IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v114y2019ic49.html
   My bibliography  Save this article

A statistical analysis of the energy effectiveness of building refurbishment

Author

Listed:
  • Barbiero, Tommaso
  • Grillenzoni, Carlo

Abstract

Owing to the rapid urban growth of past decades, the refurbishment of buildings has become a central topic of city development. A key aspect of building renovations deals with energy saving, both for economic and environmental concerns. The present literature mainly focuses on technological solutions for buildings, and the related data are studied with descriptive statistics. Instead, this paper aims to evaluate the energy effectiveness of refurbishment interventions from a global sector viewpoint. This implies building representative datasets, developing a synthetic cost indicator, estimating a proper regression model, evaluating the meaning of results and outline proper support policies. Two relevant case-studies are considered: the first is a published dataset of European service buildings, which contains detailed information on the undertaken interventions. The cost indicator is built by averaging standard costs per square meter; next, a Beta regression model is fitted to the data. This belongs to the class of generalized linear models (GLM) and it is suitable when the dependent variable (the saving rate) has an asymmetrical distribution on the interval [0,1]. The second case study is a survey on the retrofitting decisions of households in an urban area of Venice; the related dataset includes information on the cost of investment, the energy saving, and the comfort improvement. Comfort may be a subjective perception, including physical, psychological and economic wellness; however, it is also a drive for housing renovation and for energy saving itself. Statistical analyses show a significant positive dependence between all variables, confirming the energy saving effectiveness of refurbishment interventions. On the base of these results, proper refurbishment policies, both for public and private actors, are finally proposed.

Suggested Citation

  • Barbiero, Tommaso & Grillenzoni, Carlo, 2019. "A statistical analysis of the energy effectiveness of building refurbishment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
  • Handle: RePEc:eee:rensus:v:114:y:2019:i:c:49
    DOI: 10.1016/j.rser.2019.109297
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032119305052
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2019.109297?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. Mulder, Karel F., 2017. "Strategic competences for concrete action towards sustainability: An oxymoron? Engineering education for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1106-1111.
    2. James W. Hardin & Joseph W. Hilbe, 2012. "Generalized Linear Models and Extensions, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number glmext, March.
    3. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    4. Theodoros Zachariadis & Apostolos Michopoulos & Yannis Vougiouklakis & Katerina Piripitsi & Christodoulos Ellinopoulos & Benjamin Struss, 2018. "Determination of Cost-Effective Energy Efficiency Measures in Buildings with the Aid of Multiple Indices," Energies, MDPI, vol. 11(1), pages 1-20, January.
    5. Cribari-Neto, Francisco & Zeileis, Achim, 2010. "Beta Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i02).
    6. Copiello, Sergio & Grillenzoni, Carlo, 2017. "Is the cold the only reason why we heat our homes? Empirical evidence from spatial series data," Applied Energy, Elsevier, vol. 193(C), pages 491-506.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salvia, Monica & Simoes, Sofia G. & Herrando, María & Čavar, Marko & Cosmi, Carmelina & Pietrapertosa, Filomena & Gouveia, João Pedro & Fueyo, Norberto & Gómez, Antonio & Papadopoulou, Kiki & Taxeri, , 2021. "Improving policy making and strategic planning competencies of public authorities in the energy management of municipal public buildings: The PrioritEE toolbox and its application in five mediterranea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Alexandros Amprazis & Nikolaos Galanis & Georgios Malandrakis & Georgios Panaras & Penelope Papadopoulou & Alessandro Galli, 2023. "The Ecological Footprint of Greek Citizens: Main Drivers of Consumption and Influencing Factors," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
    3. Raniero Sannino, 2023. "Thermal Loads Map and Overall Energy Analysis Depending on Low-Effort Parameters Change: A Commercial Building Case Study," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    4. Marvuglia, Antonino & Havinga, Lisanne & Heidrich, Oliver & Fonseca, Jimeno & Gaitani, Niki & Reckien, Diana, 2020. "Advances and challenges in assessing urban sustainability: an advanced bibliometric review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    5. Miguel Macias Sequeira & João Pedro Gouveia, 2022. "A Sequential Multi-Staged Approach for Developing Digital One-Stop Shops to Support Energy Renovations of Residential Buildings," Energies, MDPI, vol. 15(15), pages 1-27, July.
    6. Joana Fernandes & Maria Catarina Santos & Rui Castro, 2021. "Introductory Review of Energy Efficiency in Buildings Retrofits," Energies, MDPI, vol. 14(23), pages 1-18, December.

