IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i9p5688-d810298.html
   My bibliography  Save this article

Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity

Author

Listed:
  • Chong Huang

    (Institute of Marine Economics and Management, Shandong University of Finance and Economics, Jinan 250014, China
    School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China)

  • Kedong Yin

    (Institute of Marine Economics and Management, Shandong University of Finance and Economics, Jinan 250014, China
    School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China)

  • Hongbo Guo

    (School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China)

  • Benshuo Yang

    (School of Economics, Ocean University of China, Qingdao 266100, China)

Abstract

Green development is an effective way to reconcile the main contradictions between resources, environment, and regional development. Green total factor productivity (GTFP) is an important index to measure green development; an undesirable output-oriented SBM-DEA model and GML model can be used to calculate GTFP. China’s 30 provinces (municipalities and autonomous regions) are divided into three groups: eastern, central, and western. The common frontier function and group frontier function are established, respectively, to deeply explore the temporal and spatial evolution characteristics and center of gravity shift of inter-provincial green total factor productivity (GTFP) in China, and test the convergence under group frontier, to compare the convergence problems under different regions. This study aims to point out the differences in economic growth in different regions of China, foster regional coordination and orderly progress, promote China’s green development process, and improve the high-quality economic development level. According to the results, the efficiency of green development is more reasonable under the frontier groups. The average TGR in the eastern region was 0.993, indicating that it reached 99.3% of the meta-frontier green development efficiency technology. The inter-provincial GTFP in China gradually increased, with an average value of 1.043, which means China’s green development and ecological civilization construction have achieved remarkable results and the three regions showed significant differences. Judging from the shift path of the spatial center of gravity, the spatial distribution pattern of inter-provincial GTFP in China tends to be concentrated and stable as a whole. Moreover, σ convergence only exists in the western region, while absolute β convergence and conditional β convergence exist in eastern, central, and western regions, indicating that the GTFP of different regions will converge to their stable states over time. The results provide a basis for improving the efficiency of institutional allocation of environmental resources, implementing regional differentiated environmental regulation policies, and increasing the value creation of factor resources, which is of great significance for realizing the high-quality economic development in which resources, environment, and economy are coordinated in China.

Suggested Citation

  • Chong Huang & Kedong Yin & Hongbo Guo & Benshuo Yang, 2022. "Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity," IJERPH, MDPI, vol. 19(9), pages 1-20, May.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5688-:d:810298
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/9/5688/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/9/5688/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elsadig Musa Ahmed, 2012. "Green TFP Intensity Impact on Sustainable East Asian Productivity Growth (Elsadig Musa Ahmed)," Economic Analysis and Policy, Elsevier, vol. 42(1), pages 67-78, March.
    2. Song, Malin & Peng, Licheng & Shang, Yuping & Zhao, Xin, 2022. "Green technology progress and total factor productivity of resource-based enterprises: A perspective of technical compensation of environmental regulation," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    4. Tim J. Coelli & D. S. Prasada Rao, 2005. "Total factor productivity growth in agriculture: a Malmquist index analysis of 93 countries, 1980–2000," Agricultural Economics, International Association of Agricultural Economists, vol. 32(s1), pages 115-134, January.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Yanqing Jiang, 2015. "Total Factor Productivity, Pollution and ‘Green’ Economic Growth in China," Journal of International Development, John Wiley & Sons, Ltd., vol. 27(4), pages 504-515, 05-27.
    7. Barbara Dettori & Emanuela Marrocu & Raffaele Paci, 2012. "Total Factor Productivity, Intangible Assets and Spatial Dependence in the European Regions," Regional Studies, Taylor & Francis Journals, vol. 46(10), pages 1401-1416, November.
    8. Chieko Umetsu & Thamana Lekprichakul & Ujjayant Chakravorty, 2003. "Efficiency and Technical Change in the Philippine Rice Sector: A Malmquist Total Factor Productivity Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 943-963.
    9. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    10. Yang, Zhenbing & Fan, Meiting & Shao, Shuai & Yang, Lili, 2017. "Does carbon intensity constraint policy improve industrial green production performance in China? A quasi-DID analysis," Energy Economics, Elsevier, vol. 68(C), pages 271-282.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    12. Xueli Wang & Caizhi Sun & Song Wang & Zhixiong Zhang & Wei Zou, 2018. "Going Green or Going Away? A Spatial Empirical Examination of the Relationship between Environmental Regulations, Biased Technological Progress, and Green Total Factor Productivity," IJERPH, MDPI, vol. 15(9), pages 1-23, September.
    13. Chong Huang & Kedong Yin & Zhe Liu & Tonggang Cao, 2021. "Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors," IJERPH, MDPI, vol. 18(6), pages 1-18, March.
    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. Fergül ÖZGÜN & Meral UZUNÖZ ALTAN & Ayten Nahide KORKMAZ, 2024. "Bibliometric Analysis of Studies on the Relationship Between Environmental Quality, Economic Growth and Health," Yildiz Social Science Review, Yildiz Technical University, vol. 10(2), pages 110-135, December .
    2. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    3. Liping Zhu & Rui Shi & Lincheng Mi & Pu Liu & Guofeng Wang, 2022. "Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    4. Yujian Jin & Lihong Yu & Yan Wang, 2022. "Green Total Factor Productivity and Its Saving Effect on the Green Factor in China’s Strategic Minerals Industry from 1998–2017," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    5. Silin Chen & Xiangyu Guo, 2024. "Analysis of the Club Convergence and Driving Factors of China’s Green Agricultural Development Levels," Agriculture, MDPI, vol. 14(4), pages 1-16, March.

