Identyfikatory
Warianty tytułu
Determinanty efektywności gospodarowania odpadami komunalnymi w krajach członkowskich Unii Europejskiej
Języki publikacji
Abstrakty
The main purpose of this paper is to assess the municipal solid waste management (MSWM) efficiency of European Union countries and to identify the determinants of this efficiency before and after introducing Directive (EU) 2018/851. The research was conducted for 23 EU Member States in order to analyse the two highest-priority waste treatment methods (material recycling and energy recovery) and the level of greenhouse gases emitted by the waste management sector. The data for 2015-2020 were extracted from the Eurostat database. The period of data was divided into two sub-periods: 2015-2017 (the period before introducing the Directive) and 2018-2020. MSWM efficiency scores were calculated using the DEA method. Later, the Tobit Regression Model (TRM) was applied to identify the determinants. The efficiency analysis showed that the countries which joined the EU before 2000 improved their MSWM efficiency in 2018-2020 compared with 2015-2017. On the other hand, the average efficiency scores of the countries that joined the EU after 2000 decreased. In 2015-2017, the following determinants of MSWM efficiency occurred to be statistically significant: population density, unemployment rate, the number of patents and the tourism intensity index, while in 2018-2020: population density, unemployment rate, Research & Development (R&D) expenditure, higher education proportion and MSW generated. A detailed analysis of these variables showed that the countries that joined the EU after 2000 should first increase their R&D expenditure and support their inhabitants in increasing their educational level.
Celem badania jest ocena efektywności przetwarzania odpadów przez kraje członkowskie Unii Europejskiej oraz identyfikacja determinant tej efektywności przed i po wprowadzeniu w życie Dyrektywy 2018/851. Badanie zaprezento-wane w niniejszym artykule zostało przeprowadzone dla 23 krajów członkowskich Unii Europejskiej z uwzględnieniem dwóch sposobów przetwarzania odpadów uznanych przez Unię za priorytetowe, tj. recyklingu w celu odzysku materiałów i odzysku energii. Przy szacowaniu efektywności uwzględniono również poziom gazów cieplarnianych emitowanych przez sektor gospo-darowania odpadami. Dane statystyczne dotyczyły lat 2015-2020 i pochodziły z bazy danych Eurostat. Okres analizy podzielono na dwa podokresy: 2015-2017 (okres przed wprowadzeniem Dyrektywy) oraz 2018-2020. Do obliczenia współczynników efek-tywności wykorzystano model DEA, natomiast identyfikacji determinant dokonano w oparciu o regresję tobitową. Po wprowa-dzeniu w życie Dyrektywy efektywność przetwarzania odpadów przez kraje włączone do Unii przed 2000 rokiem uległa poprawie, podczas gdy średnia efektywność krajów włączonych po 2000 roku spadła w stosunku do 2015-2017. Determinanty tej efektyw-ności również uległy zmianie. W latach 2015-2017 do istotnych czynników zaliczyć można: gęstość zaludnienia, stopę bezrobo-cia, patenty oraz wskaźnik natężenia turystycznego, natomiast w latach 2018-2020: gęstość zaludnienia, stopę bezrobocia, wydatki badawczo-rozwojowe, wykształcenie wyższe mieszkańców oraz ilość generowanych odpadów komunalnych. Analiza szczegółowa wskaźników pokazała, że kraje włączone do Unii po 2000 roku powinny w pierwszej kolejności skupić się na pod-niesieniu poziomu wydatków badawczo-rozwojowych oraz wspierać mieszkańców w podnoszeniu poziomu wykształcenia.
Czasopismo
Rocznik
Tom
Strony
art. no. 637
Opis fizyczny
Bibliogr. 40 poz., tab., wykr.
