• Energy Research

The main aim of this article is to examine empirically the impact of urbanization on carbon dioxide emissions in Singapore from 1970 to 2015. The autoregressive distributed lags (ARDL) approach is applied within the analysis. The main finding reveals a negative and significant impact of urbanization on carbon emissions in Singapore, which means that urban development in Singapore is not a barrier to the improvement of environmental quality. Thus, urbanization enhances environmental quality by reducing carbon emissions in the sample country. The result also highlighted that economic growth has a positive and significant impact on carbon emissions, which suggests that economic growth reduces environmental quality through its direct effect of increasing carbon emissions in the country. Despite the high level of urbanization in Singapore, which shows that 100 % of the populace is living in the urban center, it does not lead to more environmental degradation. Hence, urbanization will not be considered an obstacle when initiating policies that will be used to reduce environmental degradation in the country. Policy makers should consider the country's level of economic growth instead of urbanization when formulating policies to reduce environmental degradation, due to its direct impact on increasing carbon dioxide emissions.

The purpose of this research is to examine the correlation between the bioenergy industry and economic outgrowth. This study investigates the growth hypothesis within the setting of conventional Cobb–Douglas production theory from 1990 to 2013 in the EU-28 region. The authors use unit root test approach, panel cointegration analysis, cointegration assessment methods, and heterogeneous panel causality estimation analysis. The study found that bio-energy sector factors (human capital, physical capital and consumption) have a positive and significant impact on economic growth. Also, that there is a long-term stable relation among the bioenergy consumption and economic outgrowth. Heterogeneous panel causality estimations outcomes are consistent with the growth hypothesis in developed countries, feedback hypothesis in European Union area, and neutrality hypothesis in underdeveloped countries. Reference to the panel data set, the three models’ results boost the hypothesis. Given the findings, the study derived that there is a significant influence from the bioenergy industry on economic growth in EU-28 region.

This paper investigates the relationship between financial development and bio-energy consumption in the European Union (EU28) countries for the period from 1990 to 2013 through the panel autoregressive distributed lag (ARDL) approach and causality analysis. The empirical results show that financial development shows a significant positive impact, at a 1% statistical level, on bio-energy consumption for the EU28 during the studied period. In developing countries, the financial market indicator affects bio-energy consumption outgrowth positively and significantly at a 1% statistical level. For developed countries, there is a positive influence of financial institutions and financial market indicators on bio-energy consumption growth at the 1% and 10% levels, respectively. The study concludes that there is a significant relationship between the consumption of bio-energy and financial development factors. The study provides recommendations that are useful when formulating policy related to energy consumption and the promotion of bio-energy consumption. Financial development and economic outgrowth show a significant influence on the outgrowth of bio-energy consumption at a 1% statistical level.

This paper estimates the impact of renewable energy on economic growth in West African countries using panel dynamic ordinary least squares (DOLS) by employing a sample of 15 West African countries covering the 1995-2014 period. The results indicated that renewable energy consumption slows down economic growth in these countries. This is attributed to the nature and source of renewable energy used in West Africa, which is majorly wood biomass. The wood biomasses used in West Africa are usually unclean and highly polluting when burnt. On the other hand, the use of clean energy sources like solar, wind and hydropower which does not have a side effect on human health and the environment is less in West Africa. As such, renewable energy use can slow down economic growth by lowering productivity when unclean and inefficient sources are used. The study recommends that (1) cleaner technologies should be employed to optimize the benefits of wood biomass as a renewable source of energy while minimizing its adverse effects; (2) the share of other renewable energy components such as solar, wind and geothermal should be increased in the renewable energy mix of the sub-region of West Africa and (3) greater commitment to achieving sustainable renewable energy by West African authorities is needed. Keywords: Renewable energy, West Africa, Economic growth, Panel DOLS

This study contributes to the existing literature by examining bioenergy consumption and related factors in continental European countries (ECC). This study extends the current research through its focus on the ECC, which mainly consists of nationwide studies. This study analyses the determinants of bioenergy consumption in the ECC from 2005-2013, estimates its economic variables and evaluates the influence of each variable on bioenergy consumption and related significance level. A generalised method of moments estimator (GMM) was designed for ECC. The estimated models show that bioenergy capital input (CI) positively impacts bioenergy consumption. The most influential factor on use was the price of bioenergy (PR) followed by investment (INV), then gross domestic product (GDP). These results should be considered and used as a tool to develop legislation and policies that could benefit the bioenergy sector in ECC. The evidence shows that CI, INV, and PR have been the primary keys in improving bioenergy consumption in recent years in ECC countries. Thus, they have advanced the efficiency of bioenergy consumption.

Abstract Applying the data envelopment approach, this paper computes efficiency change (EFFCH) in terms of its components: pure technical and scale efficiency changes. The least squares dummy variable corrected (LSDVC) method was employed to examine the determinants of efficiency change of bioenergy industry of the EU28 countries covering the period 1990–2013. Results show that the bioenergy industry recorded an average annual rate of progress in efficiency change of 3.8% during the period studied. Interestingly, the region recorded a technical progress with both pure technical efficiency change and scale efficiency change increasing over the study period, however, scale efficiency was the major contributor to efficiency with annual increase of 4.5%. We also found variations in regional performance with EU developing region experiencing a slightly higher increase in efficiency at 3.86% while this figure is at 3.76% for the EU developed countries. Empirical finding show that economic growth, gross fixed capital formation, inflation and size of biomass input affected EFFCH of bioenergy industry of the EU28 region significantly during the period studied. Policy implications of these results are that the bioenergy industry should relentlessly pursue technical progress and aim to improve both technical and scale efficiencies simultaneously through optimal allocation of resources.

This research paper evaluates the effect of income, energy consumption and population on deforestation for environmental degradation in Nigeria. To achieve this objective, a cointegration analysis was used to verify the long-run relationship among the variables, with a dataset spanning from 1981 to 2011. The estimates of income provide evidence of a negative and important relationship with deforestation in both long- and short-run periods. This suggests that higher income can reduce deforestation and improve environmental quality. Furthermore, the coefficient of the population consistently provides evidence of a positive and important relationship with deforestation in the long- and short-run periods. Therefore, the population has been identified as the major cause of deforestation and environmental degradation in the model. Conversely, the estimates of energy consumption in both periods did not provide any evidence of a statistical relationship with deforestation. Therefore, policies of enhancing growth and curtailing deforestation were suggested.

This paper examines the dynamic effect of the economic determinants on bilateral trade intensity of the European Union (EU) region’s bioenergy industry outputs. The authors adopt the panel co-integration model approach to estimate annual trade intensity data of the EU-28 countries’ bioenergy industry outputs from 1990 to 2013. This study investigated the long-term influence of the rate of real exchange, gross domestic product (GDP), and export price on the trade intensity of bioenergy industry applying fully modified oriented least square (FMOLS), dummy oriented least square (DOLS), and pooled mean group (PMG) models. In the current study, the findings boost the empirical validity of the panel co-integration model through FMOLS, indicating that depreciation has improved the trade intensity. This study has further investigated, through the causality test, a distinct set of countries. FMOLS estimation does find proof of the long run improvement of trade intensity. Thus, the result shows that the gross domestic product (GDP) and the real exchange rate have a positive and noteworthy influence on the EU-28 region trade intensity of the bioenergy industry. Moreover, the export price affects negatively and significantly the trade intensity of the bioenergy industry in the EU-28 countries.