## Emerging Market Sovereign Bond Spreads: Estimation and Back-testing

_IMF Working Papers, August 1, 2012_

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## Bibliographic details
- Authors: Fabio Comelli
- Published: August 1, 2012
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781475505627.001

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### Summary
- Study estimates sovereign bond spreads for 28 emerging economies over the period January 1998-December 2011.
- Tests the ability of the model to generate accurate in-sample predictions for emerging economies bond spreads.
- Key comparative methods: rolling regression routines, a linear prediction method, and a random walk (random guessing).

### Methodology and scope
- Sample: 28 emerging economies; period: January 1998-December 2011.
- Frequency: monthly changes in bond spreads examined and predicted.
- Prediction approaches evaluated:
  - Rolling regression routines (panel/rolling estimation).
  - Linear prediction method.
  - Random walk (benchmark for forecasts).

### Major findings
- Heterogeneity of drivers:
  - The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions and economic periods.
- Crisis vs non-crisis differences:
  - 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.
- Forecasting performance:
  - 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.
  - Bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing.

### Implications for analysis and monitoring
- Model specification should allow for regional and period-specific variation in explanatory variable significance.
- Forecasting approaches:
  - Rolling regression routines can provide meaningful improvement in in-sample prediction accuracy for some emerging economies relative to a random walk.
  - Simple linear prediction methods may perform poorly and can be outperformed by random guessing for bond spread forecasts.
- Crisis-period analysis:
  - Reliance on macroeconomic fundamentals to explain or contain bond spreads during crises may be limited; attention to extra-economic drivers is warranted.

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## Content in this bundle

- **_wp12212 - Appendix Tables and References**
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_Source: https://www.imf.org/en/publications/wp/issues/2016/12/31/emerging-market-sovereign-bond-spreads-estimation-and-back-testing-26213_