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Integrating the bottom-up and top-down approach to energy-economy modelling: the case of Denmark

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  1. Jacobsen, Henrik Klinge, 2001. "Technological progress and long-term energy demand -- a survey of recent approaches and a Danish case," Energy Policy, Elsevier, vol. 29(2), pages 147-157, January.
  2. Daniel Neves Schmitz Gonçalves & Renata Albergaria de Mello Bandeira & Mariane Gonzalez da Costa & George Vasconcelos Goes & Tássia Faria de Assis & Márcio de Almeida D’Agosto & Isabela Rocha Pombo Le, 2020. "A Multitier Approach to Estimating the Energy Efficiency of Urban Passenger Mobility," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
  3. Lombardi, Francesco & Rocco, Matteo Vincenzo & Colombo, Emanuela, 2019. "A multi-layer energy modelling methodology to assess the impact of heat-electricity integration strategies: The case of the residential cooking sector in Italy," Energy, Elsevier, vol. 170(C), pages 1249-1260.
  4. 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.
  5. Omar Shafqat & Elena Malakhtka & Nina Chrobot & Per Lundqvist, 2021. "End Use Energy Services Framework Co-Creation with Multiple Stakeholders—A Living Lab-Based Case Study," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
  6. El-Sayed, Ahmed Hassan A. & Khalil, Adel & Yehia, Mohamed, 2023. "Modeling alternative scenarios for Egypt 2050 energy mix based on LEAP analysis," Energy, Elsevier, vol. 266(C).
  7. Enrico Giglio & Ermando Petracca & Bruno Paduano & Claudio Moscoloni & Giuseppe Giorgi & Sergej Antonello Sirigu, 2023. "Estimating the Cost of Wave Energy Converters at an Early Design Stage: A Bottom-Up Approach," Sustainability, MDPI, vol. 15(8), pages 1-39, April.
  8. 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.
  9. Clinch, J. Peter & Healy, John D., 2003. "Valuing improvements in comfort from domestic energy-efficiency retrofits using a trade-off simulation model," Energy Economics, Elsevier, vol. 25(5), pages 565-583, September.
  10. Park, Sang Yong & Yun, Bo-Yeong & Yun, Chang Yeol & Lee, Duk Hee & Choi, Dong Gu, 2016. "An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 319-329.
  11. Dellink, Rob & van Ierland, Ekko, 2006. "Pollution abatement in the Netherlands: A dynamic applied general equilibrium assessment," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 207-221, February.
  12. Halkos, George, 2014. "The Economics of Climate Change Policy: Critical review and future policy directions," MPRA Paper 56841, University Library of Munich, Germany.
  13. Koopmans, Carl C. & te Velde, Dirk Willem, 2001. "Bridging the energy efficiency gap: using bottom-up information in a top-down energy demand model," Energy Economics, Elsevier, vol. 23(1), pages 57-75, January.
  14. Boonekamp, Piet G.M., 2006. "Actual interaction effects between policy measures for energy efficiency—A qualitative matrix method and quantitative simulation results for households," Energy, Elsevier, vol. 31(14), pages 2848-2873.
  15. Pandey, Rahul, 2002. "Energy policy modelling: agenda for developing countries," Energy Policy, Elsevier, vol. 30(2), pages 97-106, January.
  16. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
  17. Nic Rivers & Mark Jaccard, 2005. "Combining Top-Down and Bottom-Up Approaches to Energy-Economy Modeling Using Discrete Choice Methods," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 83-106.
  18. Jaccard, Mark & Loulou, Richard & Kanudia, Amit & Nyboer, John & Bailie, Alison & Labriet, Maryse, 2003. "Methodological contrasts in costing greenhouse gas abatement policies: Optimization and simulation modeling of micro-economic effects in Canada," European Journal of Operational Research, Elsevier, vol. 145(1), pages 148-164, February.
  19. Silva, Felipe L.C. & Souza, Reinaldo C. & Cyrino Oliveira, Fernando L. & Lourenco, Plutarcho M. & Calili, Rodrigo F., 2018. "A bottom-up methodology for long term electricity consumption forecasting of an industrial sector - Application to pulp and paper sector in Brazil," Energy, Elsevier, vol. 144(C), pages 1107-1118.
  20. Kverndokk,S. & Rosendahl,E., 2000. "CO2 mitigation costs and ancillary benefits in the Nordic countries, the UK and Ireland : a survey," Memorandum 34/2000, Oslo University, Department of Economics.
  21. 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.
