The Impact of Geographic Factors on Credit Risk: A Study of Chinese Commercial Banks

Ma Chenchen, Cheng Dongshu, Ge Mei (), Cao Junrui, Kou Jiayang and Chen Ziyang
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Ma Chenchen: School of Economics and Finance, Xi’an Jiaotong University, Xian 710061, China
Cheng Dongshu: Guangzhou Institute of International Finance, Guangzhou University, Guangzhou, China
Ge Mei: Faculty of Business, City University of Macau, Macau 999078, China
Cao Junrui: Dongguan Securities Co., Ltd, Dongguan 523000, China
Kou Jiayang: School of Economics, Sichuan Agricultural University, Sichuan 610000, China
Chen Ziyang: Guangdong Maoming Health Vocational College, Maoming 525000, China

Economics - The Open-Access, Open-Assessment Journal, 2024, vol. 18, issue 1, 20

Abstract: Controlling credit risk is crucial for maintaining financial stability, and the role of geographic factors in this regard is a significant concern for scholars and policymakers. Drawing on the concept of information asymmetry, we developed a theoretical model to analyze how geographic factors influence credit risk. Our theoretical proposition suggests that the spatial organization of banks affects the efficiency of collecting and processing soft information, ultimately impacting the credit risk. To test this proposition, we collected microdata from Chinese commercial banks spanning the period from 2011 to 2022. Employing a mediating effect model, we empirically examined the relationship between spatial organizational structure and credit risk. Our results indicate that the distance between bank operations and functional distance impedes the collection and processing of soft information, thereby exacerbating credit risk in banks. The study focuses on examining how the spatial organizational structure of Chinese commercial banks affects credit risk. By analyzing geographic factors and information asymmetry, the study aims to understand how the organization of banks influences the collection and processing of soft information, which in turn impacts the credit risk. Furthermore, our analysis of the sample reveals that the mediating role of soft information varies between state-owned banks and joint-stock banks due to their distinct customer profiles. On the basis of these findings, we propose several policy recommendations, including a focus on enhancing the collection and processing of soft information, promoting the growth of locally based small and medium-sized banks, and reducing information barriers within bank hierarchies.

Keywords: operational distance; functional distance; soft information; credit risk; mediating effect (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:econoa:v:18:y:2024:i:1:p:20:n:1031

DOI: 10.1515/econ-2022-0086

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