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Investigating Determining Factors Affecting the Waste Collection Rate From Electrical and Electronic Equipment

Author

Listed:
  • Radu Ciobanu

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Drago? Huru

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • George ?tefan

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Margareta Florescu

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Danut Mihai

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Florin Dobre

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

Using a data sample from all 27 EU Member States from 2009-2020, the present study quantifies the factors that can lead to an increase in the collection rate of waste from electrical and electronic equipment (EEE). The results underline the fact that an increase in the quality of road infrastructure and an aggressive online campaign can lead to an obvious increase in the amount of electrical and electronic equipment used. Quantile regression forecasts show that the impact of some variables such as GDP per capita, private consumption, government effectiveness, or research and development expenses has asymmetric effects on the degree of collection but can lead to an improvement of this activity under certain conditions.

Suggested Citation

  • Radu Ciobanu & Drago? Huru & George ?tefan & Margareta Florescu & Danut Mihai & Florin Dobre, 2023. "Investigating Determining Factors Affecting the Waste Collection Rate From Electrical and Electronic Equipment," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(62), pages 134-134, February.
    • Handle: RePEc:aes:amfeco:v:25:y:2023:i:62:p:134
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    References listed on IDEAS

    as
    1. Radu Ciobanu & Claudia-Elena Țuclea & Luciana-Floriana Holostencu & Diana-Maria Vrânceanu, 2022. "Decision-Making Factors in the Purchase of Ecologic Products," Sustainability, MDPI, vol. 14(15), pages 1-26, August.
    2. Bouzon, Marina & Govindan, Kannan & Rodriguez, Carlos M.Taboada & Campos, Lucila M.S., 2016. "Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 182-197.
    3. Guzzo, Daniel & Rodrigues, Vinicius Picanço & Mascarenhas, Janaina, 2021. "A systems representation of the Circular Economy: Transition scenarios in the electrical and electronic equipment (EEE) industry," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    4. Lauridsen, Erik Hagelskjær & Jørgensen, Ulrik, 2010. "Sustainable transition of electronic products through waste policy," Research Policy, Elsevier, vol. 39(4), pages 486-494, May.
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    More about this item

    Keywords

    Circular economy; electrical and electronic equipment; EU 27; quantile regression.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • F64 - International Economics - - Economic Impacts of Globalization - - - Environment

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