An Early Warning Model for Predicting Credit Booms using Macroeconomic Aggregates
In this paper, we propose an alternative methodology to determine the existence of credit booms, which is a complex and crucial issue for policymakers. In particular, we exploit the Mendoza and Terrones (2008)’s idea that macroeconomic aggregates other than the credit growth rate contain valuable information to predict credit boom episodes. Our econometric method is used to estimate and predict the probability of being in a credit boom. We run empirical exercises on quarterly data for six Latin American countries between 1996 and 2011. In order to capture simultaneously model and parameter uncertainty, we implement the Bayesian model averaging method. As we employ panel data, the estimates may be used to predict booms of countries which are not considered in the estimation. Overall, our findings show that macroeconomic variables contain valuable information to predict credit booms. In fact, with our method the probability of detecting a credit boom is 80%, while the probability of not having false alarms is greater than 92%.
|Date of creation:||Jul 2012|
|Date of revision:|
|Contact details of provider:|| Postal: Cra 7 # 14-78 Semi-sótano|
Phone: (57-1) 3431111
Fax: (57-1) 2841686
Web page: http://www.banrep.gov.co/es/publicaciones-buscador/23
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jeffrey A. Frankel & George Saravelos, 2010. "Are Leading Indicators of Financial Crises Useful for Assessing Country Vulnerability? Evidence from the 2008-09 Global Crisis," NBER Working Papers 16047, National Bureau of Economic Research, Inc.
When requesting a correction, please mention this item's handle: RePEc:bdr:borrec:723. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Clorith Angélica Bahos Olivera)
If references are entirely missing, you can add them using this form.