Small Area Estimation of Latent Economic Well-being
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2371
- Type
- D - Journal article
- DOI
-
10.1177/0049124119826160
- Title of journal
- Sociological Methods & Research
- Article number
- -
- First page
- n/a
- Volume
- n/a
- Issue
- -
- ISSN
- 0049-1241
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
https://e-space.mmu.ac.uk/625174/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
A - Data Science
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first article in the literature where the problem of latent well-being indicators is addressed in small area estimation under factor analysis models. This is an important topic that contributes to the Sustainable Development Goals. The method that was developed in this paper has been applied in other fields e.g. criminology by Buil-Gil, Medina and Shlomo (2019) and welfare attitudes by Moretti and Whitworth (2019). The research was presented at the International Conference of Small Area Estimation in 2016 and led to a funded collaboration with researchers from University College Cork.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -