¹University of Edinburgh, Edinburgh, Lothian, UK

Correspondence: J Crook, Credit Research Centre, Management School and Economics, WRB 50 George Square, University of Edinburgh, Edinburgh, Lothian, EH89JY, UK. E-mail: j.crook@ed.ac.uk

Received December 2007; Accepted September 2008; Published online 10 December 2008.

Abstract

Survival analysis can be applied to build models for time to default on debt. In this paper, we report an application of survival analysis to model default on a large data set of credit card accounts. We explore the hypothesis that probability of default (PD) is affected by general conditions in the economy over time. These macroeconomic variables (MVs) cannot readily be included in logistic regression models. However, survival analysis provides a framework for their inclusion as time-varying covariates. Various MVs, such as interest rate and unemployment rate, are included in the analysis. We show that inclusion of these indicators improves model fit and affects PD yielding a modest improvement in predictions of default on an independent test set.