Welcome to the Toolkit on Using Small Area Estimation for SDGs!
In committing to the realization of the 2030 Agenda for Sustainable Development, Member States recognized that the dignity of the individuals is fundamental and that the Agenda’s Goals and targets should be met for all nations and people and for all segments of society. Ensuring that these commitments are translated into effective action requires a precise understanding of the target populations and progress made in addressing their particular priorities.
To properly measure this, statistics need to be presented for different population groups and geographical areas. The Sustainable Development Goal (SDG) indicator framework has included an overarching principle of data disaggregation: SDG indicators should be disaggregated, where relevant, by income, sex, age, race, ethnicity, migratory status, disability and geographic location, or other characteristics, in accordance with the Fundamental Principles of Official Statistics.
As sound statistical methods are vital to overcome this challenge, Small Area Estimation constitutes an important topic in the way forward. It covers a variety of methods used to produce survey based estimates for geographical areas or domains of study in which the sample sizes are too small, or even absent, to provide valid estimates. In order to obtain reliable estimates, additional datasets are generally brought to bear upon the process through a modelling procedure.
To enable national statistical offices to estimate disaggregated indicators, guidelines are needed to support the process. The idea of writing guidelines on how to use statistical methods and, in particular small area estimation (SAE), to receive disaggregated statistical indicators is not new. Some focus on methodological aspects, others provide methodology in a specific program language or focus on a specific topic as poverty mapping. Usability of SAE for official statistics has also been carried out over the past 10 years. So how do these guidelines differ from the existing work?
The SAE4SDG Toolkit in Wiki is a space to provide information on methods to produce disaggregated data through small area estimation. It aims to complement and use the existing methodological work and case studies to encourage and enable national statistical offices to employ SAE for the monitoring of the SDGs. The Toolkit will be an evolving project/document that will incorporate newly available methods, case studies and practical examples in future versions. The Toolkit also focuses on key steps to help countries in moving from SAE experiment to official data production. Finally, the Toolkit aims to be a space for partners to document and include references for their work on small area estimation.