IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v331y2023ics0306261922014465.html
   My bibliography  Save this article

A nonlinear interactive grey multivariable model based on dynamic compensation for forecasting the economy-energy-environment system

Author

Listed:
  • Ye, Li
  • Dang, Yaoguo
  • Fang, Liping
  • Wang, Junjie

Abstract

Achieving the goals of emissions intensity reduction and energy structure transformation while ensuring stable economic development is essential for sustainable development in China. Establishing a concise and accurate model for predicting the 3E (economy-energy-environment) system is beneficial for decision-makers in developing optimal long-term energy and environmental planning. Although previous studies have concentrated on the interaction of variables in the 3E system, frameworks for prediction have thus far been limited. In this paper, we develop a novel nonlinear interactive grey multivariable model based on dynamic compensation, denoted as DCNIGM1,N, to perform the prediction of the 3E system. More specifically, the proposed model innovatively takes into account nonlinear driving effects to elucidate nonlinear interactive relationships between the system variables. A dynamic compensation mechanism is introduced into the systematic grey modeling for the first time to adapt to a dynamic system. In addition, the Whale Optimization Algorithm (WOA) is employed to determine the optimal nonlinear parameters to improve the forecast accuracy. To evaluate the performance of the DCNIGM1,N model in forecasting the 3E system, two existing grey forecasting models, three statistical approaches, and three machine learning models are selected as the benchmark models. Moreover, two more cases with different variables of the 3E system are applied to verify the feasibility and effectiveness of the proposed model. Experimental results indicate that the DCNIGM1,N model possesses the most excellent performance in all cases, showing the effectiveness and generalizability of the proposed method. The prediction from 2019 to 2020 shows that carbon emissions, total energy consumption, and gross domestic product will grow steadily.

