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Credit Risk Modeling Of Residential Mortgage Lending In Russia

Author

Listed:
  • Agatha M. Poroshina

    (National Research University Higher School of Economics)

Abstract

This paper analyzes the problems of credit risk modeling of residential mortgage lending in Russia. Using unique mortgage loan and macro data from a regional branch of the Agency of Home Mortgage Lending (2008-2012), we find that borrower and mortgage loan characteristics affect the loan performance and play an important role in predicting default as well as a macroeconomic situation. On the residential mortgage market, borrowers with undeclared income have the lowest probability of default, mainly explained by the difference in declared and real income. Obtained results are robust under parametric and semiparametric specifications with correction for selectivity bias.

Suggested Citation

  • Agatha M. Poroshina, 2014. "Credit Risk Modeling Of Residential Mortgage Lending In Russia," HSE Working papers WP BRP 30/FE/2014, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:30/fe/2014
    as

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    File URL: http://www.hse.ru/data/2014/04/22/1320077335/30FE2014.pdf
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    References listed on IDEAS

    as
    1. Lozinskaya, Agatha & Ozhegov, Evgeniy, 2014. "Estimation of mortgage lending credit risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 3-17.
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    More about this item

    Keywords

    credit risk; default; mortgage lending; sample selection; Russia;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General

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