Nowcasting (NWC)

Source details

Junior and middle-level officials from Ministries of Finance, Central Banks, and other interested public institutions.
Participants are expected to have an advanced degree in economics or equivalent experience, a basic understanding of time-series econometrics and be comfortable using EViews (econometric software package).
It is strongly recommended that applicants have completed a few general macroeconomic courses, such as Macroeconomic Forecasting and Analysis (MFA) and Macroeconomic Diagnostic (MDS), in-person or online.

Nowcasting uses recently published data to update key economic indicators published with a significant lag, such as real GDP.
The course familiarizes participants with cutting-edge nowcasting tools that facilitate the use of mixed-frequency data in regression models.
Rationale and context:
- Emphasizes the importance of nowcasting for more timely and appropriate policy formulation during crisis periods such as the GFC or COVID-19.
Statistical methodologies and procedures covered:
- Generation of nominal and real GDP estimates.
- Box-Jenkins time-series analysis.
- Replacement of missing values.
- Seasonal adjustment procedures.
- Frequency conversion.
- Identification and preparation of high-frequency indicators.
Nowcasting approaches taught:
- BRIDGE, MIDAS, and U-MIDAS estimators, both with and without factors.
- State-space/Kalman filter approach for mixed-frequency data.
Model combination and evaluation:
- Procedures for combining nowcasts from distinct models.
- Statistical procedures for evaluating the accuracy of a sequence of nowcasts.
Practical component:
- Each topic is complemented by hands-on workshops and an assignment using country-specific data with the EViews econometric package.
- Workshops and assignments are integral to illuminate the actual steps required to generate a nowcast.

Upon completion of the course, participants should be able to:

Identify appropriate high-frequency indicators useful for 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.