IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v132y2014icp137-154.html
   My bibliography  Save this article

Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?

Author

Listed:
  • Gómez-Calvet, Roberto
  • Conesa, David
  • Gómez-Calvet, Ana Rosa
  • Tortosa-Ausina, Emili

Abstract

Over the last few years concerns have increased about the energy mix in many countries. These concerns have been of greater magnitude for countries with a common energy regulation such as European Union (EU) member states. An important aspect to take into account when choosing a given energy mix is the efficiency involved in its generation. In this context, the present study analyzes the efficiency with which electricity and derived heat was produced in 25 EU member states over the last decade. This analysis considers not only the inputs and outputs involved but, more importantly, which undesirable by-products were generated during the production process, a relevant issue for EU climate policy. To this end, two nonparametric frontier models are applied: first, a Directional Distance Function (DDF), based on Briec’s (1997) [16] proposal and, second, a modified version of Tone’s (2001) [51] Slacks-Based Measure (SBM) model, both of which are especially appropriate in this particular context due to their treatment of undesirable outputs. Results are partly innovative since, with few exceptions, applications on this issue are relatively scarce. From a policy implications’ point of view, our achievements are also interesting because they reveal remarkable efficiency differences among EU countries: those countries from the latest EU enlargements account for the lowest efficiencies, with large opportunities for improvement in CO2 abatement and primary energy saving. Results also show stable efficiencies along the evaluated period and, therefore, highlighting the need to further intensify the initiatives designed to harmonize environmental policies and identifying drivers for efficiency improvement turn out to be still key objectives.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:132:y:2014:i:c:p:137-154
    DOI: 10.1016/j.apenergy.2014.06.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914006357
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2014.06.053?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. van Beeck, Nicole & Doukas, Haris & Gioria, Michel & Karakosta, Charikleia & Psarras, John, 2009. "Energy RTD expenditures in the European union: Data gathering procedures and results towards a scientific reference system," Applied Energy, Elsevier, vol. 86(4), pages 452-459, April.
    2. Peter Bogetoft & Jens Hougaard, 1999. "Efficiency Evaluations Based on Potential (Non-Proportional) Improvements," Journal of Productivity Analysis, Springer, vol. 12(3), pages 233-247, November.
    3. Zaim, Osman, 2004. "Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework," Ecological Economics, Elsevier, vol. 48(1), pages 37-47, January.
    4. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    5. Yang, H. & Pollitt, M., 2007. "Distinguishing Weak and Strong Disposability among Undesirable Outputs in DEA: The Example of the Environmental Efficiency of Chinese Coal-Fired Power Plants," Cambridge Working Papers in Economics 0741, Faculty of Economics, University of Cambridge.
    6. Hawdon, David, 2003. "Efficiency, performance and regulation of the international gas industry--a bootstrap DEA approach," Energy Policy, Elsevier, vol. 31(11), pages 1167-1178, September.
    7. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    8. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    9. R. Russell & William Schworm, 2009. "Axiomatic foundations of efficiency measurement on data-generated technologies," Journal of Productivity Analysis, Springer, vol. 31(2), pages 77-86, April.
    10. 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.
    11. Pollitt, Michael G., 2012. "The role of policy in energy transitions: Lessons from the energy liberalisation era," Energy Policy, Elsevier, vol. 50(C), pages 128-137.
    12. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    13. Camarero, Mariam & Picazo-Tadeo, Andrés J. & Tamarit, Cecilio, 2013. "Are the determinants of CO2 emissions converging among OECD countries?," Economics Letters, Elsevier, vol. 118(1), pages 159-162.
    14. Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
    15. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
    16. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    17. Andrés J. Picazo-Tadeo & José A. Gómez-Limón & Ernest Reig-Martínez, 2010. "Assessing farming eco-efficiency: A Data Envelopment Analysis approach," Working Papers 1004, Department of Applied Economics II, Universidad de Valencia.
    18. Thollander, Patrik & Backlund, Sandra & Trianni, Andrea & Cagno, Enrico, 2013. "Beyond barriers – A case study on driving forces for improved energy efficiency in the foundry industries in Finland, France, Germany, Italy, Poland, Spain, and Sweden," Applied Energy, Elsevier, vol. 111(C), pages 636-643.
