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Gender discrimination in online peer-to-peer credit lending: evidence from a lending platform in China

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Abstract

Gender discrimination in accessing financial resources is a mounting concern in developing countries, but empirical evidence of such discrimination is limited. Using data collected from one of the largest peer-to-peer (P2P) lending platforms in China, we investigate potential gender discrimination in online P2P credit lending market in China. The results illustrate that female borrowers are more likely to be funded than male borrowers; but in exchange for higher funding success, female borrowers are found to pay higher interest rates. Moreover, the default rates of loans from female borrowers are significantly lower than those from male borrowers. Finally, we found that a borrower’s gender moderates the relationships between the borrower’ attributes and lending outcomes. The findings imply that profit-based statistical discrimination and costly taste-based discrimination co-exist in this online peer-to-peer lending market, but the underlying reasons for the discriminations are different. The implications for research and practice along with the limitations of this study are discussed accordingly.

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References

  1. Agier, I., & Szafarz, A. (2013). Microfinance and gender: Is there a glass ceiling on loan size? World Development, 42(1), 165–181.

    Article  Google Scholar 

  2. Agier, I., & Szafarz, A. (2013). Subjectivity in credit allocation to micro-entrepreneurs: evidence from Brazil. Small Business Economics, 41(1), 263–275.

    Article  Google Scholar 

  3. Alesina, A. F., Lotti, F., & Mistrulli, P. E. (2013). Do women pay more for credit? evidence from Italy. Journal of the European Economic Association, 11(s1), 45–66.

    Article  Google Scholar 

  4. Arrow, K. (1973). The Theory of Discrimination. In O. Ashenfelter & A. Rees (Eds.), Discrimination in labor markets. Princeton, NJ: Princeton University Press.

    Google Scholar 

  5. Barasinska, N. (2009). The role of gender in lending business: Evidence from an online market for peer-to-peer lending (pp. 1–25). New York: The New York Times.

    Google Scholar 

  6. Barasinska, N. 2010. Would lehman sisters have done it differently? An empirical analysis of gender differences in investment behavior, AAAI Spring Symposium on Intelligent Information Privacy Management, Stanford University, Palo Alto, CA, 2010.

  7. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261–292.

    Article  Google Scholar 

  8. Baydas, M. M., Meyer, R. L., & Aguilera-Alfred, N. (1994). Discrimination against women in formal credit markets: reality or rhetoric? World Development, 22(7), 1073–1082.

    Article  Google Scholar 

  9. Beck, T., Behr, P., & Guettler, A. (2013). Gender and banking: Are women better loan officers? Review of Finance, 17(4), 1279–1321.

    Article  Google Scholar 

  10. Becker, G. S. (2010). The economics of discrimination. Chicago: University of Chicago press.

    Google Scholar 

  11. Bellucci, A., Borisov, A., & Zazzaro, A. (2010). Does gender matter in bank-firm relationships? Evidence from small business lending. Journal of Banking & Finance, 34(12), 2968–2984.

    Article  Google Scholar 

  12. Berger, M. (1990). Sex differences in access to a small enterprise development fund in Peru. World Development, 18(5), 695–705.

    Article  Google Scholar 

  13. Berkovich, E. (2011). Search and herding effects in peer-to-peer lending: Evidence from prosper. com. Annals of Finance, 7(3), 389–405.

    Article  Google Scholar 

  14. Blanchflower, D. G., Levine, P. B., & Zimmerman, D. J. (2003). Discrimination in the small-business credit market. Review of Economics and Statistics, 85(4), 930–943.

    Article  Google Scholar 

  15. Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. The Journal of Economic Perspectives, 14(4), 75–99.

    Article  Google Scholar 

  16. Brana, S. (2013). Microcredit: An answer to the gender problem in funding? Small Business Economics, 40(1), 87–100.

    Article  Google Scholar 

  17. Browne, L. E., & Tootell, G. M. (1995). Mortgage lending in Boston: A response to the critics. New England Economic Review, 1995, 53–78.

    Google Scholar 

  18. Carter, S., Shaw, E., Lam, W., & Wilson, F. (2007). Gender, entrepreneurship, and bank lending: The criteria and processes used by bank loan officers in assessing applications. Entrepreneurship Theory and Practice, 31(3), 427–444.

    Article  Google Scholar 

  19. Cavalluzzo, K., & Wolken, J. (2005). Small business loan turndowns, personal wealth, and discrimination. The Journal of Business, 78(6), 2153–2178.

    Article  Google Scholar 

  20. Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766.

    Article  Google Scholar 

  21. Chen, D. Y., Ding, J., Jiang, S. J., and Zhang, N. 2011. Antecedents of initial trust in the online peer-to-peer lending marketplace, in 2011 International Conference on Innovation and Information Management, (pp. 1–4). Tianjing, China: IEEE Xplore.

  22. Collier, B., and Hampshire, R. 2010. Sending mixed signals: Multilevel reputation effects in peer-to-peer lending markets, ACM Conference on Computer Supported Cooperative Work, Savannah, Georhia, USA, 2010, pp. 197–206.

