{
  "title": "Mining the Gap: Extracting Firms’ Inflation Expectations From Earnings Calls",
  "publication": "IMF Working Papers, October 4, 2023",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2023/09/28/mining-the-gap-extracting-firms-inflation-expectations-from-earnings-calls-539617",
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  "summary": "Using a novel approach involving natural language processing (NLP) algorithms, we construct a new cross-country index of firms' inflation expectations from earnings call transcripts.",
  "sections": [
    {
      "heading": "Methodology",
      "content": "- Construct a new cross-country index of firms' inflation expectations using a novel approach involving natural language processing (NLP) algorithms.\n- Index is built from earnings call transcripts.\n- The method outperforms other NLP algorithms.\n- Keywords and technical terms used in the study include: Artificial intelligence, Natural Language processing, GPT3.5, expectation index, expectations disagreement, firms attention."
    },
    {
      "heading": "Validation and Robustness",
      "content": "- The index has a high correlation with existing survey-based measures of firms' inflation expectations.\n- The index is robust to external validation tests."
    },
    {
      "heading": "Key Findings (aggregate-level)",
      "content": "- In an application of the index to United States data, higher expected inflation translates into future inflation.\n- The index provides a cross-country measure of firms' inflation expectations."
    },
    {
      "heading": "Firm-level Findings",
      "content": "- Firms' inflation expectations display departures from a rational framework.\n- Firms' attention to the central enhances monetary policy effectiveness.\n- Analysis leverages firms’ earnings calls transcripts to obtain firm-level dimensions of inflation expectations."
    },
    {
      "heading": "Policy Implications",
      "content": "- Firms’ attention to central (presumably central bank or central announcements) enhances monetary policy effectiveness, implying attention channels matter for transmission of policy.\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/2023/09/28/mining-the-gap-extracting-firms-inflation-expectations-from-earnings-calls-539617"
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    "Authors: Silvia Albrizio, Allan Dizioli, Pedro Vitale Simon",
    "Published: October 4, 2023",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798400253522.001",
    "Construct a new cross-country index of firms' inflation expectations using a novel approach involving natural language processing (NLP) algorithms.",
    "Index is built from earnings call transcripts.",
    "The method outperforms other NLP algorithms.",
    "Keywords and technical terms used in the study include: Artificial intelligence, Natural Language processing, GPT3.5, expectation index, expectations disagreement, firms attention.",
    "The index has a high correlation with existing survey-based measures of firms' inflation expectations.",
    "The index is robust to external validation tests.",
    "In an application of the index to United States data, higher expected inflation translates into future inflation.",
    "The index provides a cross-country measure of firms' inflation expectations.",
    "Firms' inflation expectations display departures from a rational framework.",
    "Firms' attention to the central enhances monetary policy effectiveness.",
    "Analysis leverages firms’ earnings calls transcripts to obtain firm-level dimensions of inflation expectations.",
    "Firms’ attention to central (presumably central bank or central announcements) enhances monetary policy effectiveness, implying attention channels matter for transmission of policy.",
    "**Working Paper**"
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