{
  "title": "Consensus Forecasts and Inefficient Information Aggregation",
  "publication": "IMF Working Papers, July 1, 2010",
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  "summary": "Consensus forecasts are inefficient, over-weighting older information already in the public domain at the expense of new private information, when individual forecasters have different information sets.",
  "sections": [
    {
      "heading": "Main findings",
      "content": "- Consensus forecasts are inefficient: they over-weight older information already in the public domain at the expense of new private information when individual forecasters have different information sets.\n- Empirical results using a cross-country panel of growth forecasts:\n  - Consensus forecasts are inefficient as predicted.\n  - The inefficiency is not due to individual forecaster irrationality.\n  - Forecasters appear unaware of this inefficiency.\n  - A simple adjustment reduces forecast errors by 5 percent.\n- Similar results are found using US nominal GDP forecasts.\n- The paper discusses implications for users of forecaster surveys and for the literature on information aggregation."
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    {
      "heading": "Methodology and scope",
      "content": "- Uses a cross-country panel of growth forecasts and new methodological insights.\n- Also applies analysis to US nominal GDP forecasts."
    },
    {
      "heading": "Policy and user implications",
      "content": "- Users of forecaster surveys should account for the tendency of consensus forecasts to over-weight older public information and under-weight new private information.\n- A straightforward adjustment to consensus forecasts can reduce forecast errors, quantified here as a 5 percent reduction.\n\n---\n\n Content in this bundle\n\n- Microsoft Word - WP Consensus Forecasts and Inefficient Information Aggregation rev1.docx\n  - Microsoft Word - WP Consensus Forecasts and Inefficient Information Aggregation rev1.docx (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Microsoft Word - WP Consensus Forecasts and Inefficient Information Aggregation rev1.docx (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2016/12/31/consensus-forecasts-and-inefficient-information-aggregation-24114"
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    "Authors: Christopher W. Crowe",
    "Published: July 1, 2010",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781455201891.001",
    "Consensus forecasts are inefficient: they over-weight older information already in the public domain at the expense of new private information when individual forecasters have different information sets.",
    "Empirical results using a cross-country panel of growth forecasts:",
    "Similar results are found using US nominal GDP forecasts.",
    "The paper discusses implications for users of forecaster surveys and for the literature on information aggregation.",
    "Uses a cross-country panel of growth forecasts and new methodological insights.",
    "Also applies analysis to US nominal GDP forecasts.",
    "Users of forecaster surveys should account for the tendency of consensus forecasts to over-weight older public information and under-weight new private information.",
    "A straightforward adjustment to consensus forecasts can reduce forecast errors, quantified here as a 5 percent reduction.",
    "**Microsoft Word - WP Consensus Forecasts and Inefficient Information Aggregation rev1.docx**"
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