Circular economy indicators – multiple linear regression-Reference-Cited by-同舟云学术

Circular economy indicators – multiple linear regression

Published:2022-08-01 Issue:1 Volume:16 Page:437-445
ISSN:2558-9652
Container-title:Proceedings of the International Conference on Business Excellence
language:en
Short-container-title:

Author:

Sterie Cristina Maria¹,Stoica Gabriela Dalila²,Giucă Andreea Daniela³,Potârniche Marilena E.⁴

Affiliation:

1. University of Economic Studies , Bucharest, Romania , Research Institute of Agriculture and Rural Developement , Romania

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

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

4. University of Economic Studies , Bucharest , Romania

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.sciendo.com/pdf/10.2478/picbe-2022-0043

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