Decomposition of Long-Term Changes in Political Opinions According to Group-Specific Markov Processes
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In this paper the authoress uses longitudinal data for Poland to test the assumption that political opinion change through time is not entirely due to some universal and time-constant processes; rather, it depends on the initial conditions in a person's state. Information on Poles' evaluations of the past socialist regime available for repeated intervals, and over a sufficiently long time period - ten years - allows her to decompose long-term changes in assessment of socialism into short-term change, and the reliability of responses according to group-specific Markov processes. She obtains three types of stochastic matrices: Mt, t+10, Mt, t+1, Mrel = R , where M refers to a matrix of opinions in time t by opinions in subsequent time, t refers to specific years, and R is the reliability matrix from the measurement of opinions in one-month period. To assess the fit of the observed transition matrix for the 10-year period as a linear combination of matrices Mt, t+1 and Mrel, she applies the random effect maximum likelihood function in STATA, with the bootstrap option for obtaining the standard errors of the coefficients. Results demonstrate that Markov-type processes do not have significant explanatory power for long-term change in opinions about socialism. Substantively, this means that the 'subjective' legacy of the past, namely peoples' views of the former regime, matters.
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