IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v98y2021ics0140988321001274.html
   My bibliography  Save this article

The underlying drivers of economy-wide energy efficiency and asymmetric energy price responses

Author

Listed:
  • Tajudeen, Ibrahim A.

Abstract

A good understanding of energy efficiency trend and its potential underlying drivers is required when considering policies for energy conservation and environmental sustainability. In light of this, we estimate energy efficiency trends using index decomposition analysis, data envelopment analysis and stochastic frontier analysis as robust methods. The driving factors (including asymmetric price responses) are examined using a dynamic panel model estimated by Arellano and Bond (1991) GMM estimator. The application for 32 OECD countries found that none of the three methods leads to a consistent ranking between energy efficiency estimates and energy intensity – corroborating the criticism that energy intensity is not a good proxy for energy efficiency. The panel-data regressions using the energy efficiency estimates from the three methods show similarities in the impacts of the drivers (including energy price, foreign direct inflows, trade openness, population growth, temperature etc.) on energy efficiency. Although the results of asymmetric price responses of energy efficiency estimates vary slightly, we found insignificant evidence of asymmetric effects of total energy price but there are asymmetric responses with energy-specific prices. Thus, using energy-specific prices as well as allowing for asymmetric price effects in analysing drivers of energy efficiency is apt and informative in formulating energy policies.

Suggested Citation

  • Tajudeen, Ibrahim A., 2021. "The underlying drivers of economy-wide energy efficiency and asymmetric energy price responses," Energy Economics, Elsevier, vol. 98(C).
    • Handle: RePEc:eee:eneeco:v:98:y:2021:i:c:s0140988321001274
    DOI: 10.1016/j.eneco.2021.105222
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988321001274
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2021.105222?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    2. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    3. Birol, Fatih & Keppler, Jan Horst, 2000. "Prices, technology development and the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 457-469, June.
    4. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    5. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    6. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    7. 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.
    8. Manuel Frondel and Colin Vance, 2013. "Re-Identifying the Rebound: What About Asymmetry?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    9. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    10. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    11. David L. Ryan & Yu Wang & Andre Plourde, 1996. "Asymmetric Price Responses of Residential Energy Demand in Ontario," Canadian Journal of Economics, Canadian Economics Association, vol. 29(s1), pages 317-323, April.
    12. G. Boyd & J. F. McDonald & M. Ross & D. A. Hansont, 1987. "Separating the Changing Composition of U.S. Manufacturing Production from Energy Efficiency Improvements: A Divisia Index Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 77-96.
    13. James M. Griffin & Craig T. Schulman, 2005. "Price Asymmetry in Energy Demand Models: A Proxy for Energy-Saving Technical Change?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-22.
    14. Adom, Philip Kofi, 2015. "Asymmetric impacts of the determinants of energy intensity in Nigeria," Energy Economics, Elsevier, vol. 49(C), pages 570-580.
    15. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    16. 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.
    17. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    18. Morakinyo O. Adetutu, Anthony J. Glass, and Thomas G. Weyman-Jones, 2016. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    19. Chitnis, Mona & Hunt, Lester C., 2012. "What drives the change in UK household energy expenditure and associated CO2 emissions? Implication and forecast to 2020," Applied Energy, Elsevier, vol. 94(C), pages 202-214.
    20. Lin Zhang and Philip Kofi Adom, 2018. "Energy Efficiency Transitions in China: How Persistent are the Movements to/from the Frontier?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    21. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    22. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    23. Gardner, Douglas, 1993. "Industrial energy use in Ontario from 1962 to 1984," Energy Economics, Elsevier, vol. 15(1), pages 25-32, January.
    24. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    25. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    26. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    27. Hang, Leiming & Tu, Meizeng, 2007. "The impacts of energy prices on energy intensity: Evidence from China," Energy Policy, Elsevier, vol. 35(5), pages 2978-2988, May.
    28. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    29. repec:dau:papers:123456789/10972 is not listed on IDEAS
    30. De Witte, Kristof & Mika, Kortelainen, 2009. "Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete exogenous variables," MPRA Paper 14034, University Library of Munich, Germany.
    31. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    32. Dermot Gately & Hillard G. Huntington, 2002. "The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand," The Energy Journal, , vol. 23(1), pages 19-55, January.
    33. Hillard G. Huntington, 2006. "A Note on Price Asymmetry as Induced Technical Change," The Energy Journal, , vol. 27(3), pages 1-9, July.
    34. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    35. Saeed Moshiri & Nana Duah, 2016. "Changes in Energy Intensity in Canada," The Energy Journal, , vol. 37(4), pages 315-342, October.
    36. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    37. Vishal Chandr Jaunky and Lin Zhang, 2016. "Convergence of Operational Efficiency in Chinas Provincial Power Sectors," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    38. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    39. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    40. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
    41. Boyd, Gale A. & Pang, Joseph X., 2000. "Estimating the linkage between energy efficiency and productivity," Energy Policy, Elsevier, vol. 28(5), pages 289-296, May.
    42. Dargay, Joyce & Gately, Dermot, 1995. "The imperfect price reversibility of non-transport oil demand in the OECD," Energy Economics, Elsevier, vol. 17(1), pages 59-71, January.
    43. Adom, Philip K. & Kwakwa, Paul Adjei, 2014. "Effects of changing trade structure and technical characteristics of the manufacturing sector on energy intensity in Ghana," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 475-483.
    44. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, , vol. 29(3), pages 1-26, July.
    45. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    46. Gale A. Boyd and Joseph M. Roop, 2004. "A Note on the Fisher Ideal Index Decomposition for Structural Change in Energy Intensity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 87-102.
    47. Kumbhakar, Subal C & Hjalmarsson, Lennart, 1995. "Labour-Use Efficiency in Swedish Social Insurance Offices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 33-47, Jan.-Marc.
    48. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    49. Amuakwa-Mensah, Franklin & Klege, Rebecca A. & Adom, Philip K. & Amoah, Anthony & Hagan, Edmond, 2018. "Unveiling the energy saving role of banking performance in Sub-Sahara Africa," Energy Economics, Elsevier, vol. 74(C), pages 828-842.
    50. Peter Mulder, 2015. "International Specialization, Structural Change and the Evolution of Manufacturing Energy Intensity in OECD Countries," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    51. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    52. James P. Houck, 1977. "An Approach to Specifying and Estimating Nonreversible Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(3), pages 570-572.
    53. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    54. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    55. Filippini, Massimo & Hunt, Lester C. & Zorić, Jelena, 2014. "Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector," Energy Policy, Elsevier, vol. 69(C), pages 73-81.
    56. Feijoo, Maria L. & Franco, Juan F. & Hernandez, Jose M., 2002. "Global warming and the energy efficiency of Spanish industry," Energy Economics, Elsevier, vol. 24(4), pages 405-423, July.
    57. Mielnik, Otavio & Goldemberg, Jose, 2002. "Foreign direct investment and decoupling between energy and gross domestic product in developing countries," Energy Policy, Elsevier, vol. 30(2), pages 87-89, January.
    58. 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.
    59. 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.
    60. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    61. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    62. 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)

