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Combining Top-Down and Bottom-Up Approaches to Energy-Economy Modeling Using Discrete Choice Methods

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  1. Scarpa, Riccardo & Willis, Ken, 2010. "Willingness-to-pay for renewable energy: Primary and discretionary choice of British households' for micro-generation technologies," Energy Economics, Elsevier, vol. 32(1), pages 129-136, January.
  2. Kurt Kratena & Michael Wüger, 2008. "Combining a Demand System with the Household Production Approach. Modelling Energy Demand in Selected European Countries," WIFO Working Papers 311, WIFO.
  3. Sykes, Maxwell & Axsen, Jonn, 2017. "No free ride to zero-emissions: Simulating a region's need to implement its own zero-emissions vehicle (ZEV) mandate to achieve 2050 GHG targets," Energy Policy, Elsevier, vol. 110(C), pages 447-460.
  4. Steve Pye & Chris Bataille, 2016. "Improving deep decarbonization modelling capacity for developed and developing country contexts," Climate Policy, Taylor & Francis Journals, vol. 16(sup1), pages 27-46, June.
  5. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
  6. Gatt, Damien & Yousif, Charles & Cellura, Maurizio & Camilleri, Liberato & Guarino, Francesco, 2020. "Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  7. Li, Francis G.N. & Bataille, Chris & Pye, Steve & O'Sullivan, Aidan, 2019. "Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?," Applied Energy, Elsevier, vol. 239(C), pages 991-1002.
  8. Chris Bataille, Mark Jaccard, John Nyboer and Nic Rivers, 2006. "Towards General Equilibrium in a Technology-Rich Model with Empirically Estimated Behavioral Parameters," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 93-112.
  9. Zachary A. Wendling & David C. Warren & Barry M. Rubin & Sanya Carley & Kenneth R. Richards, 2020. "A Scalable Energy–Economy Model for State-Level Policy Analysis Applied to a Demand-Side Management Program," Economic Development Quarterly, , vol. 34(4), pages 372-386, November.
  10. Celani de Macedo, Alessandra & Cantore, Nicola & Barbier, Laura & Matteini, Marco & Pasqualetto, Giorgia, 2020. "The Impact of Industrial Energy Efficiency on Economic and Social Indicators," FACTS: Firms And Cities Towards Sustainability 305185, Fondazione Eni Enrico Mattei (FEEM) > FACTS: Firms And Cities Towards Sustainability.
  11. Chinese, D. & Patrizio, P. & Nardin, G., 2014. "Effects of changes in Italian bioenergy promotion schemes for agricultural biogas projects: Insights from a regional optimization model," Energy Policy, Elsevier, vol. 75(C), pages 189-205.
  12. Xavier Labandeira, Pedro Linares and Miguel Rodriguez, 2009. "An Integrated Approach to Simulate the impacts of Carbon Emissions Trading Schemes," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
  13. Rivers, Nic & Jaccard, Mark, 2006. "Useful models for simulating policies to induce technological change," Energy Policy, Elsevier, vol. 34(15), pages 2038-2047, October.
  14. Giraudet, Louis-Gaëtan & Guivarch, Céline & Quirion, Philippe, 2012. "Exploring the potential for energy conservation in French households through hybrid modeling," Energy Economics, Elsevier, vol. 34(2), pages 426-445.
  15. Kurt KRATENA & Ina MEYER & Michael WUEGER, 2008. "Modelling the Energy Demand of Households in a Combined Top Down/Bottom Up Approach," EcoMod2008 23800069, EcoMod.
  16. Murphy, Rose & Rivers, Nic & Jaccard, Mark, 2007. "Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application to Canada," Energy Economics, Elsevier, vol. 29(4), pages 826-846, July.
  17. Tomasz Szul & Stanisław Kokoszka, 2020. "Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization," Energies, MDPI, vol. 13(6), pages 1-17, March.
  18. Fox, Jacob & Axsen, Jonn & Jaccard, Mark, 2017. "Picking Winners: Modelling the Costs of Technology-specific Climate Policy in the U.S. Passenger Vehicle Sector," Ecological Economics, Elsevier, vol. 137(C), pages 133-147.
  19. Bhardwaj, Chandan & Axsen, Jonn & McCollum, David, 2022. "Which “second-best” climate policies are best? Simulating cost-effective policy mixes for passenger vehicles," Resource and Energy Economics, Elsevier, vol. 70(C).
  20. Huntington, Hillard G., 2021. "Model evaluation for policy insights: Reflections on the forum process," Energy Policy, Elsevier, vol. 156(C).
