IDEAS home Printed from https://ideas.repec.org/a/cuc/eforum/v14y2023i1p50-61.html

Application of forecasting methods in harmonising strategic planning for sustainable development of the state

Author

Listed:
  • Lesia Korolchuk

Abstract

Successful implementation of the global concept of sustainable development requires harmonising the strategic planning of sustainable development of the state to ensure effective monitoring of the progress of states in achieving the Sustainable Development Goals. The purpose of the research is to actualise the problem of applying forecasting methods in the process of harmonising the strategic planning of the sustainable development of the state and to develop methodological tools for its solution. In the course of the study, based on the application of such methods as: literature review, hypothetical-deductive method, comparison method, empirical method and logical analysis, the expediency is substantiated, methodological tools are developed and the method of triple exponential Holt-Winters smoothing based on a long time series is tested using the Forecast Sheet in Microsoft Excel 2016. Within the framework of a harmonised approach to strategic planning for sustainable development, to assess the country’s progress in sustainable development, the indicators of decoupling of environmental pressure from economic growth are used, as they are simple, measurable and flexible. Based on the Tapio’s methodology, a norm of non-renewable resource decoupling and environmental impact decoupling indicators is determined as a benchmark for the development and analysis of the effectiveness of the national sustainable development strategy, and a forecast of the dynamics of these indicators in the EU as a whole until 2026 is made, as a leader in the greening of the economy. The findings allowed us to identify the main trends in the EU’s sustainable development, basing on the classification of the decoupling status. The results obtained contribute to the harmonisation of national strategies to ensure the successful implementation of the global concept of sustainable development, can be used at such a stage of strategic planning as the formation of a goal tree, which makes it possible to set both attainable and relevant goals, as well as in assessing the effectiveness of strategies in achieving the Sustainable Development Goals

Suggested Citation

  • Lesia Korolchuk, 2023. "Application of forecasting methods in harmonising strategic planning for sustainable development of the state," E-Forum Working Papers, Economic Forum, vol. 14(1), pages 50-61, December.
  • Handle: RePEc:cuc:eforum:v:14:y:2023:i:1:p:50-61
    DOI: https://doi.org/10.62763/cb/1.2024.50
    as

    Download full text from publisher

    File URL: https://e-forum.com.ua/web/uploads/pdf/EF_14_1_2024_130978_11-09-2024_09-36-50-61.pdf
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.62763/cb/1.2024.50?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Alejandra Boto-Álvarez & Roberto García-Fernández, 2020. "Implementation of the 2030 Agenda Sustainable Development Goals in Spain," Sustainability, MDPI, vol. 12(6), pages 1-31, March.
    3. Kimia Chenary & Omid Pirian Kalat & Ayyoob Sharifi, 2024. "Forecasting sustainable development goals scores by 2030 using machine learning models," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(6), pages 6520-6538, December.
    4. McArthur, John W. & Rasmussen, Krista, 2019. "Classifying Sustainable Development Goal trajectories: A country-level methodology for identifying which issues and people are getting left behind," World Development, Elsevier, vol. 123(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    2. Bryan Cheng-Yu Hsu & Yu-Feng Wu & Hsin-Wei Chen & Man-Lai Cheung, 2020. "How Sport Tourism Event Image Fit Enhances Residents’ Perceptions of Place Image and Their Quality of Life," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    3. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    4. Dominik Paprotny, 2021. "Convergence Between Developed and Developing Countries: A Centennial Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 193-225, January.
    5. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    6. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    7. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    8. Singhal, Shakshi & Bano, Yasmeen & Singh, Ompal, 2025. "Investigating the role of customer's disadoption and dynamic shifts in mobile cellular diffusion: Evidence from emerging economies," Technological Forecasting and Social Change, Elsevier, vol. 219(C).
    9. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org, revised May 2025.
    10. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    11. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    12. Divya Aggarwal & Sougata Banerjee, 2025. "Forecasting of S&P 500 ESG Index by Using CEEMDAN and LSTM Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 339-355, March.
    13. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    14. Safdar, Muhammad & Zhong, Ming & Ren, Zhi & Li, Linfeng & Raza, Asif & Hunt, John Douglas, 2026. "An integrated spatial economic modeling framework for forecasting inland waterway freight demand," Transport Policy, Elsevier, vol. 176(C).
    15. Abdelfatah, Omar Sharafeldin Mohamed, 2026. "Machine Learning Approaches for Improving Demand Forecasting Accuracy in Retail Supply Chains," SocArXiv 4z9be_v1, Center for Open Science.
    16. Filipe R. Ramos & Luisa M. Martinez & Luis F. Martinez & Ricardo Abreu & Lihki Rubio, 2025. "Mapping e-commerce trends in the USA: a time series and deep learning approach," Journal of Marketing Analytics, Palgrave Macmillan, vol. 13(3), pages 606-634, September.
    17. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    18. Marco Zanotti, 2025. "Do global forecasting models require frequent retraining?," Working Papers 551, University of Milano-Bicocca, Department of Economics.
    19. Minghao Ran & Yingchao Wang & Qilu Qin & Jindi Huang & Jiading Jiang, 2025. "An Improved Grey Prediction Model Integrating Periodic Decomposition and Aggregation for Renewable Energy Forecasting: Case Studies of Solar and Wind Power," Sustainability, MDPI, vol. 17(11), pages 1-31, May.
    20. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cuc:eforum:v:14:y:2023:i:1:p:50-61. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Economic Forum (email available below). General contact details of provider: https://e-forum.com.ua/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.