Enhancing statistical capacity through the global training on small area estimation: lessons from Asia Pacific, Africa, Latin America and the Caribbean

The UN Statistical Commission recognizes the critical importance of disaggregated and granular data for informed decision-making. Small Area Estimation (SAE) plays a crucial and significant role in providing precise and reliable statistics. This side event aims to showcase the experiences and lessons learned from the Global Training on Small Area Estimation across three key regions: Latin America and the Caribbean, Asia Pacific, and Africa. It will also serve as a valuable platform for statisticians, methodologist and researchers to exchange knowledge and experiences in Small Area Estimation training by showcasing the unique challenges and successful strategies from these three regions.

The webinar will host a panel discussion for national statistical offices that have completed the Small Area Estimation (SAE) eLearning course. This event will offer participants an opportunity to share their experiences, highlighting both successes and challenges encountered during the course. It will also provide a platform for them to discuss the application of their newfound knowledge within their respective offices. Additionally, feedback on the course materials and its structure will be collected. This input is invaluable as it will guide us in enhancing our training services on this topic.

The event aims to contribute to the enhancement of global statistical capacities and promote the use of disaggregated data for sustainable development.

Objectives:

This webinar is aimed to facilitate knowledge exchange among statisticians, researchers, and policymakers by delving into the challenges and successes encountered during the implementation of the Global Training on Small Area Estimation in 2023. Participants will gain insights into methodologies, best practices, and innovative approaches to SAE, fostering collaboration and enhancing statistical capabilities within the National Statistical Offices and other institutions of the National Statistical Systems.