Asymmetric causality between renewable energy consumption and economic growth: fresh evidence from some emerging countries

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Eyuboglu K., ÜZAR U.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, vol.29, no.15, pp.21899-21911, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 29 Issue: 15
  • Publication Date: 2022
  • Doi Number: 10.1007/s11356-021-17472-9
  • Journal Name: ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Geobase, MEDLINE, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.21899-21911
  • Keywords: Renewable energy, Asymmetric causality, Economic growth, Panel data, Emerging countries, NONRENEWABLE ENERGY, TRADE OPENNESS, CO2 EMISSIONS, FINANCIAL DEVELOPMENT, PANEL, NEXUS, DYNAMICS, PRICES, IMPACT, OUTPUT
  • Karadeniz Technical University Affiliated: Yes

Abstract

Renewable energy is an important alternative energy source in terms of both sustainable growth and climate change. In this paper, the causality nexus between renewable energy consumption and economic growth is analyzed in 15 emerging countries covering the period from 1990 to 2015. The paper adopts the bootstrap panel causality test which is developed by (Konya, Econ Model 23:978-992, 2006) to consider the cross-sectional dependence. The results of (Konya, Econ Model 23:978-992, 2006) prove the validity of the neutrality hypothesis in all countries. Then, we analyze asymmetric causality among the variables. Asymmetric test denotes a causality from negative shocks of economic growth to negative shocks of renewable energy consumption in South Africa, Thailand, and Turkey. Thus, a negative shock in economic growth hampers renewable energy consumption in these countries. Our results demonstrate the consequences of the application of disaggregated data in the analyses.