Journal of Scientific Papers

ECONOMICS & SOCIOLOGY


© CSR, 2008-2019
ISSN 2071-789X

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    Centre of Sociological Research

     

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Circular economy efficiency in the context of waste management in the selected Central and Eastern European countries – evidence from DEA and fractional regression analysis

Vol. 17, No 3, 2024

Marek Potkány

 

Technical University in Zvolen,

Zvolen, Slovakia

E-mail: potkany@tuzvo.sk

ORCID 0000-0002-7477-6157 

 

Circular economy efficiency in the context of waste management in the selected Central and Eastern European countries – evidence from DEA and fractional regression analysis

 

Nikolay Neykov

 

University of Forestry,

Sofia, Bulgaria

E-mail: nneykov@ltu.bg

ORCID 0000-0002-8602-5254


Justas Streimikis

 

Lithuanian Centre for Social Sciences, Institute of Economics and Rural Development, 

Lithuania

justas.streimikis@gmail.com 

ORCID 0000-0003-2619-3229


Petra Lesníková

 

Technical University in Zvolen,

Zvolen, Slovakia

E-mail: lesnikova@tuzvo.sk

ORCID 0000-0001-9977-0811

 

Abstract. Sustainability and optimizing waste management efficiency through circular economy principles have become significant trends in recent research. This study aims to compare the circular economy efficiency within the waste management framework in selected Central and East European countries. To achieve this, the research employs Data Envelopment Analysis (DEA) and Fractional Regression Analysis, specifically using the Slack-Based Measurement model. This model measures efficiency by referencing the inefficient Decision-Making Units (DMUs) rather than the origin of the coordinate system. Key variables such as GDP per capita, GDP growth rate, and circular economy indicators were selected and analyzed using Eurostat data from 2010 to 2022. The findings reveal varying potentials for improving the efficiency of hazardous and non-hazardous waste management in the countries investigated. Additionally, differences in the mutual influence of selected variable indicators on waste efficiency are identified using Fractional Regression Analysis. These insights emphasize the pivotal role of waste management in advancing circular economy policies. 

 

Received: November, 2023

1st Revision: August, 2024

Accepted: September, 2024

 

DOI: 10.14254/2071-789X.2024/17-3/10

JEL Classification: G39, L69, O14, Q59

Keywords: circular economy, waste management, Data Envelopment Analysis, efficiency score, Fractional Regression Analysis