IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v176y2022ics0040162521008982.html
   My bibliography  Save this article

Integrating economic, environmental and societal performance within the productivity measurement

Author

Listed:
  • Shen, Zhiyang
  • Wu, Haitao
  • Bai, Kaixuan
  • Hao, Yu

Abstract

Total factor productivity (TFP) indicators or indices are usual measurements for evaluating economic performance in terms of output and input evolution. This approach has been extended in the environmental dimension in the literature. However, the social dimension is equally important for a comprehensive TFP, which is ignored in existing studies. Using provincial-level data from 2000 to 2017 in China, this paper applies a novel nonparametric approach incorporating three dimensions (economy, environment and society) to estimate the Luenberger productivity indicator in order to understand how to realize sustainable and high-quality development. Then, the overall productivity gain is decomposed into three different parts to evaluate economic, environmental, and social performance. The results show that the growth rate of TFP in China within the sample interval was 6.822%. Regarding its decomposition, medical care provided the largest contribution to the increase in TFP (3.840%), followed by emission reduction (1.981%), economic growth (0.975%), education (0.016%) and employment (0.010%). However, there is regional variety showing that eastern China had high-quality TFP growth (4.696%), while the TFP change was negative (-1.165%) in western China due to an inferior economy, environment, and educational development.

Suggested Citation

  • Shen, Zhiyang & Wu, Haitao & Bai, Kaixuan & Hao, Yu, 2022. "Integrating economic, environmental and societal performance within the productivity measurement," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  • Handle: RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162521008982
    DOI: 10.1016/j.techfore.2021.121463
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521008982
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2021.121463?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. Wu, Fangwei & Zhang, Deyuan & Zhang, Jinghua, 2008. "Unequal education, poverty and low growth--A theoretical framework for rural education of China," Economics of Education Review, Elsevier, vol. 27(3), pages 308-318, June.
    2. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2018. "Analysis of green total-factor productivity in China's regional metal industry: A meta-frontier approach," Resources Policy, Elsevier, vol. 58(C), pages 219-229.
    3. Chambers, Robert G. & Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity Growth in APEC Countries," Working Papers 197843, University of Maryland, Department of Agricultural and Resource Economics.
    4. Roshdi, Israfil & Hasannasab, Maryam & Margaritis, Dimitris & Rouse, Paul, 2018. "Generalised weak disposability and efficiency measurement in environmental technologies," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1000-1012.
    5. A. Abad & P. Ravelojaona, 2017. "Exponential environmental productivity index and indicators," Journal of Productivity Analysis, Springer, vol. 48(2), pages 147-166, December.
    6. Xiaobo Shen & Boqiang Lin & Wei Wu, 2019. "R&D Efforts, Total Factor Productivity, and the Energy Intensity in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2566-2588, September.
    7. Feng, Guohua & Serletis, Apostolos, 2014. "Undesirable outputs and a primal Divisia productivity index based on the directional output distance function," Journal of Econometrics, Elsevier, vol. 183(1), pages 135-146.
    8. Huang, Hongyun & Mo, Renbian & Chen, Xingquan, 2021. "New patterns in China's regional green development: An interval Malmquist–Luenberger productivity analysis," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 161-173.
    9. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    10. Zhang, Chunhong & Liu, Haiying & Bressers, Hans Th.A. & Buchanan, Karen S., 2011. "Productivity growth and environmental regulations - accounting for undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index," Ecological Economics, Elsevier, vol. 70(12), pages 2369-2379.
    11. Valadkhani, Abbas & Roshdi, Israfil & Smyth, Russell, 2016. "A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters," Energy Economics, Elsevier, vol. 54(C), pages 363-375.