  21. Gi-Young Chae & Seung-Hyun An & Chul-Yong Lee, 2021. "Demand Forecasting for Liquified Natural Gas Bunkering by Country and Region Using Meta-Analysis and Artificial Intelligence," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
  22. Chris Bataille & Benjamin Dachis & Nic Rivers, 2009. "Pricing Greenhouse Gas Emissions: The Impact on Canada's Competitiveness," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 280, February.
  23. Tomasz Szul & Krzysztof Nęcka & Thomas G. Mathia, 2020. "Neural Methods Comparison for Prediction of Heating Energy Based on Few Hundreds Enhanced Buildings in Four Season’s Climate," Energies, MDPI, vol. 13(20), pages 1-17, October.
  24. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2023. "Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning," Applied Energy, Elsevier, vol. 340(C).
  25. Md Mijanur Rahman & Mohammad Shakeri & Sieh Kiong Tiong & Fatema Khatun & Nowshad Amin & Jagadeesh Pasupuleti & Mohammad Kamrul Hasan, 2021. "Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
  26. Stéphane Poncin, 2018. "Energy policy tools in Luxembourg - Assessing their impact on households’ space heating energy consumption and CO2 emissions by means of the LuxHEI model," DEM Discussion Paper Series 18-23, Department of Economics at the University of Luxembourg.
  27. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
  28. Wilson, Charlie, 2010. "Growth dynamics of energy technologies: using historical patterns to validate low carbon scenarios," LSE Research Online Documents on Economics 37602, London School of Economics and Political Science, LSE Library.
  29. Shiljkut, Vladimir M. & Rajakovic, Nikola Lj., 2015. "Demand response capacity estimation in various supply areas," Energy, Elsevier, vol. 92(P3), pages 476-486.
  30. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Institute of Transportation Studies, Working Paper Series qt02n9j6cv, Institute of Transportation Studies, UC Davis.
  31. Vaccaro, Roberto & Rocco, Matteo V., 2021. "Quantifying the impact of low carbon transition scenarios at regional level through soft-linked energy and economy models: The case of South-Tyrol Province in Italy," Energy, Elsevier, vol. 220(C).
  32. Bale, Catherine S.E. & Varga, Liz & Foxon, Timothy J., 2015. "Energy and complexity: New ways forward," Applied Energy, Elsevier, vol. 138(C), pages 150-159.
  33. Mau, Paulus & Eyzaguirre, Jimena & Jaccard, Mark & Collins-Dodd, Colleen & Tiedemann, Kenneth, 2008. "The 'neighbor effect': Simulating dynamics in consumer preferences for new vehicle technologies," Ecological Economics, Elsevier, vol. 68(1-2), pages 504-516, December.
  34. Emmanuel Fragnière & Roman Kanala & Francesco Moresino & Adriana Reveiu & Ion Smeureanu, 2017. "Coupling techno-economic energy models with behavioral approaches," Operational Research, Springer, vol. 17(2), pages 633-647, July.
  35. C. Wilson & A. Grubler & N. Bauer & V. Krey & K. Riahi, 2013. "Future capacity growth of energy technologies: are scenarios consistent with historical evidence?," Climatic Change, Springer, vol. 118(2), pages 381-395, May.
  36. Jaccard, Mark & Murphy, Rose & Zuehlke, Brett & Braglewicz, Morgan, 2019. "Cities and greenhouse gas reduction: Policy makers or policy takers?," Energy Policy, Elsevier, vol. 134(C).
  37. Katharina Sammer & Rolf Wüstenhagen, 2006. "The influence of eco‐labelling on consumer behaviour – results of a discrete choice analysis for washing machines," Business Strategy and the Environment, Wiley Blackwell, vol. 15(3), pages 185-199, May.
  38. Huntington, Hillard G., 2007. "Industrial natural gas consumption in the United States: An empirical model for evaluating future trends," Energy Economics, Elsevier, vol. 29(4), pages 743-759, July.
  39. Stefano Ceolotto & Eleanor Denny, 2021. "Putting a new 'spin' on energy labels: measuring the impact of reframing energy efficiency on tumble dryer choices in a multi-country experiment," Trinity Economics Papers tep1521, Trinity College Dublin, Department of Economics.
  40. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
  41. Eoin Ó Broin & Érika Mata & Jonas Nässén & Filip Johnsson, 2015. "Quantification of the Energy Efficiency Gap in the Swedish Residential Sector," Post-Print hal-01219283, HAL.
  42. Charlie Wilson:, 2010. "Growth dynamics of energy technologies: using historical patterns to validate low carbon scenarios," GRI Working Papers 32, Grantham Research Institute on Climate Change and the Environment.
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