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Analysing the course of public trust via hidden Markov models: a focus on the Polish society

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  • Fulvia Pennoni

    () (University of Milano-Bicocca)

  • Ewa Genge

    () (University of Economics)

Abstract

We investigate public trust among the society by a statistical model suitable for panel data. At this aim, using trust’s levels measured from individual items recorded through a long-term survey we dispose of key variables with appropriate meaning. We account for the repeated and missing item responses by a hidden Markov model using longitudinal sampling weights. Since trust may be conceived as a psychological unobservable process of each person that fluctuates over time we consider observed time-varying and time-fixed individual covariates. We estimate the model parameters by a weighted log-likelihood through the Expectation–Maximization algorithm by using data collected in an East-Central European country like Poland. The latter is a country where the level of support to the national and international institutions is one of the lowest among the European member states. We apply a suitable algorithm based on the posterior probabilities to predict the best allocation to each latent typology. The proposed model is validated by generating out-of-sample responses and we find reasonable predictive values. We disentangle four hidden groups of Poles: discouraged, with no opinion, with selective trust and with fully public trust. We reveal an increasing number of people that are going to trust only some selected institutions over time.

Suggested Citation

  • Fulvia Pennoni & Ewa Genge, 2020. "Analysing the course of public trust via hidden Markov models: a focus on the Polish society," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 399-425, June.
  • Handle: RePEc:spr:stmapp:v:29:y:2020:i:2:d:10.1007_s10260-019-00483-9
    DOI: 10.1007/s10260-019-00483-9
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    References listed on IDEAS

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