    19. Robert Russell, R., 1990. "Continuity of measures of technical efficiency," Journal of Economic Theory, Elsevier, vol. 51(2), pages 255-267, August.
    20. Kaoru Tone & Miki Tsutsui, 2010. "An epsilon-based measure of efficiency in DEA revisited -A third pole of technical efficiency," GRIPS Discussion Papers 09-21, National Graduate Institute for Policy Studies.
    21. Edvardsen, Dag Fjeld & Forsund, Finn R., 2003. "International benchmarking of electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 25(4), pages 353-371, October.
    22. Tolón-Becerra, A. & Lastra-Bravo, X. & Bienvenido-Bárcena, F., 2010. "Methodology proposal for territorial distribution of greenhouse gas reduction percentages in the EU according to the strategic energy policy goal," Applied Energy, Elsevier, vol. 87(11), pages 3552-3564, November.
    23. Cagno, Enrico & Trianni, Andrea, 2013. "Exploring drivers for energy efficiency within small- and medium-sized enterprises: First evidences from Italian manufacturing enterprises," Applied Energy, Elsevier, vol. 104(C), pages 276-285.
    24. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    25. tone, Kaoru, 2010. "Variations on the theme of slacks-based measure of efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 200(3), pages 901-907, February.
    26. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    27. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    28. Jaraitė, Jūratė & Di Maria, Corrado, 2012. "Efficiency, productivity and environmental policy: A case study of power generation in the EU," Energy Economics, Elsevier, vol. 34(5), pages 1557-1568.
    29. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    30. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    31. Graus, Wina & Worrell, Ernst, 2009. "Trend in efficiency and capacity of fossil power generation in the EU," Energy Policy, Elsevier, vol. 37(6), pages 2147-2160, June.
    32. Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," European Journal of Operational Research, Elsevier, vol. 80(3), pages 474-499, February.
    33. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    34. Bousquet, Alain & Ivaldi, Marc, 1998. "An individual choice model of energy mix," Resource and Energy Economics, Elsevier, vol. 20(3), pages 263-286, September.
    35. 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.
    36. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    37. Crossland, Jarrod & Li, Bin & Roca, Eduardo, 2013. "Is the European Union Emissions Trading Scheme (EU ETS) informationally efficient? Evidence from momentum-based trading strategies," Applied Energy, Elsevier, vol. 109(C), pages 10-23.
    38. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    39. R. Robert Russell & William Schworm, 2009. "Axiomatic Foundations of Inefficiency Measurement on Space," Discussion Papers 2009-07, School of Economics, The University of New South Wales.
    40. Picazo-Tadeo, Andres J. & Reig-Martinez, Ernest & Hernandez-Sancho, Francesc, 2005. "Directional distance functions and environmental regulation," Resource and Energy Economics, Elsevier, vol. 27(2), pages 131-142, June.
    41. Yaisawarng, Suthathip & Klein, J Douglass, 1994. "The Effects of Sulfur Dioxide Controls on Productivity Change in the U.S. Electric Power Industry," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 447-460, August.
    42. Chatzimouratidis, Athanasios I. & Pilavachi, Petros A., 2008. "Multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process," Energy Policy, Elsevier, vol. 36(3), pages 1074-1089, March.
    43. Ramanathan, Ramakrishnan, 2005. "An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa," Energy, Elsevier, vol. 30(15), pages 2831-2842.
    44. Fare, Rolf & Grosskopf, Shawna & Tyteca, Daniel, 1996. "An activity analysis model of the environmental performance of firms--application to fossil-fuel-fired electric utilities," Ecological Economics, Elsevier, vol. 18(2), pages 161-175, August.
    45. 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.
    46. Zofio, Jose L. & Prieto, Angel M., 2001. "Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries," Resource and Energy Economics, Elsevier, vol. 23(1), pages 63-83, January.
    47. 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.
    48. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    49. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    50. Trianni, Andrea & Cagno, Enrico & De Donatis, Alessio, 2014. "A framework to characterize energy efficiency measures," Applied Energy, Elsevier, vol. 118(C), pages 207-220.
    51. Mariam Camarero & Juana Castillo & Andrés Picazo-Tadeo & Cecilio Tamarit, 2013. "Eco-Efficiency and Convergence in OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(1), pages 87-106, May.
    52. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    53. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    54. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    55. W. Briec, 1997. "A Graph-Type Extension of Farrell Technical Efficiency Measure," Journal of Productivity Analysis, Springer, vol. 8(1), pages 95-110, March.
