 Semiparametric estimation of default probability: Evidence from the Prosper online credit marketXiaofeng Li, Ying Shang and Zhi Su Economics Letters, 2015, vol. 127, issue C, 54-57 Abstract: This paper examines the effects of a person’s past financial characteristics on his likelihood to default in ex-post loan performance using both Probit and a semiparametric single-index estimator proposed by Klein and Spady (1993). The data used in the paper are a sample of individual loans generated on Prosper, a large US online lending market. The out of sample predictions and the model specification test suggest a misspecification of the Probit model due to the violation of the normality assumption. Estimation results suggest that a borrower’s past financial credit score is a reasonably good indicator of one’s loan performance. In general, the higher one’s credit score ranking, the lower the probability that one would default. One exceptional finding is that a borrower with score ranking B is less likely to default than a borrower with score ranking A. Such a finding suggests that individuals who are in the middle range of credit grades may be more financially credit-dependent than those with higher rankings. As a result, they are more willing to keep their loans in good standings. Keywords: Semiparametric method; Single index model; Default probability (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:127:y:2015:i:c:p:54-57 DOI: 10.1016/j.econlet.2014.11.033 Access Statistics for this article Economics Letters is currently edited by Economics Letters Editorial Office More articles in Economics Letters from Elsevier |
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