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Banking Crisis Prediction with Differenced Relative Credit

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  2. Economics, Finance, Business & Management
  3. Applied Economics Quarterly
  4. Vol. 65, Issue 4
  5. pp. 277–297

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Kauko, K., Tölö, E. Banking Crisis Prediction with Differenced Relative Credit. Applied Economics Quarterly, 65(4), 277-297. https://doi.org/10.3790/aeq.65.4.277
Kauko, Karlo and Tölö, Eero "Banking Crisis Prediction with Differenced Relative Credit" Applied Economics Quarterly 65.4, , 277-297. https://doi.org/10.3790/aeq.65.4.277
Kauko, Karlo/Tölö, Eero: Banking Crisis Prediction with Differenced Relative Credit, in: Applied Economics Quarterly, vol. 65, iss. 4, 277-297, [online] https://doi.org/10.3790/aeq.65.4.277
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Banking Crisis Prediction with Differenced Relative Credit

Kauko, Karlo | Tölö, Eero

Applied Economics Quarterly, Vol. 65 (2019), Iss. 4 : pp. 277–297

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Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/aeq.65.4.277
Language
German
Pages
21
Keywords

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€ 26.00 (incl. local VAT if applicable)

Author Details

Kauko, Karlo; corresponding author. Bank of Finland, Snellmaninaukio, 00101 Helsinki, Finland. Tel.: +358 50 387 0337

Tölö, Eero; Bank of Finland and University of Helsinki, Snellmaninaukio, 00101 Helsinki, Finland

References

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Abstract

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).

Table of Contents

Section Title Page Action Price
Karlo Kauko / Eero Tölö: Banking Crisis Prediction with Differenced Relative Credit 1
Abstract 1
1. Introduction 1
1.1 Research Question 1
1.2 Previous Literature 2
2. Method and Data 4
2.1 Alternative Ways of Calculating the Indicator 4
2.2 Data 6
2.3 Assessment Method 7
3. Results 9
4. Forecasting Horizons 1
5. Robustness Test 1
6. Conclusions 1
References 2

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