The Appropriateness of the Macroeconomic Imbalance Procedure for Central and Eastern European Countries
Geraldine Dany-Knedlik, Martina Kämpfe, Tobias Knedlik
Empirica,
Nr. 1,
2021
Abstract
The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It was published first time in 2012 by the European Commission as a reaction to public debt crises in Europe. So far, the Macroeconomic Imbalance Procedure takes a one-size-fits-all approach with regard to the identification of thresholds. The experience of Central and Eastern European Countries during the global financial crisis and in the resulting public debt crises has been largely different from that of other European countries. This paper looks at the appropriateness of scoreboard of the Macroeconomic Imbalances Procedure of the European Commission for this group of catching-up countries. It is shown that while some of the indicators of the scoreboard are helpful to predict crises in the region, thresholds are in most cases set too narrow since it largely disregarded the specifics of catching-up economies, in particular higher and more volatile growth rates of various macroeconomic variables.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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The Appropriateness of the Macroeconomic Imbalance Procedure for Central and Eastern European Countries
Martina Kämpfe, Tobias Knedlik
IWH Discussion Papers,
Nr. 16,
2017
Abstract
The experience of Central and Eastern European countries (CEEC) during the global financial crisis and in the resulting European debt crises has been largely different from that of other European countries. This paper looks at the specifics of the CEEC in recent history and focuses in particular on the appropriateness of the Macroeconomic Imbalances Procedure for this group of countries. In doing so, the macroeconomic situation in the CEEC is highlighted and macroeconomic problems faced by these countries are extracted. The findings are compared to the results of the Macroeconomic Imbalances Procedure of the European Commission. It is shown that while the Macroeconomic Imbalances Procedure correctly identifies some of the problems, it understates or overstates other problems. This is due to the specific construction of the broadened surveillance procedure, which largely disregarded the specifics of catching-up economies.
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Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
Financial Cycles and the Real Economy: Lessons for CESEE Countries,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
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Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
IWH Discussion Papers,
Nr. 8,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
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The Impact of Preferences on Early Warning Systems - The Case of the European Commission's Scoreboard
Tobias Knedlik
European Journal of Political Economy,
2014
Abstract
The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It allows the preferences of the politicians involved to be analysed with regard to the two potential errors of an early warning system – missing a crisis and issuing a false alarm. These preferences might differ with the institutional setting. Such an analysis is done for the first time in this article for early warning systems in general by using a standard signals approach, including a preference-based optimisation approach, to set thresholds. It is shown that, in general, the thresholds of the Commission’s Scoreboard are set low (resulting in more alarm signals), as compared to a neutral stand. Based on political economy considerations the result could have been expected.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Journal of International Money and Finance,
Nr. 35,
2013
Abstract
The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Abstract
The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite
indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.
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Die Bestimmung des Risikopotenzials von Finanzkrisen anhand eines Frühwarnindikatorensystems
Axel Brüggemann, Thomas Linne
Schriften des IWH,
Nr. 13,
2002
Abstract
Seit Mitte der neunziger Jahre brachen in den Ländern Mittel- und Osteuropas mehrere Finanzkrisen aus. Darunter waren mit Bulgarien, Rumänien und der Tschechischen Republik auch Länder, mit denen die EU Beitrittsverhandlungen führt. Die Krisenprävention ist nicht allein wegen der ökonomischen Ansteckungseffekte für die westeuropäischen Länder aufgrund der geografischen Nähe und den engen Handelsverflechtungen mit den Ländern bedeutsam. Vielmehr erhält die Krisenvermeidung mit dem EU-Beitritt auch eine politische Komponente. Insgesamt kommt somit einem Frühwarnsystem zur rechtzeitigen Erkennung von Krisenpotenzialen in den zukünftigen Mitgliedsländern eine hohe Bedeutung zu.
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