Small area estimation of labour force indicators under unit-level multinomial mixed models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F24%3A00379548" target="_blank" >RIV/68407700:21340/24:00379548 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1093/jrsssa/qnae033" target="_blank" >https://doi.org/10.1093/jrsssa/qnae033</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/jrsssa/qnae033" target="_blank" >10.1093/jrsssa/qnae033</a>
Alternative languages
Result language
angličtina
Original language name
Small area estimation of labour force indicators under unit-level multinomial mixed models
Original language description
This paper presents a new statistical methodology for the small area estimation of the proportion of employed, unemployed and inactive people, and of unemployment rates. The novel empirical best and plug-in predictors are based on a multinomial mixed model that is fitted to unit-level data. Model parameters are estimated by maximum-likelihood and mean-squared errors by parametric bootstrap. Several simulation experiments are carried out to empirically investigate the properties of these estimators and predictors. Finally, a detailed application to real data from the first Spanish Labour Force Survey of 2021 is included, where the target is to map labour force indicators by province, sex, and age group.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/EF16_019%2F0000778" target="_blank" >EF16_019/0000778: Center for advanced applied science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of the Royal Statistical Society Series A: Statistics in Society
ISSN
0964-1998
e-ISSN
1467-985X
Volume of the periodical
188
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
30
Pages from-to
241-270
UT code for WoS article
001202305300001
EID of the result in the Scopus database
2-s2.0-85215266995