Esteban, M.D., Hobza, T., Morales, D., Pérez, A. (2023). Small Area Estimation of Proportion-Based Indicators. In: Balakrishnan, N., Gil, M.Á., Martín, N., Morales, D., Pardo, M.d.C. (eds) Trends in Mathematical, Information and Data Sciences. Studies in Systems, Decision and Control, vol 445. Springer, Cham.

María Dolores Esteban (Miguel Hernández University of Elche), Tomáš Hobza (Czech Technical University in Prague), Domingo Morales (Miguel Hernández University of Elche) and Agustín Pérez (Miguel Hernández University of Elche)

Abstract:

This paper considers a unit-level multinomial model with logit link for small area estimation of proportion-based socioeconomic indicators. For a labour force survey, some of these indicators are totals of unemployed people, proportions of inactive people, unemployment rates or entropy indexes. A Broyden quasi-Newton algorithm is proposed to calculate the method-of-moment and maximum likelihood estimators of the model parameters. Model-based predictors of small area indicators are derived and their mean squared errors are estimated by parametric bootstrap.