{
  "title": "Quarterly National Accounts/High Frequency Indicators of Economic Activity",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2023/qnaxol23-186",
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  "summary": "Quarterly National Accounts/High Frequency Indicators of Economic Activity Training Program Qualifications Knowledge of economics and statistics or equivalent experience is helpful.",
  "publishDate": "2024-05-15",
  "sections": [
    {
      "heading": "Program logistics and qualifications",
      "content": "- Session No.: OL 23.186\n- Location: Course conducted online\n- Date: May 1, 2023 - August 31, 2023 (18 weeks)\n- Delivery Method: Online Training\n- Primary Language: English\n- Qualifications: Knowledge of economics and statistics or equivalent experience is helpful. Access to a computer with a reliable Internet connection and a Google Chrome web browser are essential."
    },
    {
      "heading": "Target audience and purpose",
      "content": "- Target Audience:\n  - Intended for anyone interested in learning how to compile and disseminate Quarterly National Accounts (QNA) and High-Frequency Indicators of Economic Activity (HFIEAs).\n  - Focus on applying recommendations of the System of National Accounts and using high-frequency data to analyze current economic developments.\n- Purpose:\n  - Introductory course to teach compilation and dissemination practices for QNA and HFIEAs and the role of high-frequency data in economic analysis."
    },
    {
      "heading": "Course content and methods",
      "content": "- Core topics covered:\n  - Concepts, data sources, and compilation techniques for producing timely and high-quality QNA and HFIEAs.\n  - Theoretical and practical compilation issues.\n  - Benchmarking and seasonal adjustment techniques.\n  - Volume estimates and the application of these techniques to time series data.\n  - Identification and assessment of available data sources.\n  - Use of real-time series databases to assess data quality.\n  - Design and implementation of a suitable revisions policy for QNA and HFIEAs.\n- Practical skills emphasized:\n  - Compiling benchmarked series and filling data gaps.\n  - Applying basic seasonal adjustment techniques to time series based on good seasonal adjustment practices.\n  - Applying volume measures and understanding the basic relation between value, quantity, and price.\n  - Detecting and addressing issues such as the need for updated weights and recognizing the loss of additivity for chain-linked volume estimates.\n  - Describing a balanced revisions policy and using a related real-time database to assess reliability of estimates."
    },
    {
      "heading": "Course objectives (learning outcomes)",
      "content": "- Upon completion, participants should be able to:\n  - Recognize the role, scope, uses, and compilation frameworks for QNA and HFIEAs.\n  - Review available data sources for compiling QNA and HFIEAs.\n  - Explain the use of volume measures and the relation between value, quantity, and price, including addressing updated weights and loss of additivity for chain-linked volume estimates.\n  - Apply basic techniques for compiling benchmarked series and filling data gaps.\n  - Apply basic seasonal adjustment techniques to time series based on good practices.\n  - Describe a balanced revisions policy and how a real-time database can be used to assess reliability of QNA and HFIEA estimates."
    }
  ],
  "bullets": [
    "Session No.: OL 23.186",
    "Location: Course conducted online",
    "Date: May 1, 2023 - August 31, 2023 (18 weeks)",
    "Delivery Method: Online Training",
    "Primary Language: English",
    "Qualifications: Knowledge of economics and statistics or equivalent experience is helpful. Access to a computer with a reliable Internet connection and a Google Chrome web browser are essential.",
    "Target Audience:",
    "Purpose:",
    "Core topics covered:",
    "Practical skills emphasized:",
    "Upon completion, participants should be able to:"
  ],
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  "generatedAtUtc": "2026-09-29T18:07:59.538Z"
}