Big Data for Macroeconomic Statistics
Apply online by July 20, 2025 Deadline extended
Session No.: JV 25.33
Location: Vienna, Austria
Date: October 27-31, 2025 (1 week)
Delivery Method: In-person Training
Primary Language: English
Apply NowTarget Audience
This course is targeted at technical staff of national statistics offices and central banks (economists or statisticians, and data scientists) working on macroeconomic statistics, nowcasting, and data science projects.
Qualifications
Participants are expected to have a degree in economics, statistics, data science or equivalent experience.
Course Description
This workshop, presented by the Statistics Department, is aimed at country officials from national statistics offices (NSOs) and central banks who are seeking to acquire the knowledge and skills necessary to leverage Big Data and advanced technologies for generating high-frequency and detailed statistics to enhance macroeconomic monitoring and research in the region. AfDB and IMF experts will deliver lectures and hands-on workshops covering various Big Data applications pertinent to macroeconomic statistics, offering insights from both producer and user standpoints. Furthermore, participants will have the opportunity to present and discuss their use cases, engage in discussions, and benefit from shared insights and experiences.The workshop is conducted jointly by staff of the AfDB Data Innovation Lab and the IMF Big Data Center.
Course Objectives
Upon completion of this course, participants should be able to:
- Provide support in setting up Big Data architecture, encompassing data extraction, preprocessing, and visualization in their various organizations.
- Demonstrate a practical knowledge of machine learning modeling, variable selection, performance analysis as well as model selection, for GDP nowcasting and trade monitoring (based on the IMF’s “PortWatch” platform).
- Demonstrate practical skills in the use of Google Earth Engine (GEE), Dynamic World, Jupyter Notebook and other geospatial and data science packages to analyze satellite data and generate high-frequency macroeconomic statistics.
- Carry out sentiment analysis with natural language processing (NLP) technologies to support macroeconomic analysis.
- Demonstrate the application of these Big Data technologies and resources to improve timelines and granularity of their official statistics.
- Facilitate peer-learning on Big Data applications and explore collaborations between agencies working on projects of mutual interest.
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