IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/54304.html
   My bibliography  Save this paper

Panel Data Parametric Frontier Technique for Measuring Total-factor Energy Efficiency: Application to Japanese Regions

Author

Listed:
  • Honma, Satoshi
  • Hu, Jin-Li

Abstract

Using the stochastic frontier analysis (SFA) model, we estimate total-factor energy efficiency (TFEE) scores for 47 regions across Japan during 1996–2008. We extend the cross-sectional SFA model proposed by Zhou et al. (Applied Energy, 2012) to panel data models and add environmental variables. The results provide not only the TFEE scores, in which statistical noise is taken into account, but also the determinants of inefficiency. The three SFA TFEEs are compared with a TFEE derived from data envelopment analysis (DEA). The four TFEEs are highly correlated with one another. For the inefficiency estimates, the higher the manufacturing industry share and wholesale and retail trade share, the lower the TFEE score.

Suggested Citation

  • Honma, Satoshi & Hu, Jin-Li, 2014. "Panel Data Parametric Frontier Technique for Measuring Total-factor Energy Efficiency: Application to Japanese Regions," MPRA Paper 54304, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:54304
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/54304/1/MPRA_paper_54304.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Miketa, Asami & Mulder, Peter, 2005. "Energy productivity across developed and developing countries in 10 manufacturing sectors: Patterns of growth and convergence," Energy Economics, Elsevier, vol. 27(3), pages 429-453, May.
    2. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    3. Recalde, Marina & Ramos-Martin, Jesús, 2012. "Going beyond energy intensity to understand the energy metabolism of nations: The case of Argentina," Energy, Elsevier, vol. 37(1), pages 122-132.
    4. Le Pen, Yannick & Sévi, Benoît, 2010. "On the non-convergence of energy intensities: Evidence from a pair-wise econometric approach," Ecological Economics, Elsevier, vol. 69(3), pages 641-650, January.
    5. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    6. Mukherjee, Kankana, 2008. "Energy use efficiency in U.S. manufacturing: A nonparametric analysis," Energy Economics, Elsevier, vol. 30(1), pages 76-96, January.
    7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    8. Mukherjee, Kankana, 2008. "Energy use efficiency in the Indian manufacturing sector: An interstate analysis," Energy Policy, Elsevier, vol. 36(2), pages 662-672, February.
    9. Nilsson, Lars J., 1993. "Energy intensity trends in 31 industrial and developing countries 1950–1988," Energy, Elsevier, vol. 18(4), pages 309-322.
    10. Satoshi Honma & Jin-Li Hu, 2011. "Industry-level Total-factor Energy Efficiency in Developed Countries," Discussion Papers 51, Kyushu Sangyo University, Faculty of Economics.
    11. 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.
    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. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-1248, September.
    14. Sözen, Adnan & Alp, Ihsan, 2009. "Comparison of Turkey's performance of greenhouse gas emissions and local/regional pollutants with EU countries," Energy Policy, Elsevier, vol. 37(12), pages 5007-5018, December.
    15. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    16. MORIKAWA Masayuki, 2012. "The Effects of the Great East Japan Earthquake and Policy Priorities for Restoring Economic Growth: Evidence from a survey of Japanese firms (Japanese)," Policy Discussion Papers (Japanese) 12010, Research Institute of Economy, Trade and Industry (RIETI).
    17. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    18. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    19. Peter Schmidt, 2011. "One-step and two-step estimation in SFA models," Journal of Productivity Analysis, Springer, vol. 36(2), pages 201-203, October.
    20. 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.
    21. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    22. repec:dau:papers:123456789/6801 is not listed on IDEAS
    23. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    24. Arens, Marlene & Worrell, Ernst & Schleich, Joachim, 2012. "Energy intensity development of the German iron and steel industry between 1991 and 2007," Energy, Elsevier, vol. 45(1), pages 786-797.
    25. Goto, Mika & Otsuka, Akihiro & Sueyoshi, Toshiyuki, 2014. "DEA (Data Envelopment Analysis) assessment of operational and environmental efficiencies on Japanese regional industries," Energy, Elsevier, vol. 66(C), pages 535-549.
