Introduction to Small Area Estimation

About

Large-scale sample surveys are not designed to produce reliable estimates for small population domains, such as specific geographical areas or population groups. This is because area sample sizes may be “too small” to compute reliable direct estimates (obtained via the use of the sample data only). Therefore, small area estimation methods that borrow strength information from auxiliary data, such as the Census or administrative data, can be used to produce reliable estimates. This course will cover widely adopted small area estimation methods based on the direct and model-based estimation approaches. It will be structured in three parts. The first part will be about the introduction to the small area estimation problem and the use of direct estimators to produce small area estimates. In the second part, we will introduce the unit-level approach based on the Battese, Harter, and Fuller model, assuming that auxiliary information is available at the unit level. The third part will focus on the area-level approach based on the Fay-Herriot model, which is useful when the auxiliary information is available at the area level only. The course will also focus on the evaluation of the small area estimates via diagnostics tools and simulation studies. Practical applications and examples will be provided in each part of the course.

Practical applications and examples will be carried out in R. We will show some common R packages available to users. Applications will be based on both real data and simulation studies

Course leader

Angelo Moretti, Utrecht University

Target group

You will find the course useful if you are a social scientist, a researcher working in the survey field, or a statistician at the PhD level or beyond, working on academic research projects and interested in learning about the small area estimation methods

Course aim

By the end of the course, you will:
- understand the small area estimation problem,
- be able to identify the appropriate small area estimation approach given specific survey data,
- be able to apply and validate relevant small area estimation methods based on the area-level and unit-level approach,
- know how to implement the methods in R software,
- know how to present and visualize the results and analyses

Fee info

The rates include the tuition fee, course materials, the academic program, social and plenary program, and coffee/tea breaks