IDEAS home Printed from https://ideas.repec.org/p/zbw/vfsc15/112975.html
   My bibliography  Save this paper

Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector

Author

Listed:
  • Seifert, Stefan

Abstract

Energy supply in Germany has undergone considerable changes during the last decade, of which especially the nuclear phase-out and enormous installations of renewable energy sources pose new challenges for conventional combustion technologies. To analyze potential adaption processes due to this changing market conditions, this paper analyzes productivity change and its components in the German electricity and heat generation sector. A unique panel data set of 1555 power plants in Germany between 2003 and 2010 allows to estimate production frontiers for coal, lignite, gas and biomass fired power plants. Production functions are estimated using stochastic non-smooth envelopment of data (StoNED) in a meta-frontier framework. Productivity developments and its components are assessed at quantiles of the input value distributions of the different technologies using a metafrontier Malmquist decomposition. Results indicate (1) a dominant position of gas-fired plants in the metafrontier, (2) productivity changes for all technologies and reductions in production potentials (3) a catch-up for biomass plants to the other technologies.

Suggested Citation

  • Seifert, Stefan, 2015. "Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112975, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc15:112975
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/112975/1/VfS_2015_pid_617.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Du, Limin & Mao, Jie & Shi, Jinchuan, 2009. "Assessing the impact of regulatory reforms on China's electricity generation industry," Energy Policy, Elsevier, vol. 37(2), pages 712-720, February.
    2. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    3. Supawat Rungsuriyawiboon & Spiro Stefanou, 2008. "The dynamics of efficiency and productivity growth in U.S. electric utilities," Journal of Productivity Analysis, Springer, vol. 30(3), pages 177-190, December.
    4. Zhao, Xiaoli & Ma, Chunbo, 2013. "Deregulation, vertical unbundling and the performance of China's large coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 474-483.
    5. 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.
    6. Stefan Seifert & Astrid Cullmann & Christian von Hirschhausen, 2014. "Technical Efficiency and CO2 Reduction Potentials: An Analysis of the German Electricity Generating Sector," Discussion Papers of DIW Berlin 1426, DIW Berlin, German Institute for Economic Research.
    7. Genius, Margarita & Stefanou, Spiro E. & Tzouvelekas, Vangelis, 2012. "Measuring productivity growth under factor non-substitution: An application to US steam-electric power generation utilities," European Journal of Operational Research, Elsevier, vol. 220(3), pages 844-852.
    8. Heshmati, Almas & Kumbhakar, Subal C. & Sun, Kai, 2014. "Estimation of productivity in Korean electric power plants: A semiparametric smooth coefficient model," Energy Economics, Elsevier, vol. 45(C), pages 491-500.
    9. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    10. Wang, Yi-Shu & Xie, Bai-Chen & Shang, Li-Feng & Li, Wen-Hua, 2013. "Measures to improve the performance of China’s thermal power industry in view of cost efficiency," Applied Energy, Elsevier, vol. 112(C), pages 1078-1086.
    11. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
    12. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    13. Lam, Pun-Lee & Shiu, Alice, 2001. "A data envelopment analysis of the efficiency of China's thermal power generation," Utilities Policy, Elsevier, vol. 10(2), pages 75-83, June.
    14. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    15. Fallahi, Alireza & Ebrahimi, Reza & Ghaderi, S.F., 2011. "Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study," Energy, Elsevier, vol. 36(11), pages 6398-6405.
    16. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    17. Scott Atkinson & Claudia Halabí, 2005. "Economic Efficiency and Productivity Growth in the Post-Privatization Chilean Hydroelectric Industry," Journal of Productivity Analysis, Springer, vol. 23(2), pages 245-273, May.
    18. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    19. J. Dean Craig and Scott J. Savage, 2013. "Market Restructuring, Competition and the Efficiency of Electricity Generation: Plant-level Evidence from the United States 1996 to 2006," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    20. Zhang, Ning & Choi, Yongrok, 2013. "A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea," Energy Policy, Elsevier, vol. 62(C), pages 324-332.
    21. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations," Energy Economics, Elsevier, vol. 40(C), pages 370-382.
    22. Ku-Hsieh Chen & Hao-Yen Yang, 2011. "A cross-country comparison of productivity growth using the generalised metafrontier Malmquist productivity index: with application to banking industries in Taiwan and China," Journal of Productivity Analysis, Springer, vol. 35(3), pages 197-212, June.
    23. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    24. Timo Kuosmanen, 2008. "Representation theorem for convex nonparametric least squares," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 308-325, July.
    25. Du, Limin & He, Yanan & Yan, Jianye, 2013. "The effects of electricity reforms on productivity and efficiency of China's fossil-fired power plants: An empirical analysis," Energy Economics, Elsevier, vol. 40(C), pages 804-812.
    26. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    27. Fleishman, Rachel & Alexander, Rob & Bretschneider, Stuart & Popp, David, 2009. "Does regulation stimulate productivity? The effect of air quality policies on the efficiency of US power plants," Energy Policy, Elsevier, vol. 37(11), pages 4574-4582, November.
    28. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    29. See, Kok Fong & Coelli, Tim, 2013. "Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis," Energy Policy, Elsevier, vol. 62(C), pages 207-214.
    30. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    31. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, December.
    32. Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simona Bigerna & Maria Chiara D’Errico & Paolo Polinori, 2022. "Sustainable Power Generation in Europe: A Panel Data Analysis of the Effects of Market and Environmental Regulations," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 445-479, October.

