Abstract
The mortgage crisis that started in the U.S. in 2007 and lasted until 2009 was characterized by an unusually large number of defaults on the subprime mortgage market. As a result, it developed into a global economic recession and placed the stability of the world banking system in jeopardy. Therefore, the issues of credit risk modeling showed the shortcomings of the current credit risk practice. Truncation, or partial observability, and simultaneous equations bias causes sample selection bias. As a result, parameter estimates are biased and inconsistent. Firstly, we provide an overview of current approaches in the mortgage literature to control for the sample selection bias correction, such as the Heckman model and bivariate probit model with selection. Secondly, a review of the most significant mortgage studies discussing this problem is introduced. Specifically, different structural models, specific datasets and empirical results are regarded. In addition, we discuss such key credit risk determinants as borrower characteristics, terms of the mortgage contract, mortgage characteristics, and macroeconomic conditions. Finally, we conclude the discussion with possible research questions.
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Acknowledgements
The author would like to thank Anil K. Bera, Andreas A. Woudenberg and Alexander Karminsky for their helpful comments. This study was carried out with support from “The National Research University Higher School of Economics’ Academic Fund Program in 2013–2014, Research Grant No. 12-01-0130.” This survey was presented at the Perm Winter School-2013. The author is responsible for any errors that remain.
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Lozinskaia, A. (2015). Sample Selection Bias in Mortgage Market Credit Risk Modeling. In: Bera, A., Ivliev, S., Lillo, F. (eds) Financial Econometrics and Empirical Market Microstructure. Springer, Cham. https://doi.org/10.1007/978-3-319-09946-0_17
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DOI: https://doi.org/10.1007/978-3-319-09946-0_17
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