2020.101199
  5. Liu, 2020, Growth sources of green economy and energy consumption in China: new evidence accounting for heterogeneous regimes, Energy J., 41, 10.5547/01956574.41.6.gliu · doi:10.5547/01956574.41.6.gliu
  6. Mannasoo, 2020, Credit constraints and R&D over the boom and bust: firm-level evidence from central and Eastern Europe, Econ. Syst., 44, 100747, 10.1016/j.ecosys.2020.100747 · doi:10.1016/j.ecosys.2020.100747
  7. Tan, 2018, What factors lead to the decline of energy intensity in China’s energy intensive industries?, Energy Econ., 71, 213, 10.1016/j.eneco.2018.02.019 · doi:10.1016/j.eneco.2018.02.019
  8. Wang, 2018, Quota allocation of coal overcapacity reduction among provinces in China, Energy Policy, 116, 170, 10.1016/j.enpol.2018.02.003 · doi:10.1016/j.enpol.2018.02.003
  9. Wen, 2020, How does China’s industrial policy affect firms’ R&D investment? Evidence from ‘China manufacturing 2025’, Appl. Econ., 1
  10. Zhang, 2019, The effect of green finance on energy sustainable development: a case study in China, Emerg. Mark. Financ. Trade, 1

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Metadata

Authors
Wen, H., Lee, C.-C., & Zhou, F.
Venue
Energy Economics
Publisher
Elsevier BV
Published
2021-02
Volume
94
Pages
105099
ISSN
0140-9883 (ISSN-L)
DOI
10.1016/j.eneco.2021.105099
OpenAlex
W3118558734
Cited by
553
References
36
FWCI
79.58
Type
journal article
Language
en
Open access
closed
Licence
Funders
  • Jiangxi Humanities and Social Sciences Key Research Base Project of University (JD18016)
  • Natural Science Foundation of Jiangxi Province (20202BAB201006)

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CoChat. (2026). Citation check: Green credit policy, credit allocation efficiency and upgrade of energy-intensive enterprises. https://app.cochat.ai/papers/10.1016/j.eneco.2021.105099
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Wen, H., Lee, C.-C., & Zhou, F. (2021). Green credit policy, credit allocation efficiency and upgrade of energy-intensive enterprises. Energy Economics. https://doi.org/10.1016/j.eneco.2021.105099

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