[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v194y2017icp184-198.html
   My bibliography  Save this article

Formalizing best practice for energy system optimization modelling

Author

Listed:
  • DeCarolis, Joseph
  • Daly, Hannah
  • Dodds, Paul
  • Keppo, Ilkka
  • Li, Francis
  • McDowall, Will
  • Pye, Steve
  • Strachan, Neil
  • Trutnevyte, Evelina
  • Usher, Will
  • Winning, Matthew
  • Yeh, Sonia
  • Zeyringer, Marianne
Abstract
Energy system optimization models (ESOMs) are widely used to generate insight that informs energy and environmental policy. Using ESOMs to produce policy-relevant insight requires significant modeler judgement, yet little formal guidance exists on how to conduct analysis with ESOMs. To address this shortcoming, we draw on our collective modelling experience and conduct an extensive literature review to formalize best practice for energy system optimization modelling. We begin by articulating a set of overarching principles that can be used to guide ESOM-based analysis. To help operationalize the guiding principles, we outline and explain critical steps in the modelling process, including how to formulate research questions, set spatio-temporal boundaries, consider appropriate model features, conduct and refine the analysis, quantify uncertainty, and communicate insights. We highlight the need to develop and refine formal guidance on ESOM application, which comes at a critical time as ESOMs are being used to inform national climate targets.

Suggested Citation

  • DeCarolis, Joseph & Daly, Hannah & Dodds, Paul & Keppo, Ilkka & Li, Francis & McDowall, Will & Pye, Steve & Strachan, Neil & Trutnevyte, Evelina & Usher, Will & Winning, Matthew & Yeh, Sonia & Zeyring, 2017. "Formalizing best practice for energy system optimization modelling," Applied Energy, Elsevier, vol. 194(C), pages 184-198.
    • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:184-198
    DOI: 10.1016/j.apenergy.2017.03.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917302192
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.03.001?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. Neil Strachan & Stephen Pye & Nicholas Hughes, 2008. "The role of international drivers on UK scenarios of a low-carbon society," Climate Policy, Taylor & Francis Journals, vol. 8(sup1), pages 125-139, December.
    2. Cayla, Jean-Michel & Maïzi, Nadia, 2015. "Integrating household behavior and heterogeneity into the TIMES-Households model," Applied Energy, Elsevier, vol. 139(C), pages 56-67.
    3. Fredrik Hedenus, Christian Azar and Kristian Lindgren, 2006. "Induced Technological Change in a Limited Foresight Optimization Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 109-122.
    4. N/A, 2011. "The UK economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 218(1), pages 3-3, October.
    5. Arnulf Grübler & Nebojsa Nakicenovic, 2001. "Identifying dangers in an uncertain climate," Nature, Nature, vol. 412(6842), pages 15-15, July.
    6. Haller, Markus & Ludig, Sylvie & Bauer, Nico, 2012. "Decarbonization scenarios for the EU and MENA power system: Considering spatial distribution and short term dynamics of renewable generation," Energy Policy, Elsevier, vol. 47(C), pages 282-290.
    7. Dodds, Paul E., 2014. "Integrating housing stock and energy system models as a strategy to improve heat decarbonisation assessments," Applied Energy, Elsevier, vol. 132(C), pages 358-369.
    8. Strachan, Neil & Kannan, Ramachandran, 2008. "Hybrid modelling of long-term carbon reduction scenarios for the UK," Energy Economics, Elsevier, vol. 30(6), pages 2947-2963, November.
    9. N/A, 2011. "The UK economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 216(1), pages 3-3, April.
    10. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    11. Pina, André & Silva, Carlos A. & Ferrão, Paulo, 2013. "High-resolution modeling framework for planning electricity systems with high penetration of renewables," Applied Energy, Elsevier, vol. 112(C), pages 215-223.
    12. Strachan, Neil, 2011. "UK energy policy ambition and UK energy modelling--fit for purpose?," Energy Policy, Elsevier, vol. 39(3), pages 1037-1040, March.
    13. Neil Strachan & Will Usher, 2012. "Failure to achieve stringent carbon reduction targets in a second-best policy world," Climatic Change, Springer, vol. 113(2), pages 121-139, July.
    14. Richard Loulou & Maryse Labriet, 2008. "ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure," Computational Management Science, Springer, vol. 5(1), pages 7-40, February.
    15. Geoffrey Blanford & Elmar Kriegler & Massimo Tavoni, 2014. "Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27," Climatic Change, Springer, vol. 123(3), pages 383-396, April.