    26. Liddle, Brantley, 2010. "Revisiting world energy intensity convergence for regional differences," Applied Energy, Elsevier, vol. 87(10), pages 3218-3225, October.
    27. Honma, Satoshi & Hu, Jin-Li, 2008. "Total-factor energy efficiency of regions in Japan," Energy Policy, Elsevier, vol. 36(2), pages 821-833, February.
    28. Herrala, Risto & Goel, Rajeev K., 2012. "Global CO2 efficiency: Country-wise estimates using a stochastic cost frontier," Energy Policy, Elsevier, vol. 45(C), pages 762-770.
    29. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    30. O. Olesen & N. Petersen, 2009. "Target and technical efficiency in DEA: controlling for environmental characteristics," Journal of Productivity Analysis, Springer, vol. 32(1), pages 27-40, August.
    31. Menegaki, Angeliki N., 2013. "Accounting for unobserved management in renewable energy & growth," Energy, Elsevier, vol. 63(C), pages 345-355.
    32. 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.
    33. Fang, Chin-Yi & Hu, Jin-Li & Lou, Tze-Kai, 2013. "Environment-adjusted total-factor energy efficiency of Taiwan's service sectors," Energy Policy, Elsevier, vol. 63(C), pages 1160-1168.
    34. Vivoda, Vlado, 2012. "Japan’s energy security predicament post-Fukushima," Energy Policy, Elsevier, vol. 46(C), pages 135-143.
    35. Hu, Jin-Li & Kao, Chih-Hung, 2007. "Efficient energy-saving targets for APEC economies," Energy Policy, Elsevier, vol. 35(1), pages 373-382, January.
    36. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    37. Lozano, Sebastián & Gutiérrez, Ester, 2008. "Non-parametric frontier approach to modelling the relationships among population, GDP, energy consumption and CO2 emissions," Ecological Economics, Elsevier, vol. 66(4), pages 687-699, July.
    38. Iglesias, Guillermo & Castellanos, Pablo & Seijas, Amparo, 2010. "Measurement of productive efficiency with frontier methods: A case study for wind farms," Energy Economics, Elsevier, vol. 32(5), pages 1199-1208, September.
    39. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    2. 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.
    3. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    4. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    5. Satoshi Honma & Jin-Li Hu, 2011. "Industry-level Total-factor Energy Efficiency in Developed Countries," Discussion Papers 51, Kyushu Sangyo University, Faculty of Economics.
    6. Huaping Sun & Bless Kofi Edziah & Xiaoqian Song & Anthony Kwaku Kporsu & Farhad Taghizadeh-Hesary, 2020. "Estimating Persistent and Transient Energy Efficiency in Belt and Road Countries: A Stochastic Frontier Analysis," Energies, MDPI, vol. 13(15), pages 1-19, July.
    7. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    8. 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.
    9. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    10. 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.
    11. Satoshi Honma & Jin-Li Hu, 2018. "A meta-stochastic frontier analysis for energy efficiency of regions in Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-16, December.
    12. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    13. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    14. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    15. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    16. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    17. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    18. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    19. Georgia Makridou, Kostas Andriosopoulos, Michael Doumpos, and Constantin Zopounidis, 2015. "A Two-stage approach for energy efficiency analysis in European Union countries," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    20. Li, Nan & Jiang, Yuqing & Mu, Hailin & Yu, Zhixin, 2018. "Efficiency evaluation and improvement potential for the Chinese agricultural sector at the provincial level based on data envelopment analysis (DEA)," Energy, Elsevier, vol. 164(C), pages 1145-1160.

    More about this item

    Keywords

    Stochastic frontier analysis (SFA); Data envelopment analysis (DEA); Total-factor energy efficiency (TFEE); Panel data; Shephard distance functions;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

    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:pra:mprapa:54304. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.