Twórcy
autor
- Poznan University of Economics and Business, Niepodległości Avenue 10, 61-875 Poznan, Poland
Bibliografia
- Canty, A., & Ripley, B. (2022, November 22). Package ‘boot’. https://cran.r-project.org/web/packages/boot/boot.pdf
- Charnes, A., Cooper, W. W., & Rhodes, E. (1978), Measuring the efficiency of decision making units. European Journal Operational Research., 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
- Col-Serrano, V., Bolos, V., & Benitez Suarez, R. (2023, May 2). Package ‘deaR’. https://cran.r-project.org/web/packages/deaR/deaR.pdf
- Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to Data Envelopment Analysis and its uses. New York: Springer. https://doi.org/10.1007/0-387-29122-9
- Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on Data Envelopment Analysis. New York: Springer. https://doi.org/10.1007/978-1-4419-6151-8
- Dellnitz, A., Kleine, A., & Rodder, W. (2018). CCR or BCC: what if we are in the wrong model? Journal of Business Economics, 88(3), 831-850. https://doi.org/10.1007/s11573-018-0906-8
- Directive (EU) 2008/98/EC of the European Parliament and of the Council of 19 November 2008 on waste and repealing certain Directives, Pub. L. No. 32008L0098, 312 OJ L (2008). http://data.europa.eu/eli/dir/2008/98/oj
- Directive (EU) 2018/851 of the European Parliament and of the Council of 30 May 2018 amending Directive 2008/98/EC on waste, Pub. L. No. 32018L0851, 150 OJ L (2018). http://data.europa.eu/eli/dir/2018/851/oj
- European Commission. (2018). Report from the Commission to the European Parliament, the Council, the European Economic and Social Committee of the regions on the implementation of EU waste legislation, including the early warning report for Member States at risk of missing the 2020 preparation for re-use/recycling target on municipal waste, Pub. L. No. 52018DC0656. https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX%3A52018DC0656
- European Commission. (2020). Investing in the circular economy – A blueprint for a green recovery. https://data.europa.eu/doi/10.2779/48431
- European Parliament. (2018). Cutting EU greenhouse gas emissions: national targets for 2030. https://www.europarl.europa.eu/news/en/headlines/society/20180208STO97442/cutting-eu-greenhouse-gas-emissions-national-targets-for-2030?&at_campaign=20234-Green&at_medium=Google_Ads&at_platform=Search&at_creation=RSA&at_goal=TR_G&at_audience=greenhouse%20gas%20emissions&at_topic=Greenhouse&at_location=PO&gclid=CjwKCAjw1YCkBhAOEiwA5aN4ATocCi-DfQ-0MEqMhgEpk4hrcDFAN6QahNPBtCGW10Ze3pc-YEGIaRoCzB0QAvD_BwE
- Eurostat. (2023). Database. https://ec.europa.eu/eurostat/web/main/data/database
- Gennitsaris, S., & Sofianopulou, S. (2022). Sustainable Goals as a Guide for Sustainability Evaluation of Wind Turbine Decommissioning Scenarios Applying an Integrated LCA and DEA Approach. Proceedings of the First Australian International Conference on Industrial Engineering and Operations Management, Australia. https://doi.org/10.46254/AU01.20220136
- Guerrini, A., Carvalho, P., Romano, G., Marques, R., & Leardini, C. (2017). Assessing efficiency drivers in municipal solid waste collection services through a non-parametric method. Journal of Cleaner Production, 147, 431-441. https://doi.org/10.1016/j.jclepro.2017.01.079
- Guzik, B. (2009). Podstawowe modele DEA w badaniu efektywności gospodarczej i społecznej. Poznań: Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu. (in Polish).
- Halkos, G., & Petrou, K. N. (2018). Assessment of national waste generation in EU Member States’ efficiency. https://mpra.ub.uni-muenchen.de/84590/1/MPRA_paper_84590.pdf
- Halkos, G., & Papageorgiou, G. (2014). Spatial environmental efficiency indicators in regional waste generation: A nonparametric approach. Journal of Environmental Planning and Management, 59(1), 62–78. https://doi.org/10.1080/09640568.2014.983592
- Kleiber, C., & Zeileis, V. (2024). Package ‘AER’. https://cloud.r-project.org/web/packages/AER/AER.pdf
- Kostrzewska, J. (2011). Interpretacja w modelach tobitowych. Przegląd statystyczny, 58(3-4), 256-280. http://bazekon.icm.edu.pl/bazekon/element/bwmeta1.element.ekon-element-000171212389 (in Polish).
- Lacko, M., & Hajduova, Z. (2018). Determinants of Environmental Efficiency of the EU Countries Using Two-Step DEA Approach. Sustainability, 10(10), 207-217. https://doi.org/10.3390/su10103525
- Lander, J. P. (2018). R dla każdego. Zaawansowane analizy i grafika statystyczna. Warszawa: APN Promise. (in Polish).
