Title: Small area estimation

Speaker: Domingo Morales

Affiliation: Instituto Universitario Centro de Investigación Operativa. Universidad Miguel Hernández de Elche.

Abstract: Statistical Offices design surveys to estimate population parameters and select sample sizes to achieve an a priori fixed precision.In practice, statisticians are often required to give estimates of subpopulations or small areas, where sample sizes are small.Direct estimators of small area parameters, calculated using only the sample data from the corresponding area, are not reliable enough. The  use  of  models  that  include  auxiliary  variables  and  borrow  strength  from  cross-sectional data or time  and spatial correlation may produce estimates that are more accurate. Small  Area  Estimation  is  a  part  of  statistical  science  that  improves  the  efficiency  of  direct estimators by combining methodologies from survey sampling and finite population inference with statistical models.The talk introduces the model-based approaches and outlines some recent advances related to empirical best predictors of small area bivariate parameters, like ratios of sums or sums of ratios. An application to real data from the Spanish household budget survey illustrates the statistical methodology by giving estimators of ratios of food household expenditures by provinces.