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 (SAE) 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 |