  This paper introduces empirical best predictors of small area bivariate
parameters, like ratios of sums or sums of ratios, by assuming that the target
unit-level vector follows a bivariate nested error regression model. The
corresponding means squared errors are estimated by parametric bootstrap.
Several simulation experiments empirically study the behavior of the introduced
statistical methodology. An application to real data from the Spanish household
budget survey gives estimators of ratios of food household expenditures by
provinces.
