Can conventional energy be replaced by renewable energy without harming economic growth in non-oil-MENA? Evidence from Granger causality in VECM

Abstract

Purpose The purpose of this paper is to examine the relationship between renewable energy consumption and economic growth in non-oil countries in the Middle East and North Africa (non-oil-MENA) during the period from 2000 to 2014. The Pedroni (2000) test shows that there is a long-term cointegration relationship between those variables; however, the Granger causality test in the vector error correction model (VECM) shows that this relationship is bidirectional in the short and long term. Thus, to ensure sustainable economic growth without pollution and to reduce dependence on abroad, renewable energies can be chosen as substitutes for conventional energies in the non-oil-MENA countries. Design/methodology/approach First, LLC and IPS unit root tests are used to test the variables stationarity; and, second, Pedroni panel cointegration and Engle–Granger causality by VECM analysis are used to check the relationship between the studied variables. Findings Empirical results show that the renewable energy consumption and economic growth are cointegrated and that there are two-way causal relationships between them in the long and in the short term. These countries must therefore encourage the consumption of renewable energy instead of traditional energy to reduce their dependence on energy from abroad and CO2 pollution. Originality/value The originality of this work lies in the measurements of the study variables and the empirical investigation methods used.

Gold-oil-exchange rate volatility, Bombay stock exchange and global financial contagion 2008: Application of NARDL model with dynamic multipliers for evidences beyond symmetry

“…We have identified the following four most important research gaps in the existing literature. Firstly, in existing literature number of research articles have only explored linear linkages between stock indexes, exchange rate fluctuations, oil price volatilities, and gold prices by utilizing linear models like VECM (Badry, 2019;Keswani & Wadhwa, 2018;Neveen, 2018;Rajesh, 2019;Sahu et al, 2014;Shiva & Sethi, 2015), VAR (Areli Bermudez Delgado et al, 2018;Ghulam, 2018;Huang et al, 2018), ARDL modeling approach (Ho, 2018;Singhal et al, 2019) and limited efforts have been made to explore the asymmetrical impact of Exchange rates-Gold-Oil price volatility on stock indexes by using NARDL model by (Shin et al, 2014).…”