    12. Xuesong Guo & Jun Zhang & Zhiwei Xu & Xin Cong & Zhenli Zhu, 2021. "The efficiency of provincial government health care expenditure after China’s new health care reform," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-16, October.
    13. Jean-Philippe Boussemart & Hervé Leleu & Zhiyang Shen & Vivian Valdmanis, 2020. "Performance analysis for three pillars of sustainability," Journal of Productivity Analysis, Springer, vol. 53(3), pages 305-320, June.
    14. Ariizumi, Hideki, 2008. "Effect of public long-term care insurance on consumption, medical care demand, and welfare," Journal of Health Economics, Elsevier, vol. 27(6), pages 1423-1435, December.
    15. Atella, Vincenzo & Brugiavini, Agar & Pace, Noemi, 2015. "The health care system reform in China: Effects on out-of-pocket expenses and saving," China Economic Review, Elsevier, vol. 34(C), pages 182-195.
    16. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    17. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, Oxford University Press, vol. 124(4), pages 1403-1448.
    18. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    19. Wu, Haitao & Hao, Yu & Weng, Jia-Hsi, 2019. "How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models," Energy Policy, Elsevier, vol. 127(C), pages 24-38.
    20. Shen, Zhiyang & Bai, Kaixuan & Hong, Tianyang & Balezentis, Tomas, 2021. "Evaluation of carbon shadow price within a non-parametric meta-frontier framework: The case of OECD, ASEAN and BRICS," Applied Energy, Elsevier, vol. 299(C).
    21. Yang, Yuying & Guo, Haixiang & Chen, Linfei & Liu, Xiao & Gu, Mingyun & Ke, Xiaoling, 2019. "Regional analysis of the green development level differences in Chinese mineral resource-based cities," Resources Policy, Elsevier, vol. 61(C), pages 261-272.
    22. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    23. Wang, Yongpei & Li, Jun, 2019. "Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China's provinces," Renewable Energy, Elsevier, vol. 136(C), pages 317-330.
    24. Rawat, Pankaj S. & Sharma, Seema, 2021. "TFP growth, technical efficiency and catch-up dynamics: Evidence from Indian manufacturing," Economic Modelling, Elsevier, vol. 103(C).
    25. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2021. "Water company productivity change: A disaggregated approach accounting for changes in inputs and outputs," Utilities Policy, Elsevier, vol. 70(C).
    26. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    27. 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.
    28. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    29. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    30. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    31. Amartya Sen & Joseph Stiglitz & Jean-Paul Fitoussi, 2010. "Mis-measuring our lives : why GDP doesn't add up?," Post-Print hal-03415632, HAL.
    32. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry," European Journal of Operational Research, Elsevier, vol. 216(3), pages 668-678.
    33. Zhu, Xuehong & Chen, Ying & Feng, Chao, 2018. "Green total factor productivity of China's mining and quarrying industry: A global data envelopment analysis," Resources Policy, Elsevier, vol. 57(C), pages 1-9.
    34. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
    35. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    36. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    37. Hao, Yu & Gai, Zhiqiang & Wu, Haitao, 2020. "How do resource misallocation and government corruption affect green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 143(C).
    38. Subhash C. Ray & Kankana Mukherjee & Anand Venkatesh, 2018. "Nonparametric measures of efficiency in the presence of undesirable outputs: a by-production approach," Empirical Economics, Springer, vol. 54(1), pages 31-65, February.
    39. Hu, Wei & Fan, Yuemin, 2020. "City size and energy conservation: Do large cities in China consume more energy?," Energy Economics, Elsevier, vol. 92(C).
    40. Kerstens, Kristiaan & Shen, Zhiyang & Van de Woestyne, Ignace, 2018. "Comparing Luenberger and Luenberger-Hicks-Moorsteen productivity indicators: How well is total factor productivity approximated?," International Journal of Production Economics, Elsevier, vol. 195(C), pages 311-318.
    41. Sun, Caizhi & Yang, Yudi & Zhao, Liangshi, 2015. "Economic spillover effects in the Bohai Rim Region of China: Is the economic growth of coastal counties beneficial for the whole area?," China Economic Review, Elsevier, vol. 33(C), pages 123-136.
