Abstract
This paper builds a three-stage sequential logit model to examine bank credit demand and constraints faced by non-agricultural self-employed households in China. Our analysis reveals a stark reality: In 2013 and 2015, over half of self-employed households seeking bank loans faced credit constraints, either discouraged from applying or rejected by banks. While we found no evidence of gender or age discrimination in loan approvals, factors like wealth, saving status, education and financial literacy significantly impact the likelihood of credit demand, application, and granting. Notably, less wealthy and less-educated households are significantly more likely to be credit constrained, highlighting the need for targeted policy interventions to promote self-employment. Furthermore, our findings suggest that informal loans often supplement bank loans in financing self-employment businesses, implying a potential underestimate of credit constraints in the bank credit market.
Session ID 66: Empirical Finance III
Session ID 66: Empirical Finance III
Original language | English |
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Publication status | Published - 9 Jun 2024 |
Event | Conference of the International Association for Applied Econometrics (IAAE) 2024 Annual Conference - Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China Duration: 7 Jun 2024 → 9 Jun 2024 https://conf.xmu.edu.cn/iaae2024/ (IAAE 2024 Annual Conference information) |
Conference
Conference | Conference of the International Association for Applied Econometrics (IAAE) 2024 Annual Conference |
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Abbreviated title | IAAE 2024 Annual Conference |
Country/Territory | China |
City | Xiamen |
Period | 7/06/24 → 9/06/24 |
Internet address |
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Keywords
- self-employment
- credit demand
- credit constraints
- sequential logit model