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Democracy, Geography and Model Uncertainty

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  • Doris A. Oberdabernig
  • Stefan Humer
  • Jesus Crespo Cuaresma

Abstract

We analyse the nature of robust determinants of differences in democracy levels across countries taking explicitly into account uncertainty in the choice of covariates and spatial spillovers. We make use of recent developments in Bayesian model averaging to assess the effect of a large number of potential factors affecting democratisation processes and account for several specifications of spatial linkages. Our results indicate that spatial spillovers are present in the data even after controlling for a large number of geographical covariates. Addressing the determinants of democracy without modelling such spillovers may lead to flawed inference about the nature of the determinants of democratisation processes. In particular, our results emphasise the role played by Muslim religion, population size, trade volumes, English language, natural resource rents, GDP per capita, being a MENA country and the incidence of armed conflicts as factors affecting democracy robustly.

Suggested Citation

  • Doris A. Oberdabernig & Stefan Humer & Jesus Crespo Cuaresma, 2018. "Democracy, Geography and Model Uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(2), pages 154-185, May.
    • Handle: RePEc:bla:scotjp:v:65:y:2018:i:2:p:154-185
    DOI: 10.1111/sjpe.12140
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    2. Sajad Rahimian, 2021. "The Determinants of Democracy Revisited: An Instrumental Variable Bayesian Model Averaging Approach," Papers 2103.04255, arXiv.org.
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    6. Wolfer, Sascha & Koplenig, Alexander, 2024. "Leakage explains the apparent superiority of Bayesian random effect models – a preregistered comment on Claessens, Kyritsis and Atkinson (2023)," OSF Preprints ex267_v1, Center for Open Science.

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