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Small area estimation techniques are used in sample surveys, where direct estimates for small domains are not reliable due to small sample sizes in the domains. We estimate the domain means by generalized linear compositions of the weighted sample means and the synthetic estimators that are obtained from the regression-synthetic model of fixed effects, based on the domain level auxiliary information. In the proposed method, the number of parameters of optimal compositions is reduced to a single unknown parameter, which is further evaluated by minimizing an empirical risk function. We apply various composite and related estimators to estimate proportions of the unemployed in a simulation study, based on the Lithuanian Labor Force Survey data. Conclusions on advantages and disadvantages of the proposed compositions are obtained from this empirical comparison.

Even though Lithuania's household income inequality is among the highest in the European Union (EU), little empirical work has been carried out to explain such disparities. We investigate it using the EU Statistics on Income and Living Conditions sample microdata. We confirm that income inequality in Lithuania is high compared to the EU average. Our decompositions reveal that the number of employed household members in Lithuania's households affects income inequality more as compared to the EU. It is related to a larger labour income, and self-employment income, in particular, contribution to inequality in Lithuania. Moreover, taxes, social contributions, and transfers reduce income inequality in Lithuania less than in the EU. Specifically, income taxes and social contributions are less progressive while transfers constitute a smaller share of income in Lithuania than in the EU. Income taxes and social contributions are effectively regressive for the selfemployed in Lithuania.

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