  23. Cotter, D. A., Hermsen, J. M., Ovadia, S., & Vanneman, R. (2001). The Glass ceiling effect. Social Forces, 80(2), 655–681.

    Article  Google Scholar 

  24. D’Espallier, B., Guérin, I., & Mersland, R. (2011). Women and repayment in microfinance: A global analysis. World Development, 39(5), 758–772.

    Article  Google Scholar 

  25. Davis, J. M., & Tuttle, B. M. (2013). A heuristic–systematic model of end-user information processing when encountering is exceptions. Information & Management, 50(2), 125–133.

    Article  Google Scholar 

  26. De Mel, S., McKenzie, D., & Woodruff, C. (2009). Are women more credit constrained? Experimental evidence on gender and microenterprise returns. American Economic Journal: Applied Economics, 1(3), 1–32.

    Google Scholar 

  27. Doleac, J. L., & Stein, L. C. (2013). The visible hand: Race and online market outcomes. The Economic Journal, 123(572), F469–F492.

    Article  Google Scholar 

  28. Duarte, J., Siegel, S., & Young, L. (2012). Trust and credit: The role of appearance in peer-to-peer lending. Review of Financial Studies, 25(8), 2455–2484.

    Article  Google Scholar 

  29. Duleep, H. O., & Sanders, S. (1992). Discrimination at the top: American-born Asian and white men. Industrial Relations: A Journal of Economy and Society, 31(3), 416–432.

    Google Scholar 

  30. Everett, CR. 2008. Group membership, relationship banking and loan default risk: The case of online social lending, in Working Paper.

  31. Fernandez, M. (1998). Asian Indian Americans in the bay area and the glass ceiling. Sociological Perspectives, 41(1), 19–49.

    Article  Google Scholar 

  32. Ferran, C., & Watts, S. (2008). Videoconferencing in the field: A heuristic processing model. Management Science, 54(9), 1565–1578.

    Article  Google Scholar 

  33. Fidell, B. G., and Tabachnick, L. S. 2007. Using multivariate statistics (5th Ed), (Pearson: Boston, Montreal).

  34. Fletschner, D. (2009). Rural women’s access to credit: Market imperfections and intrahousehold dynamics. World Development, 37(3), 618–631.

    Article  Google Scholar 

  35. Frankforter, S. A. (1996). The progression of women beyond the glass ceiling. Journal of Social Behavior and Personality, 11(5), 121–132.

    Google Scholar 

  36. Ge, Y., & Qiu, J. (2007). Financial development, bank discrimination and trade credit. Journal of Banking & Finance, 31(2), 513–530.

    Article  Google Scholar 

  37. Greiner, M. E., & Wang, H. (2010). Building consumer-to-consumer trust in e-finance marketplaces: An empirical analysis. International Journal of Electronic Commerce, 15(2), 105–136.

    Article  Google Scholar 

  38. Han, S. (2004). Discrimination in lending: Theory and evidence. Journal of Real Estate Finance and Economics, 29(1), 5–46.

    Article  Google Scholar 

  39. Herzenstein, M., Dholakia, U. M., & Andrews, R. L. (2011). Strategic herding behavior in peer-to-peer loan auctions. Journal of Interactive Marketing, 25(1), 27–36.

    Article  Google Scholar 

  40. Igbaria, M., & Baroudi, J. J. (1995). The impact of job performance evaluations on career advancement prospects: An examination of gender differences in the is workplace. MIS Quarterly, 19(1), 107–123.

    Article  Google Scholar 

  41. Jaccard, J., and Turrist, R. 2003. Interaction effects in multiple regression in Sage University Papers Series on Quantitative Applications in the Social Sciences, (2nd Ed.), Thousand Oaks, CA: Sage.

  42. Jappelli, T. (1990). Who is credit constrained in the us economy? The Quarterly Journal of Economics, 105(1), 219–234.

    Article  Google Scholar 

  43. Klapper, L. F., & Parker, S. C. (2010). Gender and the business environment for new firm creation. World Bank Research Observer, 26(2), 237–257.

    Article  Google Scholar 

  44. Kuhn, P., & Shen, K. (2013). Gender discrimination in job ads: Evidence from China. The Quarterly Journal of Economics, 128(1), 287–336.

    Article  Google Scholar 

  45. Lee, E., & Lee, B. (2012). Herding behavior in online p2p lending: An empirical investigation. Electronic Commerce Research and Applications, 2012(11), 495–503.

    Article  Google Scholar 

  46. Lin, M. F., Prabhala, N. R., and Viswanathan, S. 2009. Social networks as signaling mechanisms: Evidence from online peer-to-peer lending,” Working Paper).

  47. Lin, M. F., Prabhala, N. R., & Viswanathan, S. (2013). Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending. Management Science, 59(1), 17–35.

    Article  Google Scholar 

  48. Liu, D., Brass, D. J., Lu, Y., & Chen, D. Y. (2015). Friendships in online peer-to-peer lending: Pipes, prisms, and relational herding. MIS Quarterly, 39(3), 729–742.

