A FRAMEWORK FOR ESTIMATING STRUCTURAL MODELS
OF MORTGAGE DEBTORS’ BEHAVIOR
JUAN ESTEBAN CARRANZA
Abstract. Empirical techniques are discussed to estimate structural models
of mortgage holders’ behavior. The discussed methodologies yield estimates
of the primitives of the model that allow computation of default probabilities
and consistent simulation of counterfactual equilibria. Techniques to estimate
static version of the model, as well as dynamic ones are discussed. It is shown
that popular multinomial techniques impose severe structural restrictions on
the underlying behavioral model. The framework is general enough to allow for
multiple modelling variations and is a potential contribution to the empirical
literature on mortgage default and pricing. No results are shown yet.
1. Introduction
This paper discusses alternative approaches to estimate models of behavior of
mortgage debtors. Specifically, the focus is on the understanding of default de-
cisions. The goal is the development of empirical techniques that yield estimates
of the structural parameters of the model that generates observed behavior. Such
estimation would allow the computation of default probabilities and the evalua-
tion of counterfactual equilibria in a manner that is consistent with an underlying
economic model.
The literature on the behavior of homeowners with mortgages has relied on con-
tingent claims models a la Black and Scholes, treating mortgages and houses as
any other financial asset. On the empirical side, it is very common the use of
multinomial qualitative regressions, such as proportional hazard models, to corre-
late behavior with the theoretically relevant variables. Such models are difficult to
tie to an underlying behavioral model that incorporates the specificities of mortgage
financing; therefore the empirical models and the obtained estimates are difficult to
interpret as more than empirical regularities. For example, it will be shown below
that multinomial choice models impose structural restrictions on the underlying