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The role of economic and policy variables in energy-efficient retrofitting assessment. A stochastic Life Cycle Costing methodology

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  • Baldoni, Edoardo
  • Coderoni, Silvia
  • D'Orazio, Marco
  • Di Giuseppe, Elisa
  • Esposti, Roberto

Abstract

Energy saving is a major policy objective worldwide and in the EU in particular. Evaluating the convenience of energy-efficient investments, however, is complex. This paper aims to apply stochastic Life Cycle Costing to assess the economic value of energy-efficient building retrofitting investments. The proposed approach investigates how macroeconomic variables affect such an evaluation by explicitly taking into account their interdependent stochastic nature. Consequently, the economic evaluation of an investment is itself stochastic thus expressing both its expected value and its inherent uncertainty and risk. On this basis, an illustrative case-study is presented, where alternative designs of the energy-saving intervention are compared and a sensitivity analysis performed to identify the determinants of the LCC outcome and of its variability. In terms of policy implications, a tool providing a sounder evaluation of the convenience of such investments can suggest when and to what extent incentives may be appropriate to facilitate these investments and what possible financial instruments could be put forward in order to reduce the associated risk.

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  • Baldoni, Edoardo & Coderoni, Silvia & D'Orazio, Marco & Di Giuseppe, Elisa & Esposti, Roberto, 2019. "The role of economic and policy variables in energy-efficient retrofitting assessment. A stochastic Life Cycle Costing methodology," Energy Policy, Elsevier, vol. 129(C), pages 1207-1219.
  • Handle: RePEc:eee:enepol:v:129:y:2019:i:c:p:1207-1219
    DOI: 10.1016/j.enpol.2019.03.018
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    Cited by:

    1. Postacchini, Matteo & Di Giuseppe, Elisa & Eusebi, Anna Laura & Pelagalli, Leonardo & Darvini, Giovanna & Cipolletta, Giulia & Fatone, Francesco, 2022. "Energy saving from small-sized urban contexts: Integrated application into the domestic water cycle," Renewable Energy, Elsevier, vol. 199(C), pages 1300-1317.
    2. Junjun Zheng & Mingmiao Yang & Gang Ma & Qian Xu & Yujie He, 2020. "Multi-Agents-Based Modeling and Simulation for Carbon Permits Trading in China: A Regional Development Perspective," IJERPH, MDPI, vol. 17(1), pages 1-20, January.
    3. Edoardo Baldoni & Silvia Coderoni & Elisa Di Giuseppe & Marco D’Orazio & Roberto Esposti & Gianluca Maracchini, 2021. "A Software Tool for a Stochastic Life Cycle Assessment and Costing of Buildings’ Energy Efficiency Measures," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    4. Xiaolin Yang & Zhuoxi Chen & Yukai Zou & Fengdeng Wan, 2023. "Improving the Energy Performance and Economic Benefits of Aged Residential Buildings by Retrofitting in Hot–Humid Regions of China," Energies, MDPI, vol. 16(13), pages 1-21, June.
    5. Cremer, Leo & Weber, Christine, 2022. "Deep energy retrofits: How effective and robust are policy instruments?," Energy Policy, Elsevier, vol. 170(C).
    6. Oleksii Lyulyov & Tetyana Pimonenko & Aleksy Kwilinski & Henryk Dzwigol & Mariola Dzwigol-Barosz & Vladyslav Pavlyk & Piotr Barosz, 2021. "The Impact of the Government Policy on the Energy Efficient Gap: The Evidence from Ukraine," Energies, MDPI, vol. 14(2), pages 1-13, January.
    7. Elisa Di Giuseppe & Marco D’Orazio & Guangli Du & Claudio Favi & Sébastien Lasvaux & Gianluca Maracchini & Pierryves Padey, 2020. "A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings," Sustainability, MDPI, vol. 12(4), pages 1-35, February.
    8. Haonan Zhang, 2023. "Leveraging policy instruments and financial incentives to reduce embodied carbon in energy retrofits," Papers 2304.03403, arXiv.org.
    9. Paulo Afonso & Vishad Vyas & Ana Antunes & Sérgio Silva & Boris P. J. Bret, 2021. "A Stochastic Approach for Product Costing in Manufacturing Processes," Mathematics, MDPI, vol. 9(18), pages 1-23, September.
    10. Boldyryev, Stanislav & Gil, Tatyana & Ilchenko, Mariia, 2022. "Environmental and economic assessment of the efficiency of heat exchanger network retrofit options based on the experience of society and energy price records," Energy, Elsevier, vol. 260(C).
    11. Antonio Artino & Riccardo Caponetto & Gianpiero Evola & Giuseppe Margani & Edoardo Michele Marino & Emanuele Murgano, 2020. "Decision Support System for the Sustainable Seismic and Energy Renovation of Buildings: Methodological Layout," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    12. Dongri Han & Tuochen Li & Shaosong Feng & Ziyi Shi, 2020. "Application of Threshold Regression Analysis to Study the Impact of Clean Energy Development on China’s Carbon Productivity," IJERPH, MDPI, vol. 17(3), pages 1-16, February.

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    More about this item

    Keywords

    LCC; Life cycle costing; VAR; Vector autoregression; Sensitivity analysis; Energy efficiency policy;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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