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The Role of Credit in Predicting US Recessions
Author(s) -
Ponka Harri
Publication year - 2017
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2448
Subject(s) - recession , probit model , economics , econometrics , bond , control variable , sample (material) , credit risk , probit , actuarial science , finance , statistics , keynesian economics , mathematics , chemistry , chromatography
We study the role of credit in forecasting US recession periods with probit models. We employ both classical recession predictors and common factors based on a large panel of financial and macroeconomic variables as control variables. Our findings suggest that a number of credit variables are useful predictors of US recessions over and above the control variables both in and out of sample. In particular, the excess bond premium, capturing the cyclical changes in the relationship between default risk and credit spreads, is found to be a powerful predictor of recession periods. Copyright © 2016 John Wiley & Sons, Ltd.