Replication Data for: Využití víceúrovňových modelů při analýze kontextuálních efektů míry ekonomické aktivity na podporu přerozdělování v komparativních longitudinálních datech

This article studies associations between a country's labour force participation rate and attitudes towards income redistribution. The article also demonstrates how to specify a multilevel model when analysing contextual effects. The paper presents several types of random effects structures (Schmidt-Catran, Fairbrother 2016) and options for centering explanatory variables in comparative longitudinal survey data. The contextual effect is decomposed into longitudinal and cross-sectional components for time-varying contextual variables, such as labour force participation rate. The analysis of redistribution support based on ESS data from 27 countries and nine rounds shows how fundamentally the mentioned properties might influence substantive conclusions. Performed analyses do not provide evidence for the associations between redistribution support and labour force participation rate. However, the hypothetical configurations of multilevel models presented in this article cover all possible substantive effects of the labour force participation rate. Contextual effects analysis may thus lead to highly unreliable results when a multilevel model fails to control for compositional effects of individual-level predictors, does not specify random effects at the level with the variance of the outcome variable, or does not distinguish between longitudinal and cross-sectional effects of time-varying variables.