    16. Liao, Gwo-Liang & Chen, Yen Hung & Sheu, Shey-Huei, 2009. "Optimal economic production quantity policy for imperfect process with imperfect repair and maintenance," European Journal of Operational Research, Elsevier, vol. 195(2), pages 348-357, June.
    17. Li, Francis G.N. & Trutnevyte, Evelina, 2017. "Investment appraisal of cost-optimal and near-optimal pathways for the UK electricity sector transition to 2050," Applied Energy, Elsevier, vol. 189(C), pages 89-109.
    18. Pye, Steve & Usher, Will & Strachan, Neil, 2014. "The uncertain but critical role of demand reduction in meeting long-term energy decarbonisation targets," Energy Policy, Elsevier, vol. 73(C), pages 575-586.
    19. Evelina Trutnevyte & Céline Guivarch & Robert Lempert & Neil Strachan, 2016. "Reinvigorating the scenario technique to expand uncertainty consideration," Climatic Change, Springer, vol. 135(3), pages 373-379, April.
    20. Kesicki, Fabian & Anandarajah, Gabrial, 2011. "The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis," Energy Policy, Elsevier, vol. 39(11), pages 7224-7233.
    21. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    22. Huntington, Hillard G & Weyant, John P & Sweeney, James L, 1982. "Modeling for insights, not numbers: the experiences of the energy modeling forum," Omega, Elsevier, vol. 10(5), pages 449-462.
    23. Maurizio Gargiulo & Brian Ó Gallachóir, 2013. "Long-term energy models: Principles, characteristics, focus, and limitations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 2(2), pages 158-177, March.
    24. Trutnevyte, Evelina & Barton, John & O'Grady, Áine & Ogunkunle, Damiete & Pudjianto, Danny & Robertson, Elizabeth, 2014. "Linking a storyline with multiple models: A cross-scale study of the UK power system transition," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 26-42.
    25. Richard Loulou, 2008. "ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation," Computational Management Science, Springer, vol. 5(1), pages 41-66, February.
    26. Kannan, Ramachandran, 2011. "The development and application of a temporal MARKAL energy system model using flexible time slicing," Applied Energy, Elsevier, vol. 88(6), pages 2261-2272, June.
    27. Bosetti, Valentina & Tavoni, Massimo, 2009. "Uncertain R&D, backstop technology and GHGs stabilization," Energy Economics, Elsevier, vol. 31(Supplemen), pages 18-26.
    28. Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, April.
    29. Daly, Hannah E. & Ramea, Kalai & Chiodi, Alessandro & Yeh, Sonia & Gargiulo, Maurizio & Gallachóir, Brian Ó, 2014. "Incorporating travel behaviour and travel time into TIMES energy system models," Applied Energy, Elsevier, vol. 135(C), pages 429-439.
    30. Paul Ekins & Gabrial Anandarajah & Neil Strachan, 2011. "Towards a low-carbon economy: scenarios and policies for the UK," Climate Policy, Taylor & Francis Journals, vol. 11(2), pages 865-882, March.
    31. García-Gusano, Diego & Espegren, Kari & Lind, Arne & Kirkengen, Martin, 2016. "The role of the discount rates in energy systems optimisation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 56-72.
    32. Hughes, Nick, 2013. "Towards improving the relevance of scenarios for public policy questions: A proposed methodological framework for policy relevant low carbon scenarios," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 687-698.
    33. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    34. Usher, Will & Strachan, Neil, 2012. "Critical mid-term uncertainties in long-term decarbonisation pathways," Energy Policy, Elsevier, vol. 41(C), pages 433-444.
    35. DeCarolis, Joseph F., 2011. "Using modeling to generate alternatives (MGA) to expand our thinking on energy futures," Energy Economics, Elsevier, vol. 33(2), pages 145-152, March.
    36. Bunch, David S. & Bradley, Mark & Golob, Thomas F. & Kitamura, Ryuichi & Occhiuzzo, Gareth P., 1993. "Demand for clean-fuel vehicles in California: A discrete-choice stated preference pilot project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(3), pages 237-253, May.
    37. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    38. Gabrielle Wong-Parodi & Baruch Fischhoff & Ben Strauss, 2014. "A method to evaluate the usability of interactive climate change impact decision aids," Climatic Change, Springer, vol. 126(3), pages 485-493, October.
    39. Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
    40. Niclas Mattsson, 2002. "Introducing uncertain learning in an energy system model: a pilot study using GENIE," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 18(2/3/4), pages 253-265.
