Examining the Industrial Energy Consumption Determinants: A Panel Bayesian Model Averaging Approach

Borozan, Djula; Borozan, Luka

doi:10.3390/en13010070

Cited by 4 publications

(5 citation statements)

References 34 publications

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“…The CSEs (independent variables) were collected by the National Expert Survey of the Global Entrepreneurship Monitor (GEM 2021b). We used the 12 indicators provided (Table 2) as used by the authors (Lopes et al 2018a(Lopes et al , 2021aBorozan and Borozan 2020;Sa and Pinho 2019).…”

Section: Measurementmentioning

confidence: 99%

The Impacts of the Entrepreneurial Conditions on Economic Growth: Evidence from OECD Countries

et al. 2022

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This study aims to assess the impacts of entrepreneurial framework conditions on economic growth based on the level of economic development in transition-driven economies and innovation-driven economies. The data were organised into a panel (2000–2019) and obtained from the National Expert Survey (NES), the Global Monitor Entrepreneurship (GEM), and the World Bank. By applying the generalised method of moments (GMM) estimation, we found that R&D transfer has a negative impact on economic growth that is innovation-driven, but positively impacts transition-driven economies. The results further highlighted that regardless of the level of development of the country, business and professional infrastructure do not positively impact economic growth. However, taxes and bureaucracy and physical and service infrastructure were shown to positively impact only innovation-driven economies, as in transition-driven economies, they were shown to have negative impacts on economic growth. The present study contributes to a better understanding of the link between economic growth and the conditions for entrepreneurship in economies with different degrees of economic growth. This study can serve as a basis for policy makers to adjust or develop new policies to accelerate economic growth.

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Section: Measurementmentioning

confidence: 99%

The Impacts of the Entrepreneurial Conditions on Economic Growth: Evidence from OECD Countries

et al. 2022

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“…Before the energy efficiency evaluation, it is necessary to carry out data preprocessing to unify data types and conduct dimensionless processing. Original index data is collected to construct an evaluation matrix Z (1) :…”

Section: B Construct a Standardized Evaluation Matrixmentioning

confidence: 99%

“…where (1) ij z represents the original index value; * ij z represents the value after positive management.…”

Section: B Construct a Standardized Evaluation Matrixmentioning

confidence: 99%

“…Energy is vital to the existence and development of modern society. In the last few decades, energy and environmental issues have become increasingly prominent in global economic growth [1]. The improvement of energy utilization efficiency is an important way to reduce energy consumption intensity and to release the contradiction of energy supplydemand structure [2], [3].…”

Section: Introductionmentioning

confidence: 99%

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Energy Efficiency Evaluation and Optimization of Industrial Park Customers Based on PSR Model and Improved Grey-TOPSIS Method

Zhao

2021

IEEE Access

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Energy efficiency evaluation of industrial park customers is carried out to help customers develop optimization strategies and improve the energy efficiency level. The evaluation indexes are proposed based on pressure-state-response (PSR) model and the redundant indexes are selected by combining principal component analysis (PCA) and correlation analysis. Thus the dynamic energy efficiency index system is constructed. The weight of indexes is calculated by the entropy weight method (EWM). An energy efficiency evaluation model based on improved Grey-technique for order preference by similarity to ideal solution (TOPSIS) is proposed, which replaces the Euclidean distance by weighted grey correlation degree and can accurately evaluate customers' energy efficiency level. An energy efficiency optimization model is proposed, which can maximize optimization benefits while improving energy efficiency. The validity of the evaluation and optimization models is verified by the case study of an industrial park.INDEX TERMS Energy efficiency evaluation, industrial park customers, pressure-state-response model, Grey-technique for order preference by similarity to ideal solution, energy efficiency optimization This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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“…Increased income allows countries to cover developing RE technologies while also supporting the costs of government policies promoting and regulating RE. Several studies have focused on the determinants of REC in the economic literature [8][9][10].…”

Section: Literature Reviewmentioning

confidence: 99%

Factors of Renewable Energy Consumption in the European Countries—The Bayesian Averaging Classical Estimates Approach

et al. 2021

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The paper aims to identify the most likely factors that determine the demand for energy consumption from renewable sources (renewable energy consumption—REC) in European countries. Although in Europe, a high environmental awareness is omnipresent, countries differ in scope and share of REC due to historical energetic policies and dependencies, investments into renewable and traditional energetic sectors, R&D development, structural changes required by energetic policy change, and many other factors. The study refers to a set of macroeconomic, institutional, and social factors affecting energetic renewable policy and REC in selected European countries in two points of time: i.e., before and after the Paris Agreement. The Bayesian Average Classical Estimates (BACE) is applied to indicate the most likely factors affecting REC in 2015 and 2018. The comparison of the results reveals that the Gross Domestic Product (GDP) level, nuclear and hydro energy consumption were the determinants significant in both analyzed years. Furthermore, it became clear that in 2015, the REC depended strongly on the energy consumption structure, while in 2018, the foreign direct investment and trade openness played their role in increasing renewable energy consumption. The direction of changes is gradual and positive. It complies with the Sustainable Development Goals (SDGs).

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Examining the Industrial Energy Consumption Determinants: A Panel Bayesian Model Averaging Approach

Cited by 4 publications

References 34 publications

The Impacts of the Entrepreneurial Conditions on Economic Growth: Evidence from OECD Countries

The Impacts of the Entrepreneurial Conditions on Economic Growth: Evidence from OECD Countries

Energy Efficiency Evaluation and Optimization of Industrial Park Customers Based on PSR Model and Improved Grey-TOPSIS Method

Factors of Renewable Energy Consumption in the European Countries—The Bayesian Averaging Classical Estimates Approach

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