Investigating the energy efficiency determinants in EU countries by using multi-criteria decision analysis and the Tobit regression model

ABSTRACT

This study investigates the effects of several contextual variables, including renewable energy intensity, capital stock per labor, natural resource rent, the share of imported energy in total energy consumption, the ratio of carbon emissions to GDP, population, and energy production on energy efficiency in EU countries. While Tobit regression is used to examine the effects of contextual variables on energy efficiency, Data Envelopment Analysis (DEA), Slack-Based Data Envelopment Analysis (SBM-DEA), and Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) are used to calculate energy efficiency values of countries. Four different Tobit regression models are estimated as a function of the censored value for the energy efficiency series. The results show that renewable energy intensity, the ratio of carbon emissions to GDP, and population size have negative effects on energy efficiency. In contrast, regardless of the efficiency level, the share of imported energy in total energy consumption, total energy production, capital stock per labor, and technological progress have positive effects on energy efficiency.

KEYWORDS:

• SBM-DEA
• TOPSIS
• energy efficiency
• Tobit panel regression
• energy in EU

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ Matrices are indicated in this paper by bold capital letters.

² Here the weighting of the individual criteria is calculated as.${\tilde{w}}_j=\frac{{\sigma }_j}{{\sum }_{k=1}^m{\sigma }_k}$

³ Renewable energy consumption (2023) and total energy consumption are from the Energy Information Administration (EIA 2022); capital stock and labor force are from Penn World Table 10 (Groningen Growth and Development Centre 2021); total natural resource rents, gross domestic production (GDP), CO2 emissions, total population, and share of imported energy in total energy consumption are from the World Bank (2022) Development Indicators Database.