When to Lean Against the Wind

Moritz Schularick, Paul Wachtel and Richter, Björn

No 12188, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: This paper shows that policy-makers can distinguish between good and bad credit booms with high accuracy and they can do so in real time. Evidence from 17 countries over nearly 150 years of modern financial history shows that credit booms that are accompanied by house price booms and a rising loan-to-deposit-ratio are much more likely to end in a systemic banking crisis. We evaluate the predictive accuracy for different classification models and show that the characteristics of the credit boom contain valuable information for sorting the data into good and bad booms. Importantly, we demonstrate that policy-makers have the ability to spot dangerous credit booms on the basis of data available in real time. We also show that these results are robust across alternative specifications and time-periods.

Keywords: Banking crisis; Crisis prediction; Credit booms; Macroprudential policy (search for similar items in EconPapers)
JEL-codes: E32 E52 G01 (search for similar items in EconPapers)
Date: 2017-07
New Economics Papers: this item is included in nep-ban, nep-cba, nep-his and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

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Journal Article: When to Lean against the Wind (2021)
Working Paper: When to Lean Against the Wind (2018)
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