Anton Korinek - Capital Flows, Crises and Externalities: A Primer
Downloadable! We formulate a simple theoretical model of a banking industry that we use to identify and construct theory-based measures of systemic bank shocks (SBS). These measures differ from "banking crisis" (BC) indicators employed in many empirical studies, which are constructed using primarily information on. Many empirical studies of banking crises have employed "banking crisis" (BC) indicators constructedusing primarily information on government actions u. We formulate a simple theoretical model of a banking industry that we use to identify and construct theory-based measures of systemic bank shocks (SBS). These m.
Banking Crises and Crisis Dating: Theory and Evidence
Many empirical studies of banking crises have employed "banking crisis" BC indicators constructed using primarily information on government actions undertaken in response to bank distress. We form ulate a simple theoretical model of a banking industry which we use to identify see more construct theory-based measures of systemic bank shocks SBS.
Using both country-level and firm-level sam ples, we show that SBS indicators consistently predict BC indicators based on four major BC series that have appeared in the literature.
Therefore, BC indicators actually measure lagged g overnment responses to systemic bank shocks, rather than the occurrence of crises per se. We re- examine the separate impact of macroeconomic factors, bank market structure, deposit insurance, and external shocks on the probability of article source systemic bank shocks and on the probability of government responses to bank distress.
The impact of these variables on the likelihood of a government response to bank distress is totally different from that on the likelihood of a systemic bank shock.
Disentangling the effects of systemic bank shocks and government responses turns out to be crucial in understanding the roots of bank fragility. Bank - ing Crisis Database.
We then re-examine the impact of macroeconomic factors, bank market structure, deposit insurance, and external shocks on the probability of systemic bank shocks SBS and on "banking crisis" BC indicators. We find that the impact of these variables on the likelihood of a policy response to banking distress as represented by BC indicators is frequently quite different from that on the likelihood of a systemic bank shock SBS. We believe that many findings of a large empirical literature need to be re-assessed. Working Papers describe research in progress by the author s and are published to elicit comments and to further debate. Theory and Evidence July
Jan J Money Credit Bank. Apr Natl Inst Econ Rev.
It also allows you to accept potential citations to this item that we are uncertain about. This allows to link your profile to this item. Publisher conditions are provided by RoMEO. Size, Charter Value and Risk in Banking:
Discover more publications, questions and projects in Banking. The aim of the paper is to analyse the determinants of financial crises in a sample of nine transition countries in Central and Eastern Europe with a modified logit model.
A Comparative Analysis of the Banking Crises in the U.S. and Japan
The modification takes explicitly into account the rare event characteristic of a currency crisis. Our results suggest that it is possible to explain the occurrence of crises with only a small number of macroeconomic An evaluation of leading indicators of currency crises.
This study tries to construct leading indicators for currency crisis using probit model, logit model and binary quantile regression. Speculative Attacks under Financial Liberalization. This article aims at identifying the determinants of currency crises in Turkey for the post financial liberalization period A broad set of explanatory variables were tested through signals approach and bivariate and multivariate logit regressions.
The same procedure is then repeated for the post-capital account liberalization period Explaining Financial Crises in Emerging Markets: A Logit Model on the Turkish Data This article aims at explaining the financial crises Turkey experienced in the last decade through a random effects logit model which incorporates 26 macroeconomic, political, and financial sector variables.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed.
Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.
This publication is from a journal that may support self archiving.