Econometric modeling risk of consumer loans

Ludmila Nivorozhkina (), Lilia Ovcharova () and Tatiana Sinyavskaya ()
Additional contact information
Ludmila Nivorozhkina: Rostov State Economic University, Rostov-on-Don, Russia
Lilia Ovcharova: Higher School of Economics, Moscow, Russia
Tatiana Sinyavskaya: Rostov State Economic University, Rostov-on-Don, Russia

Applied Econometrics, 2013, vol. 30, issue 2, 65-76

Abstract: The paper regards problems of risk estimation in consumer lending and credit scoring. Econometric bivariate probit models estimated on GGS data are used to evaluate risk of having bank debt on condition that household have bank loan. The results allow profiling safe and unsafe borrowers. Keywords: credit risk; credit scoring; bivariate probit model.

Keywords: credit risk; credit scoring; bivariate probit model (search for similar items in EconPapers)
JEL-codes: C01 D14 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://pe.cemi.rssi.ru/pe_2013_2_65-76.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0210

Access Statistics for this article

Applied Econometrics is currently edited by Anatoly Peresetsky

More articles in Applied Econometrics from Russian Presidential Academy of National Economy and Public Administration (RANEPA)
Bibliographic data for series maintained by Anatoly Peresetsky ().