IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3122-d344977.html
   My bibliography  Save this article

Research on Green Productivity of Chinese Real Estate Companies—Based on SBM-DEA and TOBIT Models

Author

Listed:
  • Zhao Yang

    (School of Economics & Management, Beihang University, Beijing 100191, China)

  • Hong Fang

    (School of Economics & Management, Beihang University, Beijing 100191, China)

Abstract

Apart from promoting social-economic development and increasing social employment, the real estate industry in China has also brought up problems such as high energy consumption and high emissions. Scholars now focus more on energy conservation, emission reduction and sustainable development of real estate companies in their current research. The data used by this paper are three-year panel data from 2015 to 2018, with observations from 15 representative real estate companies. CO 2 and green credit index are introduced as the undesirable output and the green output of real estate companies respectively. First, with the DEA model and the Malmquist index model, this paper evaluates the green productivity of real estate companies statically and dynamically. The Tobit model is then employed by the author to analyze factors that may affect green productivity. Our results indicate that (1) the green productivities of 15 Chinese real estate companies have improved by various degrees. The average green productivity rises from 0.701 in 2015 to 0.849 in 2018, indicating that the energy utilization rate of enterprises has gradually increased. From the calculation and decomposition of the Malmquist total factor productivity index, we know that technological progress is vital in improving the green productivity of real estate companies. (2) As for the influencing factors, the green productivity is positively related to factors such as policy compliance indicator P, environmental responsibility commitment indicator R, indicator of green innovation capability I, and indicator of green development information disclosure M. The asset-liability ratio on the contrary has a negative impact on green productivity. It’s worth to point out that the green innovation index and green productivity is significantly correlated and the correlation coefficient can be up to 0.636, which implies that the key to improving green productivity is to increase research and development investment.

Suggested Citation

  • Zhao Yang & Hong Fang, 2020. "Research on Green Productivity of Chinese Real Estate Companies—Based on SBM-DEA and TOBIT Models," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3122-:d:344977
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3122/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3122/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    2. Ma-Lin Song & Yuan-Xiang Zhou, 2015. "Analysis of Carbon Emissions and Their Influence Factors Based on Data from Anhui of China," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 359-374, October.
    3. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    4. Lozano, Sebastián & Iribarren, Diego & Moreira, María Teresa & Feijoo, Gumersindo, 2010. "Environmental impact efficiency in mussel cultivation," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1269-1277.
    5. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    6. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    7. Nguyen, Khac Minh & Giang, Thanh Long, 2005. "Efficiency of Construction Firms in Vietnam," MPRA Paper 968, University Library of Munich, Germany, revised Nov 2006.
    8. 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.
    9. Pittman, Russell W, 1983. "Multilateral Productivity Comparisons with Undesirable Outputs," Economic Journal, Royal Economic Society, vol. 93(372), pages 883-891, December.
    10. 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.
    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. Tinghui Li & Jiehua Ma & Bin Mo, 2021. "Does the Land Market Have an Impact on Green Total Factor Productivity? A Case Study on China," Land, MDPI, vol. 10(6), pages 1-19, June.
    2. Hirofumi Fukuyama & Yong Tan, 2023. "Estimating market power under a nonparametric analysis: evidence from the Chinese real estate sector," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 599-622, June.
    3. Xiangyu Hua & Haiping Lv & Xiangrong Jin, 2021. "Research on High-Quality Development Efficiency and Total Factor Productivity of Regional Economies in China," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    4. Zhifeng Zhang & Hongyan Duan & Shuangshuang Shan & Qingzhi Liu & Wenhui Geng, 2022. "The Impact of Green Credit on the Green Innovation Level of Heavy-Polluting Enterprises—Evidence from China," IJERPH, MDPI, vol. 19(2), pages 1-19, January.

    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. Zhang, Junfeng & Fang, Hong & Wang, Hongxia & Jia, Mingshun & Wu, Junjie & Fang, Siran, 2017. "Energy efficiency of airlines and its influencing factors: A comparison between China and the United States," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 1-8.
    2. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    3. Young-Tae Chang & Nan Zhang, 2017. "Environmental efficiency of transportation sectors in China and Korea," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 68-93, March.
    4. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    5. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    6. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.
    7. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    8. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    9. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "The Impact of Economic Growth and Air Pollution on Public Health in 31 Chinese Cities," IJERPH, MDPI, vol. 16(3), pages 1-26, January.
    10. 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.
    11. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    12. Li, Tao & Yang, Wenyue & Zhang, Haoran & Cao, Xiaoshu, 2016. "Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China," Transport Policy, Elsevier, vol. 45(C), pages 66-76.
    13. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    14. Ying Li & Yung-ho Chiu & Liang Chun Lu, 2019. "New Energy Development and Pollution Emissions in China," IJERPH, MDPI, vol. 16(10), pages 1-24, May.
    15. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    16. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    17. Ching-Cheng Lu & Yung-ho Chiu & I-Fang Lin & Tai-Yu Lin, 2023. "Dynamic total factors’ environmental efficiency in European union countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10055-10072, September.
    18. Linlin Zhao & Yong Zha & Kangning Wei & Liang Liang, 2017. "A target-based method for energy saving and carbon emissions reduction in China based on environmental data envelopment analysis," Annals of Operations Research, Springer, vol. 255(1), pages 277-300, August.
    19. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    20. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.

    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:jsusta:v:12:y:2020:i:8:p:3122-:d:344977. 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.