    42. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    43. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    44. Chen, Bin & Jin, Yingmei, 2020. "Adjusting productivity measures for CO2 emissions control: Evidence from the provincial thermal power sector in China," Energy Economics, Elsevier, vol. 87(C).
    45. Wang, Jun & Hu, Yong & Zhang, Zhiming, 2021. "Skill-biased technological change and labor market polarization in China," Economic Modelling, Elsevier, vol. 100(C).
    46. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
    47. Gao, Yuning & Zhang, Meichen & Zheng, Jinghai, 2021. "Accounting and determinants analysis of China's provincial total factor productivity considering carbon emissions," China Economic Review, Elsevier, vol. 65(C).
    48. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    49. Huang, Po-Chun & Yang, Tzu-Ting, 2021. "The welfare effects of extending unemployment benefits: Evidence from re-employment and unemployment transfers," Journal of Public Economics, Elsevier, vol. 202(C).
    50. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 130-143.
    51. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    52. Xiao, Yixiong & Chen, Xiang & Li, Qiang & Jia, Pengfei & Li, Luning & Chen, Zhifen, 2021. "Towards healthy China 2030: Modeling health care accessibility with patient referral," Social Science & Medicine, Elsevier, vol. 276(C).
    53. Kristoffersen, Ingebjørg, 2018. "Great expectations: Education and subjective wellbeing," Journal of Economic Psychology, Elsevier, vol. 66(C), pages 64-78.
    54. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    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. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    2. Shen, Zhiyang & Bai, Kaixuan & Hong, Tianyang & Balezentis, Tomas, 2021. "Evaluation of carbon shadow price within a non-parametric meta-frontier framework: The case of OECD, ASEAN and BRICS," Applied Energy, Elsevier, vol. 299(C).
    3. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    4. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    5. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    6. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    7. Roshdi, Israfil & Hasannasab, Maryam & Margaritis, Dimitris & Rouse, Paul, 2018. "Generalised weak disposability and efficiency measurement in environmental technologies," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1000-1012.
    8. Jean-Philippe Boussemart & Hervé Leleu & Zhiyang Shen & Vivian Valdmanis, 2020. "Performance analysis for three pillars of sustainability," Journal of Productivity Analysis, Springer, vol. 53(3), pages 305-320, June.
    9. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    10. Wang, Zhaohua & He, Weijun & Wang, Bo, 2017. "Performance and reduction potential of energy and CO2 emissions among the APEC's members with considering the return to scale," Energy, Elsevier, vol. 138(C), pages 552-562.
    11. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    12. Tomas Balezentis & Kristiaan Kerstens & Zhiyang Shen, 2022. "Economic and Environmental Decomposition of Luenberger-Hicks-Moorsteen Total Factor Productivity Indicator: Empirical Analysis of Chinese Textile Firms With a Focus on Reporting Infeasibilities and Qu," Post-Print hal-03833245, HAL.
    13. Ke Wang & Zhifu Mi & Yi‐Ming Wei, 2019. "Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach," Journal of Industrial Ecology, Yale University, vol. 23(2), pages 389-401, April.
    14. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.
    15. Margaréta Halická & Mária Trnovská, 2018. "Negative features of hyperbolic and directional distance models for technologies with undesirable outputs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 887-907, December.
    16. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    17. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    18. Qingyou Yan & Xu Wang & Tomas Baležentis & Dalia Streimikiene, 2018. "Energy–economy–environmental (3E) performance of Chinese regions based on the data envelopment analysis model with mixed assumptions on disposability," Energy & Environment, , vol. 29(5), pages 664-684, August.
    19. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    20. Fang, Lei, 2020. "Opening the “black box” of environmental production technology in a nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 769-780.

    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:tefoso:v:176:y:2022:i:c:s0040162521008982. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.sciencedirect.com/science/journal/00401625 .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.