JVI is gradually resuming classroom delivery. Courses not labelled as virtual are scheduled to take place at JVI, but may have to be delivered virtually in case safe travel to and in-person training in Vienna will not be possible. The decision to offer virtual instead of onsite training will be made within 5 weeks of the course start date.
TARGET GROUP | 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), Macroeconomic Diagnostic (MDS), face-to-face or online.
DESCRIPTION | This course, presented by the Institute for Capacity Development, provides participants with cutting-edge nowcasting tools that familiarize them with the concepts and methods to incorporate high-frequency economic indicators into the forecasting process, while integrating this training into technical assistance on data compilation and dissemination. Each topic is complemented by hands-on workshops and assignments designed to illuminate the steps required to formulate a nowcasting model and generate a nowcast. The NWC course is five days in face-to-face mode, or nine days in virtual mode.
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; and 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.