Nowcasting (NWC)
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Bibliographic details
- Session: SA 26.06
- Location: New Delhi, India New location
- Dates: February 16-27, 2026 (2 weeks)
- Delivery method: In-person Training
- Primary language: English
- Status: New dates
Training Program and Logistics
- Session No.: SA 26.06
- Location: New Delhi, India
- Date: February 16-27, 2026 (2 weeks)
- Delivery Method: In-person Training
- Primary Language: English
- Target Audience:
- Junior and middle-level officials from ministries of finance, central banks, and other interested public institutions.
Invitation and Qualifications
- Participants are expected to have:
- An advanced degree in economics or equivalent experience.
- A basic understanding of time-series econometrics.
- Comfort using EViews (econometric software package).
- Recommended prior coursework:
- Macroeconomic Forecasting and Analysis (MFA)
- Macroeconomic Diagnostic (MDS)
- These may be face-to-face or online.
Course Description
- Presented by the Institute for Capacity Development.
- Provides participants with cutting-edge nowcasting tools to incorporate high-frequency economic indicators into the forecasting process.
- Integrates training into technical assistance on data compilation and dissemination.
- Each topic is complemented by hands-on workshops and assignments to illuminate steps required to formulate a nowcasting model and generate a nowcast.
Course Objectives
Upon completion of this course, participants should be able to:
- Understand and be proficient in the steps required to manage time-series data in EViews, estimate an OLS regression and calculate its associated forecasts in EViews.
- Formulate several useful statistical procedures in EViews, including:
- Consolidation of time series from higher to lower frequencies;
- Interpolation techniques;
- Seasonal adjustment;
- Use of leading indicators.
- 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, including Bridge, MIDAS, and U-MIDAS estimators.
- 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 own country data and interpret the nowcast appropriately in policy making settings.