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.
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