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EN
We compare how logit (fixed effects) and probit early warning systems (EWS) predict in-sample and out-of-sample currency crises in emerging markets (EMs). We look at episodes of currency crises that took place in 29 EMs between January 1995 and December 2012. Stronger real GDP growth rates and higher net foreign assets signifi cantly reduce the probability of experiencing a currency crisis, while high levels of credit to the private sector increase it. We find that the logit and probit EWS out-of-sample performances are broadly similar, and that the EWS performance can be very sensitive both to the size of the estimation sample, and to the crisis definition employed. For macroeconomic policy purposes, we conclude that a currency crisis definition identifying more rather than less crisis episodes should be used, even if this may lead to the risk of issuing false alarms.
EN
In the paper we try to analyze the interrelations between currencies in Central Europe during the financial crisis in 2008. In order to find out the transition mechanism of the crisis we estimate the jumps (i.e. sudden changes) in exchange rates of four currencies of the region: Polish Zloty, Hungarian Forint, Czech Crown and Slovakian Crown. We use the obtained moments of jumps as dummy variables in GARCH models for exchange rates. Then we also estimate co-jumps for pairs of analyzed currencies to check how much of the volatility is due to the common jumps. The results suggest that sudden jumps in any currency causes the changes in levels of other currencies (although not in volatility of other currencies) and that the common jumps in Polish zloty and Hungarian forint had the greatest influence.
PL
W artykule zajmujemy się analizą powiązań walut Europy Środkowej w okresie kryzysu z końca roku 2008. Staramy się odpowiedzieć na pytanie o mechanizmy przenoszenia tego kryzysu. W tym celu wyznaczamy skoki – gwałtowne zmiany kursów – dla czterech walut regionu: polskiego złotego, węgierskiego forinta, czeskiej korony i korony słowackiej. Otrzymane momenty skoków wykorzystujemy przy opisie zmienności kursów modelami GARCH. Następnie estymujemy wspólne skoki dla par walut i sprawdzamy, jaka część zmienności kursów jest przez nie spowodowana. Otrzymane wyniki sugerują, że gwałtowne zmiany kursu jednej waluty miały wpływ na poziom kursów innych walut (ale już nie zawsze na ich zmienność) oraz, że największy wpływ miały tu wspólne skoki polskiego złotego i węgierskiego forinta.
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