Estimating Regional Income Indicators under Transformations and Access to Limited Population Auxiliary Information
نویسندگان
چکیده
Abstract Spatially disaggregated income indicators are typically estimated by using model-based methods that assume access to auxiliary information from population micro-data. In many countries like Germany and the UK micro-data not publicly available. this work we propose small area methodology when only aggregate population-level is We use data-driven transformations of response satisfy parametric assumptions used models. absence micro-data, appropriate bias-corrections for prediction needed. Under approach in paper, statistics (means covariances) kernel density estimation resolve issue having further explore mean squared error bootstrap. Extensive design-based simulations compare proposed method alternative methods. Finally, applied 2011 Socio-Economic Panel census same year estimate average 96 regional planning regions Germany.
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society
سال: 2022
ISSN: ['0035-9238', '2397-2327']
DOI: https://doi.org/10.1111/rssa.12913