IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i4p811-d1335711.html
   My bibliography  Save this article

An Econometric Analysis of the Energy-Saving Performance of the Italian Plastic Manufacturing Sector

Author

Listed:
  • Valeria Costantini

    (Department of Economics, Roma Tre University, 00145 Rome, Italy)

  • Mariagrazia D’Angeli

    (Department of Economics, Roma Tre University, 00145 Rome, Italy)

  • Martina Mancini

    (Department of Economics, Roma Tre University, 00145 Rome, Italy)

  • Chiara Martini

    (Italian National Agency for New Technologies, Environment and Sustainable Economic Development (ENEA), 00196 Rome, Italy)

  • Elena Paglialunga

    (Department of Economics, Roma Tre University, 00145 Rome, Italy)

Abstract

In a scenario characterised by mitigation concerns and calls for greater resilience in the energy sector, energy audits (EAs) emerge as an essential mean for enhancing end-use energy consumption awareness and efficiency. Such a tool allows us to assess the different energy carriers consumed in a productive sector, offering insight into existing energy efficiency improvement opportunities. This opens avenues for research to devise an econometrics-based methodology that encapsulate production sites and their environmental essentials. This paper contributes to the literature by exploiting the EAs received by the Italian National agency for New technologies, Energy, and Sustainable Economic Development (ENEA) in 2019 from the Italian plastics manufacturing sector, matched with Italian firm-based data extracted from the Analisi Informatizzata delle Aziende Italiane (Italian company information and business intelligence) (AIDA) database. In particular, we investigate how the implementation of energy efficiency measures (EEMs) is influenced by a set of contextual factors, as well as features relating to the companies and EEMs themselves. The empirical investigation focuses on the EAs submitted to ENEA in 2019, which was strategically chosen due to its unique data availability and adequacy for extensive analysis. The selection of 2019 is justified as it constitutes the second mandatory reporting period for energy audits, in contrast to the 2022 data, which are currently undergoing detailed refinement. In line with the literature, the adopted empirical approach involves the use of both the OLS and logistic regression models. Empirical results confirm the relevance of economic and financial factors in guiding the decisions surrounding the sector’s energy performance, alongside the analogous influence of the technical characteristics of the measures themselves and of the firms’ strategies. In particular, the OLS model with no fixed effects shows that a one-percent variation in investments is associated with an increase in savings performance equal to 0.63%. As for the OLS model, including fixed effects, the elasticity among the two variables concerned reaches 0.87%, while in the logistic regression, if the investment carried out by the production sites increases, the expected percentage change in the probability that the energy-saving performance is above its average is about 187.77%. Contextual factors that prove to be equally influential include the incentive mechanism considered and the traits of the geographical area in which the companies are located. Relevant policy implications derived from this analysis include the importance of reducing informational barriers about EEMs and increasing technical assistance, which can be crucial for identifying and implementing effective energy solutions.

