Modeling public opinion over time and space : Trust in state institutions in Europe, 1989-2019

Combining public opinion data from different sources enables new cross-national and longitudinal research, but is accompanied by unique challenges related to the comparability of the source survey data. The analytic strategy we propose relies on Bayesian explanatory item response theory models to address differences in the measurement of attitudes, and poststratification that uses administrative population data to improve the quality of estimates and correct for differences in sample representativeness. Partially pooled models with data from all countries would be prohibitively slow, so we estimate separate by-country models in a way that maintains comparability of estimates across countries. We apply this strategy to data from 13 cross-national research projects from 27 European countries to estimate trajectories of political trust between 1989-2019.