    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. Paulus, Anne & Hagemann, Nina & Baaken, Marieke C. & Roilo, Stephanie & Alarcón-Segura, Viviana & Cord, Anna F. & Beckmann, Michael, 2022. "Landscape context and farm characteristics are key to farmers' adoption of agri-environmental schemes," Land Use Policy, Elsevier, vol. 121(C).
    2. Ameztegui, Aitor & Coll, Lluís & Messier, Christian, 2015. "Modelling the effect of climate-induced changes in recruitment and juvenile growth on mixed-forest dynamics: The case of montane–subalpine Pyrenean ecotones," Ecological Modelling, Elsevier, vol. 313(C), pages 84-93.
    3. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
    4. Jillian M Rung & Leonard H Epstein, 2020. "Translating episodic future thinking manipulations for clinical use: Development of a clinical control," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.
    5. Zhang, Dengjun & Xie, Yifan, 2022. "Customer environmental concerns and profit margin: Evidence from manufacturing firms," Journal of Economics and Business, Elsevier, vol. 120(C).
    6. Buntaine, Mark T., 2011. "Does the Asian Development Bank Respond to Past Environmental Performance when Allocating Environmentally Risky Financing?," World Development, Elsevier, vol. 39(3), pages 336-350, March.
    7. Yukako Sado-Inamura & Kensuke Fukushi, 2018. "Considering Water Quality of Urban Rivers from the Perspectives of Unpleasant Odor," Sustainability, MDPI, vol. 10(3), pages 1-14, February.
    8. Li-Chu Chien, 2013. "Multiple deletion diagnostics in beta regression models," Computational Statistics, Springer, vol. 28(4), pages 1639-1661, August.
    9. Dengjun Zhang, 2022. "Capacity utilization under credit constraints: A firm‐level study of Latin American manufacturing," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1367-1386, January.
    10. Jodrá, P. & Jiménez-Gamero, M.D., 2016. "A note on the Log-Lindley distribution," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 189-194.
    11. Abbasiharofteh, Milad & Kriesch, Lukas, 2024. "Not all twins are identical: the digital layer of “twin” transition market applications," Papers in Innovation Studies 2024/16, Lund University, CIRCLE - Centre for Innovation Research.
    12. López Prol, Javier & Zilberman, David, 2023. "No alarms and no surprises: Dynamics of renewable energy curtailment in California," Energy Economics, Elsevier, vol. 126(C).
    13. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(10), pages 1-1.
    14. Frank A. La Sorte & Alison Johnston & Toby R. Ault, 2021. "Global trends in the frequency and duration of temperature extremes," Climatic Change, Springer, vol. 166(1), pages 1-14, May.
    15. Pablo Mitnik & Sunyoung Baek, 2013. "The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation," Statistical Papers, Springer, vol. 54(1), pages 177-192, February.
    16. Tariq Maqsood & Mark Edwards & Ioanna Ioannou & Ioannis Kosmidis & Tiziana Rossetto & Neil Corby, 2016. "Seismic vulnerability functions for Australian buildings by using GEM empirical vulnerability assessment guidelines," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1625-1650, February.
    17. Steven B Kim & Dong Sub Kim & Xiaoming Mo, 2021. "An image segmentation technique with statistical strategies for pesticide efficacy assessment," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-12, March.
    18. Johnson, Caroline A. & Flage, Roger & Guikema, Seth D., 2019. "Characterising the robustness of coupled power-law networks," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    19. Antonio Calcagnì & Luigi Lombardi, 2022. "Modeling random and non-random decision uncertainty in ratings data: a fuzzy beta model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 145-173, March.
    20. Chen, Kee Kuo & Chiu, Rong-Her & Chang, Ching-Ter, 2017. "Using beta regression to explore the relationship between service attributes and likelihood of customer retention for the container shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 1-16.

    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:rensus:v:114:y:2019:i:c:49. 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/600126/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.