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Can the digital economy improve green total factor productivity? An empirical study based on Chinese urban data

  • Received: 07 December 2022 Revised: 15 January 2023 Accepted: 16 January 2023 Published: 07 February 2023
  • With the new generation of technological revolution, the digital economy has progressively become a key driver of global economic development. In this context, how to promote green economic growth and improve green total factor productivity (GTFP) with the help of the digital economy is an important issue that urgently needs empirical research. We adopted the panel data of 278 Chinese prefecture-level cities from 2011 to 2020 to test whether the digital economy improves the GTFP through the Gaussian Mixed Model (GMM) dynamic panel model. The moderating effect model has been used to explore the impact mechanism from the perspectives of industrial structure upgrade and environmental regulation. In addition, a grouping regression was applied to the sample cities to test the heterogeneous impact of the digital economy on the GTFP. Based upon the empirical findings, this work has the following conclusions. First, the digital economy plays a significant role in improving the GTFP. Second, an industrial structure upgrade has a positive moderating effect on the ability of the digital economy to enhance the GTFP. The environmental regulation, in contrast, has a negative moderating effect. Third, the digital economy exerts heterogeneous impacts on the GTFP across regions, but not at the city level.

    Citation: Yue Liu, Chunying Ma, Zhehao Huang. Can the digital economy improve green total factor productivity? An empirical study based on Chinese urban data[J]. Mathematical Biosciences and Engineering, 2023, 20(4): 6866-6893. doi: 10.3934/mbe.2023296

    Related Papers:

  • With the new generation of technological revolution, the digital economy has progressively become a key driver of global economic development. In this context, how to promote green economic growth and improve green total factor productivity (GTFP) with the help of the digital economy is an important issue that urgently needs empirical research. We adopted the panel data of 278 Chinese prefecture-level cities from 2011 to 2020 to test whether the digital economy improves the GTFP through the Gaussian Mixed Model (GMM) dynamic panel model. The moderating effect model has been used to explore the impact mechanism from the perspectives of industrial structure upgrade and environmental regulation. In addition, a grouping regression was applied to the sample cities to test the heterogeneous impact of the digital economy on the GTFP. Based upon the empirical findings, this work has the following conclusions. First, the digital economy plays a significant role in improving the GTFP. Second, an industrial structure upgrade has a positive moderating effect on the ability of the digital economy to enhance the GTFP. The environmental regulation, in contrast, has a negative moderating effect. Third, the digital economy exerts heterogeneous impacts on the GTFP across regions, but not at the city level.



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    [1] D. Tapscott, The digital economy anniversary edition: Rethinking promise and peril in the age of networked intelligence, Innovation J., 19 (1999), 156–168.
    [2] D. W. Jorgenson, M. S. Ho, K. J. Stiroh, A retrospective look at the US productivity growth resurgence, J. Econ. Perspect., 22 (2008), 3–24. https://doi.org/10.1257/jep.22.1.3 doi: 10.1257/jep.22.1.3
    [3] D. J. Teece, Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world, Res. Policy, 47 (2018), 1367–1387. https://doi.org/10.1016/j.respol.2017.01.015 doi: 10.1016/j.respol.2017.01.015
    [4] R. Adner, J. Chen, F. Zhu, Frenemies in platform markets: Heterogeneous profit foci as drivers of compatibility decisions, Manage. Sci., 66 (2020). https://doi.org/10.1287/mnsc.2019.3327 doi: 10.1287/mnsc.2019.3327
    [5] A. Timonina-Farkas, COVID-19: data-driven dynamic asset allocation in times of pandemic, Quant. Finance Econ., 5 (2021), 198–227. https://doi.org/10.3934/QFE.2021009 doi: 10.3934/QFE.2021009
    [6] M. K. V. Bhanu, K. Anjala, S. Rishika, Digital economy in a global perspective: is there a digital divide, Transnational Corporations Rev., 13 (2021), 1–15. https://doi.org/10.1080/19186444.2020.1871257 doi: 10.1080/19186444.2020.1871257
    [7] D. Agyapong, Implications of digital economy for financial institutions in Ghana: an exploratory inquiry, Transnational Corporations Rev., 13 (2021), 51–61. https://doi.org/10.1080/19186444.2020.1787304 doi: 10.1080/19186444.2020.1787304
    [8] H. Bakhshi, A. Bravo-Biosca, J. Mateos-Garcia, The analytical firm: Estimating the effect of data and online analytics on firm performance, Nesta Working Paper, 2014.
