Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis

Yassir Alharbi, Yassir Alharbi, Daniel Arribas-Bel, Frans Coenen

2021

Abstract

A framework for UN Sustainability for Development Goal (SDG) attainment prediction is presented, the SDG Track, Trace & Forecast (SDG-TTF) framework. Unlike previous SDG attainment frameworks, SDG-TTF takes into account the potential for causal relationship between SDG indicators both with respect to the geographic entity under consideration (intra-entity), and neighbouring geographic entities to the current entity (inter-entity). The challenge is in the discovery of such causal relationships. Six alternatives mechanisms are considered. The identified relationships are used to build multivariate time series prediction models which feed into a bottom-up SDG prediction taxonomy, which in turn is used to make SDG attainment predictions. The framework is fully described and evaluated. The evaluation demonstrates that the SDG-TTF framework is able to produce better predictions than alternative models which do not take into consideration the potential for intra and inter-causal relationships.

Paper Citation

in Harvard Style

Alharbi Y., Arribas-Bel D. and Coenen F. (2021). Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA, ISBN 978-989-758-526-5, pages 123-131. DOI: 10.5220/0010546101230131

in Bibtex Style

@conference{delta21,
author={Yassir Alharbi and Daniel Arribas-Bel and Frans Coenen},
title={Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis},
booktitle={Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA,},
year={2021},
pages={123-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010546101230131},
isbn={978-989-758-526-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA,
TI - Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis
SN - 978-989-758-526-5
AU - Alharbi Y.
AU - Arribas-Bel D.
AU - Coenen F.
PY - 2021
SP - 123
EP - 131
DO - 10.5220/0010546101230131