Comparing Parametric and Non-parametric Early Warning Systems for Currency Crises in Emerging Market Economies

May 30, 2013

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Format: Chicago

Fabio Comelli. Comparing Parametric and Non-parametric Early Warning Systems for Currency Crises in Emerging Market Economies, (USA: International Monetary Fund, 2013) accessed September 21, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

The purpose of this paper is to compare in-sample and out-of-sample performances of three parametric and non-parametric early warning systems (EWS) for currency crises in emerging market economies (EMs). The parametric EWS achieves superior out-of-sample results compared to the non-parametric EWS, as the total misclassification error of the former is lower than that of the latter. In addition, we find that the performances of the parametric and non-parametric EWS do not improve if the policymaker becomes more prudent. From a policy perspective, the policymaker faces the standard trade-off when using EWS. Greater prudence allows the policymaker to correctly call more crisis episodes, but this comes at the cost of issuing more false alarms. The benefit of correctly calling more currency crises needs to be traded off against the cost of issuing more false alarms and of implementing corrective macroeconomic policies prematurely.

Subject: Central banks, Currency crises, Early warning systems, Financial crises, Global financial crisis of 2008-2009, International reserves

Keywords: Crisis incidence, Crisis probability, Currency crises, Currency crisis, Early warning systems, Emerging markets., Foreign exchange, Global, Global financial crisis of 2008-2009, International reserves, Macroeconomic indicator, Money stock, WP

Publication Details

Pages:

29
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2013/134
Stock No:

WPIEA2013134
ISBN:

9781484300589
ISSN:

1018-5941

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