{
  "title": "Emerging Market Sovereign Bond Spreads: Estimation and Back-testing",
  "publication": "IMF Working Papers, August 1, 2012",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2016/12/31/emerging-market-sovereign-bond-spreads-estimation-and-back-testing-26213",
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  "summary": "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.",
  "sections": [
    {
      "heading": "Summary",
      "content": "- Study estimates sovereign bond spreads for 28 emerging economies over the period January 1998-December 2011.\n- Tests the ability of the model to generate accurate in-sample predictions for emerging economies bond spreads.\n- Key comparative methods: rolling regression routines, a linear prediction method, and a random walk (random guessing)."
    },
    {
      "heading": "Methodology and scope",
      "content": "- Sample: 28 emerging economies; period: January 1998-December 2011.\n- Frequency: monthly changes in bond spreads examined and predicted.\n- Prediction approaches evaluated:\n  - Rolling regression routines (panel/rolling estimation).\n  - Linear prediction method.\n  - Random walk (benchmark for forecasts)."
    },
    {
      "heading": "Major findings",
      "content": "- Heterogeneity of drivers:\n  - The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions and economic periods.\n- Crisis vs non-crisis differences:\n  - 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.\n- Forecasting performance:\n  - 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.\n  - Rolling regression-based bond spread predictions appear to convey more information than those obtained with a linear prediction method.\n  - Bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing."
    },
    {
      "heading": "Implications for analysis and monitoring",
      "content": "- Model specification should allow for regional and period-specific variation in explanatory variable significance.\n- Forecasting approaches:\n  - Rolling regression routines can provide meaningful improvement in in-sample prediction accuracy for some emerging economies relative to a random walk.\n  - Simple linear prediction methods may perform poorly and can be outperformed by random guessing for bond spread forecasts.\n- Crisis-period analysis:\n  - Reliance on macroeconomic fundamentals to explain or contain bond spreads during crises may be limited; attention to extra-economic drivers is warranted.\n\n---\n\n Content in this bundle\n\n- wp12212 - Appendix Tables and References\n  - wp12212 - Appendix Tables and References (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - wp12212 - Appendix Tables and References (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2016/12/31/emerging-market-sovereign-bond-spreads-estimation-and-back-testing-26213"
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    "Authors: Fabio Comelli",
    "Published: August 1, 2012",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781475505627.001",
    "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).",
    "Sample: 28 emerging economies; period: January 1998-December 2011.",
    "Frequency: monthly changes in bond spreads examined and predicted.",
    "Prediction approaches evaluated:",
    "Heterogeneity of drivers:",
    "Crisis vs non-crisis differences:",
    "Forecasting performance:",
    "Model specification should allow for regional and period-specific variation in explanatory variable significance.",
    "Forecasting approaches:",
    "Crisis-period analysis:",
    "**_wp12212 - Appendix Tables and References**"
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