    56. Thieme, Claudio & Prior, Diego & Tortosa-Ausina, Emili, 2013. "A multilevel decomposition of school performance using robust nonparametric frontier techniques," Economics of Education Review, Elsevier, vol. 32(C), pages 104-121.
    57. 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.
    58. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    59. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    60. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    61. Wei, Chu & Ni, Jinlan & Du, Limin, 2012. "Regional allocation of carbon dioxide abatement in China," China Economic Review, Elsevier, vol. 23(3), pages 552-565.
    62. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    63. Mariam Camarero & Juana Castillo-Giménez & Andrés Picazo-Tadeo & Cecilio Tamarit, 2014. "Is eco-efficiency in greenhouse gas emissions converging among European Union countries?," Empirical Economics, Springer, vol. 47(1), pages 143-168, August.
    64. Philippe Barla & Sergio Perelman, 2005. "Sulphur emissions and productivity growth in industrialised countries," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 76(2), pages 275-300, June.
    65. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    66. Forsund, Finn R., 2009. "Good Modelling of Bad Outputs: Pollution and Multiple-Output Production," International Review of Environmental and Resource Economics, now publishers, vol. 3(1), pages 1-38, August.
    67. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    68. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    69. 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.
    70. 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.
    71. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    72. Sims, Ralph E. H. & Rogner, Hans-Holger & Gregory, Ken, 2003. "Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy resources for electricity generation," Energy Policy, Elsevier, vol. 31(13), pages 1315-1326, October.
    73. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    74. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    75. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    76. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    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. 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.
    3. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    4. Tsolas, Ioannis E., 2011. "Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA," Resources Policy, Elsevier, vol. 36(2), pages 159-167, June.
    5. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    6. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.
    7. Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Hsu, Shih-Hsun & Managi, Shunsuke, 2015. "The enhanced Russell-based directional distance measure with undesirable outputs: Numerical example considering CO2 emissions," Omega, Elsevier, vol. 53(C), pages 30-40.
    8. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    9. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    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. Li, Mingquan & Wang, Qi, 2014. "International environmental efficiency differences and their determinants," Energy, Elsevier, vol. 78(C), pages 411-420.
    12. Barros, Carlos Pestana & Managi, Shunsuke & Matousek, Roman, 2012. "The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output," Omega, Elsevier, vol. 40(1), pages 1-8, January.
    13. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    14. Bretholt, Abraham & Pan, Jeh-Nan, 2013. "Evolving the latent variable model as an environmental DEA technology," Omega, Elsevier, vol. 41(2), pages 315-325.
    15. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    16. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    17. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    18. Noor Ramli & Susila Munisamy & Behrouz Arabi, 2013. "Scale directional distance function and its application to the measurement of eco-efficiency in the manufacturing sector," Annals of Operations Research, Springer, vol. 211(1), pages 381-398, December.
    19. Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Managi, Shunsuke, 2014. "Non-Radial Directional Performance Measurement with Undesirable Outputs," MPRA Paper 57189, University Library of Munich, Germany.
    20. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.

    More about this item

    Keywords

    Efficiency; Energy; Data envelopment analysis; European Union; Slacks-based measure;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • 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:appene:v:132:y:2014:i:c:p:137-154. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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/wps/find/journaldescription.cws_home/405891/description#description .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.