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Activity Number: 477
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract - #304940
Title: Regression for Recovery Rates with Both Continuous and Discrete Characteristic
Author(s): Raffaella Calabrese*+
Companies: University of Milan-Bicocca
Address: Bicocca degli Arcimboldi Street, 8, Milan, International, 20126, Italy
Keywords: recovery rate ; mixed random variable ; mixture ; link function
Abstract:

I propose to consider the recovery rate as a mixed random variable, obtained as the mixture of a Bernoulli random variable and a beta random variable with support (0,1). The recovery rate is considered as a dependent variable in a regression model. I suggest to apply the logistic regression model for the extreme values of the recovery rates. For the recovery rates belonging to the interval (0,1), I propose to model jointly the conditional expectation and the conditional dispersion by using two link functions. This model accommodates skewness and heteroscedastic errors. The estimation procedure is the maximum likelihood method. Finally, the proposed estimation methodology is applied to the survey on loan recovery process of Italian banks, conducted in 2000 by the Bank of Italy.

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