    [9] B. van Gils, H. A. Proper. Enterprise modelling in the age of digital transformation, in 11th IFIP WG 8.1. Working Conference on the Practice of Enterprise Modeling (PoEM), Springer, Cham, 335 (2018). https://doi.org/10.1007/978-3-030-02302-7_16
    [10] Y. Lu, Industry 4.0: A survey on technologies, applications and open research issues, J. Ind. Inf. Integr., 6 (2017), 1–10. https://doi.org/10.1016/j.jii.2017.04.005 doi: 10.1016/j.jii.2017.04.005
    [11] Z. Li, C. Yang, Z. Huang, How does the fintech sector react to signals from central bank digital currencies, Finance Res. Lett., 50 (2022), 103308. https://doi.org/10.1016/j.frl.2022.103308 doi: 10.1016/j.frl.2022.103308
    [12] OECD, Data-driven Innovation for Growth and Well-being: Interim Synthesis Report, Paris, 2014. https://doi.org/10.1787/9789264229358-en
    [13] M. Farboodi, L. L. Veldkamp, A Growth Model of the Data Economy, NBER Working Paper No. w28427, 2021.
    [14] G. Garau, Total factor productivity and relative prices: the case of Italy, Natl. Account. Rev., 4 (2022), 16–37. http://dx.doi.org/10.3934/NAR.2022002 doi: 10.3934/NAR.2022002
    [15] R. W. Pittman, Multilateral productivity comparisons with undesirable outputs, Econ. J., 93 (1983), 883–891. https://doi.org/10.2307/2232753 doi: 10.2307/2232753
    [16] Y. H. Chung, R. Färe, S. Grosskopf, Productivity and undesirable outputs: A directional distance function approach, J. Environ. Manage., 51 (1997), 229–240. https://doi.org/10.1006/jema.1997.0146 doi: 10.1006/jema.1997.0146
    [17] K. Tone, A slacks-based measure of efficiency in data envelopment analysis, Eur. J. Oper. Res., 130 (2001), 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5 doi: 10.1016/S0377-2217(99)00407-5
    [18] D. Oh, A global Malmquist-Luenberger productivity index, J. Prod. Anal., 34 (2010), 183–197, https://doi.org/10.1007/s11123-010-0178-y doi: 10.1007/s11123-010-0178-y
    [19] P. Chakraborty, C. Chatterjee, Does environmental regulation indirectly induce upstream innovation? New evidence from India, Res. Policy, 46 (2017), 939–955. https://doi.org/10.1016/j.respol.2017.03.004 doi: 10.1016/j.respol.2017.03.004
    [20] Y. Su, Z. Li, C. Yang, Spatial interaction spillover effects between digital financial technology and urban ecological efficiency in China: an empirical study based on spatial simultaneous equations, IJERPH, 18 (2021), 8535. https://doi.org/10.3390/ijerph18168535 doi: 10.3390/ijerph18168535
    [21] I. S. Farouq, N. U. Sambo, A. U. Ahmad, A. H. Jakada, I. A. Danmaraya, et al., Does financial globalization uncertainty affect CO2 emissions? Empirical evidence from some selected SSA countries, Quant. Finance Econ., 5 (2021), 247–263, http://dx.doi.org/10.3934/QFE.2021011 doi: 10.3934/QFE.2021011
    [22] Z. Li, D. Li, W. Yang, X. Qi, The spatial-temporal evolution and spatial convergence of ecological total factor productivity in China, Energy Environ., 33 (2022), 617–639. https://doi.org/10.1177/0958305X20941141 doi: 10.1177/0958305X20941141
    [23] M. L. Song, J. T. Du, K. H. Tan, Impact of fiscal decentralization on green total factor productivity, Int. J. Prod. Econ., 205 (2018), 359–367.https://doi.org/10.1016/j.ijpe.2018.09.019 doi: 10.1016/j.ijpe.2018.09.019