Suggested Citation

  • Ye, Li & Dang, Yaoguo & Fang, Liping & Wang, Junjie, 2023. "A nonlinear interactive grey multivariable model based on dynamic compensation for forecasting the economy-energy-environment system," Applied Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922014465
    DOI: 10.1016/j.apenergy.2022.120189
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922014465
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120189?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, Chiun-Sin & Liou, Fen-May & Huang, Chih-Pin, 2011. "Grey forecasting model for CO2 emissions: A Taiwan study," Applied Energy, Elsevier, vol. 88(11), pages 3816-3820.
    2. Halicioglu, Ferda, 2009. "An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey," Energy Policy, Elsevier, vol. 37(3), pages 1156-1164, March.
    3. Yu, Shiwei & Wei, Yi-ming, 2012. "Prediction of China's coal production-environmental pollution based on a hybrid genetic algorithm-system dynamics model," Energy Policy, Elsevier, vol. 42(C), pages 521-529.
    4. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    5. Oliveira, Carla & Antunes, Carlos Henggeler, 2004. "A multiple objective model to deal with economy-energy-environment interactions," European Journal of Operational Research, Elsevier, vol. 153(2), pages 370-385, March.
    6. Ding, Song & Li, Ruojin & Wu, Shu & Zhou, Weijie, 2021. "Application of a novel structure-adaptative grey model with adjustable time power item for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 298(C).
    7. Kefan Wang & Bangzhu Zhu & Ping Wang & Yi-Ming Wei, 2016. "Examining the links among economic growth, energy consumption, and CO 2 emission with linear and nonlinear causality tests," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 1147-1159, March.
    8. al Irsyad, M. Indra & Halog, Anthony & Nepal, Rabindra, 2018. "Estimating the impacts of financing support policies towards photovoltaic market in Indonesia: A social-energy-economy-environment (SE3) model simulation," Working Papers 2018-09, University of Tasmania, Tasmanian School of Business and Economics.
    9. Ang, James B., 2007. "CO2 emissions, energy consumption, and output in France," Energy Policy, Elsevier, vol. 35(10), pages 4772-4778, October.
    10. Omri, Anis, 2013. "CO2 emissions, energy consumption and economic growth nexus in MENA countries: Evidence from simultaneous equations models," Energy Economics, Elsevier, vol. 40(C), pages 657-664.
    11. Ahmad, Najid & Du, Liangsheng & Lu, Jiye & Wang, Jianlin & Li, Hong-Zhou & Hashmi, Muhammad Zaffar, 2017. "Modelling the CO2 emissions and economic growth in Croatia: Is there any environmental Kuznets curve?," Energy, Elsevier, vol. 123(C), pages 164-172.
    12. Wang, Zheng-Xin & Jv, Yue-Qi, 2021. "A non-linear systematic grey model for forecasting the industrial economy-energy-environment system," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    13. Lv, J. & Li, Y.P. & Huang, G.H. & Ding, Y.K. & Li, X. & Li, Y., 2022. "Planning energy economy and eco-environment nexus system under uncertainty: A copula-based stochastic multi-level programming method," Applied Energy, Elsevier, vol. 312(C).
    14. Wolde-Rufael, Yemane, 2004. "Disaggregated industrial energy consumption and GDP: the case of Shanghai, 1952-1999," Energy Economics, Elsevier, vol. 26(1), pages 69-75, January.
    15. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sato, João Ricardo, 2015. "On the relationships between CO2 emissions, energy consumption and income: The importance of time variation," Energy Economics, Elsevier, vol. 49(C), pages 629-638.
    16. Wu, Lifeng & Liu, Sifeng & Fang, Zhigeng & Xu, Haiyan, 2015. "Properties of the GM(1,1) with fractional order accumulation," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 287-293.
    17. Dehghan Shabani, Zahra & Shahnazi, Rouhollah, 2019. "Energy consumption, carbon dioxide emissions, information and communications technology, and gross domestic product in Iranian economic sectors: A panel causality analysis," Energy, Elsevier, vol. 169(C), pages 1064-1078.
    18. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    19. Pao, Hsiao-Tien & Chen, Haipeng (Allan) & Li, Yi-Ying, 2015. "Competitive dynamics of energy, environment, and economy in the U.S," Energy, Elsevier, vol. 89(C), pages 449-460.
    20. Bölük, Gülden & Mert, Mehmet, 2015. "The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 587-595.
    21. Dogan, Eyup & Aslan, Alper, 2017. "Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional depen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 239-245.
    22. Ma, Xuejiao & Jiang, Ping & Jiang, Qichuan, 2020. "Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    23. Zhao, Ze & Wang, Jianzhou & Zhao, Jing & Su, Zhongyue, 2012. "Using a Grey model optimized by Differential Evolution algorithm to forecast the per capita annual net income of rural households in China," Omega, Elsevier, vol. 40(5), pages 525-532.
    24. Gorus, Muhammed Sehid & Aydin, Mucahit, 2019. "The relationship between energy consumption, economic growth, and CO2 emission in MENA countries: Causality analysis in the frequency domain," Energy, Elsevier, vol. 168(C), pages 815-822.
    25. Liu, Yaqin & Zhang, Jingchao & Zhu, Zhishuang & Zhao, Guohao, 2019. "Impacts of the 3E (economy, energy and environment) coordinated development on energy mix in China: The multi-objective optimisation perspective," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 56-64.
    26. Mei, H. & Li, Y.P. & Suo, C. & Ma, Y. & Lv, J., 2020. "Analyzing the impact of climate change on energy-economy-carbon nexus system in China," Applied Energy, Elsevier, vol. 262(C).
    27. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    28. Şahin, Utkucan & Ballı, Serkan & Chen, Yan, 2021. "Forecasting seasonal electricity generation in European countries under Covid-19-induced lockdown using fractional grey prediction models and machine learning methods," Applied Energy, Elsevier, vol. 302(C).
    29. Alshehry, Atef Saad & Belloumi, Mounir, 2015. "Energy consumption, carbon dioxide emissions and economic growth: The case of Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 237-247.
    30. Ene, Seval & Öztürk, Nursel, 2017. "Grey modelling based forecasting system for return flow of end-of-life vehicles," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 155-166.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Jie & Wu, Wen-Ze & Liu, Chong & Xie, Wanli & Zhang, Tao, 2024. "An extensive conformable fractional grey model and its application," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    2. An, Yimeng & Dang, Yaoguo & Wang, Junjie & Zhou, Huimin & Mai, Son T., 2024. "Mixed-frequency data Sampling Grey system Model: Forecasting annual CO2 emissions in China with quarterly and monthly economic-energy indicators," Applied Energy, Elsevier, vol. 370(C).
    3. Xia, Lin & Ren, Youyang & Wang, Yuhong & Pan, Yangyang & Fu, Yiyang, 2024. "Forecasting China's renewable energy consumption using a novel dynamic fractional-order discrete grey multi-power model," Renewable Energy, Elsevier, vol. 233(C).
    4. Ke Zhou & Ziji Zhao & Lin Xia & Jinghua Wu, 2024. "Advancing Grey Modeling with a Novel Time-Varying Approach for Predicting Solar Energy Generation in the United States," Sustainability, MDPI, vol. 16(24), pages 1-17, December.
    5. Ding, Song & Cai, Zhijian & Qin, Xinghuan & Shen, Xingao, 2024. "Comparative assessment and policy analysis of forecasting quarterly renewable energy demand: Fresh evidence from an innovative seasonal approach with superior matching algorithms," Applied Energy, Elsevier, vol. 367(C).
    6. Li, Hui & Nie, Weige & Duan, Huiming, 2024. "A Haavelmo grey model based on economic growth and its application to energy industry investments," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    7. Yingyue Li & Hongjun Li & Rui Miao & He Qi & Yi Zhang, 2023. "Energy–Environment–Economy (3E) Analysis of the Performance of Introducing Photovoltaic and Energy Storage Systems into Residential Buildings: A Case Study in Shenzhen, China," Sustainability, MDPI, vol. 15(11), pages 1-25, June.
    8. Yifei Chen & Zhihan Fu, 2023. "Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    9. Yuvaraj Natarajan & Sri Preethaa K. R. & Gitanjali Wadhwa & Young Choi & Zengshun Chen & Dong-Eun Lee & Yirong Mi, 2024. "Enhancing Building Energy Efficiency with IoT-Driven Hybrid Deep Learning Models for Accurate Energy Consumption Prediction," Sustainability, MDPI, vol. 16(5), pages 1-23, February.

