Predicting Bank Loan Recovery Rates in a Mixed Continuous-Discrete model

I propose to consider the recovery rate as a mixed random variable, obtained as the mixture of a Bernoulli and a beta random variables. I estimate the mixture weights and the Bernoulli parameter by two logistic regression models. For the recovery rates belonging to the interval (0,1), I model, jointly, the mean and the dispersion by using two link functions, so I propose the joint beta regression model that accommodates skewness and heteroscedastic errors. The estimation procedure is the maximum likelihood method. Finally, the methodological proposal is applied to a comprehensive survey on loan recovery process of Italian banks. Macroeconomic variables are relevant to explain the recovery rate and allow to estimate it in downturn conditions, as Basel II requires.