Assessing the current and future efficiency of OECD countries in municipal solid waste management
Abstract views: 177
/ 
PDF downloads: 59
Keywords:
Municipal Solid Waste, OECD, forecasts, wavelet analysis, Burg modelAbstract
The purpose of this paper is to assess the current and future efficiency of OECD countries in managing municipal solid waste. The methodology is twofold. To assess the current efficiency, the authors develop a ratio of municipal solid waste to GDP, assuming that producing more of goods and services, measured with GDP, means producing more municipal solid waste. Based on this ratio, results show that Turkey was the least efficient manager in municipal solid waste in 2020, followed by Colombia, Mexico, Chile and Greece. Norway was the most efficient manager in municipal solid waste in 2020 with the lowest ratio, followed by Luxembourg, Ireland, Switzerland, and Sweden. To assess future efficiency of OECD countries in managing municipal solid waste, 2100 projections of municipal solid waste are obtained by forecasting with wavelet analysis historical time series gathered by OECD from 35 countries excluding Australia, Canada, and Costa Rica for lack of data.
References
Burg, JP. (1975). Maximum Entropy Spectral Analysis. Retrieved from http://sepwww.stanford.edu/theses/sep06/
Chen, D.M.C., Bodirsky, B.L., Krueger, T., Mishra, A., Popp, A. (2020). The world's growing municipal solid waste: trends and impacts. Environmental Research Letters, 15, 074021, DOI 10.1088/1748-9326/ab8659
Retrieved from https://iopscience.iop.org/article/10.1088/1748-9326/ab8659
Kaza, S., Yao, L. Bhada-Tata, P., and Van Woerden, F. (2018). What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050. The World Bank. Retrieved from https://datatopics.worldbank.org/what-a-waste/
Kolekar, K.A., Hazra, T., Chakrabarty, S.N. (2016). A Review on Prediction of Municipal Solid Waste Generation Models, Procedia Environmental Sciences, 35, 238-244, ISSN 1878-0296, https://doi.org/10.1016/j.proenv.2016.07.087.
Retrieved from https://www.sciencedirect.com/science/article/pii/S1878029616301761
OECD (2023a). Who we are. Retrieved from Oecd.org/about/
OECD (2023b). Time series of Municipal waste generated in Tonnes, Thousands. Retrieved from https://stats.oecd.org/index.aspx?DataSetCode=MUNW
Renaud, O., Starck, J.L., & Murtagh, F. (2002). Wavelet-based Forecasting Short and Long Memory Time Series. Cahiers du departement d’econometrie, Universite de Geneve, 4.
Rostan, P., Belhachemi, R., & Rostan, A. (2015). Appraising the financial sustainability of a pension system with signal processing. Studies of Applied Economics, 33(3), 1-16. doi: http://dx.doi.org/10.25115/eea.v33i3.3134 Retrieved from http://ojs.ual.es/ojs/index.php/eea/article/view/3134
Rostan, P., Belhachemi, R., & Racicot, F.E. (2017). Forecasting the yield curve with the Burg model. Journal of Forecasting, 36(1), 91-99. doi: 10.1002/for.2416 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2416
Rostan, P., & Rostan, A. (2017). Population Projections and Pension System Sustainability. Saarbrücken: Lambert Academic Publishing. ISBN 978-620-2-06479-8 Retrieved from https://www.morebooks.de/gb/search?utf8=%E2%9C%93&q=978-620-2-06479-8
Rostan, P., & Rostan, A. (2018a). The versatility of spectrum analysis for forecasting financial time series. The Journal of Forecasting, 37(3), 327-339. doi: https://doi.org/10.1002/for.2504
Rostan, P., & Rostan, A. (2018b). Will Saudi Arabia Get Older? Will its pension system be sustainable? Spectral Answers. PSU Research Review, 2(3), 189-205. doi: https://doi.org/10.1108/PRR-12-2017-0045 Retrieved from https://www.emeraldinsight.com/doi/full/10.1108/PRR-12-2017-0045 .
