{
  "title": "Quarterly National Accounts/High Frequency Indicators of Economic Activity",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2025/qnaxol25-200",
  "canonical": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2025/qnaxol25-200",
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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": "2025-05-01",
  "sections": [
    {
      "heading": "Target audience & qualifications",
      "content": "- Target audience: officials worldwide responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA).\n- Qualifications:\n  - Participants are 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 logistics",
      "content": "- Session No.: OL 25.200\n- Location: Course conducted online\n- Date: May 1, 2025 - April 15, 2026 (50 weeks)\n- Delivery Method: Online Training\n- Primary Language: Spanish\n- Status: Deadline passed"
    },
    {
      "heading": "Course description",
      "content": "- Presented by the Statistics Department.\n- Prepares participants to compile QNA and/or HFIEA by providing a thorough understanding of the concepts, source data, and compilation techniques used for producing these datasets.\n- Covers both theoretical and practical compilation issues.\n- Introduces benchmarking, seasonal adjustment techniques, and volume estimates; explains the application of these techniques to time series data.\n- Teaches participants to identify and assess available data sources for compiling QNA and HFIEAs; use related real-time series databases to assess the quality of QNA and HFIEAs; and implement a suitable revisions policy."
    },
    {
      "heading": "Course objectives",
      "content": "Upon completion of the course, participants should be able to:\n- 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).\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. 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": [
    "Target audience: officials worldwide responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA).",
    "Qualifications:",
    "Session No.: OL 25.200",
    "Location: Course conducted online",
    "Date: May 1, 2025 - April 15, 2026 (50 weeks)",
    "Delivery Method: Online Training",
    "Primary Language: Spanish",
    "Status: Deadline passed",
    "Presented by the Statistics Department.",
    "Prepares participants to compile QNA and/or HFIEA by providing a thorough understanding of the concepts, source data, and compilation techniques used for producing these datasets.",
    "Covers both theoretical and practical compilation issues.",
    "Introduces benchmarking, seasonal adjustment techniques, and volume estimates; explains the application of these techniques to time series data.",
    "Teaches participants to identify and assess available data sources for compiling QNA and HFIEAs; use related real-time series databases to assess the quality of QNA and HFIEAs; and implement a suitable revisions policy.",
    "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": "2026-09-29T18:48:37.818Z"
}