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Authors: Shyam Ranganathan 1 ; Viktoria Spaiser 2 and David J. T. Sumpter 3

Affiliations: 1 Uppsala University, Sweden ; 2 Institute for Futures Studies, Sweden ; 3 Uppsala University and Institute for Futures Studies, Sweden

Keyword(s): Bayesian Methods, Model Selection, Dynamical Systems, Mathematical Modeling, Social Sciences.

Related Ontology Subjects/Areas/Topics: Complex Systems Modeling and Simulation ; Domain-Specific Tools ; Dynamical Systems Models and Methods ; Formal Methods ; Non-Linear Systems ; Simulation and Modeling ; Simulation Tools and Platforms ; Social Systems Simulation

Abstract: The paper presents a new modeling approach using longitudinal or panel data to study social phenomena and to make predictions of dynamic changes. While the most common way in social sciences to study the relations between variables is using regression, our modeling approach describes the changes in variables as a function of all included variables, using differential equations with polynomial terms that capture linear and/or nonlinear effects. The mathematical models represented by these differential equations are derived directly from data. The models can then be run forward to forecast future changes. A two-step model-fitting approach is applied to identify the best-fit models and included visualisation methods based on phase portraits help to illustrate modeling results. We show this approach on an example relating democracy to economic growth.

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Paper citation in several formats:
Ranganathan, S.; Spaiser, V. and J. T. Sumpter, D. (2013). A Bayesian Approach to Modeling Dynamical Systems in the Social Sciences. In Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH; ISBN 978-989-8565-69-3; ISSN 2184-2841, SciTePress, pages 125-131. DOI: 10.5220/0004480901250131

@conference{simultech13,
author={Shyam Ranganathan. and Viktoria Spaiser. and David {J. T. Sumpter}.},
title={A Bayesian Approach to Modeling Dynamical Systems in the Social Sciences},
booktitle={Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH},
year={2013},
pages={125-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004480901250131},
isbn={978-989-8565-69-3},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH
TI - A Bayesian Approach to Modeling Dynamical Systems in the Social Sciences
SN - 978-989-8565-69-3
IS - 2184-2841
AU - Ranganathan, S.
AU - Spaiser, V.
AU - J. T. Sumpter, D.
PY - 2013
SP - 125
EP - 131
DO - 10.5220/0004480901250131
PB - SciTePress

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