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We estimate sovereign bond spreads of 28 emerging economies over the period January 1998-December 2011 and test the ability of the model in generating accurate in-sample predictions for emerging economies bond spreads. The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions, as well as economic periods. During crisis times, good macroeconomic fundamentals are helpful in containing bond spreads, but less than in non-crisis times, possibly reflecting the impact of extra-economic forces on bond spreads when a financial crisis occurs. For some emerging economies, in-sample predictions of the monthly changes in bond spreads obtained with rolling regression routines are significantly more accurate than forecasts obtained with a random walk. Rolling regression-based bond spread predictions appear to convey more information than those obtained with a linear prediction method. By contrast, bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing.

This paper reviews the approaches to systemic risk analysis in 32 central bank financial stability reports (FSRs). We compare and contrast the systemic risk analysis in FSRs with the IMF Article IV staff reports, noting that Article IV staff reports and FSRs frequently pick up analytical content from each other. All reviewed FSRs include a systemic risk assessment, which has not always been the case in Article IV staff reports. Also, compared to Article IV staff reports, on average, FSRs tend to cover a wider range of financial risks and vulnerabilities and tend to have more extensive discussions of the policy mix to mitigate systemic risk. In these assessments, FSRs utilize sophisticated analytical tools, such as stress tests and growth-at-risk, more frequently than Article IV staff reports. We emphasize that a central bank FSR typically presents a rich resource that IMF country teams can leverage, as already done by some, in forming their independent view about systemic risk.

We estimate sovereign bond spreads of 28 emerging economies over the period January 1998-December 2011 and test the ability of the model in generating accurate in-sample predictions for emerging economies bond spreads. The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions, as well as economic periods. During crisis times, good macroeconomic fundamentals are helpful in containing bond spreads, but less than in non-crisis times, possibly reflecting the impact of extra-economic forces on bond spreads when a financial crisis occurs. For some emerging economies, in-sample predictions of the monthly changes in bond spreads obtained with rolling regression routines are significantly more accurate than forecasts obtained with a random walk. Rolling regression-based bond spread predictions appear to convey more information than those obtained with a linear prediction method. By contrast, bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing

We compare how logit (fixed effects) and probit early warning systems (EWS) predict insample and out-of-sample currency crises in emerging markets (EMs). We look at episodes of currency crises that took place in 29 EMs between January 1995 and December 2012. Stronger real GDP growth rates and higher net foreign assets significantly reduce the probability of experiencing a currency crisis, while high levels of credit to the private sector increase it. We find that the logit and probit EWS out-of-sample performances are broadly similar, and that the EWS performance can be very sensitive both to the size of the estimation sample, and to the crisis definition employed. For macroeconomic policy purposes, we conclude that a currency crisis definition identifying more rather than less crisis episodes should be used, even if this may lead to the risk of issuing false alarms.

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.