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Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections

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  • Aleksejus Kononovicius

Abstract

We analyze a parties’ vote share distribution across the polling stations during the Lithuanian parliamentary elections of 1992, 2008, and 2012. We find that the distribution is rather well fitted by the Beta distribution. To reproduce this empirical observation, we propose a simple multistate agent-based model of the voting behavior. In the proposed model, agents change the party they vote for either idiosyncratically or due to a linear recruitment mechanism. We use the model to reproduce the vote share distribution observed during the election of 1992. We discuss model extensions needed to reproduce the vote share distribution observed during the other elections.

Suggested Citation

  • Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    • Handle: RePEc:hin:complx:7354642
    DOI: 10.1155/2017/7354642
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    1. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    2. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.
    3. Carpentras, Dino & Quayle, Michael, 2022. "Propagation of measurement error in opinion dynamics models: The case of the Deffuant model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    4. Levene, Mark & Fenner, Trevor, 2021. "A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1227-1234.
    5. Mark Levene & Aleksejus Kononovicius, 2018. "Empirical Survival Jensen-Shannon Divergence as a Goodness-of-Fit Measure for Maximum Likelihood Estimation and Curve Fitting," Papers 1809.11052, arXiv.org, revised Jun 2019.

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