Original scientific paper
https://doi.org/10.1080/1331677X.2022.2097448
Non-parametric research methods to measure energy efficiency and renewable energy nexus: evidence from emerging economies
Nan Ye
Ling Yuan
Yong Xu
Abstract
This study aims to analyse the connection between energy efficiency
and renewable energy consumption in the emerging seven
(E7) economies during the period 1990–2020. This study also
examines the impact of economic growth, carbon emissions and
technological innovation on renewable energy. This study
employs various panel data approaches that validate the irregular
distribution of data and the heterogeneous slopes coefficients.
The cross-section dependence test confirms that cross-section
dependence is present in the study variables. While these variables
are cointegrated. Using non-parametric panel data
approaches, the moments’ quantile regression results unveil that
economic growth is positively associated with renewable energy
in all quantiles. Whereas energy efficiency and carbon emissions
showed mixed results, negatively affect renewable energy consumption
in the lower quantiles, insignificant in the medium
quantiles and positive in the higher quantiles. On the other hand,
technological innovation is found negatively related to renewable
energy consumption. Bidirectional causal association is found
between explanatory variables and renewable energy consumption.
Based on the empirical findings, this study suggests policies
to divert economic growth from fossil fuel energy consumption,
enhancing investment in the renewable energy sector, promoting
energy efficiency and investment in environmental-related technologies
to promote renewable energy.
Keywords
Energy efficiency; renewable energy; economic growth; carbon emissions; technological innovation; method of moment quantile regression
Hrčak ID:
304269
URI
Publication date:
31.3.2023.
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