  22. Ioannis Pappis & Andreas Sahlberg & Tewodros Walle & Oliver Broad & Elusiyan Eludoyin & Mark Howells & Will Usher, 2021. "Influence of Electrification Pathways in the Electricity Sector of Ethiopia—Policy Implications Linking Spatial Electrification Analysis and Medium to Long-Term Energy Planning," Energies, MDPI, vol. 14(4), pages 1-36, February.
  23. Klinge Jacobsen, Henrik, 1999. "Taxing CO2 and subsidising biomass. Analysed in a macroeconomic and sectoral model," MPRA Paper 43495, University Library of Munich, Germany.
  24. Henrik Klinge Jacobsen, 2000. "Technology Diffusion in Energy-Economy Models: The Case of Danish Vintage Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 43-71.
  25. Seunghun Joh & Yun-Mi Nam & ShangGyoo Shim & Joohon Sung & Youngchul Shin, 2003. "Empirical study of environmental ancillary benefits due to greenhouse gas mitigation in Korea," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 6(3), pages 311-327.
  26. Krook-Riekkola, Anna & Berg, Charlotte & Ahlgren, Erik O. & Söderholm, Patrik, 2017. "Challenges in top-down and bottom-up soft-linking: Lessons from linking a Swedish energy system model with a CGE model," Energy, Elsevier, vol. 141(C), pages 803-817.
  27. Guo, Jinyu & Ma, Jinji & Li, Zhengqiang & Hong, Jin, 2022. "Building a top-down method based on machine learning for evaluating energy intensity at a fine scale," Energy, Elsevier, vol. 255(C).
  28. Wu, Pei-Ing & Chen, Chai Tzu & Liou, Je-Liang, 2013. "The meta-technology cost ratio: An indicator for judging the cost performance of CO2 reduction," Economic Modelling, Elsevier, vol. 35(C), pages 1-9.
  29. Rivers, Nic & Jaccard, Mark, 2006. "Useful models for simulating policies to induce technological change," Energy Policy, Elsevier, vol. 34(15), pages 2038-2047, October.
  30. Mark K. Jaccard & John Nyboer & Crhis Bataille & Bryn Sadownik, 2003. "Modeling the Cost of Climate Policy: Distinguishing Between Alternative Cost Definitions and Long-Run Cost Dynamics," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 49-73.
  31. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
  32. Jaccard, Mark & Murphy, Rose & Rivers, Nic, 2004. "Energy-environment policy modeling of endogenous technological change with personal vehicles: combining top-down and bottom-up methods," Ecological Economics, Elsevier, vol. 51(1-2), pages 31-46, November.
  33. 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.
  34. Theodoridou, Ifigeneia & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "A feasibility evaluation tool for sustainable cities – A case study for Greece," Energy Policy, Elsevier, vol. 44(C), pages 207-216.
  35. 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.
  36. Graham, Paul W. & Williams, David J., 2003. "Optimal technological choices in meeting Australian energy policy goals," Energy Economics, Elsevier, vol. 25(6), pages 691-712, November.
  37. Horne, Matt & Jaccard, Mark & Tiedemann, Ken, 2005. "Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions," Energy Economics, Elsevier, vol. 27(1), pages 59-77, January.
  38. Ignaciuk, Adriana M. & Dellink, Rob B., 2006. "Biomass and multi-product crops for agricultural and energy production--an AGE analysis," Energy Economics, Elsevier, vol. 28(3), pages 308-325, May.
  39. da Silva, Felipe L.C. & Cyrino Oliveira, Fernando L. & Souza, Reinaldo C., 2019. "A bottom-up bayesian extension for long term electricity consumption forecasting," Energy, Elsevier, vol. 167(C), pages 198-210.
  40. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
  41. Wu, Pei-Ing & Chen, Chai Tzu & Cheng, Pei-Ching & Liou, Je-Liang, 2014. "Climate game analyses for CO2 emission trading among various world organizations," Economic Modelling, Elsevier, vol. 36(C), pages 441-446.
  42. 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.
  43. Cao, Jing & Ho, Mun & Jorgenson, Dale, 2008. "“Co-benefits†of Greenhouse Gas Mitigation Policies in China: An Integrated Top-Down and Bottom-Up Modeling Analysis," RFF Working Paper Series dp-08-10-efd, Resources for the Future.
  44. 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.
  45. Murphy, Rose & Jaccard, Mark, 2011. "Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US," Energy Policy, Elsevier, vol. 39(11), pages 7146-7155.
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