Abstract
Using a stochastic frontier analysis log-linear function and comparable data for 26 economies over the 2008–2020 period, the relationship between selected socioeconomic indicators of energy poverty and the eco-efficiency measures for a sample of European countries, is examined. Concerning selected energy poverty determinants, the main empirical findings derived from the estimations of a time-varying fixed-effects model, a true random-effects model and an inefficiency effects model under truncated-normal, point to a significant interaction between those same socioeconomic determinants and relevant measures of eco-efficiency. Thus, we can consider the results of the estimated regression frontiers of inefficiency effects model (truncated-normal), that in the period of the first Kyoto commitment (2008–2012), Sweden, Hungary, France, Latvia and Lithuania stand out in the TOP5 in terms of technical eco-efficiency, while in the second Kyoto period 2013–2018 in this TOP5, we have the same economies occupying the same position in the ranking, except the position of Lithuania that no longer belongs, being substituted in its position by Slovenia. While additional research would help disentangle this relationship, important socioeconomic and environmental policy implications can be drawn from our findings.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Baloch, Z. A., Tan, Q., Iqbal, N., Mohsin, M., Abbas, Q., Iqbal, W., & Chaudhry, I. (2020). Trilemma assessment of energy intensity, efficiency, and environmental index: evidence from BRICS countries. Environmental Science and Pollution Research, 27, 34337–34347. https://doi.org/10.1007/s11356-020-09578-3
Battese, G. E., Coelli, T. J., & T. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3(1), 153–169. https://doi.org/10.1007/BF00158774
Bellotti, F., Daidone, S., Ilardi, G., & Atella, V. (2013). Stochastic frontier analysis using Stata. The Stata Journal, 13(4), 719–758. https://journals.sagepub.com/doi/pdf/10.1177/1536867X1301300404
Betto, F., Garengo, P., & Lorenzoni, A. (2020). A new measure of Italian hidden energy poverty. Energy Policy, 138, 111237. https://doi.org/10.1016/j.enpol.2019.111237
Bouzarovski, S., & Thomson, H. (2020). Towards an inclusive energy transition in the European Union: confronting energy poverty amidst a global crisis. Publications Office of the European Union, Energy Poverty Observatory. https://doi.org/doi.org/10.2833/103649
Brodny, J., & Tutak, M. (2020). Analyzing Similarities between the European Union Countries in Terms of the Structure and Volume of Energy Production from Renewable Energy Sources. Energies, 13(4), 1–10. https://ideas.repec.org/a/gam/jeners/v13y2020i4p913-d321967.html
Camarero, M., Castillo-Giménez, J., Picazo-Tadeo, A. J., & Tamarit, C. (2014). Is eco-efficiency in greenhouse gas emissions converging among European Union countries? Empirical Economics, 47, 143–168. https://doi.org/10.1007/s00181-013-0734-1
Cornwell, C., Schmidt, P., & Sickles, R. (1990). Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46(1), 185–200. https://doi.org/10.1016/0304-4076(90)90054-W
Day, R., Walker, G., & Simcock, N. (2016). Conceptualising energy use and energy poverty using a capabilities framework. Energy Policy, 93, 255–264. https://doi.org/10.1016/j.enpol.2016.03.019
Ehsanullah, S., Tran, Q. H., Sadiq, M., et al. (2021). How energy insecurity leads to energy poverty? Do environmental consideration and climate change concerns matters. Environmental Science and Pollution Research, 28, 55041–55052. https://doi.org/10.1007/s11356-021-14415-2
European Commission (2019). EU guidance document on a strategic framework for further supporting the deployment of EU-level green and blue Infrastructure SWD, 193 Final, 2019. European Commission: Brussels, Belgium.
