Financial development in the aftermath of banking crises
This paper examines the dynamic impact of systemic banking crises on financial development. Causal effects are identified using a propensity-score-based method for time series and panel data. Specifically, to address the non-random nature of banking crisis onsets, we apply inverse propensity score w...
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Published in | Journal of international money and finance Vol. 157; p. 103395 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
01.08.2025
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ISSN | 0261-5606 |
DOI | 10.1016/j.jimonfin.2025.103395 |
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Abstract | This paper examines the dynamic impact of systemic banking crises on financial development. Causal effects are identified using a propensity-score-based method for time series and panel data. Specifically, to address the non-random nature of banking crisis onsets, we apply inverse propensity score weighting to create a quasi-random distribution of crisis and non-crisis episodes. The appropriate weights are derived from a banking crisis prediction model that accounts for financial development in the run-up to crises. Using data on banking crises and a comprehensive set of financial development indicators for 174 countries from 1980 to 2019, we present novel evidence demonstrating that banking crisis shocks have a persistent negative effect on financial development. This finding holds across multiple dimensions of financial development.
•Using data for 174 countries over the period 1980–2019, we present novel evidence that demonstrates banking crisis shocks have a negative persistent effect on financial development.•This finding holds across multiple dimensions of financial development.•Causal effects are identified using inverse propensity score weighting (IPW), with the weights estimated from a banking crisis prediction model. |
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AbstractList | This paper examines the dynamic impact of systemic banking crises on financial development. Causal effects are identified using a propensity-score-based method for time series and panel data. Specifically, to address the non-random nature of banking crisis onsets, we apply inverse propensity score weighting to create a quasi-random distribution of crisis and non-crisis episodes. The appropriate weights are derived from a banking crisis prediction model that accounts for financial development in the run-up to crises. Using data on banking crises and a comprehensive set of financial development indicators for 174 countries from 1980 to 2019, we present novel evidence demonstrating that banking crisis shocks have a persistent negative effect on financial development. This finding holds across multiple dimensions of financial development.
•Using data for 174 countries over the period 1980–2019, we present novel evidence that demonstrates banking crisis shocks have a negative persistent effect on financial development.•This finding holds across multiple dimensions of financial development.•Causal effects are identified using inverse propensity score weighting (IPW), with the weights estimated from a banking crisis prediction model. |
ArticleNumber | 103395 |
Author | Everaert, Gerdie Pozzi, Lorenzo |
Author_xml | – sequence: 1 givenname: Gerdie surname: Everaert fullname: Everaert, Gerdie email: gerdie.everaert@ugent.be organization: Department of Economics, Ghent University, Sint-Pietersplein 6, 9000 Gent, Belgium – sequence: 2 givenname: Lorenzo orcidid: 0000-0001-6219-5315 surname: Pozzi fullname: Pozzi, Lorenzo email: pozzi@ese.eur.nl organization: Department of Economics, Erasmus University Rotterdam & Tinbergen Institute, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands |
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Keywords | F30 F40 Panel data G20 C23 Financial development Inverse probability weighting Banking crises Local projections |
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SubjectTerms | Banking crises Financial development Inverse probability weighting Local projections Panel data |
Title | Financial development in the aftermath of banking crises |
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