{
  "title": "Quarterly National Accounts/High Frequency Indicators of Economic Activity",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101",
  "canonical": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101",
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  "summary": "Quarterly National Accounts/High Frequency Indicators of Economic Activity Training Program Target Audience This online course is designed for officials worldwide who are responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA).",
  "publishDate": "2025-02-10",
  "sections": [
    {
      "heading": "Training program and delivery",
      "content": "- Session No.: OL 24.101\n- Location: Course conducted online\n- Date: March 28, 2024 - May 16, 2024 (10 weeks)\n- Delivery Method: Online Training\n- Primary Language: French\n- Status: Deadline passed\n- Presented by: Statistics Department"
    },
    {
      "heading": "Target audience and qualifications",
      "content": "- Target audience:\n  - Officials worldwide who are responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA).\n- Qualifications:\n  - Expected to have a degree in economics or statistics; or equivalent experience.\n  - Access to a computer with a reliable Internet connection and a Google Chrome web browser are essential."
    },
    {
      "heading": "Course description — scope and techniques",
      "content": "- Purpose:\n  - Prepares participants to compile QNA and/or HFIEA by providing a thorough understanding of concepts, source data, and compilation techniques.\n- Coverage:\n  - Theoretical and practical compilation issues.\n  - Benchmarking.\n  - Seasonal adjustment techniques.\n  - Volume estimates and their application to time series data.\n- Data and assessment:\n  - Identifying and assessing available data sources for compiling QNA and HFIEAs.\n  - Using related real-time series databases to assess the quality of QNA and HFIEAs.\n  - Implementing a suitable revisions policy."
    },
    {
      "heading": "Course objectives and learning outcomes",
      "content": "Upon completion of the course, participants should be able to:\n- Recognize the role, scope, and uses of QNA and HFIEAs.\n- Describe the compilation framework for the QNA and the different compilation methods for HFIEAs (including composite leading indicators).\n- Review available data sources for compiling QNA by the income, expenditure and production approaches, and HFIEAs.\n- Explain the use of volume measures and the basic relation between value, quantity, and price—expanding on how to detect and address issues such as the need for updated weights; and recognizing the loss of additivity for chain-linked volume estimates.\n- Compile benchmarked series using the recommended techniques.\n- Apply basic techniques for filling data gaps.\n- Identify good seasonal adjustment practices and apply basic seasonal adjustment techniques to time series.\n- Formulate a balanced revisions policy taking account of how related real-time database can be used to assess the reliability of the QNA/HFIEA estimates."
    }
  ],
  "bullets": [
    "Session No.: OL 24.101",
    "Location: Course conducted online",
    "Date: March 28, 2024 - May 16, 2024 (10 weeks)",
    "Delivery Method: Online Training",
    "Primary Language: French",
    "Status: Deadline passed",
    "Presented by: Statistics Department",
    "Target audience:",
    "Qualifications:",
    "Purpose:",
    "Coverage:",
    "Data and assessment:",
    "Recognize the role, scope, and uses of QNA and HFIEAs.",
    "Describe the compilation framework for the QNA and the different compilation methods for HFIEAs (including composite leading indicators).",
    "Review available data sources for compiling QNA by the income, expenditure and production approaches, and HFIEAs.",
    "Explain the use of volume measures and the basic relation between value, quantity, and price—expanding on how to detect and address issues such as the need for updated weights; and recognizing the loss of additivity for chain-linked volume estimates.",
    "Compile benchmarked series using the recommended techniques.",
    "Apply basic techniques for filling data gaps.",
    "Identify good seasonal adjustment practices and apply basic seasonal adjustment techniques to time series.",
    "Formulate a balanced revisions policy taking account of how related real-time database can be used to assess the reliability of the QNA/HFIEA estimates."
  ],
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  },
  "generatedAtUtc": "2026-09-29T18:28:16.892Z"
}