    [24] P. Z. Liu, Y. Zhao, J. Zhu, C. Yang, Technological industry agglomeration, green innovation efficiency, and development quality of city cluster, Green Finance, 4 (2022), 411–435. http://dx.doi.org/10.3934/gf.2022020 doi: 10.3934/GF.2022020
    [25] Z. Huang, G. Liao, Z. Li, Loaning scale and government subsidy for promoting green innovation, Technol. Forecasting Social Change, 144 (2019), 148–156. https://doi.org/10.1016/j.techfore.2019.04.023 doi: 10.1016/j.techfore.2019.04.023
    [26] Y. Yao, D. Hu, C. Yang, Y. Tan, The impact and mechanism of fintech on green total factor productivity, Green Finance, 3 (2021), 198–221. http://dx.doi.org/10.3934/GF.2021011 doi: 10.3934/GF.2021011
    [27] Y. Lyu, W. Wang, Y. Wu, J. Zhang, How does digital economy affect green total factor productivity? Evidence from China, Sci. Total Environ., 857 (2022), 159428. https://doi.org/10.1016/j.scitotenv.2022.159428 doi: 10.1016/j.scitotenv.2022.159428
    [28] Z. Huang, H. Dong, S. Jia, Equilibrium pricing for carbon emission in response to the target of carbon emission peaking, Energy Econ., 112 (2022), 106160. https://doi.org/10.1016/j.eneco.2022.106160 doi: 10.1016/j.eneco.2022.106160
    [29] Q. B. Guo, Y. Wang, X. B. Dong, Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China, Appl. Energy, 313 (2022). https://doi.org/10.1016/j.apenergy.2022.118879 doi: 10.1016/j.apenergy.2022.118879
    [30] D. Ma, Q. Zhu, Innovation in emerging economies: Research on the digital economy driving high-quality green development, J. Bus. Res., 145 (2022), 801–813. https://doi.org/10.1016/j.jbusres.2022.03.041 doi: 10.1016/j.jbusres.2022.03.041
    [31] F. Meng, Y. Zhao, How does digital economy affect green total factor productivity at the industry level in China: from a perspective of global value chain, Environ. Sci. Pollut. Res., 29 (2022), 79497–79515. https://doi.org/10.1007/s11356-022-21434-0 doi: 10.1007/s11356-022-21434-0
    [32] Z. Zhang, W. K. Fu, L. Ma, The impact of digital economy on green development in China, Front. Environ. Sci., 10 (2022). http://dx.doi.org/10.3389/fenvs.2022.991278 doi: 10.3389/fenvs.2022.991278
    [33] X. Hao, S. Wen, Y. Xue, H. Wu, Y. Hao, How to improve environment, resources and economic efficiency in the digital era, Resour. Policy, 80 (2023), 103198. https://doi.org/10.1016/j.resourpol.2022.103198 doi: 10.1016/j.resourpol.2022.103198
    [34] V. Ranta, A. S. Leena, J. M. Väisänen, Digital technologies catalyzing business model innovation for circular economy—Multiple case study, Resour. Conserv. Recycl., 164 (2021). https://doi.org/10.1016/j.resconrec.2020.105155 doi: 10.1016/j.resconrec.2020.105155
    [35] H. Wen, C. C. Lee, Z. Song, Digitalization and environment: how does ICT affect enterprise environmental performance, Environ. Sci. Pollut. Res., 28 (2021), 54826–54841. https://doi.org/10.1007/s11356-021-14474-5 doi: 10.1007/s11356-021-14474-5
    [36] B. M. Teresa, E. Camiña, Á. Díaz-Chao, J. Torrent-Sellens, Productivity and employment effects of digital complementarities, J. Innovation Knowl., 6 (2021), 177–190. https://doi.org/10.1016/j.jik.2020.10.006 doi: 10.1016/j.jik.2020.10.006