    41. Ad Seebregts & Tom Kram & Gerrit Jan Schaeffer & Alexandra Bos, 2000. "Endogenous learning and technology clustering: analysis with MARKAL model of the Western European energy system," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 289-319.
    42. Klinge Jacobsen, Henrik, 1998. "Integrating the bottom-up and top-down approach to energy-economy modelling: the case of Denmark," Energy Economics, Elsevier, vol. 20(4), pages 443-461, September.
    43. Jean Charles Hourcade & Mark Jaccard & Chris Bataille & Frédéric Ghersi, 2006. "Hybrid Modeling: New Answers to Old Challenges," Post-Print halshs-00471234, HAL.
    44. Jeffrey C Peters, 2016. "The GTAP-Power Data Base: Disaggregating the Electricity Sector in the GTAP Data Base," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 1(1), pages 209-250, June.
    45. Gass, Viktoria & Schmidt, Johannes & Strauss, Franziska & Schmid, Erwin, 2013. "Assessing the economic wind power potential in Austria," Energy Policy, Elsevier, vol. 53(C), pages 323-330.
    46. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    47. Anandarajah, Gabrial & Strachan, Neil, 2010. "Interactions and implications of renewable and climate change policy on UK energy scenarios," Energy Policy, Elsevier, vol. 38(11), pages 6724-6735, November.
    48. Strachan, Neil & Pye, Steve & Kannan, Ramachandran, 2009. "The iterative contribution and relevance of modelling to UK energy policy," Energy Policy, Elsevier, vol. 37(3), pages 850-860, March.
    49. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    50. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    51. Greene, David L., 2011. "Uncertainty, loss aversion, and markets for energy efficiency," Energy Economics, Elsevier, vol. 33(4), pages 608-616, July.
    52. Trutnevyte, Evelina, 2016. "Does cost optimization approximate the real-world energy transition?," Energy, Elsevier, vol. 106(C), pages 182-193.
    53. Welsch, M. & Howells, M. & Bazilian, M. & DeCarolis, J.F. & Hermann, S. & Rogner, H.H., 2012. "Modelling elements of Smart Grids – Enhancing the OSeMOSYS (Open Source Energy Modelling System) code," Energy, Elsevier, vol. 46(1), pages 337-350.
    54. Martinsen, Dag & Krey, Volker & Markewitz, Peter, 2007. "Implications of high energy prices for energy system and emissions--The response from an energy model for Germany," Energy Policy, Elsevier, vol. 35(9), pages 4504-4515, September.
    55. Trutnevyte, Evelina, 2013. "EXPANSE methodology for evaluating the economic potential of renewable energy from an energy mix perspective," Applied Energy, Elsevier, vol. 111(C), pages 593-601.
    56. Simoes, Sofia & Zeyringer, Marianne & Mayr, Dieter & Huld, Thomas & Nijs, Wouter & Schmidt, Johannes, 2017. "Impact of different levels of geographical disaggregation of wind and PV electricity generation in large energy system models: A case study for Austria," Renewable Energy, Elsevier, vol. 105(C), pages 183-198.
    57. Ludig, Sylvie & Haller, Markus & Schmid, Eva & Bauer, Nico, 2011. "Fluctuating renewables in a long-term climate change mitigation strategy," Energy, Elsevier, vol. 36(11), pages 6674-6685.
    58. Hunter, Kevin & Sreepathi, Sarat & DeCarolis, Joseph F., 2013. "Modeling for insight using Tools for Energy Model Optimization and Analysis (Temoa)," Energy Economics, Elsevier, vol. 40(C), pages 339-349.
    59. DeCarolis, Joseph F. & Hunter, Kevin & Sreepathi, Sarat, 2012. "The case for repeatable analysis with energy economy optimization models," Energy Economics, Elsevier, vol. 34(6), pages 1845-1853.
    60. Jean-Charles Hourcade, Mark Jaccard, Chris Bataille, and Frederic Ghersi, 2006. "Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of The Energy Journal," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 1-12.
    61. Trutnevyte, Evelina & McDowall, Will & Tomei, Julia & Keppo, Ilkka, 2016. "Energy scenario choices: Insights from a retrospective review of UK energy futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 326-337.
    62. Pye, Steve & Sabio, Nagore & Strachan, Neil, 2015. "An integrated systematic analysis of uncertainties in UK energy transition pathways," Energy Policy, Elsevier, vol. 87(C), pages 673-684.
