{
  "title": "Nowcasting (NWC)",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/st/2022/nwcst22-31",
  "canonical": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/st/2022/nwcst22-31",
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  "summary": "Nowcasting Training Program Target Audience Junior and middle-level officials from Ministries of Finance, Central Banks, and other interested public institutions.",
  "publishDate": "2023-03-11",
  "sections": [
    {
      "heading": "Course description and content",
      "content": "- Nowcasting is defined as the practice of using recently published data to update key economic indicators that are published with a significant lag, such as real GDP.\n- The course aims to familiarize participants with cutting-edge nowcasting tools that facilitate the use [of] mixed-frequency data in regression models.\n- Motivations: Importance of nowcasting for more timely and appropriate policy formulation during crisis periods such as the GFC or COVID-19.\n- Methods and estimators covered:\n  - BRIDGE estimators\n  - MIDAS estimators\n  - U-MIDAS estimators\n  - Each estimator both with and without dynamic factors\n  - State-space/Kalman filter approach to formulating and estimating a nowcasting model with mixed-frequency data\n- Additional topics:\n  - Procedures for combining nowcasts from distinct models\n  - Statistical procedures for evaluating the accuracy of a sequence of nowcasts\n- Practical component:\n  - Hands-on workshops and assignments using country-specific data with the EViews econometric package\n  - Workshops and assignments are an integral component designed to illuminate the actual steps required to generate a nowcast"
    },
    {
      "heading": "Course objectives",
      "content": "Upon completion of this course, participants should be able to:\n- Identify appropriate high-frequency indicators useful for the nowcasting macroeconomic variables and prepare them for use in a nowcasting exercise.\n- Formulate and estimate a nowcasting regression using several approaches.\n- Generate a nowcast from the base regression and consolidate competing forecasts using combination forecasts.\n- Evaluate the accuracy of the nowcast using several forecasting performance indicators.\n- Apply the nowcasting tools to their country data and interpret the nowcast appropriately in policy making settings."
    }
  ],
  "bullets": [
    "Nowcasting is defined as the practice of using recently published data to update key economic indicators that are published with a significant lag, such as real GDP.",
    "The course aims to familiarize participants with cutting-edge nowcasting tools that facilitate the use [of] mixed-frequency data in regression models.",
    "Motivations: Importance of nowcasting for more timely and appropriate policy formulation during crisis periods such as the GFC or COVID-19.",
    "Methods and estimators covered:",
    "Additional topics:",
    "Practical component:",
    "Identify appropriate high-frequency indicators useful for the nowcasting macroeconomic variables and prepare them for use in a nowcasting exercise.",
    "Formulate and estimate a nowcasting regression using several approaches.",
    "Generate a nowcast from the base regression and consolidate competing forecasts using combination forecasts.",
    "Evaluate the accuracy of the nowcast using several forecasting performance indicators.",
    "Apply the nowcasting tools to their country data and interpret the nowcast appropriately in policy making settings."
  ],
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  },
  "generatedAtUtc": "2026-09-29T20:31:09.647Z"
}