R
Roula Inglesi-Lotz
Researcher at University of Pretoria
Publications - 107
Citations - 3835
Roula Inglesi-Lotz is an academic researcher from University of Pretoria. The author has contributed to research in topics: Granger causality & Renewable energy. The author has an hindex of 22, co-authored 91 publications receiving 2441 citations. Previous affiliations of Roula Inglesi-Lotz include University of Cape Town.
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The impact of renewable energy consumption to economic growth: A panel data application
TL;DR: In this paper, the authors investigated the impact of renewable energy consumption on economic welfare by employing panel data techniques and found that the influence of renewable energies consumption or its share to the total energy mix to economic growth is positive and statistically significant.
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The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators
Roula Inglesi-Lotz,Eyup Dogan +1 more
TL;DR: In this article, the authors estimate the determinants of CO2 emissions for the ten biggest electricity generators in Sub-Saharan Africa for the period 1980 to 2011 by employing panel estimation techniques robust to cross dependence.
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The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries
TL;DR: In this article, the causal link between electricity consumption, economic growth and CO 2 emissions in the BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) for the period 1990-2010, using panel causality analysis.
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The impact of economic structure to the environmental Kuznets curve (EKC) hypothesis: evidence from European countries
Eyup Dogan,Roula Inglesi-Lotz +1 more
TL;DR: The main finding of the study is that the overall economic growth is the factor with which CO 2 emissions exhibit an inverted U-shaped relationship in the studied country group.
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Factors affecting CO2 emissions in top countries on renewable energies: A LMDI decomposition application
TL;DR: In this paper, the authors analyzed the effects evolution of CO2 emissions using a larger available data span that runs from 1985 until 2011, to determine which of the effects had more impact over changes of CO 2 emissions.