Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa

In this data article, we present datasets from the construction of a composite indicator, the Photovoltaic Decentralised Energy Investment (PV-DEI) index, presented in detail in [1]. This article consists of a comprehensive energy-related data collected in practice from several sources, and from the...

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Main Authors: A. Bender, M. Moner-Girona, W. Becker, K. Bódis, S. Szabó, A.G. Kararach, L.D. Anadon
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340921005497
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author A. Bender
M. Moner-Girona
W. Becker
K. Bódis
S. Szabó
A.G. Kararach
L.D. Anadon
author_facet A. Bender
M. Moner-Girona
W. Becker
K. Bódis
S. Szabó
A.G. Kararach
L.D. Anadon
author_sort A. Bender
collection DOAJ
description In this data article, we present datasets from the construction of a composite indicator, the Photovoltaic Decentralised Energy Investment (PV-DEI) index, presented in detail in [1]. This article consists of a comprehensive energy-related data collected in practice from several sources, and from the outputs of the methodology described in [1]. The PV-DEI was designed and developed to measure the multidimensional factors that currently direct decentralised renewable energy investments. The PV-DEI index includes 52 indicators and was constructed because factors stimulating investment cannot be captured by a single indicator, e.g. competitiveness, affordability, or governance [1]. The PV-DEI index was built in alignment with a theoretical framework guided by an extensive review of the literature surrounding investment in decentralised Photovoltaic (PV), which led to the selection of its indicators. The structure of the PV-DEI was evaluated for its soundness using correlational assessments and principal component analyses (PCA). The raw data provided in this article can enable stakeholders to focus on specific country indicators, and how scores on these indicators contributed to a countries overall rank within the PV-DEI index. The data can be used to weight indicators depending on the specifications of several different stakeholders (such as NGOs, private sector or international institutions).
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spelling doaj.art-c80fb871640e4a2c9032a84e0f20e9442022-12-21T20:00:27ZengElsevierData in Brief2352-34092021-08-0137107265Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan AfricaA. Bender0M. Moner-Girona1W. Becker2K. Bódis3S. Szabó4A.G. Kararach5L.D. Anadon6University of Cambridge, Centre for Environment, Energy and Natural Resource Governance, Cambridge, United Kingdom; Victoria University of Wellington, Geography, Environment and Earth Sciences, New ZealandEuropean Commission, Joint Research Centre (JRC), Ispra, Italy; Corresponding author.European Commission, Joint Research Centre (JRC), Ispra, ItalyInstitute of Advanced Studies (iASK), Kőszeg, HungaryEuropean Commission, Joint Research Centre (JRC), Ispra, Italy; European Institute of Innovation and Technology, Budapest, HungaryAfrican Development Bank Group, South AfricaUniversity of Cambridge, Centre for Environment, Energy and Natural Resource Governance, Cambridge, United KingdomIn this data article, we present datasets from the construction of a composite indicator, the Photovoltaic Decentralised Energy Investment (PV-DEI) index, presented in detail in [1]. This article consists of a comprehensive energy-related data collected in practice from several sources, and from the outputs of the methodology described in [1]. The PV-DEI was designed and developed to measure the multidimensional factors that currently direct decentralised renewable energy investments. The PV-DEI index includes 52 indicators and was constructed because factors stimulating investment cannot be captured by a single indicator, e.g. competitiveness, affordability, or governance [1]. The PV-DEI index was built in alignment with a theoretical framework guided by an extensive review of the literature surrounding investment in decentralised Photovoltaic (PV), which led to the selection of its indicators. The structure of the PV-DEI was evaluated for its soundness using correlational assessments and principal component analyses (PCA). The raw data provided in this article can enable stakeholders to focus on specific country indicators, and how scores on these indicators contributed to a countries overall rank within the PV-DEI index. The data can be used to weight indicators depending on the specifications of several different stakeholders (such as NGOs, private sector or international institutions).http://www.sciencedirect.com/science/article/pii/S2352340921005497AfricaPhotovoltaicEnergy accessMini-gridMultidimensional approachEnergy development policy
spellingShingle A. Bender
M. Moner-Girona
W. Becker
K. Bódis
S. Szabó
A.G. Kararach
L.D. Anadon
Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
Data in Brief
Africa
Photovoltaic
Energy access
Mini-grid
Multidimensional approach
Energy development policy
title Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
title_full Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
title_fullStr Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
title_full_unstemmed Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
title_short Dataset for multidimensional assessment to incentivise decentralised energy investments in Sub-Saharan Africa
title_sort dataset for multidimensional assessment to incentivise decentralised energy investments in sub saharan africa
topic Africa
Photovoltaic
Energy access
Mini-grid
Multidimensional approach
Energy development policy
url http://www.sciencedirect.com/science/article/pii/S2352340921005497
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