Brief introduction of the organisation

ADB is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Pacific, while sustaining its efforts to eradicate extreme poverty. Established in 1966, it is owned by 68 members—49 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance.

A description of the SAE work within the organisation

In 2017, the Asian Development Bank (ADB) launched the Data for Development project which aims to support the statistical capacity of national statistics offices (NSOs) in Asia and the Pacific, helping them comply with the many and varied data requirements for policymaking and monitoring of development goals and targets. One of the components of the project is the subnational disaggregation of data to monitor the Sustainable Development Goals (SDGs). This component focuses on strengthening the capacity of NSOs to generate fine-grained data for policies and programs targeted to vulnerable sectors of society.

One of the outputs of this component is a guide on disaggregation of official statistics, which includes an inventory of various small area estimation (SAE) methodologies to yield granular data for official statistics compiled from surveys. SAE methodologies are used to provide reliable disaggregated statistics for population segments which are more granular than pre-defined survey domains. The guide explains SAE techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes.

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Future work on SAE

The guide compiles various SAE techniques and worked examples on how to implement the methodology, which were covered in a series of country training workshops provided to the staff of several national statistics offices, and other regional workshops held in 2018 to 2019. The training workshops were designed to strengthen the skills of NSO staff in applying SAE methods that can be used to meet the disaggregated data requirements of the SDGs. Furthermore, since its publication in May 2020, several researchers and academics have reported the usefulness of the guide in their work. 

Moving forward, the team will continue exploring potential areas of collaboration with national statistical systems who may need technical assistance in building capacity on the application of SAE methods.

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