IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v12y2024i7p160-d1421890.html
   My bibliography  Save this article

Data Envelopment Analysis-Based Approach to Improving of the Budget Allocation System for Decarbonization Targets

Author

Listed:
  • Svetlana V. Ratner

    (Department of Economic and Mathematical Modelling, Peoples’ Friendship University of Russia, 6 Miklukho-Maklaya St., 117198 Moscow, Russia
    Economic Dynamics and Innovation Management Laboratory, V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, 65 Profsoyuznaya St., 117997 Moscow, Russia
    College of Information Technologies and Computer Sciences, National University of Science and Technology “MISIS”, 4 Leninsky Ave., Bldg. 1, 119049 Moscow, Russia)

  • Andrey V. Lychev

    (College of Information Technologies and Computer Sciences, National University of Science and Technology “MISIS”, 4 Leninsky Ave., Bldg. 1, 119049 Moscow, Russia)

  • Vladimir E. Krivonozhko

    (College of Information Technologies and Computer Sciences, National University of Science and Technology “MISIS”, 4 Leninsky Ave., Bldg. 1, 119049 Moscow, Russia)

Abstract

Energy innovation plays an important role in the transition to a zero-carbon economy. Governments in IEA member countries are investing in the R&D, demonstration, and deployment of new energy technologies as part of their energy and climate policies. However, government subsidies for energy innovation are not always efficient in achieving climate policy goals. This paper proposes a two-stage Data Envelopment Analysis model with shared inputs to determine the optimal allocation of public funds for the energy innovation process. The innovation process is divided into two stages: the R&D stage and the commercialization stage. The inputs to the model (budget expenditures for energy innovations) are distributed between the first and second stages. As intermediate products, we use the number of patents in clean energy and hydrocarbon energy. The outputs of the model are the changes in carbon intensity and energy efficiency. This model can be used to assess the effectiveness of government spending on energy innovation. The results show that some IEA member countries should allocate a large part of the fossil fuel technology budget (more than 70%) to the research and development phase. The proposed model can support decision making at the international level to increase the effectiveness of public policies in achieving decarbonization and energy efficiency goals.

Suggested Citation

  • Svetlana V. Ratner & Andrey V. Lychev & Vladimir E. Krivonozhko, 2024. "Data Envelopment Analysis-Based Approach to Improving of the Budget Allocation System for Decarbonization Targets," Economies, MDPI, vol. 12(7), pages 1-16, June.
  • Handle: RePEc:gam:jecomi:v:12:y:2024:i:7:p:160-:d:1421890
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/12/7/160/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7099/12/7/160/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    2. Tom Broekel & Nicky Rogge & Thomas Brenner, 2018. "The innovation efficiency of German regions – a shared-input DEA approach," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 38(1), pages 77-109, February.
    3. Feng Li & Qingyuan Zhu & Jun Zhuang, 2018. "Analysis of fire protection efficiency in the United States: a two-stage DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 23-68, January.
    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. Xiyang Lei & Yongjun Li & Alec Morton, 2022. "Dominance and ranking interval in DEA parallel production systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 649-675, June.
    2. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    3. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    4. Jiao, Hong-Wei & Liu, San-Yang, 2015. "A practicable branch and bound algorithm for sum of linear ratios problem," European Journal of Operational Research, Elsevier, vol. 243(3), pages 723-730.
    5. Qingyou Yan & Fei Zhao & Xu Wang & Tomas Balezentis, 2021. "The Environmental Efficiency Analysis Based on the Three-Step Method for Two-Stage Data Envelopment Analysis," Energies, MDPI, vol. 14(21), pages 1-14, October.
    6. Phung, Manh-Trung & Cheng, Cheng-Ping & Guo, Chuanyin & Kao, Chen-Yu, 2020. "Mixed Network DEA with Shared Resources: A Case of Measuring Performance for Banking Industry," Operations Research Perspectives, Elsevier, vol. 7(C).
    7. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    8. Panpan Liu & Guanghui Han & Haichao Yang & Xiaobo Li, 2024. "A Sustainable Development Study on Innovation Factor Allocation Efficiency and Spatial Correlation Based on Regions along the Belt and Road in China," Sustainability, MDPI, vol. 16(7), pages 1-22, April.
    9. Meng, Fanyong & Xiong, Beibei, 2021. "Logical efficiency decomposition for general two-stage systems in view of cross efficiency," European Journal of Operational Research, Elsevier, vol. 294(2), pages 622-632.
    10. Li, Feng & Zhu, Qingyuan & Chen, Zhi, 2019. "Allocating a fixed cost across the decision making units with two-stage network structures," Omega, Elsevier, vol. 83(C), pages 139-154.
    11. Guccio, Calogero & Martorana, Marco & Mazza, Isidoro & Pignataro, Giacomo & Rizzo, Ilde, 2020. "An assessment of the performance of Italian public historical archives: Preservation vs utilisation," Journal of Policy Modeling, Elsevier, vol. 42(6), pages 1270-1286.
    12. Kao, Chiang & Liu, Shiang-Tai, 2019. "Cross efficiency measurement and decomposition in two basic network systems," Omega, Elsevier, vol. 83(C), pages 70-79.
    13. Wan, Qunchao & Chen, Jin & Yao, Zhu & Yuan, Ling, 2022. "Preferential tax policy and R&D personnel flow for technological innovation efficiency of China's high-tech industry in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    14. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    15. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    16. Madjid Tavana & Kaveh Khalili-Damghani & Francisco J. Santos Arteaga & Arousha Hashemi, 2020. "A Malmquist productivity index for network production systems in the energy sector," Annals of Operations Research, Springer, vol. 284(1), pages 415-445, January.
    17. Moraes, Ricardo Kalil & Wanke, Peter Fernandes & Faria, João Ricardo, 2021. "Unveiling the endogeneity between social-welfare and labor efficiency: Two-stage NDEA neural network approach," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    18. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    19. Feng Li & Qingyuan Zhu & Liang Liang, 2019. "A new data envelopment analysis based approach for fixed cost allocation," Annals of Operations Research, Springer, vol. 274(1), pages 347-372, March.
    20. Cristian Barra & Nazzareno Ruggiero, 2022. "How do dimensions of institutional quality improve Italian regional innovation system efficiency? The Knowledge production function using SFA," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 591-642, April.

    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:gam:jecomi:v:12:y:2024:i:7:p:160-:d:1421890. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.