    Citations

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


    Cited by:

    1. Lin, Boqiang & Xie, Yongjing, 2022. "Analysis on operational efficiency and its influencing factors of China’s nuclear power plants," Energy, Elsevier, vol. 261(PA).
    2. Alberini, Anna & Bezhanishvili, Levan & Ščasný, Milan, 2022. "“Wild” tariff schemes: Evidence from the Republic of Georgia," Energy Economics, Elsevier, vol. 110(C).
    3. Lin, Boqiang & Xie, Yongjing, 2023. "Does digital transformation improve the operational efficiency of Chinese power enterprises?," Utilities Policy, Elsevier, vol. 82(C).
    4. Andrzej Jezierski & Cezary Mańkowski & Rafał Śpiewak, 2021. "Energy Savings Analysis in Logistics of a Wind Farm Repowering Process: A Case Study," Energies, MDPI, vol. 14(17), pages 1-23, September.
    5. Adekoya, Oluwasegun B. & Kenku, Oluwademilade T. & Oliyide, Johnson A. & Al-Faryan, Mamdouh Abdulaziz Saleh & Ogunjemilua, Oluwafemi D., 2023. "Does economic complexity drive energy efficiency and renewable energy transition?," Energy, Elsevier, vol. 278(C).
    6. Lee, Chien-Chiang & Ho, Shan-Ju, 2022. "Impacts of export diversification on energy intensity, renewable energy, and waste energy in 121 countries: Do environmental regulations matter?," Renewable Energy, Elsevier, vol. 199(C), pages 1510-1522.
    7. 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).
    8. Adom, Philip Kofi & Amuakwa-Mensah, Franklin & Akorli, Charity Dzifa, 2023. "Energy efficiency as a sustainability concern in Africa and financial development: How much bias is involved?," Energy Economics, Elsevier, vol. 120(C).
    9. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    10. Zhou, P. & Zhang, H. & Zhang, L.P., 2022. "The drivers of energy intensity changes in Chinese cities: A production-theoretical decomposition analysis," Applied Energy, Elsevier, vol. 307(C).
    11. Yun Yang, 2023. "The Impact of Green Finance and Resource Tax Policy on Regional Energy Efficiency Based on the Non-Desired Output Super-Efficiency SBM-Tobit Model," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    12. Park, Jiyong & Woo, JongRoul, 2023. "Analyzing consumers' willingness to purchase energy-efficient appliances in response to energy price changes: Case study of South Korea," Energy Economics, Elsevier, vol. 127(PA).
    13. Zhu, Minglei & Huang, Haiyan & Ma, Weiwen, 2023. "Transformation of natural resource use: Moving towards sustainability through ICT-based improvements in green total factor energy efficiency," Resources Policy, Elsevier, vol. 80(C).

    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. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    2. 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).
    3. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    4. Tajudeen, Ibrahim A. & Wossink, Ada & Banerjee, Prasenjit, 2018. "How significant is energy efficiency to mitigate CO2 emissions? Evidence from OECD countries," Energy Economics, Elsevier, vol. 72(C), pages 200-221.
    5. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    6. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    7. 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).
    8. Victor von Loessl & Heike Wetzel, 2019. "Revenue decoupling and energy consumption: Empirical evidence from the U.S. electric utilities sector," MAGKS Papers on Economics 201918, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    9. 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.
    10. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    11. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    12. Giovanni Marin & Alessandro Palma, 2015. "Technology Invention and Diffusion in Residential Energy Consumption. A Stochastic Frontier Approach," Working Papers 2015.104, Fondazione Eni Enrico Mattei.
    13. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
    14. Joanne Evans & Massimo Filippini & Lester C. Hunt, 2013. "The contribution of energy efficiency towards meeting CO2 targets," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 8, pages 175-223, Edward Elgar Publishing.
    15. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    16. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    17. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    18. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    19. 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.
    20. Ajayi, V. & Reiner, D., 2018. "European Industrial Energy Intensity: The Role of Innovation 1995-2009," Cambridge Working Papers in Economics 1835, Faculty of Economics, University of Cambridge.

    More about this item

    Keywords

    Energy efficiency; Asymmetric price effects; Index decomposition analysis; Data envelopment analysis; Stochastic frontier analysis; Dynamic panel data regression for OECD;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:eee:eneeco:v:98:y:2021:i:c:s0140988321001274. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.