{
  "title": "Macrofinancial Causes of Optimism in Growth Forecasts",
  "publication": "IMF Working Papers, November 12, 2021",
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  "summary": "We analyze the causes of the apparent bias towards optimism in growth forecasts underpinning the design of IMF-supported programs, which has been documented in the literature. We find that financial variables observable to forecasters are strong predictors of growth forecast errors.",
  "sections": [
    {
      "heading": "Main findings",
      "content": "- Financial variables observable to forecasters are strong predictors of growth forecast errors.\n- The greater the expansion of the credit-to-GDP gap in the years preceding a program, the greater its over-optimism about growth over the next two years.\n- Over-optimism is strongest among forecasts that were most optimistic.\n- Among the most optimistic forecasts, errors are also increasing in the economy’s degree of liability dollarization.\n- Improved macrofinancial analysis represents a promising avenue for reducing over-optimism in growth forecasts."
    },
    {
      "heading": "Broader evidence and robustness",
      "content": "- The inefficient use of financial information applies beyond IMF-supported programs:\n  - It also applies to the IMF’s forecasts in the World Economic Outlook.\n  - It also applies to forecasts produced by professional forecasters compiled by Consensus Economics."
    },
    {
      "heading": "Policy implications and recommendations",
      "content": "- Integrate observable financial variables (e.g., credit-to-GDP gap, indicators of liability dollarization) systematically into growth forecasting frameworks used for program design.\n- Prioritize macrofinancial analysis to reduce optimism bias in short-run (next two years) growth projections that underpin program design and policy decisions.\n- Pay particular attention to economies with recent expansions in the credit-to-GDP gap and higher degrees of liability dollarization when assessing forecast uncertainty and downside risks."
    },
    {
      "heading": "Research scope and context",
      "content": "- Work examines growth forecasts underpinning IMF-supported programs and assesses links between forecast errors and macrofinancial conditions observable to forecasters.\n- Finds consistent patterns across IMF program forecasts, World Economic Outlook forecasts, and Consensus Economics professional forecasts.\n- Conclusion emphasizes the potential for better macrofinancial analysis to improve forecasting accuracy.\n\nSource: \"Macrofinancial Causes of Optimism in Growth Forecasts\", Yan Carriere-Swallow and José Marzluf, November 12, 2021, IMF Working Paper No. 2021/275.\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2021/11/12/macrofinancial-causes-of-optimism-in-growth-forecasts-506834"
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    "Authors: Yan Carriere-Swallow, José Marzluf",
    "Published: November 12, 2021",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781616356392.001",
    "Financial variables observable to forecasters are strong predictors of growth forecast errors.",
    "The greater the expansion of the credit-to-GDP gap in the years preceding a program, the greater its over-optimism about growth over the next two years.",
    "Over-optimism is strongest among forecasts that were most optimistic.",
    "Among the most optimistic forecasts, errors are also increasing in the economy’s degree of liability dollarization.",
    "Improved macrofinancial analysis represents a promising avenue for reducing over-optimism in growth forecasts.",
    "The inefficient use of financial information applies beyond IMF-supported programs:",
    "Integrate observable financial variables (e.g., credit-to-GDP gap, indicators of liability dollarization) systematically into growth forecasting frameworks used for program design.",
    "Prioritize macrofinancial analysis to reduce optimism bias in short-run (next two years) growth projections that underpin program design and policy decisions.",
    "Pay particular attention to economies with recent expansions in the credit-to-GDP gap and higher degrees of liability dollarization when assessing forecast uncertainty and downside risks.",
    "Work examines growth forecasts underpinning IMF-supported programs and assesses links between forecast errors and macrofinancial conditions observable to forecasters.",
    "Finds consistent patterns across IMF program forecasts, World Economic Outlook forecasts, and Consensus Economics professional forecasts.",
    "Conclusion emphasizes the potential for better macrofinancial analysis to improve forecasting accuracy.",
    "**Working Paper**"
  ],
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