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The Dynamics of Democracy, Development and Cultural Values
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
2014 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 9, no 6, e97856- p.Article in journal (Refereed) Published
Abstract [en]

Over the past decades many countries have experienced rapid changes in their economies, their democratic institutions and the values of their citizens. Comprehensive data measuring these changes across very different countries has recently become openly available. Between country similarities suggest common underlying dynamics in how countries develop in terms of economy, democracy and cultural values. We apply a novel Bayesian dynamical systems approach to identify the model which best captures the complex, mainly non-linear dynamics that underlie these changes. We show that the level of Human Development Index (HDI) in a country drives first democracy and then higher emancipation of citizens. This change occurs once the countries pass a certain threshold in HDI. The data also suggests that there is a limit to the growth of wealth, set by higher emancipation. Having reached a high level of democracy and emancipation, societies tend towards equilibrium that does not support further economic growth. Our findings give strong empirical evidence against a popular political science theory, known as the Human Development Sequence. Contrary to this theory, we find that implementation of human-rights and democratisation precede increases in emancipative values.

Place, publisher, year, edition, pages
2014. Vol. 9, no 6, e97856- p.
National Category
URN: urn:nbn:se:uu:diva-234216DOI: 10.1371/journal.pone.0097856ISI: 000341869000014OAI: oai:DiVA.org:uu-234216DiVA: diva2:755871
Available from: 2014-10-15 Created: 2014-10-15 Last updated: 2016-01-27Bibliographically approved
In thesis
1. Non-linear dynamic modelling for panel data in the social sciences
Open this publication in new window or tab >>Non-linear dynamic modelling for panel data in the social sciences
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Non-linearities and dynamic interactions between state variables are characteristic of complex social systems and processes. In this thesis, we present a new methodology to model these non-linearities and interactions from the large panel datasets available for some of these systems. We build macro-level statistical models that can verify theoretical predictions, and use polynomial basis functions so that each term in the model represents a specific mechanism. This bridges the existing gap between macro-level theories supported by statistical models and micro-level mechanistic models supported by behavioural evidence. We apply this methodology to two important problems in the social sciences, the demographic transition and the transition to democracy.

The demographic transition is an important problem for economists and development scientists. Research has shown that economic growth reduces mortality and fertility rates, which reduction in turn results in faster economic growth. We build a non-linear dynamic model and show how this data-driven model extends existing mechanistic models. We also show policy applications for our models, especially in setting development targets for the Millennium Development Goals or the Sustainable Development Goals.

The transition to democracy is an important problem for political scientists and sociologists. Research has shown that economic growth and overall human development transforms socio-cultural values and drives political institutions towards democracy. We model the interactions between the state variables and find that changes in institutional freedoms precedes changes in socio-cultural values. We show applications of our models in studying development traps.

This thesis comprises the comprehensive summary and seven papers. Papers I and II describe two similar but complementary methodologies to build non-linear dynamic models from panel datasets. Papers III and IV deal with the demographic transition and policy applications. Papers V and VI describe the transition to democracy and applications. Paper VII describes an application to sustainable development.

Place, publisher, year, edition, pages
Uppsala: Department of Mathematics, 2015. 40 p.
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 91
Dynamical systems, stochastic models, Bayesian, panel data, social sciences, development
National Category
Research subject
Mathematics with specialization in Applied Mathematics
urn:nbn:se:uu:diva-261289 (URN)978-91-506-2481-6 (ISBN)
Public defence
2015-11-06, Polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 10:00 (English)
Available from: 2015-10-14 Created: 2015-09-01 Last updated: 2016-01-27

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Ranganathan, ShyamMann, Richard P.Sumpter, David J. T.
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