The authors of the ECB working paper want to provide policymakers with a set of early warning indicators helpful in guiding decisions on when to activate macroprudential tools targeting excessive credit growth and leverage.
ECB working paper
Source: European Central Bank
Lucia Alessi, European Central Bank
Carsten Detken, European Central Bank
The working paper identifying excessive credit growth and leverage aims at providing policymakers with a set of early warning indicators helpful in guiding decisions on when to activate macroprudential tools targeting excessive credit growth and leverage. To robustly select the key indicators the authors apply the “Random Forest” method, which bootstraps and aggregates a multitude of decision trees. On these identified key indicators they grow a binary classification tree which derives the associated optimal early warning thresholds. The authors say, by using credit to GDP gaps, credit to GDP ratios and credit growth rates, as well as real estate variables in addition to a set of other conditioning variables, the model not only predicts banking crises but is also able to give an indication on which macro-prudential policy instrument would be best suited to address specific vulnerabilities.