    [37] Y. Ding, H. Zhang, S. Tang, How does the digital economy affect the domestic value-added rate of chinese exports, J. Global Inf. Manage., 29 (2021). https://doi.org/10.4018/JGIM.20210901.oa5 doi: 10.4018/JGIM.20210901.oa5
    [38] S. Lange, J. Pohl, T. Santarius, Digitalization and energy consumption. Does ICT reduce energy demand, Ecol. Econ., 176 (2020), 106760. https://doi.org/10.1016/j.ecolecon.2020.106760 doi: 10.1016/j.ecolecon.2020.106760
    [39] Q. Liu, H. Zhang, J. Leng, X. Chen, Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system, Int. J. Prod. Res., 57 (2019), 3903–3919. https://doi.org/10.1080/00207543.2018.1471243 doi: 10.1080/00207543.2018.1471243
    [40] A. B. Savchenko, T. L. Borodina, Green and digital economy for sustainable development of urban areas, Reg. Res. Russ., 10 (2020), 583–592. https://doi.org/10.1134/S2079970520040097 doi: 10.1134/S2079970520040097
    [41] W. Pan, The economic disparity between difference regions of China and its reduction—An analysis from the geographical perspective, Soc. Sci. China, 1 (2010), 72–84,222–223.
    [42] T. Zhao, Z. Zhang, S. K. Liang, Digital economy, entrepreneurial activity and high-quality development: Empirical evidence from Chinese cities, Manage. World, 36 (2020), 65–76. http://dx.doi.org/10.19744/j.cnki.11-1235/f.2020.0154 doi: 10.19744/j.cnki.11-1235/f.2020.0154
    [43] T. Li, J. Wen, D. Zeng, K. Liu, Has enterprise digital transformation improved the efficiency of enterprise technological innovation? A case study on Chinese listed companies, Math. Biosci. Eng., 19 (2022), 12632–12654. https://doi.org/10.3934/mbe.2022590 doi: 10.3934/mbe.2022590
    [44] S. Wang, Y. C. Liang, W. D. Li, X. T. Cai, Big data enabled intelligent immune system for energy efficient manufacturing management, J. Clean Prod., 195 (2018), 507–520. https://doi.org/10.1016/j.jclepro.2018.05.203 doi: 10.1016/j.jclepro.2018.05.203
    [45] M. Wang, L. Li, H. Lan, The measurement and analysis of technological innovation diffusion in China's manufacturing industry, Natl. Account. Rev., 3 (2021), 452–471. http://dx.doi.org/10.3934/NAR.2021024 doi: 10.3934/NAR.2021024
    [46] Z. Li, J. Zhong, Impact of economic policy uncertainty shocks on China's financial conditions, Finance Res. Lett., 35 (2020), 101303. https://doi.org/10.1016/j.physa.2019.01.100 doi: 10.1016/j.frl.2019.101303
    [47] Y. Xue, C. Jiang, Y. Guo, J. Liu, H. Wu, Y. Hao, Corporate social responsibility and high-quality development: Do green innovation, environmental investment and corporate governance matter, Emerging Mark. Finance Trade, 58 (2020), 3191–3214. https://doi.org/10.1080/1540496X.2022.2034616 doi: 10.1080/1540496X.2022.2034616
    [48] S. Albrizio, T. Kozluk, V. Zipperer, Environmental policies and productivity growth: Evidence across industries and firms, J. Environ. Econ. Manage., 81 (2017), 209–226. https://doi.org/10.1016/j.jeem.2016.06.002 doi: 10.1016/j.jeem.2016.06.002
    [49] Y. Liu, P. Failler, Y. Ding, Enterprise financialization and technological innovation: Mechanism and heterogeneity, PLoS ONE, 17 (2022), e0275461. https://doi.org/10.1371/journal.pone.0275461 doi: 10.1371/journal.pone.0275461
