Year: 2026
Type: preprint
Abstract: The 2030 Agenda for Sustainable Development of the United Nations outlines 17 goals as global challenges for countries of the world to address in their development. However, the progress of countries towards these goals has been much slower than expected. In a previous study, we analyzed the data over two decades (2000--2022), using unsupervised machine learning techniques. Based on this study, we take into account three main factors to construct a mathematical model to simulate and predict the dynamical behavior of the SDGs. These factors are: (1) the distribution of amount of resources that each country uses to meet the goals, (2) the cooperation between countries, and (3) the correlations between the goals. In this work, we show that the model is capable of reproducing the real data and therefore could be used to simulate hypothetical scenarios that could help to improve actions towards optimal fulfillment of the goals.
Source: arXiv (Cornell University)
Topic: Human Rights and Development
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7155494356
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