Macroeconomic variable selection for creditor recovery rates

We study the relationship between U.S. corporate bond recovery rates and macroeconomic variables used in the credit risk literature. The least absolute shrinkage and selection operator (LASSO) is used in selecting macroeconomic variables. The LASSO-selected macroeconomic variables are considered to be explanatory variables in ordinary least squares regressions, bootstrap aggregating (bagging), regression trees, boosting, LASSO, ridge regression and support vector regression techniques. We compare the out-of-sample predictive power of two types of models (LASSO-selected models with models that add principal components derived from 179 macroeconomic variables as explanatory variables). We find the recovery models with LASSO-selected macroeconomic variables outperform suggested models in the literature.