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The current wave of decreasing electricity supply to meet the immediate demand of the populace is influencing not only economic growth but also the industrial productivity of the ECOWAS sub-region. In this context, this paper investigates the long-run and causal relationships between electricity consumption and industrial output in selected ECOWAS countries over the period 1971–2017.

The Autoregressive Distributed Lag (ARDL) bound testing approach is employed to determine the existence of relationships among the variables. The causal nexus between electricity consumption and industrial output is examined using both the Toda-Yamamoto causality test and the bootstrap-corrected causality technique.

The long run results indicated that increasing electricity supply enhances industrial output only in Benin, Cote d'Ivoire, Gambia, Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. Furthermore, the causality test results confirmed the presence of all four hypotheses in this study, but the two causality tests agree, particularly in the evidence of growth and neutrality hypotheses. In the cases of Benin, Burkina Faso, Gambia, Ghana, Nigeria, and Sierra Leone, a unilateral causality running from electricity consumption to industrial output is found. However, no evidence of causality between electricity consumption and industrial production has been confirmed in Cote d'Ivoire, Guinea Bissau, Liberia and Niger.

The relevant energy stakeholders in the subregion need to reprioritize their policy framework to focus more on the electricity sector of their economies since electricity consumption is identified as an important driver of industrial growth in the West African countries.

This is the first study to provide a comparative and country-specific investigation of the nexus between electricity consumption and industrial output in Africa, particularly in the West African region.

The exchange rate has been an important topic in the Turkish Economy for many years. It affects prices with exchange rate pass-through. The aim of this chapter is to analyze the dual relationship between exports and imports, exports and the exchange rate, imports and the exchange rate by using time series analysis. The results indicate that there is only one causal relationship between exports and imports. The direction is from imports to exports.

This study aims to investigate the dynamic relationship between renewable and non-renewable energy sources on the economic growth of eight countries, the capital stock and labour force being used as control variables in each case. Questions that need to be asked include the following: Is there is an asymmetric and, hence, a non-linear relationship between variables? If yes, how does economic growth interact with both renewable and non-renewable energy consumption (EC)? How different are these relationships in the countries highly rated in the performance of renewable EC compared to those lowly rated?

This paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables.

A newly developed asymmetric panel quantile approach suggests that EC has a significant effect on economic growth in both directions of shocks as well as for the considered sample. The results further support the findings in recent literature on renewable energy deployment, given the importance of renewable EC for economic growth with the increased levels of renewable EC, although the initial investments may have a negative effect on economic growth for some countries.

This study contributes to the literature in twofold. Firstly, it aims to contribute to the ongoing debate in literature by incorporating both renewable and non-renewable energy resources in the production function with labour and capital to test their asymmetric impact on economic growth. Secondly, this paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables. Another point that should be emphasised in this study is the need for studies analysing economic growth and EC for a sample of G20 countries based on a comparative view for the renewable and non-renewable EC in literature.

This study aims to explore the diverse sources of electricity generation (coal, natural gas, oil and hydroelectricity) and their respective associations with economic growth and environmental quality.

This study uses static panel data analysis with a random effects model for six selected ASEAN countries (Indonesia, Malaysia, Filipina, Thailand, Vietnam and Myanmar) from 1994 to 2014.

This study reveals that economic growth in six selected ASEAN countries is enhanced by electricity generation from all sources, while the contribution of electricity production from hydroelectricity remains the largest and strongest. There is no environmental impact of electricity production from hydroelectric, whereas fossil fuel-based electricity production emits carbon dioxide, with coal sources being the largest contributor, followed by natural gas and oil.

Based on the results, these six ASEAN countries should invest more in hydropower projects, reduce the coal mix in power generation and promote clean coal technology to improve economic efficiency and environmental sustainability.

To the best of the authors’ knowledge, no research has examined the relationship between electricity production, environmental quality and economic growth in Southeast Asian nations. Therefore, the outcome of this study is expected to provide insightful results to supplement the framing and implementation of national and collective regional strategies for sustainable electricity generation in ASEAN countries.

The purpose of this study is to investigate the relationship between natural gas consumption and economic growth of France.

To analyze the relationship, an extended Cobb–Douglas production function is used. The auto-regressive distributive lag bounds testing approach is applied to test the existence of the long-run relationship between the series. The vector error correction model Granger causality approach is implemented to detect the direction of causal relation between the variables.

The results show that variables are cointegrated for the long-run relationship. They also indicate that natural gas consumption, exports, capital and labor are the contributing factors to economic growth in France. The causality analysis indicates that feedback hypothesis is validated between gas consumption and economic growth. The bidirectional causality is also found between exports and economic growth, gas consumption and exports and capital and gas consumption.

