IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i18p8202-d1481911.html
   My bibliography  Save this article

Unveiling the Age Factor: The Influence of Cabinet Members’ Age on Waste Electrical and Electronic Equipment Recycling Rates in European Nations

Author

Listed:
  • Erdal Arslan

    (Department of Economics, Faculty of Economics and Administrative Sciences, Selçuk University, Konya 42250, Turkey)

  • Musa Şanal

    (Department of Business Administration, Faculty of Economics and Administrative Sciences, Çukurova University, Adana 01330, Turkey)

  • Cuneyt Koyuncu

    (Department of Economics, Faculty of Economics and Administrative Sciences, Bilecik Seyh Edebali University, Bilecik 11230, Turkey)

  • Rasim Yilmaz

    (Department of Economics, Faculty of Economics and Administrative Sciences, Tekirdag Namik Kemal University, Tekirdag 59030, Turkey)

Abstract

Utilizing panel quantile regression on an unbalanced dataset for 30 European countries from 2008 to 2018, this article seeks to investigate how the age of cabinet members influences e-waste recycling rates in European countries, alongside other relevant factors. Prior research has overlooked the age of cabinet members as a determinant of e-waste recycling. By addressing this gap, this study introduces a novel factor that could impact e-waste recycling rates. Thus, this study provides insights into how the demographic characteristics of parliament members, particularly the age of cabinet members, impact environmental improvement, as indicated by e-waste recycling rates. Estimation results indicate the existence of a nonlinear relationship (i.e., an inverted U-shaped environmental Kuznets curve) between the age of cabinet members and the e-waste recycling rate, rather than a linear relationship. The calculated average turning point age is 49.087, indicating that the e-waste recycling rate increases as the age of cabinet members rises until reaching 49.087, after which the e-waste recycling rate declines. Overall, this study underscores the importance of the demographic characteristics of parliament members, particularly the age of cabinet members, in shaping e-waste recycling policies and environmental sustainability efforts. It emphasizes that the age of cabinet members and generational perspectives can influence their awareness, understanding, and commitment to addressing contemporary challenges such as e-waste.