Fuente-Mella, H., Vallina-Hernandez, A., & Fuentes-Solís, R. (2020). Stochastic analysis of the economic growth of OECD countries. Economic Research-Ekonomska Istraživanja, 33(1), 2189–2202. https://doi.org/10.1080/1331677X.2019.1685397
Galvin, R. (2020). Energy poverty research: A perspective from the poverty side. In R. Galvin (Ed.), Inequality and Energy (pp. 221–248. ISBN 9780128176740). Academic Press. https://doi.org/10.1016/B978-0-12-817674-0.00010-2
Gómez-Calvet, R., Conesa, D., Gómez-Calvet, A. R., & Tortosa-Ausina, E. (2016). On the dynamics of eco-efficiency performance in the European Union. Computers & Operations Research, 66, 336–350. https://doi.org/10.1016/j.cor.2015.07.018
González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47(July 2015), 377–385. https://doi.org/10.1016/j.rser.2015.03.013
Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126(2), 269–303. https://doi.org/10.1016/j.jeconom.2004.05.003
Halkos, G. E., & Gkampoura, E.-C. (2021). Evaluating the effect of economic crisis on energy poverty in Europe. Renewable and Sustainable Energy Reviews, 144, 110981. https://doi.org/10.1016/j.rser.2021.110981
Horta, A., Gouveia, J. P., Schmidt, L., Sousa, J. C., Palma, P., & Simões, S. (2019). Energy poverty in Portugal: Combining vulnerability mapping with household interviews. Energy and Buildings, 203, 109423. https://doi.org/10.1016/j.enbuild.2019.109423
Khan, M. K., Teng, J. Z., Khan, M. I., & Khan, M. O. (2019). Impact of globalization, economic factors and energy consumption on CO2 emissions in Pakistan. Science of the Total Environment, 688, 424–436. https://doi.org/10.1016/j.scitotenv.2019.06.065
Kumbhakar, S. C. (1990). Production frontiers, panel data, and time-varying technical inefficiency. Journal of Econometrics, 46(1), 201–211. https://doi.org/10.1016/0304-4076(90)90055-X
Kuosmanen, T., & Kortelainen, M. (2005). Measuring Eco-efficiency of Production with Data Envelopment Analysis. Journal of Industrial Ecology, 9(4), 59–72. https://doi.org/10.1162/108819805775247846
Kounetas, K. (2015). Heterogeneous technologies, strategic groups and environmental efficiency technology gaps for European countries. Energy Policy, 83, 277–287. https://doi.org/10.1016/j.enpol.2015.01.036
Mashhoodi, B., Stead, D., & Van Timmeren, A. (2019). Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension. Annals of GIS, 25(1), 19–31.
Medved, D., & Kavcic, S. (2012). An empirical study of efficiency in Croatia and Slovenia insurance markets. Economic Research-Ekonomska Istrazivanja, 25(1), 87–98. https://doi.org/10.1080/1331677X.2012.11517496
Middlemiss, L. (2020). Energy poverty: Understanding and addressing systemic inequalities. In R. Galvin (Ed.), Inequality and Energy: How Extremes of Wealth and Poverty in High Income Countries Affect CO2 Emissions and Access to Energy (pp. 99–114). Academic Press. ISBN 978-0-12-817674-0.
