Balance of payment crises in emerging markets: how early were the ‘early’ warning signals?

Bussière, Matthieu

doi:10.1080/00036846.2011.633891

Cited by 42 publications

(37 citation statements)

References 32 publications

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“…The recent literature has focused on the identification of crises and imbalances for large samples of countries, including both developing and developed economies (Rose and Spiegel, 2011;Frankel and Saravelos, 2012). Alternatively, attention has been given to developing and emerging economies (Berg et al, 2005;Bussiere, 2013;Davis and Karim, 2008) or the OECD countries (Barrell et al, 2010;Alessi and Detken, 2011). …”

Section: Countries In the Samplementioning

confidence: 99%

Leading indicators of crisis incidence: Evidence from developed countries

Babecký

Havránek

Matějů

et al. 2013

Journal of International Money and Finance

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MaRs is to develop core conceptual frameworks, models and/or tools supporting macro-prudential supervision in the EU. The research is carried out in three work streams: 1) Macro-financial models linking financial stability and the performance of the economy; 2) Early warning systems and systemic risk indicators; 3) Assessing contagion risks. MaRs is chaired by Philipp Hartmann (ECB). Paolo Angelini (Banca d'Italia), Laurent Clerc (Banque de France), Carsten Detken (ECB), Cornelia Holthausen (ECB) and Katerina Šmídková (Czech National Bank) are workstream coordinators. Xavier Freixas (Universitat Pompeu Fabra) and Hans Degryse (Katholieke Universiteit Leuven and Tilburg University) act as external consultant. Angela Maddaloni (ECB) and Kalin Nikolov (ECB) share responsibility for the MaRs Secretariat. The refereeing process of this paper has been coordinated by a team composed of Cornelia Holthausen, Kalin Nikolov and Bernd Schwaab (all ECB). The paper is released in order to make the research of MaRs generally available, in preliminary form, to encourage comments and suggestions prior to final publication. The views expressed in the paper are the ones of the author(s) and do not necessarily reflect those of the ECB or of the ESCB. Acknowledgements 1 AbstractWe search for early warning indicators that could indicate important risks in developed economies. We therefore examine which indicators are most useful in explaining costly macroeconomic developments following the occurrence of economic crises in EU and OECD countries between 1970 and 2010. To define our dependent variable, we bring together a (continuous) measure of crisis incidence, which combines the output and employment loss and the fiscal deficit into an index of real costs, with a (discrete) database of crisis occurrence. In contrast to recent studies, we explicitly take into account model uncertainty in two steps. First, for each potential leading indicator, we select the relevant prediction horizon by using panel vector autoregression. Second, we identify the most useful leading indicators with Bayesian model averaging. Our results suggest that domestic housing prices, share prices, and credit growth, and some global variables, such as private credit, are risk factors worth monitoring in developed economies. When the global turmoil demonstrated that developed economies can be also among those hit significantly by a crisis, it was not obvious whether the previously identified early warning indicators should be employed again. We try to take up this challenge and contribute to the early warning literature by focusing solely on developed economies and by offering several methodological improvements for explaining crisis incidence.In the first step, we refine the measure of the real costs of crises to the economy by combining a continuous index of real costs with a binary index of crisis occurrence. The continuous index reflects the output and employment loss along with the fiscal deficit, while the binary index captures the occurrence of various (bank...

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Section: Countries In the Samplementioning

confidence: 99%

Leading indicators of crisis incidence: Evidence from developed countries

Babecký

Havránek

Matějů

et al. 2013

Journal of International Money and Finance

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“…The reason for which the logit model is preferred is because the logistic distribution (logit model) has heavier tails than the normal distribution (probit model) (Manasse, Roubini and Schimmelpfennig, 2003;Bussière, 2007). However, differences are small (Cornelli, 2014).…”

Section: Binary Logit Modelmentioning

confidence: 99%

“…Compared to the signal approach, the logit and probit models have advantages. First, the methods consider all the variables simultaneously (Kaminsky, Lizondo and Reinhart, 1998), and second, the independent variables can have a nonlinear effect on the probability of a crisis, which is appropriate because of the presence of strong nonlinear effects in currency crises mechanisms (Bussière, 2007).…”

Section: Logit Modelsmentioning

confidence: 99%

Early Warning Systems with Real-Time Data

et al. 2017

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: This paper investigates the performance of early warning systems in real-time, using forecasts of indicators that were available at the moment predictions are to be made. The study analyzes currency crises in eight Latin American and Central and Eastern European countries, distinguishing an estimation period 1990-2009 and a prediction period 2010-2014. We apply two varieties of early warning systems: the signal approach and the logit models. For both methods we find that using forecasts of the indicators worsens the predictive ability of early warning systems compared to using the most recently available information (ex post). Terms of use: Documents in

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“…Note that the weights are frequently the inverse of the standard deviation ( ) of the corresponding component. However, Bussiere and Fratzscher (2006) and Bussiere (2013) prefer to use the inverse of the variance ( 2  ) of the corresponding component. On the other hand, some authors also utilize arbitrary weights: for instance in Corsetti et al (2001) the weights assigned to exchange rate and reserves are, respectively, 0.75 and 0.25.…”

Section: Dating Crises: a Literature Surveymentioning

confidence: 99%

A Comparison of Currency Crisis Dating Methods: Turkey 1990-2014

Ari¹,

Cergibozan²

2016

MJE

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This paper aims to assess the robustness of currency crisis dating methods. Hence, we reproduce a broad set of the ten most representative indicators from the literature, and develop two new crisis indicators derived from Cointegration and ARDL Bounds tests for the Turkish economy which underwent several currency crises over the last 30 years. Contrary to early studies (Edison, 2003;Perez, 2005;Lestano and Jacobs, 2007), we indicate that different crisis indicators produce similar results, at the same threshold level, in identifying the Turkish currency crises of post-liberalization period. JEL classification:C14, F31, G01

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Balance of payment crises in emerging markets: how early were the ‘early’ warning signals?

Cited by 42 publications

References 32 publications

Leading indicators of crisis incidence: Evidence from developed countries

Leading indicators of crisis incidence: Evidence from developed countries

Early Warning Systems with Real-Time Data

A Comparison of Currency Crisis Dating Methods: Turkey 1990-2014

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