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Cited by 503

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Inside the black box: Bank credit allocation in China’s private sector

Open access
Firth, Michael, Lin, Chen, Liu, Ping, Wong, Sonia M.L.·2009·Journal of Banking & Finance

Abstract

This study examines how the Chinese state-owned banks allocate loans to private firms. We find that the banks extend loans to financially healthier and better-governed firms, which implies that the banks use commercial judgments in this segment of the market. We also find that having the state as a minority owner helps firms obtain bank loans and this suggests that political connections play a role in gaining access to bank finance. In addition, we find that commercial judgments are important determinants of the lending decisions for manufacturing firms, large firms, and firms located in regions with a more developed banking sector; political connections are important for firms in service industries, large firms, and firms located in areas with a less developed banking sector.

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Registry

Crossref · 10.1016/j.jbankfin.2008.12.008

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Metadata

Authors
Firth, M., Lin, C., Liu, P., & Wong, S. M. L.
Venue
Journal of Banking & Finance
Publisher
Elsevier BV
Published
2009-06
Volume
33
Issue
6
Pages
1144-1155
ISSN
0378-4266 (ISSN-L)
OpenAlex
W3122862660
Cited by
503
References
49
FWCI
20.73
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Inside the black box: Bank credit allocation in China’s private sector. https://app.cochat.ai/papers/10.1016/j.jbankfin.2008.12.008
The paper
Firth, M., Lin, C., Liu, P., & Wong, S. M. L. (2009). Inside the black box: Bank credit allocation in China’s private sector. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2008.12.008

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.