Early Warning Systems: A Survey and a Regime-Switching Approach

Abiad, Abdul

doi:10.2139/ssrn.581141

Cited by 114 publications

(154 citation statements)

References 27 publications

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“…Departing from discrete choice models, continuous crisis indicators have been proposed Spiegel, 2009, Frankel andSaravelos, 2010) that allow the EWM to explain the scale of real costs without the need to decide if it is sufficiently high to produce a 'yes' value. Markov switching models (Peria, 2002, Abiad, 2003 have also found their use in this area. Moreover, the literature improved the toolkits with methods such as non-parametric clustering methods like the binary recursive tree method (Barrel et al 2009).…”

Section: Related Literaturementioning

confidence: 99%

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

et al. 2015

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Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models' relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments.The obligatory copyright note: We certify that we have the right to deposit the contribution with MPRA.

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Section: Related Literaturementioning

confidence: 99%

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

et al. 2015

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“…Switching approach (Martinez-Peria, 2002, Abiad, 2003 and extreme value theory to identify crises (Pozo and Amuedo-Dorantes, 2003). Another trend is towards focusing on regional studies, such as Esquivel and Larrain (1999), Brueggemann and Linne (2002) or Pasternak (2003).…”

Section: Introductionmentioning

confidence: 99%

Robust lessons about practical early warning systems

Beckmann¹,

Menkhoff²,

Sawischlewski³

2006

Journal of Policy Modeling

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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. Early warning systems (EWSs) are subject to restrictions that apply to exchange rates in general: fundamentals matter but their influence is small and unstable. Keeping this in mind, five lessons emerge: First, EWSs have robust forecasting power and thus help policy-makers to prevent crises. Second, among competing crisis definitions there is one which is most practical. Third, take a logit model to condense information from various fundamental variables. Fourth, add a regional contagion dummy to the standard set of variables. Fifth, one may be tempted to address instability over time and countries by taking shorter samples and regional EWSs. JEL-Classification: F33, F37, F31 Terms of use: Documents in EconStor may

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“…On the one hand, we include real world interest rates (proxied by real 3-month LIBOR) because high real international interest rates may trigger debt servicing problems that require subsequent Fund assistance (Bird and Rowlands 2001). Additionally, the real 3-month LIBOR is a good indicator for capital flows to emerging markets since higher real world interest rates usually decrease capital flows to emerging markets (Abiad 2003). On the other hand, higher real world GDP growth increases the demand for exports from developing countries, helping to lower current account deficits, and hence, the need to borrow from the Fund falls.…”

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confidence: 99%