A Case Study on Hierarchical Linear Models Applied to the UN’s Sustainable Development Goals (SDGs): A Perspective Using the World and Brazil’s Data

This study analyzed the statistical relation between the Sustainable Development Goals and their relative indicators for the UN’s 2030 Agenda through the implementation of a two-level linear hierarchical model (HLM2) using STATA/SE 16 statistical software. The objective of this model was to address...

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Veröffentlicht in:Sustainability 2023-05, Vol.15 (10), p.8304
Hauptverfasser: Lemes, Murilo, Belfiore, Patrícia, Fávero, Luiz Paulo
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creator Lemes, Murilo
Belfiore, Patrícia
Fávero, Luiz Paulo
description This study analyzed the statistical relation between the Sustainable Development Goals and their relative indicators for the UN’s 2030 Agenda through the implementation of a two-level linear hierarchical model (HLM2) using STATA/SE 16 statistical software. The objective of this model was to address priorities by saying how much and where each country should invest so that they can achieve these goals by the end of the decade. Intrinsically, it was checked whether the indicators listed by the UN are statistically capable of describing the expected output. After analyzing the results, SDGs 8, 9 and 7 were, respectively, identified as priorities. The HLM2 also pointed out that economic growth is the most important variable amongst all considered. Finally, it was concluded that a generic answer does not serve to respond to the complexities worldwide, and therefore, it would be more appropriate to direct actions on a case-by-case basis.
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source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; MDPI - Multidisciplinary Digital Publishing Institute
subjects Analysis
Case studies
Climate change
Coronaviruses
COVID-19
Economic development
Economic growth
Indicators
Pandemics
Priorities
Statistics
Sustainable development
Variables
title A Case Study on Hierarchical Linear Models Applied to the UN’s Sustainable Development Goals (SDGs): A Perspective Using the World and Brazil’s Data
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