    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. Shen Zhong & Aizhi Li & Jing Wu, 2023. "Eco-efficiency of freshwater aquaculture in China: an assessment considering the undesirable output of pollutant emissions," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(4), pages 3555-3576, April.
    2. Dakpo, K Hervé & Desjeux, Yann & Jeanneaux, Philippe & Latruffe , Laure, 2017. "Productivity, technical efficiency and technological change in French agriculture during 2002-2014: A Färe-Primont index decomposition," Working Papers 263010, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    3. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    4. Guihuan Yan & Liming Jiang & Chongqing Xu, 2022. "How Environmental Regulation Affects Industrial Green Total Factor Productivity in China: The Role of Internal and External Channels," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    5. Qunwei Wang & Ye Hang & Jin‐Li Hu & Ching‐Ren Chiu, 2018. "An alternative metafrontier framework for measuring the heterogeneity of technology," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(5), pages 427-445, August.
    6. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    7. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    8. Shuo Wang & Naixu Tian & Yuqi Dai & Haiyan Duan, 2022. "Measurement of Resource Environmental Performance of Crop Planting Water Consumption Based on Water Footprint and Data Enveloped Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 641-658, January.
    9. Ze Tian & Fang-Rong Ren & Qin-Wen Xiao & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Cross-Regional Comparative Study on Carbon Emission Efficiency of China’s Yangtze River Economic Belt Based on the Meta-Frontier," IJERPH, MDPI, vol. 16(4), pages 1-19, February.
    10. Meng, Ming & Qu, Danlei, 2022. "Understanding the green energy efficiencies of provinces in China: A Super-SBM and GML analysis," Energy, Elsevier, vol. 239(PA).
    11. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    12. Dakpo, K Hervé & Desjeux, Yann & Jeanneaux, Philippe & Latruffe, Laure, 2016. "Productivity, efficiency and technological change in French agriculture during 2002-2014: A Färe-Primont index decomposition," 149th Seminar, October 27-28, 2016, Rennes, France 244793, European Association of Agricultural Economists.
    13. Zhou, Di & Yin, Xiaoshuo & Xie, Dongchun, 2023. "Local governments’ environmental targets and green total factor productivity in Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    14. Yongyi Cheng & Tianyuan Shao & Huilin Lai & Manhong Shen & Yi Li, 2019. "Total-Factor Eco-Efficiency and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration, China," IJERPH, MDPI, vol. 16(20), pages 1-14, October.
    15. Juan Aparicio & Magdalena Kapelko, 2019. "Enhancing the Measurement of Composite Indicators of Corporate Social Performance," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 807-826, July.
    16. Yiming Hou & Guanwen Yin & Yanbin Chen, 2022. "Environmental Regulation, Financial Pressure and Industrial Ecological Efficiency of Resource-Based Cities in China: Spatiotemporal Characteristics and Impact Mechanism," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    17. Liu, Biao & Wang, Jinman & Feng, Yu & Yang, Man & Mu, Jiayin, 2024. "Mitigating the disparities in carbon emission efficiency enhancement in China's coal resource-based cities," Energy, Elsevier, vol. 307(C).
    18. Xi Zhang & Rui Li & Jinglei Zhang, 2022. "Understanding the Green Total Factor Productivity of Manufacturing Industry in China: Analysis Based on the Super-SBM Model with Undesirable Outputs," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    19. Deshan Li & Rongwei Wu, 2018. "A Dynamic Analysis of Green Productivity Growth for Cities in Xinjiang," Sustainability, MDPI, vol. 10(2), pages 1-13, February.
    20. Teng, Xiangyu & Zhuang, Weiwei & Liu, Fan-peng & Chang, Tzu-han & Chiu, Yung-ho, 2023. "China's path of carbon neutralization to develop green energy and improve energy efficiency," Renewable Energy, Elsevier, vol. 206(C), pages 397-408.

    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:jijerp:v:19:y:2022:i:9:p:5688-:d:810298. 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.