What Do a Billion Observations Say About Distance and Relationship Lending?

54 Pages Posted: 17 Jul 2018 Last revised: 15 Jun 2019

See all articles by Haoyu Gao

Haoyu Gao

Central University of Finance and Economics (CUFE)

Hong Ru

Nanyang Technological University (NTU)

Xiaoguang Yang

Chinese Academy of Sciences (CAS)

Date Written: June 14, 2019

Abstract

Using a large sample of the locations of bank branches and corporate borrowers in China, we measure lender-borrower geographic proximity and find a nontrivial amount of distant lending. Banks overcome great physical distance to borrowers by collecting soft information via interfirm network. We use novel data on monthly internal loan ratings for each loan to directly measure soft information by tracing whether banks downgrade ratings before delinquency. When distant borrowers are connected to banks’ local borrowers, banks can predict delinquency events more accurately. This effect is more pronounced for small and medium enterprises. Consequently, connected borrowers’ delinquency rates are lower.

Keywords: Big Data; Distance; Firm Network; Soft Information

JEL Classification: G21, G28, G32, L51

Suggested Citation

Gao, Haoyu and Ru, Hong and Yang, Xiaoguang, What Do a Billion Observations Say About Distance and Relationship Lending? (June 14, 2019). Available at SSRN: https://ssrn.com/abstract=3195616 or http://dx.doi.org/10.2139/ssrn.3195616

Haoyu Gao

Central University of Finance and Economics (CUFE) ( email )

39 South College Road
Haidian District
Beijing, Beijing 100081
China

Hong Ru (Contact Author)

Nanyang Technological University (NTU) ( email )

S3-B1A-07
50 Nanyang Avenue
Singapore, 639798
Singapore
(+65) 67904661 (Phone)

HOME PAGE: http://https://hongru.mit.edu/

Xiaoguang Yang

Chinese Academy of Sciences (CAS) ( email )

52 Sanlihe Rd.
Datun Road, Anwai
Beijing, Xicheng District 100864
China

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