    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. Stefan Seifert, 2015. "Measuring Productivity When Technologies Are Heterogeneous: A Semi-Parametric Approach for Electricity Generation," Discussion Papers of DIW Berlin 1526, DIW Berlin, German Institute for Economic Research.
    2. Seifert, Stefan & Cullmann, Astrid & von Hirschhausen, Christian, 2016. "Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector," Energy Economics, Elsevier, vol. 56(C), pages 9-19.
    3. Stefan Seifert & Astrid Cullmann & Christian von Hirschhausen, 2014. "Technical Efficiency and CO2 Reduction Potentials: An Analysis of the German Electricity Generating Sector," Discussion Papers of DIW Berlin 1426, DIW Berlin, German Institute for Economic Research.
    4. 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.
    5. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    6. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    7. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Technology heterogeneity in European industries' energy efficiency performance. The role of climate, greenhouse gases, path dependence and energy mix," MPRA Paper 92314, University Library of Munich, Germany.
    8. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    9. Bai-Chen Xie & Jie Gao & Shuang Zhang & ZhongXiang Zhang, 2017. "What Factors Affect the Competiveness of Power Generation Sector in China? An Analysis Based on Game Cross-efficiency," Working Papers 2017.12, Fondazione Eni Enrico Mattei.
    10. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    11. Lin, Boqiang & Sai, Rockson, 2021. "A multi factor Malmquist CO2emission performance indices: Evidence from Sub Saharan African public thermal power plants," Energy, Elsevier, vol. 223(C).
    12. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    13. Sun, Chuanwang & Liu, Xiaohong & Li, Aijun, 2018. "Measuring unified efficiency of Chinese fossil fuel power plants: Intermediate approach combined with group heterogeneity and window analysis," Energy Policy, Elsevier, vol. 123(C), pages 8-18.
    14. Yung-Hsiang Lu & Ku-Hsieh Chen & Jen-Chi Cheng & Chih-Chun Chen & Sian-Yuan Li, 2019. "Analysis of Environmental Productivity on Fossil Fuel Power Plants in the U.S," Sustainability, MDPI, vol. 11(24), pages 1-27, December.
    15. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    16. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
    17. Jin, Qianying & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2020. "Metafrontier productivity indices: Questioning the common convexification strategy," European Journal of Operational Research, Elsevier, vol. 283(2), pages 737-747.
    18. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
    19. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
    20. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.

    More about this item

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:zbw:vfsc15:112975. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vfsocea.html .

    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.