    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. Zhihui Lv & Amanda M. Y. Chu & Michael McAleer & Wing-Keung Wong, 2019. "Modelling Economic Growth, Carbon Emissions, and Fossil Fuel Consumption in China: Cointegration and Multivariate Causality," IJERPH, MDPI, vol. 16(21), pages 1-35, October.
    2. Dogan, Eyup & Seker, Fahri, 2016. "Determinants of CO2 emissions in the European Union: The role of renewable and non-renewable energy," Renewable Energy, Elsevier, vol. 94(C), pages 429-439.
    3. Sofien, Tiba & Omri, Anis, 2016. "Literature survey on the relationships between energy variables, environment and economic growth," MPRA Paper 82555, University Library of Munich, Germany, revised 14 Sep 2016.
    4. Acheampong, Alex O., 2018. "Economic growth, CO2 emissions and energy consumption: What causes what and where?," Energy Economics, Elsevier, vol. 74(C), pages 677-692.
    5. Tiba, Sofien & Frikha, Mohamed, 2019. "The controversy of the resource curse and the environment in the SDGs background: The African context," Resources Policy, Elsevier, vol. 62(C), pages 437-452.
    6. Richard Gardiner & Petr Hajek, 2020. "Interactions among energy consumption, CO2, and economic development in European Union countries," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 723-740, July.
    7. Pata, Ugur Korkut, 2018. "The influence of coal and noncarbohydrate energy consumption on CO2 emissions: Revisiting the environmental Kuznets curve hypothesis for Turkey," Energy, Elsevier, vol. 160(C), pages 1115-1123.
    8. Ertugrul, Hasan Murat & Çetin, Murat & Şeker, Fahri & Dogan, Eyüp, 2015. "The impact of trade openness on global carbon dioxide emissions: Evidence from the top ten emitters among developing countries," MPRA Paper 97539, University Library of Munich, Germany, revised 10 Mar 2016.
    9. Wang, Jing & Wan, Guanghua & Wang, Chen, 2019. "Participation in GVCs and CO2 emissions," Energy Economics, Elsevier, vol. 84(C).
    10. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    11. Kais, Saidi & Sami, Hammami, 2016. "An econometric study of the impact of economic growth and energy use on carbon emissions: Panel data evidence from fifty eight countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1101-1110.
    12. Hu, Hui & Xie, Nan & Fang, Debin & Zhang, Xiaoling, 2018. "The role of renewable energy consumption and commercial services trade in carbon dioxide reduction: Evidence from 25 developing countries," Applied Energy, Elsevier, vol. 211(C), pages 1229-1244.
    13. Dogan, Eyup & Seker, Fahri, 2016. "The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1074-1085.
    14. Samargandi, Nahla, 2017. "Sector value addition, technology and CO2 emissions in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 868-877.
    15. Armenia Androniceanu & Irina Georgescu, 2023. "The Impact of CO 2 Emissions and Energy Consumption on Economic Growth: A Panel Data Analysis," Energies, MDPI, vol. 16(3), pages 1-17, January.
    16. Ye, Li & Yang, Deling & Dang, Yaoguo & Wang, Junjie, 2022. "An enhanced multivariable dynamic time-delay discrete grey forecasting model for predicting China's carbon emissions," Energy, Elsevier, vol. 249(C).
    17. Cerdeira Bento, João Paulo, 2014. "The determinants of CO2 emissions: empirical evidence from Italy," MPRA Paper 59166, University Library of Munich, Germany.
    18. Shahbaz, Muhammad & Haouas, Ilham & Hoang, Thi Hong Van, 2019. "Economic growth and environmental degradation in Vietnam: Is the environmental Kuznets curve a complete picture?," Emerging Markets Review, Elsevier, vol. 38(C), pages 197-218.
    19. Jing Gao & Wen Xu & Lei Zhang, 2021. "Tourism, economic growth, and tourism-induced EKC hypothesis: evidence from the Mediterranean region," Empirical Economics, Springer, vol. 60(3), pages 1507-1529, March.
    20. Prapatchon Jariyapan, 2012. "Determination of transport CO2 emission using the General Method of Moments: Empirical evidence from 16 countries," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(2), pages 1-12, June.

    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:eee:appene:v:331:y:2023:i:c:s0306261922014465. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.