IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i7p2611-d337027.html
   My bibliography  Save this article

Energy and Emission Efficiency of the Slovak Regions

Author

Listed:
  • Vladimír Baláž

    (Institute for Forecasting, Centre of Social and Psychological Sciences, Slovak Academy of Sciences, 813 64 Bratislava, Slovakia)

  • Eduard Nežinský

    (Institute for Forecasting, Centre of Social and Psychological Sciences, Slovak Academy of Sciences, 813 64 Bratislava, Slovakia
    Department of Economic Policy, University of Economics in Bratislava, Bratislava 85106, Slovakia)

  • Tomáš Jeck

    (Institute of Economic Research, Slovak Academy of Sciences, 811 05 Bratislava, Slovakia)

  • Richard Filčák

    (Institute for Forecasting, Centre of Social and Psychological Sciences, Slovak Academy of Sciences, 813 64 Bratislava, Slovakia)

Abstract

This paper examines changing regional patterns of energy and emission efficiency in the Slovak regions in the period of 2008–18. Firstly; we review literature on key approaches to evaluating energy and emission efficiency; followed by discussing the pros and cons of specific methods. A slacks-based model of data envelopment analysis is applied in order to investigate changing patterns of energy and emission efficiency in 79 Slovak regions (LAU 1). Thereafter; changes in energy and emission efficiency are associated with policy interventions supported by the European Structural and Cohesion Funds (ESCF) in the period of 2011–15. The evaluation found no support for the hypothesis with regard to the positive impact of the ESCF on the increase in energy and emission efficiency. Combined support from three ESCF policy measures (€606.44m) was substantial; but accounted for a mere 6.3% of the total firm expenditure on product and process innovations in the period of 2007–15 (€9,573m). Productivity-boosting technological innovations and structural changes in the Slovak economy (a shift towards industries with a lower consumption of energy but a higher production of gross value added GVA) were major drivers of trends in energy and emission efficiency. If an increase in energy (emission) efficiency; rather than energy savings (a decrease in pollution), is a major objective of sustainable development policies; then innovation-oriented policies and changes in the structure of economic activities should be preferred to schemes supporting simple energy-saving (emission-cutting) projects

Suggested Citation

  • Vladimír Baláž & Eduard Nežinský & Tomáš Jeck & Richard Filčák, 2020. "Energy and Emission Efficiency of the Slovak Regions," Sustainability, MDPI, vol. 12(7), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2611-:d:337027
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/7/2611/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/7/2611/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Honma, Satoshi & Hu, Jin-Li, 2009. "Total-factor energy productivity growth of regions in Japan," Energy Policy, Elsevier, vol. 37(10), pages 3941-3950, October.
    2. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    3. Daniela A. Miteva & Subhrendu K. Pattanayak & Paul J. Ferraro, 2012. "Evaluation of biodiversity policy instruments: what works and what doesn’t?," Oxford Review of Economic Policy, Oxford University Press, vol. 28(1), pages 69-92, Spring.
    4. Kenneth Gillingham & Amelia Keyes & Karen Palmer, 2018. "Advances in Evaluating Energy Efficiency Policies and Programs," Annual Review of Resource Economics, Annual Reviews, vol. 10(1), pages 511-532, October.
    5. Atalla, Tarek & Bean, Patrick, 2017. "Determinants of energy productivity in 39 countries: An empirical investigation," Energy Economics, Elsevier, vol. 62(C), pages 217-229.
    6. Haifeng Huang & Tao Wang, 2017. "The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    7. Wan, Jun & Baylis, Kathy & Mulder, Peter, 2015. "Trade-facilitated technology spillovers in energy productivity convergence processes across EU countries," Energy Economics, Elsevier, vol. 48(C), pages 253-264.
    8. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    9. Meredith Fowlie & Michael Greenstone & Catherine Wolfram, 2018. "Do Energy Efficiency Investments Deliver? Evidence from the Weatherization Assistance Program," The Quarterly Journal of Economics, Oxford University Press, vol. 133(3), pages 1597-1644.
    10. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    11. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    12. Zuoren Sun & Chao An & Huachen Sun, 2018. "Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-28, July.
    13. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    14. Bertug Ozarisoy & Hasim Altan, 2017. "Adoption of Energy Design Strategies for Retrofitting Mass Housing Estates in Northern Cyprus," Sustainability, MDPI, vol. 9(8), pages 1-23, August.
    15. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach," Energy, Elsevier, vol. 36(5), pages 2765-2772.
    16. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    17. Lucas W. Davis & Alan Fuchs & Paul Gertler, 2014. "Cash for Coolers: Evaluating a Large-Scale Appliance Replacement Program in Mexico," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 207-238, November.
    18. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    19. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    20. Wang, Chunhua, 2011. "Sources of energy productivity growth and its distribution dynamics in China," Resource and Energy Economics, Elsevier, vol. 33(1), pages 279-292, January.
    21. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    22. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    23. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Shuangjie Li & Li Li & Liming Wang, 2020. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry," Energies, MDPI, vol. 14(1), pages 1-17, December.
    3. Tao, Xueping & Wang, Ping & Zhu, Bangzhu, 2016. "Provincial green economic efficiency of China: A non-separable input–output SBM approach," Applied Energy, Elsevier, vol. 171(C), pages 58-66.
    4. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    5. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    6. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.
    7. Haider, Salman & Danish, Mohd Shadab & Sharma, Ruchi, 2019. "Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis," Energy Economics, Elsevier, vol. 81(C), pages 454-464.
    8. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    9. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    10. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    11. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    12. Shuangjie Li & Hongyu Diao & Liming Wang & Chunqi Li, 2021. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    13. Ze Tian & Fang-Rong Ren & Qin-Wen Xiao & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Cross-Regional Comparative Study on Carbon Emission Efficiency of China’s Yangtze River Economic Belt Based on the Meta-Frontier," IJERPH, MDPI, vol. 16(4), pages 1-19, February.
    14. Haifeng Huang & Tao Wang, 2017. "The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    15. Li, Bo & Han, Yukai & Wang, Chensheng & Sun, Wei, 2022. "Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China," Energy Policy, Elsevier, vol. 167(C).
    16. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    17. Guo, Ran & Yuan, Yijun, 2020. "Different types of environmental regulations and heterogeneous influence on energy efficiency in the industrial sector: Evidence from Chinese provincial data," Energy Policy, Elsevier, vol. 145(C).
    18. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    19. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "The Impact of Economic Growth and Air Pollution on Public Health in 31 Chinese Cities," IJERPH, MDPI, vol. 16(3), pages 1-26, January.
    20. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2611-:d:337027. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.