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Can Social Capital Variables Help to Determine Loan to Value Approved by Banks?

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  • Josep Maria Raya

Abstract

This paper sheds some light on the effects of social capital variables (social network data, physical appearance, etc.) on loan-to-value (LTV), a crucial variable to evaluate systemic risk. Using a unique database created by merging several sources of data, we show that the introduction of social capital variables are shown to be statistically significantly related to LTV. In particular, Facebook likes in a month and creditworthiness are a negative determinant of LTV while beauty and certain personality traits play a role in borrowers obtaining a higher LTV. We distinguish these effects depending on the LTV variable used: loan-to-appraisal (entirely under the control of lender) and loan-to-transaction (in which the transaction price can also be influenced). As policy implications we found that social capital variables capture information that would otherwise be unobservable using only the traditional variables in the sense that they are related to information lenders may have at lending that the researchers do not observe.

Suggested Citation

  • Josep Maria Raya, 2022. "Can Social Capital Variables Help to Determine Loan to Value Approved by Banks?," Journal of Real Estate Research, Taylor & Francis Journals, vol. 44(3), pages 355-376, January.
    • Handle: RePEc:taf:rjerxx:v:44:y:2022:i:3:p:355-376
    DOI: 10.1080/08965803.2021.2024678
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