- Łozowicka, A., & Lach, B. (2022). CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+. Sustainability, 14(6), 3610. https://doi.org/10.3390/su14063610
- Michels, M., & Musshoff, O. (2022). A tobit regression model for the timing of smartphone adoption in agriculture. Heliyon, 8(11), E11272. https://doi.org/10.1016/j.heliyon.2022.e11272
- Molinos-Senante, M., Maziotis, A., Sala-Garrido, R., & Mocholi-Arce, M. (2023). Factors influencing eco-efficiency of municipal solid waste management in Chile: A double-bootstrap approach. Waste Management & Research, 41(2), 457-466. https://doi.org/10.1177/0734242X221122514
- Moore, A., Nolan, J., & Segal, G. (2003). Putting out the trash: measuring municipal service efficiency in U.S. cities. Urban Affiairs Review, 41(2). https://doi.org/10.2139/ssrn.448860
- Pai, P., Khan, B. M., & Kachwala, T. (2020). Data Envelopment Analysis –Is BCC model better than CCR model? Case of Indian Life Insurance companies. NMIMS Management Review, 38(1), 17-35. https://management-review.nmims.edu/wp-content/uploads/2020/01/MR%201-17-35.pdf
- Rios, A., & Picazo-Tadeo, A. (2021). Evaluating the Efficiency of Municipal Solid Waste Management in China. Ecological Indicators, 123, 107328. https://doi.org/10.1016/j.ecolind.2020.107328
- Sala-Garrido, R., Mocholi-Arce, M., Molinos-Senante, M., & Maziotis, A. (2022). Measuring technical, environmental and eco-efficiency in municipal solid waste management in Chile. International Journal of Sustainable Engineering, 15(1), 71-85. https://doi.org/10.1080/19397038.2022.2053606
- Seiford, L. M., & Zhu, J. (2002). Modelling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142(1), 16-20. https://doi.org/10.1016/S0377-2217(01)00293-4
- Silpa, K., Yao, L., Bhada-Tata, P., & Woerden, F. (2018). What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-1329-0
- Simar, L., & Wilson, P. W. (2007). Estimation and Inference in Two-Stage, Semi-Parametric Models of Production Processes. Journal of Econometrics, 136(1), 31-64. https://doi.org/10.1016/j.jeconom.2005.07.009
- Smol, M., Kulczycka, J., Czaplicka-Kotas, A., & Włóka, D. (2019). Zarządzanie i monitorowanie gospodarki odpadami komunalnymi w Polsce w kontekście realizacji gospodarki o obiegu zamkniętym (GOZ). Zeszyty Naukowe Instytutu Gospodarki Surowcami Mineralnymi i Energią PAN, 108, 165-184. https://doi.org/10.24425/znigsme.2019.130174 (in Polish).
- Storto, C. (2021). Productivity Analysis of Municipal Solid Waste Collection in Italy using SBM DEA Malmquist Index. IOP Conference Series: Earth and Environmental Science, 837, 012002. https://doi.org/10.1088/1755-1315/837/1/012002
- Storto, C. (2021a). Effectiveness-efficiency nexus in municipal solid waste management: A non-parametric evidence-based study. Ecological Indicators, 131, 108185. https://doi.org/10.1016/j.ecolind.2021.108185
- Struk, M. (2014). Municipal Solid Waste Management Attributes and its Efficiency. Proceedings of the 18th International Conference: Current Trends in Public Sector Research, Brno, 336-343. https://www.researchgate.net/publication/308900363_Municipal_Solid_Waste_Management_and_its_Efficiency
- The World Bank. (2022, February 11). Global Waste to Grow by 70 Percent by 2050 Unless Urgent Action is Taken: World Bank Report. https://www.worldbank.org/en/topic/urbandevelopment/brief/solid-waste-management
- Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. https://doi.org/10.2307/1907382
- Valencikova, M., & Fandel, P. (2007). Assessing waste management efficiency in the European Union: A focus on the Slovak Republic. Ecocycles, 9(2), 7-25. https://doi.org/10.19040/ecocycles.v9i2.285
- Yang, Q., Fu, L., Liu, X., & Cheng, M. (2018). Measuring environmental performance in the treatment of municipal solid waste: The case of the European Union-28. International Journal of Environmental Research and Public Health, 15(11), 2448. https://doi.org/10.3390/ijerph15112448
- Zhu, J., & Zhang, R. (2019). Efficiency Evaluation of Industrial Solid Waste Recycling Utilization Based on Improved DEA Model. IOP Conference Series: Earth and Environmental Science, 295(3). https://doi.org/10.1088/1755-1315/295/3/032024
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f2a47ca6-24c8-42a3-a312-5709a9d3a239