    [50] Z. Li, G. Liao, K. Albitar, Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation, Bus. Strategy Environ., 29 (2019). http://dx.doi.org/10.1002/bse.2416 doi: 10.1002/bse.2416
    [51] Z. Li, F. Zou, B. Mo, Does mandatory CSR disclosure affect enterprise total factor productivity, Ekon. Istraz., 35 (2022), 4902–4921. https://doi.org/10.1080/1331677X.2021.2019596 doi: 10.1080/1331677X.2021.2019596
    [52] G. Liao, P. Hou, X. Shen, K. Albitar, The impact of economic policy uncertainty on stock returns: The role of corporate environmental responsibility engagement, Int. J. Finance Econ., 26 (2021), 4386–4392. https://doi.org/10.1002/ijfe.2020 doi: 10.1002/ijfe.2020
    [53] F. Deng, H. Li, M. Yang, W. Zhao, Z. Gai, Y. Guo, et al., On the nonlinear relationship between energy consumption and economic and social development: evidence from Henan Province, China, Environ. Sci. Pollut. Res., 28 (2021), 33192–33207. https://doi.org/10.1007/s11356-021-12623-4 doi: 10.1007/s11356-021-12623-4
    [54] J. W. Zhang, G. Y. Wu, J. P. Zhang, China's inter-provincial material capital stock estimation: 1952–2000, Econ. Res. J., 10 (2004), 35–44.
    [55] J. Ma, Z. Li, Measuring China's urban digital economy, Natl. Account. Rev., 4 (2022), 329–361. http://dx.doi.org/10.3934/NAR.2022019 doi: 10.3934/NAR.2022019
    [56] S. Liu, Y. Yang, Y. Cao, N. Xie, A summary on the research of GRA models, Grey Syst. Theory Appl., 3 (2013), 7–15. https://doi.org/10.1108/20439371311293651 doi: 10.1108/20439371311293651
    [57] L. H. Fu, An empirical study on the relationship between the industrial structure advancement and economic growth in China, Stat. Res., 27 (2010), 79–81. http://dx.doi.org/10.19343/j.cnki.11-1302/c.2010.08.011 doi: 10.19343/j.cnki.11-1302/c.2010.08.011
    [58] S. Huang, Y. Ding, P. Failler, Does the government's environmental attention affect ambient pollution? Empirical research on Chinese cities, Sustainability, 14 (2022), 3242. https://doi.org/10.3390/su14063242 doi: 10.3390/su14063242
    [59] H. Wu, M. Sun, Can urbanization move ahead with energy conservation and emission reduction? New evidence from China, Energy Environ. Sci., 2022. https://doi.org/10.1177/0958305X221138822 doi: 10.1177/0958305X221138822
    [60] B. Lin, J. Zhu, Fiscal spending and green economic growth: Evidence from China, Energy Econ., 83 (2019), 264–271. https://doi.org/10.1016/j.eneco.2019.07.010 doi: 10.1016/j.eneco.2019.07.010
    [61] Z. Li, H. Chen, B. Mo, Can digital finance promote urban innovation? Evidence from China, Borsa Istanbul Rev., in press, 2022. https://doi.org/10.1016/j.bir.2022.10.006
    [62] Y. Liu, P. Failler, Z. Liu, Impact of environmental regulations on energy efficiency: A case study of China's air pollution prevention and control action plan, Sustainability, 14 (2022), 3168. https://doi.org/10.3390/su14063168 doi: 10.3390/su14063168
    [63] Y. Liu, Z. Li, M. Xu, The influential factors of financial cycle spillover: Evidence from China, Emerging Mark. Finance Trade, 56 (2020), 1336–1350. https://doi.org/10.1080/1540496x.2019.1658076 doi: 10.1080/1540496X.2019.1658076
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