Moutinho, V., & Madaleno, M. (2021). Assessing eco-efficiency in Asian and African countries using stochastic frontier analysis. Energies, 14, 1168. https://doi.org/10.3390/en14041168
Nawaz, S. (2021). Energy poverty, climate shocks, and health deprivations. Energy Economics, 100, 105338. https://doi.org/10.1016/j.eneco.2021.105338
Nguyen, H. T. (2020). A closer look at stochastic frontier analysis in economics. Asian Journal of Economics and Banking, 4(3), 3–28. https://doi.org/10.1108/AJEB-07-2020-0032
Ntaintasis, E., Mirasgedis, S., & Tourkolias, C. (2019). Comparing different methodological approaches for measuring energy poverty: Evidence from a survey in the region of Attika, Greece. Energy Policy, 125, 160–169. https://doi.org/10.1016/j.enpol.2018.10.048
Papadopoulou, S.-D., Kalaitzoglou, N., Psarra, M., Lefkeli, S., Karasmanaki, E., & Tsantopoulos, G. (2019). Addressing energy poverty through transitioning to a carbon-free environment. Sustainability, 11(9), 2634. https://doi.org/10.3390/su11092634
Qurat-ul-Ann, A. R., & Mirza, F. M. (2021). Multidimensional energy poverty in Pakistan: Empirical evidence from household level micro data. Social Indicators Research, 155, 211–258. https://doi.org/10.1007/s11205-020-02601-7
Recalde, M., Peralta, A., Oliveras, L., Tirado-Herrero, S., Borrell, C., Palència, L., Gotsens, M., Artazcoz, L., & Marí-Dell’Olmo, M. (2019). Structural energy poverty vulnerability and excess winter mortality in the European Union: Exploring the association between structural determinants and health. Energy Policy, 133, a110869. https://doi.org/10.1016/j.enpol.2019.07.005
Santillán, O. S., Cedano, K. G., & Martínez, M. (2020). Analysis of energy poverty in 7 Latin American countries using multidimensional energy poverty index. Energies, 13(7), 1608. https://doi.org/10.3390/en13071608
Streimikiene, D., Kyriakopoulos, G., Lekavicius, V., et al. (2021). Energy poverty and low carbon just energy transition: comparative study in Lithuania and Greece. Social Indicators Research, 158, 319–371. https://doi.org/10.1007/s11205-021-02685-9
Thema, J., & Vondung, F. (2021). Expenditure-based indicators of energy poverty—an analysis of income and expenditure elasticities. Energies, 14(1), 8. https://doi.org/10.3390/en14010008
Tundys, B., Bretyn, A., & Urbaniak, M. (2021). Energy Poverty and sustainable economic development: an exploration of correlations and interdependencies in European Countries. Energies, 14, 7640. https://doi.org/10.3390/en14227640
United Nations Environmental Programme. (2019). Emissions Gap Report (2019). Executive summary. United Nations Environmental Programme.
Ürge-Vorsatz, D., & Herrero, S. T. (2012). Building synergies between climate change mitigation and energy poverty alleviation. Energy Policy, 49. https://doi.org/10.1016/j.enpol.2011.11.093
Walker, G., Simcock, N., & Day, R. (2016). Necessary energy uses and a minimum standard of living in the United Kingdom: Energy justice or escalating expectations? Energy Research & Social Science, 18, 129–138. https://doi.org/10.1016/j.erss.2016.02.007
Yu, Z., Abdul, S., Khan, R., Ponce, P., Lopes, A. B., & Jabbour, C. J. C. (2022). Factors affecting carbon emissions in emerging economies in the context of a green recovery: Implications for sustainable development goals. Technological Forecasting and Social Change, 176, 121417. https://doi.org/10.1016/j.techfore.2021.121417
Zhao, J., Jiang, Q., Dong, X., & Dong, K. (2021). Assessing energy poverty and its efect on CO2 emissions: The case of China. Energy Economics, 97, 105191. https://doi.org/10.1016/j.eneco.2021.10519
Acknowledgements
The authors wish to thank NECE- Research Center in Business Sciences and CEOS - Centre for Social and Organizational Studies.
Funding This research was supported in the scope of Project PRIMA 2020, 3599-PPCDT, Environment and Global Change: Improving MEDiterranean irrigation system and water supply for smallholder farmers by providing efficient, low-cost and nature-based technologies and practices. PRIMA/0008/2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Moutinho, V., Leitão, J., Silva, P.M., Serrasqueiro, J. (2023). Examining the Relationship Between Eco-efficiency and Energy Poverty: A Stochastic Frontier Models Approach. In: Devezas, T.C., Leitão, J.C.C., Yegorov, Y., Chistilin, D. (eds) Global Challenges of Climate Change, Vol.2. World-Systems Evolution and Global Futures. Springer, Cham. https://doi.org/10.1007/978-3-031-16477-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-16477-4_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-16476-7
Online ISBN: 978-3-031-16477-4
eBook Packages: Economics and FinanceEconomics and Finance (R0)