Determinants of technical efficiency in the bioenergy industry in the EU28 region

Abstract

Most previous bioenergy industry research has concentrated on how to implement a certain level of yield. However, few articles have paid attention to rational resource allocation to increase efficiency. To enhance bioenergy production through proper use of available resources, this study identified the effects of internal (country-specific) and external (macroeconomic) determinants of technical efficiency level in the bioenergy industry for the EU28 region. The study was established based on a conceptual framework suggesting a correlation between input use and level of technical efficiency. A panel data analysis method was employed for the analysis and a panel regression analysis framework based on the Fixed Effect (FE) model and Random Effect (RE) model was used to examine the potential determinants of technical efficiency level in the bioenergy industry for the EU28 region for the period between 1990 and 2013. The results indicate that the technical efficiency level of the bioenergy industry in developing countries is higher than in developed countries. The empirical findings also suggest that technical efficiency has greater influence on pure technical efficiency levels. Capital input, labor input, gross domestic product, inflation and interest rate significantly affected the technical efficiency of the bioenergy industry in the developing and developed countries in the EU28 region during the period of this study. The findings clearly call for regulators and decision makers to review the technical efficiency level of the bioenergy industry within the EU28 region. This study also provides better information and guidance to the boards of the bioenergy industry, as they need to have a clear understanding of the influence technical efficiency has on bioenergy production performance. Moreover, the results of this study have implications for investors who focus mainly on profits from their investments.

Estimating the Economic Determinants of Technical Efficiency of Bioenergy in EU-28: An Application of Tobit Analysis

“…Model 1 shows the influence of specific-country determinants and environmental (external) economics determinants on the TE rate in the EU-28 zone starting from 1990 till 2013 see Table 1. Following previous study Anastasopoulos (2016) Tobit estimator is highly sufficient and aligned with findings of previous study Alsaleh et al (2017) regarding the positive correlation of lnCI and TE. Moreover, shows that lnLI impact positively and significantly on the dependent variable TE at the 1% statistical level.…”

“…In consistent with previous study Alsaleh et al (2017) (Berndes et al, 2009;Sufian and Habibullah, 2011;Meriküll et al, 2012). The EU-28 zone can react variously to the exact TE factors because of the various terms impact (Nielsen, 2011 sufficient to provide privilege, like raised bio-energy generation product, characteristics and more advantages from various sources of traditional energy aligned with an earlier paper (Scarlat et al, 2013).…”

“…Model 1 and Model 2 estimation results propose that a higher percentage of economic outgrowth and evolvement indexes leads to higher benefits, like increasing bio-energy outcomes, greater goodness products, larger privilege in the energy market, and high rate of job creating, in line with the former study (Chang et al, 2003). Corresponding with previous study, Model 1 and Model 2 shows that lnRIR negatively and significantly affect the TE at 1% statistical level (Alsaleh et al, 2017). lnRIR factor may have an insignificant influence like an amendment in the IR and significant effect such as enhancing the capital that affects bio-energy sector efficiency.…”

“…Accordingly, in Model 1 we have created interaction dummy variable to shows the impact of labour input in developing and developed countries on the TE level. Matching with prior study, Model 1 and Model 2 indicates to that ln GDP influence positively and significantly the TE at the 1% statistical level (Alsaleh et al, 2017). Model 1 and Model 2 shows that lnGDP has positively and significantly impacted the TE value in the bio-energy sector in the EU-28 zone; the great the economic outgrowth, the larger TE rate.…”

“…;Sufian and Habibullah (2013);Sufian and Kamarudin (2015) and;Alsaleh et al (2017);Coelli et al (1998) among others, the current study uses the TE results as the dependent variable and indicator for the bio-energy sector development in the EU-28 zone. In regards to the factors of TE which calculated by the DEA mathematical approach.…”