Training Program
Big Data for Macroeconomic Statistics (BDMS)
Invitation
Session No.: PT 26.03
Location: Asuncion, Paraguay
Date: May 4-8, 2026 (1 week)
Delivery Method: In-person Training
Primary Language: English
Interpretation Language: Spanish
Target Audience
This course is intended for technical staff and managers from national statistics offices and central banks who are involved in macroeconomic statistics, nowcasting, and data science projects. It is suitable for economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.
Qualifications
This course is intended for technical staff and managers from national statistics offices and central banks who are involved in macroeconomic statistics, nowcasting, and data science projects. It is suitable for economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.
Course Description
This workshop 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. The workshop is delivered by data scientists of the IMF Big Data Center through lectures and hands-on workshops covering various Big Data applications pertinent to macroeconomic statistics, offering insights from both producer and user standpoints. Furthermore, participants have the opportunity to present and discuss their use cases, engage in discussions, and benefit from shared insights and experiences.
Travel, accommodation, and per diem costs are to be arranged and funded by the participants' sponsoring agencies.
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 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.
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