Big Data for Macroeconomic Statistics (BDMS)

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Big Data for Macroeconomic Statistics (BDMS)

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Bibliographic details

• Published: July 26, 2025

Upcoming offerings

Overview

• Workshop aimed at country officials from national statistics offices (NSOs) and central banks to acquire knowledge and skills to leverage Big Data and advanced technologies for generating high-frequency and detailed statistics to enhance macroeconomic monitoring and research in the region.
• Delivered by data scientists of the IMF Big Data Center through lectures and hands-on workshops.
• Offers insights from both producer and user standpoints.
• Participants present and discuss use cases, engage in discussions, and benefit from shared insights and experiences.
• Topic: Macroeconomic Statistics

Target audience

• Technical staff and managers from national statistics offices and central banks involved in macroeconomic statistics, nowcasting, and data science projects.
• Suitable for economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.

Course objectives

Upon completion, 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 textual 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.
• Gain insights into setting up effective data science teams and developing institutional Big Data strategies to support innovation for macroeconomic statistics.

Delivery and core topics

• Combination of lectures and hands-on workshops led by IMF Big Data Center data scientists.
• Practical applications relevant to macroeconomic statistics, including GDP nowcasting and trade monitoring via the IMF's PortWatch platform.
• Geospatial analysis using Google Earth Engine (GEE), Dynamic World, and Jupyter Notebook.
• Textual analysis using natural language processing (NLP).
• Emphasis on both technical implementation (data extraction, preprocessing, visualization) and institutional practices (team setup, strategy development).

Expected competencies and institutional outcomes

• Ability to set up and support organizational Big Data architectures for macroeconomic statistics.
• Practical machine learning and model evaluation skills applicable to nowcasting and monitoring.
• Capability to produce high-frequency, geospatially informed macroeconomic indicators from satellite data.
• Competence in NLP-based textual analysis to enrich macroeconomic monitoring and research.
• Strengthened inter-agency collaboration and peer-learning on Big Data projects.
• Foundations for institutional Big Data strategies and effective data science teams to support innovation in official statistics.

References

• In-person Training
• AT 26.27
• ST 26.24
• CE 26.46
• Apply online