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Setting development goals using stochastic, dynamical system models
Virginia Polytech Inst & State Univ, Dept Stat, Blacksburg, VA 24061 USA.
Univ Libre Bruxelles, Fac Sci, Serv Chim Phys & Biol Theor, Campus Plaine,CP 231, Brussels, Belgium.
Stockholm Sch Econ, Mistra Ctr Sustainable Markets, Stockholm, Sweden.; Sodertorn Univ, Stockholm, Sweden.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
2017 (English)In: Plos One, Vol. 12, no 2, e0171560Article in journal (Refereed) Published
Abstract [en]

The Millennium Development Goals (MDG) programme was an ambitious attempt to encourage a globalised solution to important but often-overlooked development problems. The programme led to wide-ranging development but it has also been criticised for unrealistic and arbitrary targets. In this paper, we show how country-specific development targets can be set using stochastic, dynamical system models built from historical data. In particular, we show that the MDG target of two-thirds reduction of child mortality from 1990 levels was infeasible for most countries, especially in sub-Saharan Africa. At the same time, the MDG targets were not ambitious enough for fast-developing countries such as Brazil and China. We suggest that model-based setting of country-specific targets is essential for the success of global development programmes such as the Sustainable Development Goals (SDG). This approach should provide clear, quantifiable targets for policymakers.

Place, publisher, year, edition, pages
2017. Vol. 12, no 2, e0171560
National Category
Economics
Identifiers
URN: urn:nbn:se:uu:diva-320152DOI: 10.1371/journal.pone.0171560ISI: 000395934400006PubMedID: 28241057OAI: oai:DiVA.org:uu-320152DiVA: diva2:1088830
Funder
Swedish Research Council, D049040
Available from: 2017-04-16 Created: 2017-04-16 Last updated: 2017-04-27Bibliographically approved

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CiteExportLink to record
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