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Small Area Estimation of Latent Economic Well-being
[journal article]
Abstract Small area estimation (SAE) plays a crucial role in the social sciences due to the growing need for reliable and accurate estimates for small domains. In the study of well-being, for example, policy makers need detailed information about the geographical distribution of a range of social indicators.... view more
Small area estimation (SAE) plays a crucial role in the social sciences due to the growing need for reliable and accurate estimates for small domains. In the study of well-being, for example, policy makers need detailed information about the geographical distribution of a range of social indicators. We investigate data dimensionality reduction using factor analysis models and implement SAE on the factor scores under the empirical best linear unbiased prediction approach. We contrast this approach with the standard approach of providing a dashboard of indicators or a weighted average of indicators at the local level. We demonstrate the approach in a simulation study and a real data application based on the European Union Statistics for Income and Living Conditions for the municipalities of Tuscany.... view less
Keywords
estimation; EU; Italy; factor analysis; method; data; indicator; weighting
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
EU-SILC; composite estimation; direct estimation; EBLUP; factor scores; model-based estimation
Document language
English
Publication Year
2019
Page/Pages
p. 1-34
Journal
Sociological Methods & Research (2019)
DOI
https://doi.org/10.1177/0049124119826160
ISSN
1552-8294
Status
Published Version; peer reviewed