    Article  Google Scholar 

  49. Luke, D. A. (2004). Multilevel modeling (3rd ed.). Sage: Thousand Oaks.

    Book  Google Scholar 

  50. Luo, B., & Lin, Z. (2013). A decision tree model for herd behavior and empirical evidence from the online p2p lending market. Information Systems and e-Business Management, 11(1), 141–160.

    Article  Google Scholar 

  51. Majchrzak, A., & Jarvenpaa, S. L. (2010). Safe contexts for interorganizaitonal collaborations among homeland security professionals. Journal of Management Information Systems, 131(4), 9–38.

    Google Scholar 

  52. McCarter, E. (2006). Women and microfinance: Why we should do more. U. Md. LJ Race, Religion, Gender & Class, 6, 353.

    Google Scholar 

  53. Munnell, A. H., Tootell, G. M., Browne, L. E., & McEneaney, J. (1996). Mortgage lending in Boston: Interpreting hmda data. The American Economic Review, 86(1), 25–53.

    Google Scholar 

  54. Petty, R. E., & Brinol, P. (2008). Persuasion: From single to multiple to metacognitive processes. Perspectives on Psychological Science, 3(2), 137–147.

    Article  Google Scholar 

  55. Phelps, E. S. (1972). The statistical theory of racism and sexism. The American Economic Review, 62(4), 659–661.

    Google Scholar 

  56. Puro, L., Teich, J. E., Wallenius, H., & Wallenius, J. (2010). Borrower decision aid for people-to-people lending. Decision Support System, 49(1), 52–60.

    Article  Google Scholar 

  57. Rigbi, O. (2013). The effects of usury laws: Evidence from the online loan market. Review of Economics and Statistics, 95(4), 1238–1248.

    Article  Google Scholar 

  58. Rosti, L., & Chelli, F. (2005). Gender discrimination, entrepreneurial talent and self-employment. Small Business Economics, 24(2), 131–142.

    Article  Google Scholar 

  59. Stiglitz, J. E. (1973). Approaches to the economics of discrimination. The American Economic Review, 63(2), 287–295.

    Google Scholar 

  60. Stiglitz, J. E., & Andrew, M. W. (1981). Credit rationing in markets with imperfect information. American Economic Review, 71(3), 393–410.

    Google Scholar 

  61. Storey, D. J. (2004). Racial and gender discrimination in the micro firms credit market?: Evidence from Trinidad and Tobago. Small Business Economics, 23(5), 401–422.

    Article  Google Scholar 

  62. Sunden, A. E., & Surette, B. J. (1998). Gender differences in the allocation of assets in retirement savings plans. American Economic Review, 88(2), 207–211.

    Google Scholar 

  63. Sydnor, J. R., & Pope, D. G. (2011). What’s a picture? Evidence of discriminations of loan fundability in the prosper. com marketplace. Journal of Human Resources, 46(1), 53–92.

    Google Scholar 

  64. Truman, G. E., & Baroudi, J. J. (1994). Gender differences in the information systems managerial ranks: An assessment of potential discriminatory practices. MIS Quarterly, 18(2), 129–142.

    Article  Google Scholar 

  65. Verheul, I., & Thurik, R. (2001). Start-up capital: Does gender matter? Small Business Economics, 16(4), 329–346.

    Article  Google Scholar 

  66. Walter, T. 2008. Competition to default: Racial discrimination in the market for online peer-to-peer lending in Business, pp. 1–44.

  67. Weller, C. E. (2009). Credit access, the costs of credit and credit market discrimination. The Review of Black Political Economy, 36(1), 7–28.

    Article  Google Scholar 

  68. Yum, H., Lee, B., & Chae, M. (2012). From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms. Electronic Commerce Research and Applications, 11(5), 469–483.

    Article  Google Scholar 

  69. Zhang, J. J., & Liu, P. (2012). Rational herding in microloan markets. Management Science, 58(2), 892–912.

    Article  Google Scholar 

  70. Zhang, K. Z. K., Zhao, S. J., Cheung, C. M. K., & Lee, M. K. O. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic-systematic model. Decision Support Systems, 67(2014), 78–89.

    Article  Google Scholar 

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Acknowledgements

This study is funded by the National Science Foundation of China (Project No. 71302008 and 71471125).

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Authors and Affiliations

  1. Research Center for Smarter Supply Chain, Soochow Think Tank & Dongwu Business School, Soochow University, Suzhou, China

    Dongyu Chen & Fujun Lai

  2. College of Business and Economics, Towson University, Towson, USA

    Xiaolin Li

  3. College of Business, University of Southern Mississippi, Long Beach, MS, 39560, USA

    Fujun Lai

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  1. Dongyu Chen
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Correspondence to Fujun Lai.

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Chen, D., Li, X. & Lai, F. Gender discrimination in online peer-to-peer credit lending: evidence from a lending platform in China. Electron Commer Res 17, 553–583 (2017). https://doi.org/10.1007/s10660-016-9247-2

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