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Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals

Guerrero, OA; Castañeda, G; (2020) Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals. Data & Policy , 2 , Article e17. 10.1017/dap.2020.18. Green open access

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Abstract

We build a computational framework to support the planning of development and the evaluation of budgetary strategies toward the 2030 Agenda. The methodology takes into account some of the complexities of the political economy underpinning the policymaking process: the multidimensionality of development, the interlinkages between these dimensions, and the inefficiencies of policy interventions, as well as institutional factors that promote or discourage these inefficiencies. The framework is scalable and usable even with limited publicly available information: development-indicator data. However, it can be further refined as more data becomes available, for example, on public expenditure. We demonstrate its usage through an application for the Mexican federal government. For this, we infer historical policy priorities, that is, the non-observable allocations of transformative resources that generated past changes in development indicators. We also show how to use the tool to assess the feasibility of development goals, to measure policy coherence, and to identify accelerators. Overall, the framework and its computational tools allow policymakers and other stakeholders to embrace a complexity (and a quantitative) view to tackle the challenges of the Sustainable Development Goals.

Type: Article
Title: Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals
Open access status: An open access version is available from UCL Discovery
DOI: 10.1017/dap.2020.18
Publisher version: https://doi.org/10.1017/dap.2020.18
Language: English
Additional information: Copyright © The Author(s), 2020. Published by Cambridge University Press in association with Data for Policy. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Keywords: agent-based model, agent-computing, complexity, policy priorities, sustainable development
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/10118149
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