Banking Crisis Prediction with Differenced Relative Credit
Karlo Kauko and
Eero Tölö
Applied Economics Quarterly (formerly: Konjunkturpolitik), 2019, vol. 65, issue 4, 277-297
Abstract:
Indicators based on the ratio of credit to GDP have been found to be highly useful predictors of banking crises. Differences in this ratio seem a highly promising early warning indicator. We test a large number of slightly different versions of the differenced credit-to-GDP ratio with data on euro area members. The optimal time interval of the difference is about two years. Using the moving average of GDP over several years rather than the latest annual data is shown to have little impact on forecasting performance. The proposed indicator demonstrates particular promise at relatively short forecasting horizons (2 – 3 years).
Keywords: banking crises; early warning indicators; differenced relative credit; credit intensity; countercyclical capital buffer (search for similar items in EconPapers)
JEL-codes: G01 G17 G28 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.3790/aeq.65.4.277 (application/pdf)
Access to full text is restricted to subscribers (2008 onwards); Pay-per-view access from https://elibrary.duncker-humblot.com/journals/aeq (2008 onwards) and http://www.genios.de (2008 onwards)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:dah:aeqaeq:v65_y2019_i4_q4_p277-297
Ordering information: This journal article can be ordered from
https://www.duncker-humblot.de/zeitschriften/aeq
Access Statistics for this article
Applied Economics Quarterly (formerly: Konjunkturpolitik) is currently edited by Cinzia Alcidi, Christian Dreger and Daniel Gros
More articles in Applied Economics Quarterly (formerly: Konjunkturpolitik) from Duncker & Humblot GmbH, Berlin
Bibliographic data for series maintained by E-Publishing-Team ().