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Local bias versus home bias: Evidence from debt-based crowdfunding

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Listed:
  • Jianwen Li
  • Yang Zhou
  • Jinyan Hu
  • Feng Guo

Abstract

Local bias and home bias are conventional phenomena in the financial market. This paper examines whether local bias and home bias exist in virtual loan transactions on the debt-based crowdfunding marketplace. Using loan-level and lender-level transaction data from a large crowdfunding marketplace in China and employing a potential-dyad approach, we find that lenders are more likely to invest in local borrowers rather than in their hometown borrowers, indicating that local bias exists in this virtual marketplace rather than home bias. More interestingly, the local bias is more pronounced for local lenders whose work area and hometown are the same than for moving lenders who leave their hometowns. Furthermore, lenders’ local bias is more pronounced if lenders (borrowers) are from more trust-propensity (trustworthy) regions. Finally, we find that lending to local borrowers cannot significantly increase the welfare of lenders. Various specifications, alternative dependent variables, and alternative potential-dyad sets show that our empirical-based results are robust.

Suggested Citation

  • Jianwen Li & Yang Zhou & Jinyan Hu & Feng Guo, 2024. "Local bias versus home bias: Evidence from debt-based crowdfunding," Applied Economics, Taylor & Francis Journals, vol. 56(23), pages 2705-2719, May.
  • Handle: RePEc:taf:applec:v:56:y:2024:i:23:p:2705-2719
    DOI: 10.1080/00036846.2023.2200230
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