Macroeconomic environment and the future performance of loans: Evidence from three peer-to-peer platforms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F24%3A00139609" target="_blank" >RIV/00216224:14560/24:00139609 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S105752192400348X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S105752192400348X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.irfa.2024.103416" target="_blank" >10.1016/j.irfa.2024.103416</a>
Alternative languages
Result language
angličtina
Original language name
Macroeconomic environment and the future performance of loans: Evidence from three peer-to-peer platforms
Original language description
The literature on peer-to-peer loan market performance focuses predominantly on the microlevel variables connected to individual borrower or loan characteristics. We hypothesize that the economic environment, reflected by macroeconomic variables at the time of loan origination, should play a role in explaining loans’ future performance. Our dataset comprises two US-based platforms and one UK-based platform, which provides a rich field to verify our hypothesis with numerous loan-related variables. Specifically, we consider Lending Club with 1,169,976 individual loans and 128 variables, Prosper with 386,685 loans and 142 variables, and Zopa with 440,493 loans and 192 variables. Using linear and threshold regressions, we observe three main findings: (i) accounting for the macroeconomic environment systematically improves our understanding of the variation in the future performance of individual loans; (ii) demand-side variables, particularly the unemployment rate and industrial production, have stronger effects as supply-side and economic uncertainty variables; and (iii) the importance (effect size) of the macroeconomic environment is at least at the level of that of calendar and geographic variables but much smaller than the importance of loan or borrower characteristics. These results suggest that the economic environment might be useful in individual loan-level credit risk models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
<a href="/en/project/GF22-35130K" target="_blank" >GF22-35130K: Network-based credit risk models on P2P lending markets</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
ISSN
1057-5219
e-ISSN
1873-8079
Volume of the periodical
95
Issue of the periodical within the volume
October
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
16
Pages from-to
1-16
UT code for WoS article
001267730500001
EID of the result in the Scopus database
2-s2.0-85197519001