Rostan, P., & Rostan, A. (2018c). Forecasting Spanish and Euro Area GDPs with Spectral Analysis. Estudios De Economía Aplicada, 36(1), 217-234. Retrieved from https://dialnet.unirioja.es/servlet/articulo?codigo=6283924
Rostan, P., & Rostan, A. (2018d). Where is Greek’s Economy Heading? International Journal of Management and Applied Science (IJMAS), 4(3), 28-31. Retrieved from http://ijmas.iraj.in/paper_detail.php?paper_id=11490&name=Where_is_Greece%E2%80%99s_Economy_Heading?_A_Spectral_Perspective
Rostan, P., & Rostan, A. (2019). When will European Muslim Population be majority and in which country. PSU Research Review, 3(2). doi: https://doi.org/10.1108/PRR-12-2018-0034 Retrieved from https://www.emerald.com/insight/content/doi/10.1108/PRR-12-2018-0034/full/html
Rostan, P., & Rostan, A. (2020). Where is Austria’s Economy Heading? Economic and Business Review, 22(1), 105-130. doi: https://doi.org/10.15458/ebr97. Retrieved from https://www.ebrjournal.net/uploads/ebr/public/document/13-ebr_221_d_rostan_barvni_en.pdf
Rostan, P., & Rostan, A. (2021a). Where is Saudi Arabia’s Economy Heading? International Journal of Emerging Markets, 16(8), 2009-2033. doi: https://doi.org/10.1108/IJOEM-08-2018-0447). Retrieved from https://www.emerald.com/insight/content/doi/10.1108/IJOEM-08-2018-0447/full/html
Rostan, P., & Rostan, A. (2021b). Where are fossil fuels prices heading? International Journal of Energy Sector Management, 15(2), 309-327. doi: https://doi.org/10.1108/IJESM-07-2019-0009. Retrieved from https://www.emerald.com/insight/content/doi/10.1108/IJESM-07-2019-0009/full/html
Rostan, P., & Rostan, A. (2022a). 2050 Projections of the Persian Gulf Economies. Iranian Economic Review, 26(2), 269-288. doi: 10.22059/ier.2022.88164. Retrieved from https://ier.ut.ac.ir/article_88164.html
Rostan, P., & Rostan, A. (2022b). Assessing the Resilience of Turkey’s Economy during the Covid-19 Pandemic with its 2050 Projections. Journal of Emerging Economies & Policy, 7(2), 38-49. Retrieved from https://dergipark.org.tr/en/download/article-file/2595010
Rostan, P., & Rostan, A. (2022c). Assessing The Resilience of UK’s Economy After the Covid-19 Pandemic and Brexit. Online Journal Modelling the New Europe, 40, 47-77. doi: 10.24193/OJMNE.2022.40.03. Retrieved from http://neweurope.centre.ubbcluj.ro/wp-content/uploads/2022/12/3.pdf
Rostan, P., & Rostan, A. (2023a). How Australia’s economy gained momentum because of Covid-19. Australian Economic Papers, doi: https://doi.org/10.1111/1467-8454.12308. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-8454.12308
Rostan, P., & Rostan, A. (2023b). How South Korea’s economy gained momentum because of Covid-19, Studies of Applied Economics, 41(2). doi: 10.25115/sae.v41i2.9096, Retrieved from https://ojs.ual.es/ojs/index.php/eea/article/view/9096
Rostan, P., & Rostan, A. (2023c). The Benefit of the Covid-19 Pandemic on Global Temperature Projections, Journal of Forecasting, DOI: https://doi.org/10.1002/for.3011, Retrieved from https://onlinelibrary.wiley.com/doi/10.1002/for.3011
Rostan, P., & Rostan, A. (2023d). How Brazil’s, Mexico’s and Argentina’s economies coped with the Covid-19 pandemic, Studies of Applied Economics, article in press.
Rostan, P., & Rostan A. (2023e). How Cyprus’ Economy Coped With The Covid-19 Pandemic, Online Journal Modelling The New Europe, vol. 42, pp. 109-137, September 2023, DOI: 10.24193/OJMNE.2023.42.06 Retrieved from http://neweurope.centre.ubbcluj.ro/wp-content/uploads/2023/09/06-rostan.pdf
Rostan, P., Rostan, A., & Nurunnabi, M. (2023a). Forewarned is forearmed: Forecasting expansions and contractions of the Saudi economy. Journal of Emerging Economies & Policy, 8 (1), 178-190, Retrieved from https://dergipark.org.tr/tr/download/article-file/3051860
Rostan, P., Rostan, A. & Wall, J. (2023b). Measuring the resilience to the Covid-19 pandemic of Eurozone Economies with their 2050 forecasts, Computational Economics, DOI: 10.1007/s10614-023-10425-z, article in press
Sanjrani, M. A., PirBux, M., Bux, B. K., Bhutto, S. H., & Shaikh, R. (2023). Impact of Plastic waste on the environment and humans health in Pakistan: Effective Waste Management Strategies and sustainable solutions. Journal of Recycling Economy & Sustainability Policy, 2(1), 34–41. Retrieved from https://respjournal.com/index.php/pub/article/view/18
Stoica, P., & Moses, R. (2005). Spectral Analysis of Signals. Upper Saddle River, NJ: Prentice Hall.
Teshome, Y.M., Habtu, N.G., Molla, M.B, Ulsido, M.D. (2023). Municipal solid wastes quantification and model forecasting. Global Journal of Environmental Science and Management, 9(2), 227-240, DOI: 10.22034/gjesm.2023.02.04, Retrieved from https://www.gjesm.net/article_254253_c7e9eddd4ebdadfdd1a4a1f323f374d9.pdf
US EPA (2023). US Environmental Protection Agency. Municipal Solid Waste. Retrieved from https://archive.epa.gov/epawaste/nonhaz/municipal/web/html/
Valens, C. (1999). A Really Friendly Guide to Wavelets. Retrieved from http://agl.cs.unm.edu/~williams/cs530/arfgtw.pdf
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Journal of Recycling Economy & Sustainability Policy
This work is licensed under a Creative Commons Attribution 4.0 International License.
