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Circular economy indicators – multiple linear regression

Author

Listed:
  • Sterie Cristina Maria

    (University of Economic Studies, Bucharest, Romania, Research Institute of Agriculture and Rural Developement, Romania)

  • Stoica Gabriela Dalila

    (University of Economic Studies, s, Bucharest, Romania, stoicagabriela16@stud.ase.ro, Research Institute of Agriculture and Rural Developement, Romania)

  • Giucă Andreea Daniela

    (University of Economic Studies, Bucharest, Romania, giucaandreea16@stud.ase.ro, Research Institute of Agriculture and Rural Developement, Romania)

  • Potârniche Marilena E.

    (University of Economic Studies, Bucharest, Romania)

Abstract

The aim of this work is to compare EU countries in their efforts to implement the circular economy model and to indicate the EU’s strategic objectives in this area, by analyzing circular economy indicators within the member states. To achieve this, a qualitative and quantitative analysis of the following indicators in THE EUROSTAT database has been carried out: total waste recycling rate, recycling rate of construction and demolition waste, recycling rate of electronic waste, and contribution of recyclable materials to the demand for raw materials in 2019 within the EU. A linear multiple regression was achieved through the SRSS program, which showed that the dependent variable of gross domestic product (GDP) is explained by 69%, and 68% respectively of the recycling rate of construction waste and the recycling rate of electronic waste. The analysis has shown significant correlation between the recycling rate of construction waste and the recycling rate of electronic waste.

Suggested Citation

  • Sterie Cristina Maria & Stoica Gabriela Dalila & Giucă Andreea Daniela & Potârniche Marilena E., 2022. "Circular economy indicators – multiple linear regression," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 437-445, August.
    • Handle: RePEc:vrs:poicbe:v:16:y:2022:i:1:p:437-445:n:50
    DOI: 10.2478/picbe-2022-0043
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