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Analysing Mechanisms for Meeting Global Emissions Target - A Dynamical Systems Approach
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
2014 (English)Report (Other academic)
Abstract [en]

Global emissions beyond 44 gigatonnes of carbondioxide equivalent (GtCO2e) in 2020 can potentially lead the world to an irreversible climate change. Employing a novel dynamical system modeling approach, we predict that in a business-asusual scenario, it will reach 61 GtCO2e by 2020. Testing estimated parameters, we nd that limiting the burden of emission reduction to the top 25 global emitters, does not increase their encumbrance. In absence of emission cuts, technology and preferences for environmental quality have to improve by at least 2.6 percent and 3.5 percent if the emission target has to be met by 2020.

Place, publisher, year, edition, pages
2014. , 40 p.
Series
Working paper / Department of Economics, Uppsala University (Online), ISSN 1653-6975 ; 2014:10
National Category
Economics
Research subject
Economics
Identifiers
URN: urn:nbn:se:uu:diva-235543OAI: oai:DiVA.org:uu-235543DiVA: diva2:761054
Available from: 2014-11-05 Created: 2014-11-05 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.
Series
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 91
Keyword
Dynamical systems, stochastic models, Bayesian, panel data, social sciences, development
National Category
Mathematics
Research subject
Mathematics with specialization in Applied Mathematics
Identifiers
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)
Opponent
Supervisors
Available from: 2015-10-14 Created: 2015-09-01 Last updated: 2016-01-27

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Ranganathan, ShyamBali Swain, Ranjula

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