Suggested Citation

  • Valeria Costantini & Mariagrazia D’Angeli & Martina Mancini & Chiara Martini & Elena Paglialunga, 2024. "An Econometric Analysis of the Energy-Saving Performance of the Italian Plastic Manufacturing Sector," Energies, MDPI, vol. 17(4), pages 1-29, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:811-:d:1335711
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/4/811/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/4/811/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlos Herce & Enrico Biele & Chiara Martini & Marcello Salvio & Claudia Toro, 2021. "Impact of Energy Monitoring and Management Systems on the Implementation and Planning of Energy Performance Improved Actions: An Empirical Analysis Based on Energy Audits in Italy," Energies, MDPI, vol. 14(16), pages 1-21, August.
    2. Zhang, Zhenhua & Zhang, Yunpeng & Zhao, Mingcheng & Muttarak, Raya & Feng, Yanchao, 2023. "What is the global causality among renewable energy consumption, financial development, and public health? New perspective of mineral energy substitution," Resources Policy, Elsevier, vol. 85(PA).
    3. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    4. Kounetas, Kostas & Skuras, Dimitris & Tsekouras, Kostas, 2011. "Promoting energy efficiency policies over the information barrier," Information Economics and Policy, Elsevier, vol. 23(1), pages 72-84, March.
    5. Anderson, Soren T. & Newell, Richard G., 2004. "Information programs for technology adoption: the case of energy-efficiency audits," Resource and Energy Economics, Elsevier, vol. 26(1), pages 27-50, March.
    6. Blass, Vered & Corbett, Charles J. & Delmas, Magali A. & Muthulingam, Suresh, 2014. "Top management and the adoption of energy efficiency practices: Evidence from small and medium-sized manufacturing firms in the US," Energy, Elsevier, vol. 65(C), pages 560-571.
    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. Mette Talseth Solnørdal & Lene Foss, 2018. "Closing the Energy Efficiency Gap—A Systematic Review of Empirical Articles on Drivers to Energy Efficiency in Manufacturing Firms," Energies, MDPI, vol. 11(3), pages 1-30, February.
    2. Jose García-Quevedo & Xavier Massa-Camps, 2019. "Why firms invest (or not) in energy efficiency? A review of the econometric evidence," Working Papers 2019/07, Institut d'Economia de Barcelona (IEB).
    3. Zhao, Bo & Ondrich, Jan & Yinger, John, 2006. "Why do real estate brokers continue to discriminate? Evidence from the 2000 Housing Discrimination Study," Journal of Urban Economics, Elsevier, vol. 59(3), pages 394-419, May.
    4. Trianni, Andrea & Cagno, Enrico & Farné, Stefano, 2016. "Barriers, drivers and decision-making process for industrial energy efficiency: A broad study among manufacturing small and medium-sized enterprises," Applied Energy, Elsevier, vol. 162(C), pages 1537-1551.
    5. Perroni, Marcos G. & Gouvea da Costa, Sergio E. & Pinheiro de Lima, Edson & Vieira da Silva, Wesley, 2017. "The relationship between enterprise efficiency in resource use and energy efficiency practices adoption," International Journal of Production Economics, Elsevier, vol. 190(C), pages 108-119.
    6. Solnørdal, Mette Talseth & Thyholdt, Sverre Braathen, 2019. "Absorptive capacity and energy efficiency in manufacturing firms – An empirical analysis in Norway," Energy Policy, Elsevier, vol. 132(C), pages 978-990.
    7. Barbetta, Gian Paolo & Canino, Paolo & Cima, Stefano, 2015. "The impact of energy audits on energy efficiency investment of public owners. Evidence from Italy," Energy, Elsevier, vol. 93(P1), pages 1199-1209.
    8. Saurabh Bansal & Suresh Muthulingam, 2022. "Can precise numbers boost energy efficiency?," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3264-3287, August.
    9. Cagno, Enrico & Accordini, Davide & Trianni, Andrea & Katic, Mile & Ferrari, Nicolò & Gambaro, Federico, 2022. "Understanding the impacts of energy efficiency measures on a Company’s operational performance: A new framework," Applied Energy, Elsevier, vol. 328(C).
    10. Suvrat Dhanorkar & Enno Siemsen, 2021. "How Nudges Lead to Improved Energy Efficiency in Manufacturing: Evidence from Archival Data and a Field Study," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3735-3757, October.
    11. Suvrat S. Dhanorkar & Enno Siemsen & Kevin W. Linderman, 2018. "Promoting Change from the Outside: Directing Managerial Attention in the Implementation of Environmental Improvements," Management Science, INFORMS, vol. 64(6), pages 2535-2556, June.
    12. Marlene Preiß, 2021. "Treiber und Hemmnisse betrieblicher Effizienzmaßnahmen – Vernetzung als Erfolgsfaktor [Drivers and barriers of operational efficiency measures—networking as a success factor]," Sustainability Nexus Forum, Springer, vol. 29(2), pages 93-106, June.
    13. Meiryani Meiryani & Shi-Ming Huang & A. S. L. Lindawati & Agung Purnomo & Mochammad Fahlevi & Gazali Salim, 2023. "Corporate Energy Management Disclosure : Empirical Evidence from Indonesia Stock Exchange," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 516-525, March.
    14. Basak Kalkanci & Erica L. Plambeck, 2020. "Managing Supplier Social and Environmental Impacts with Voluntary Versus Mandatory Disclosure to Investors," Management Science, INFORMS, vol. 66(8), pages 3311-3328, August.
    15. Choi, Seok Joon & Ondrich, Jan & Yinger, John, 2005. "Do rental agents discriminate against minority customers? Evidence from the 2000 Housing Discrimination Study," Journal of Housing Economics, Elsevier, vol. 14(1), pages 1-26, March.
    16. Ariel Pakes & Jack Porter, 2024. "Moment inequalities for multinomial choice with fixed effects," Quantitative Economics, Econometric Society, vol. 15(1), pages 1-25, January.
    17. Laisney, François & Pohlmeier, Winfried & Staat, Matthias, 1991. "Estimation of labour supply functions using panel data: a survey," ZEW Discussion Papers 91-05, ZEW - Leibniz Centre for European Economic Research.
    18. Apriani Soepardi & Pratikto Pratikto & Purnomo Budi Santoso & Ishardita Pambudi Tama & Patrik Thollander, 2018. "Linking of Barriers to Energy Efficiency Improvement in Indonesia’s Steel Industry," Energies, MDPI, vol. 11(1), pages 1-22, January.
    19. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    20. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.

    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:gam:jeners:v:17:y:2024:i:4:p:811-:d:1335711. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.