Suggested Citation

  • Erdal Arslan & Musa Şanal & Cuneyt Koyuncu & Rasim Yilmaz, 2024. "Unveiling the Age Factor: The Influence of Cabinet Members’ Age on Waste Electrical and Electronic Equipment Recycling Rates in European Nations," Sustainability, MDPI, vol. 16(18), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8202-:d:1481911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/18/8202/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/18/8202/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diana Hummel & Alexandra Lux, 2007. "Population decline and infrastructure: The case of the German water supply system," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 5(1), pages 167-191.
    2. Bilal Boubellouta & Sigrid Kusch-Brandt, 2023. "Driving factors of e-waste recycling rate in 30 European countries: new evidence using a panel quantile regression of the EKC hypothesis coupled with the STIRPAT model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7533-7560, August.
    3. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    4. Zhang, Bin & Du, Zhanjie & Wang, Bo & Wang, Zhaohua, 2019. "Motivation and challenges for e-commerce in e-waste recycling under “Big data” context: A perspective from household willingness in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 436-444.
    5. Pablo-Romero, María P. & Sánchez-Braza, Antonio & Gil-Pérez, Jesús, 2023. "Is deforestation needed for growth? Testing the EKC hypothesis for Latin America," Forest Policy and Economics, Elsevier, vol. 148(C).
    6. Cerqueira, Pedro A. & Soukiazis, Elias, 2022. "Socio-economic and political factors affecting the rate of recycling in Portuguese municipalities," Economic Modelling, Elsevier, vol. 108(C).
    7. Chen, Wenhui & Lei, Yalin, 2018. "The impacts of renewable energy and technological innovation on environment-energy-growth nexus: New evidence from a panel quantile regression," Renewable Energy, Elsevier, vol. 123(C), pages 1-14.
    8. Rasim Yilmaz & Cuneyt Koyuncu, 2023. "The Impact of Globalization on the Rate of E-waste Recycling: Evidence From European Countries," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(62), pages 180-180, February.
    9. Xu, Bin & Lin, Boqiang, 2020. "Investigating drivers of CO2 emission in China’s heavy industry: A quantile regression analysis," Energy, Elsevier, vol. 206(C).
    10. Cadoret, Isabelle & Padovano, Fabio, 2016. "The political drivers of renewable energies policies," Energy Economics, Elsevier, vol. 56(C), pages 261-269.
    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. Neves, Sónia Almeida & Marques, António Cardoso & Silva, Inês Patrício, 2024. "Promoting the circular economy in the EU: How can the recycling of e-waste be increased?," Structural Change and Economic Dynamics, Elsevier, vol. 70(C), pages 192-201.
    2. Bilal Boubellouta & Sigrid Kusch-Brandt, 2023. "Driving factors of e-waste recycling rate in 30 European countries: new evidence using a panel quantile regression of the EKC hypothesis coupled with the STIRPAT model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7533-7560, August.
    3. Erdal Arslan & Cuneyt Koyuncu & Rasim Yilmaz, 2023. "The Influence of Government Ideology on Renewable Energy Consumption in the European Union Countries," Sustainability, MDPI, vol. 15(20), pages 1-18, October.
    4. Zheng, Shuhong & Yang, Juan & Yu, Shiwei, 2021. "How renewable energy technological innovation promotes renewable power generation: Evidence from China's provincial panel data," Renewable Energy, Elsevier, vol. 177(C), pages 1394-1407.
    5. Mohsen Khezri & Mohammad Sharif Karimi & Jamal Mamkhezri & Reza Ghazal & Larry Blank, 2022. "Assessing the Impact of Selected Determinants on Renewable Energy Sources in the Electricity Mix: The Case of ASEAN Countries," Energies, MDPI, vol. 15(13), pages 1-15, June.
    6. Jin, Taeyoung & Kim, Jinsoo, 2018. "What is better for mitigating carbon emissions – Renewable energy or nuclear energy? A panel data analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 464-471.
    7. Hassan, Taimoor & Song, Huaming & Khan, Yasir & Kirikkaleli, Dervis, 2022. "Energy efficiency a source of low carbon energy sources? Evidence from 16 high-income OECD economies," Energy, Elsevier, vol. 243(C).
    8. Canh, Nguyen Phuc & Schinckus, Christophe & Thanh, Su Dinh & Chong, Felicia Hui Ling, 2021. "The determinants of the energy consumption: A shadow economy-based perspective," Energy, Elsevier, vol. 225(C).
    9. Qin, Lu & Aziz, Ghazala & Hussan, Muhammad Wasim & Qadeer, Afifa & Sarwar, Suleman, 2024. "Empirical evidence of fintech and green environment: Using the green finance as a mediating variable," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 33-49.
    10. Qin, Yong & Xu, Zeshui & Wang, Xinxin & Škare, Marinko, 2023. "The effects of financial institutions on the green energy transition: A cross-sectional panel study," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 524-542.
    11. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    12. Mac Clay, Pablo & Börner, Jan & Sellare, Jorge, 2023. "Institutional and macroeconomic stability mediate the effect of auctions on renewable energy capacity," Energy Policy, Elsevier, vol. 180(C).
    13. Djula Borozan, 2023. "Institutions and Environmentally Adjusted Efficiency," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4489-4510, December.
    14. Ren, Siyu & Hao, Yu & Xu, Lu & Wu, Haitao & Ba, Ning, 2021. "Digitalization and energy: How does internet development affect China's energy consumption?," Energy Economics, Elsevier, vol. 98(C).
    15. Ostadzad, Ali Hossein, 2022. "Innovation and carbon emissions: Fixed-effects panel threshold model estimation for renewable energy," Renewable Energy, Elsevier, vol. 198(C), pages 602-617.
    16. Fan, Fei & Dai, Shangze & Yang, Bo & Ke, Haiqian, 2023. "Urban density, directed technological change, and carbon intensity: An empirical study based on Chinese cities," Technology in Society, Elsevier, vol. 72(C).
    17. Faik Bilgili & Daniel Balsalobre-Lorente & Sevda Kuşkaya & Mohammed Alnour & Seyit Önderol & Mohammad Enamul Hoque, 2024. "Are research and development on energy efficiency and energy sources effective in the level of CO2 emissions? Fresh evidence from EU data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 24183-24219, September.
    18. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2009. "Driving Factors of Carbon Dioxide Emissions and the Impact from Kyoto Protocol," Ibero America Institute for Econ. Research (IAI) Discussion Papers 190, Ibero-America Institute for Economic Research.
    19. Juan Antonio Duro & Jordi Teixidó-Figueras & Emilio Padilla, 2017. "The Causal Factors of International Inequality in $$\hbox {CO}_{2}$$ CO 2 Emissions Per Capita: A Regression-Based Inequality Decomposition Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(4), pages 683-700, August.
    20. Lei Gao & Taowu Pei & Jingran Zhang & Yu Tian, 2022. "The “Pollution Halo” Effect of FDI: Evidence from the Chinese Sichuan–Chongqing Urban Agglomeration," IJERPH, MDPI, vol. 19(19), pages 1-17, September.

    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:jsusta:v:16:y:2024:i:18:p:8202-:d:1481911. 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.