A0170
Title: Small area estimation of labour force indicators under bivariate Fay-Herriot model with correlated time and area effects
Authors: Esteban Cabello - Universidad Miguel Hernandez de Elche (Spain) [presenting]
Domingo Morales - University Miguel Hernandez of Elche (Spain)
Agustin Perez Martin - University Miguel Hernandez of Elche (Spain)
Maria-Dolores Esteban - University-Miguel Hernandez of Elche (Spain)
Abstract: An area-level temporal bivariate linear mixed model is developed which incorporates correlated time effects for estimating socioeconomic indicators in small areas. The model is applied through the residual maximum likelihood method, deriving empirical best linear unbiased predictors for these indicators. Additionally, an approximation for the matrix of mean squared errors (MSE) is provided, and four MSE estimators are proposed. The first estimator involves a plug-in approach to the MSE approximation, while the remaining estimators are based on parametric bootstrap procedures. Three simulation experiments are conducted to assess the performance of the fitting algorithm, predictors, and MSE estimators. An application to real data from the 2016 to 2022 Spanish Living Conditions Survey is conducted. The focus is on estimating poverty proportions and gaps for the year 2022, categorized by provinces and sex.
