Comparative Public Trust in Courts

Why

Judges in most countries are not directly elected, yet courts still depend on public trust to function. Rulings carry weight only when the public accepts them, and contested elections are only resolved peacefully when the losing side accepts the court's verdict. The public is therefore the repository of judicial legitimacy, and tracking how this varies across countries and over time tells us where the foundation is robust and where it may be eroding.

The data

Millions of responses are pooled from every national and cross-national programme that asks about trust or confidence in courts. These include Gallup, the World Values Survey, the regional Barometers, the European Social Survey, and ISSP. The programmes use very different response scales, ranging from binary through four-point and ten- or eleven-point ladders to continuous composites. Before fitting, every response is collapsed to a yes/no question: did the respondent give an above-the-middle answer? That lets one model accept every programme without having to decide which scales are mutually comparable.

The model

For each country we estimate a latent trust level that evolves year by year as a smooth random walk, following the dynamic latent-trait framework of Claassen (2019). The trusting answers to each survey item are modelled as a beta-binomial count, so a single noisy fielding carries less weight than a large, consistent one. Every survey item has its own difficulty and its own sensitivity to the underlying trust level, and each item-country pairing carries a small bias, which lets programmes on very different scales be pooled without assuming they are interchangeable:

yikt  ~  BetaBinomial( sikt, φηikt, φ(1−ηikt) ) ηikt = logit−1( λk + γk · θit + δik )

Here yikt is the number of trusting answers out of sikt respondents to item k in country i and year t; θit is the country's latent trust level in that year; λk and γk are the item's difficulty and slope; δik is the item-country bias; and φ sets how far surveys scatter around the latent proportion. The numbers shown throughout the app put this latent scale on a probability by evaluating η at a common Gallup anchor item (with its item-country bias set to zero), giving P(trust) = logit−1anchor + γanchor·θ). Fitting is by Hamiltonian Monte Carlo (NUTS) in NumPyro.

Claassen, Christopher. 2019. “Estimating Smooth Country–Year Panels of Public Opinion.” Political Analysis 27(1): 1–20. doi:10.1017/pan.2018.32.

Coverage

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The items capture trust in courts or the judicial system in general, with no specific court named (j_trust_gen); trust in the supreme court (j_trust_sc); and trust in the constitutional court (j_trust_cc). Together they account for over 90% of all court-related survey responses in the data. Where a respondent answered more than one, only the first available in that order enters the model, so no individual is counted more than once.

Authors

Michal Ovádek is a lecturer in the Department of Political Science, University College London.

Umut Yüksel is a postdoctoral researcher in the Department of Political Science, University College London.

Citation

@unpublished{ovadekyuksel2026,
  author = {Michal Ov{\'a}dek and Umut Y{\"u}ksel},
  title  = {Comparative Public Trust in Courts},
  note   = {OSF Preprints},
  url    = {https://osf.io},
  year   = {2026}
}

Data version: …