TY  - JOUR
A1  - Vogt, Martin
A1  - Lahiri, Partha
A1  - Münnich, Ralf
T1  - Spatial prediction in small area estimation
T2  - Statistics in Transition new series
N2  - Small area estimation methods have become a widely used tool to provide accurate estimates for regional indicators such as poverty measures. Recent research has provided evidence that spatial modelling still can improve the precision of regional and local estimates. In this paper, we provide an intrinsic spatial autocorrelation model and prove the propriety of the posterior under a flat prior. Further, we show using the SAIPE poverty data that the gain in efficiency using a spatial model can be essentially important in the presence of a lack of strong auxiliary variables.
KW  - Fay-Herriot
KW  - CAR
KW  - poverty estimation
KW  - spatial models
KW  - Armut
KW  - Messung
KW  - Modellierung
Y1  - 2023
UR  - https://hst.opus.hbz-nrw.de/frontdoor/index/index/docId/1009
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:tr5-10094
VL  - 24
IS  - 3
SP  - 77
EP  - 94
PB  - Statistics Poland
ER  -