The feedback hypothesis between gas consumption and economic growth implies that adoption of energy conservation policies should be discouraged; rather, gas consumption and economic growth policies should be jointly implemented.

This study is an original work for France and shows the results of the relationship between natural gas consumption and economic growth. In line with the results of this study, new direction for policy makers is opened up to formulate a comprehensive energy policy to sustain long-term economic growth in France.

This paper aims to investigate the dynamic relationship between renewable energy and economic growth in African OPEC member countries (Angola, Algeria and Nigeria).

The fully modified ordinary least squares technique for heterogeneous cointegrated panels (Pedroni, 2000) is used to estimate the parameters of the model.

The study revealed four main findings. First, there is a bidirectional causality between renewable energy and economic growth in the long and the short run. Second, a bidirectional causality exists between non-renewable energy and economic growth in the short and long run. Third, a bidirectional causality exists between CO₂ emissions and economic growth. Fourth, a unidirectional causality was also found between CO₂ emissions and non-renewable energy consumption with the direction of causality stemming from the consumption of non-renewable energy to CO₂ emissions.

Because renewable consumption enhances growth, OPEC-member Africa countries should encourage investment in modern renewable sources that has high conversion efficiency such as solar, wind and hydro to strengthen their response to mitigating the impacts of climate change.

This study applies multiple methods to analyze the relationship between renewable energy and economic growth in African OPEC countries.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

This paper aims to investigate the relationship between gross domestic product (GDP) by sector and energy consumption by type in 16 emerging countries.

The panel model was utilized taking the period 1980-2010.

The results revealed that GDP by sector and energy consumption by type are cointegrated. Moreover, the Granger causality concluded a bi-directional causal relationship between oil, natural gas and renewable energy consumption and the value of the manufacturing, industrial and services sector. Furthermore, a bi-directional causal relationship was also found between coal consumption and the value of the services sector. Furthermore, a one-way causal relationship was found from oil consumption to the value of the agriculture sector, the value of the agriculture sector to coal consumption, and coal consumption to the value of the manufacturing and the industrial sectors.

This study recommended that these countries should increase their renewable energy consumption to achieve their GDP growth.

This study is different from the previous studies, as it disaggregated the GDP into four sectors, namely, agriculture, manufacturing, industrial and the services sector. In addition, this study will disaggregate energy consumption into oil consumption, gas consumption, coal consumption and electricity consumption.

The purpose of this study was to investigate the relationship between gross domestic product (GDP) growth and renewable and non-renewable energy consumption in 82 developing countries categorized by region.

To achieve the goal of this study, the panel model was used taking the period 1990-2009.

The Kao co-integration test results showed that both renewable and non-renewable energy consumption had a long-running relationship with all the economic sectors in all regions. Moreover, the FMOLS revealed that the renewable and non-renewable energy consumption had a long-run positive relationship with the economic sectors. However, the results also revealed that non-renewable energy consumption has a more significant effect on the economic sectors than the renewable energy consumption. In addition, the Granger causality showed the same results, that the causal relationship between the economic sectors and non-renewable energy consumption is more significant than the causal relationship between the economic sectors and renewable energy.

The reason behind these results is that these regions still depend on fossil fuels to promote their economic growth. Fossil fuels basically contribute more than 80 per cent of their total energy consumption. Thus, the study recommends the developing countries to increase their investment on renewable energy projects to increase the share of the renewable energy of total energy consumption.

This study is considered different from all the previous studies because it will investigate the disaggregate relationship between GDP and energy consumption (renewable and non-renewable) in East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, South Asia and the Sub-Saharan African developing countries.

In all existing theoretical papers on causality it is assumed that the lag length is known a priori. However, in applied research the lag length has to be selected before testing for causality. The purpose of this paper is to suggest that in investigating the effectiveness of various Granger causality testing methodologies, including those using bootstrapping, the lag length choice should be endogenized, by which we mean the data‐driven preselection of lag length should be taken into account.

The size and power of a bootstrap test with endogenized lag‐length choice are investigated by simulation methods. A statistical software component is produced to implement the test, which is available online.

The simulation results show that this test performs well. An application of the test provides empirical support for the hypothesis that the UAE financial market is integrated with the US market.

The empirical results based on this test are expected to be more precise.

This paper considers a bootstrap test for causality with endogenous lag order. This test has superior properties compared to existing causality tests in terms of size, with similar if not better power and it is robust to ARCH effects that usually characterize financial data. Practitioners interested in causal inference based on time series data might find the test valuable.