Currency Crises in Transition Economies: Some Further Evidence

Liargovas, Panagiotis; Dapontas, Dimitrios

doi:10.1080/00213624.2008.11507203

Cited by 7 publications

(8 citation statements)

References 32 publications

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“…Possibility over 50% is a positive sign of existence of crisis. I have chosen the variables that seem to be important for each country under the Z-statistic confidence interval along with the framework developed by the study that analyzed the same countries in the same period as referred (Liargovas and Dapontas, 2008). I have chosen the latest incidents in order to achieve the best possible results.…”

Section: The Set Of Models and Empirical Resultsmentioning

confidence: 99%

“…Kenneth Galbraith said that there are two kinds of forecasters: Those who that their forecast is wrong, and those who don't know that their forecast is wrong. Although, the arguments on forecasting practices, my work has to do with countries from the same sample developed by an earlier work on Central and Eastern European crises (Liargovas and Dapontas, 2008) and its ability and significance as an early warning system. My dataset consists of five countries of central and Eastern Europe (Belarus, Bulgaria, Moldova, Romania, and Ukraine) for a thirteen year period (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008).…”

Section: Introductionmentioning

confidence: 99%

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Were the Currency Crises in Eastern Europe (1995-2008) Predictable? An Empirical Approach

Dapontas¹

2012

Annals of the Alexandru Ioan Cuza University - Economics

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This paper is based on finding the characteristics that could have made crises in Central and Eastern Europe occurred n the pats forecastable based on lagged time series analysed as a set of binary models estimated with the extreme value approach which is suitable for irregular non stationary data on rare events. This method has been used in order to predict the possibility of rare events such as earthquakes, floods or other unpredictable by trend disasters. I use this method for the very first time in macroeconomics and especially in currency crisis events. The sample consists of five countries of central and Eastern Europe (Belarus, Bulgaria, Moldova, Romania, and Ukraine respectively) for a thirteen year period (1995-2008). The results show that explanatory variables can work as a predictor in the case of Bulgaria, Belarus and Moldova but not in the cases of Romania and Ukraine.

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Section: The Set Of Models and Empirical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Were the Currency Crises in Eastern Europe (1995-2008) Predictable? An Empirical Approach

Dapontas¹

2012

Annals of the Alexandru Ioan Cuza University - Economics

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“…Also previous works framework as analyzed in the second sector has considered. Some of them have been seasonally adjusted according to similar literature (Liargovas P. and Dapontas D. 2008).The variables used are the described as follows:…”

Section: Methodology Variables and Resultsmentioning

confidence: 99%

Examining Eurozone Crisis and Unemployment Relationship Using Var Models

Dapontas

2013

Annals of the Alexandru Ioan Cuza University - Economics

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“…The variables blanket each of the three known and connected generations along with their modified ones and the introducing fourth generation. In later works following the global credit crunch (Liargovas and Dapontas, 2008) suggested a set of variables such as economic freedom. Another approach (Dapontas, 2010, andDapontas, 2013) suggested a double dimension on fourth generation crises analysis explaining crisis through contagion and banking crises existence.…”

Section: The Data Set and The Main Variables Usedmentioning

confidence: 99%

“…Later based on eastern European crises on the latest years (Liargovas and Dapontas, 2008;and Dapontas, 2012a) using CATREG models or extreme value analysis to predict and explain them In three out of five cases the forecast was successful. The same model applied on the recent European crises where in a six countries sample the model successfully predicted all of them (Dapontas, 2012a).…”

Section: Empirical Researchmentioning

confidence: 99%