    63. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    64. Martinsen, Thomas, 2011. "Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models," Energy Policy, Elsevier, vol. 39(6), pages 3327-3336, June.
    65. Chen, Wenying & Wu, Zongxin & He, Jiankun & Gao, Pengfei & Xu, Shaofeng, 2007. "Carbon emission control strategies for China: A comparative study with partial and general equilibrium versions of the China MARKAL model," Energy, Elsevier, vol. 32(1), pages 59-72.
    66. Messner, Sabine & Schrattenholzer, Leo, 2000. "MESSAGE–MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively," Energy, Elsevier, vol. 25(3), pages 267-282.
    67. Jablonski, Sophie & Strachan, Neil & Brand, Christian & Bauen, Ausilio, 2010. "The role of bioenergy in the UK's energy future formulation and modelling of long-term UK bioenergy scenarios," Energy Policy, Elsevier, vol. 38(10), pages 5799-5816, October.
    68. Keppo, Ilkka & Strubegger, Manfred, 2010. "Short term decisions for long term problems – The effect of foresight on model based energy systems analysis," Energy, Elsevier, vol. 35(5), pages 2033-2042.
    69. Hughes, Nick & Strachan, Neil, 2010. "Methodological review of UK and international low carbon scenarios," Energy Policy, Elsevier, vol. 38(10), pages 6056-6065, October.
    70. E. Downey Brill, Jr. & Shoou-Yuh Chang & Lewis D. Hopkins, 1982. "Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning," Management Science, INFORMS, vol. 28(3), pages 221-235, March.
    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. Price, James & Keppo, Ilkka, 2017. "Modelling to generate alternatives: A technique to explore uncertainty in energy-environment-economy models," Applied Energy, Elsevier, vol. 195(C), pages 356-369.
    2. Trutnevyte, Evelina, 2016. "Does cost optimization approximate the real-world energy transition?," Energy, Elsevier, vol. 106(C), pages 182-193.
    3. Li, Francis G.N. & Trutnevyte, Evelina, 2017. "Investment appraisal of cost-optimal and near-optimal pathways for the UK electricity sector transition to 2050," Applied Energy, Elsevier, vol. 189(C), pages 89-109.
    4. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    5. Berntsen, Philip B. & Trutnevyte, Evelina, 2017. "Ensuring diversity of national energy scenarios: Bottom-up energy system model with Modeling to Generate Alternatives," Energy, Elsevier, vol. 126(C), pages 886-898.
    6. Borasio, M. & Moret, S., 2022. "Deep decarbonisation of regional energy systems: A novel modelling approach and its application to the Italian energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    7. Trutnevyte, Evelina & Barton, John & O'Grady, Áine & Ogunkunle, Damiete & Pudjianto, Danny & Robertson, Elizabeth, 2014. "Linking a storyline with multiple models: A cross-scale study of the UK power system transition," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 26-42.
    8. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    9. Roberts, Simon H. & Foran, Barney D. & Axon, Colin J. & Warr, Benjamin S. & Goddard, Nigel H., 2018. "Consequences of selecting technology pathways on cumulative carbon dioxide emissions for the United Kingdom," Applied Energy, Elsevier, vol. 228(C), pages 409-425.
    10. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    11. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    12. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    13. Pye, Steve & Sabio, Nagore & Strachan, Neil, 2015. "An integrated systematic analysis of uncertainties in UK energy transition pathways," Energy Policy, Elsevier, vol. 87(C), pages 673-684.
    14. Anandarajah, Gabrial & McDowall, Will, 2012. "What are the costs of Scotland's climate and renewable policies?," Energy Policy, Elsevier, vol. 50(C), pages 773-783.
    15. Fais, Birgit & Sabio, Nagore & Strachan, Neil, 2016. "The critical role of the industrial sector in reaching long-term emission reduction, energy efficiency and renewable targets," Applied Energy, Elsevier, vol. 162(C), pages 699-712.
    16. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    17. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    18. Trutnevyte, Evelina & McDowall, Will & Tomei, Julia & Keppo, Ilkka, 2016. "Energy scenario choices: Insights from a retrospective review of UK energy futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 326-337.
    19. Pizarro-Alonso, Amalia & Ravn, Hans & Münster, Marie, 2019. "Uncertainties towards a fossil-free system with high integration of wind energy in long-term planning," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    20. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.

    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:194:y:2017:i:c:p:184-198. 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/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. RePEc uses bibliographic data supplied by the respective publishers.