Industrial pollution comes not only from within industries, but also from between industries that are strongly linked. From the perspective of agglomeration, this study explores the mutual transmission of pollution between different manufacturing industries. We found that there is an inverted U-shape relationship between inter-industry agglomeration and environmental pollution among 20 Chinese manufacturing industries. Energy intensity, which is an important transmission path from agglomeration to pollution, is positively related to the energy consumption of industries with some degree of agglomeration. Besides, the expansion of production scale caused by inter-industry agglomeration leads to more energy consumption and pollution. Furthermore, the innovative technology resulting from inter-industry agglomeration reduces environmental pollution but does not have a significant impact on energy consumption.
Citation: Li Xu, Ping Guo, Guoqin Pan. Effects of inter-industry agglomeration on environmental pollution: Evidence from China[J]. Mathematical Biosciences and Engineering, 2023, 20(4): 7113-7139. doi: 10.3934/mbe.2023307
Industrial pollution comes not only from within industries, but also from between industries that are strongly linked. From the perspective of agglomeration, this study explores the mutual transmission of pollution between different manufacturing industries. We found that there is an inverted U-shape relationship between inter-industry agglomeration and environmental pollution among 20 Chinese manufacturing industries. Energy intensity, which is an important transmission path from agglomeration to pollution, is positively related to the energy consumption of industries with some degree of agglomeration. Besides, the expansion of production scale caused by inter-industry agglomeration leads to more energy consumption and pollution. Furthermore, the innovative technology resulting from inter-industry agglomeration reduces environmental pollution but does not have a significant impact on energy consumption.
[1] | L. Zhu, Y. Hao, Z. N. Lu, H. Wu, Q. Ran, Do economic activities cause air pollution? Evidence from China's major cities, Sust. Cities Soc., 49 (2019), 1–10. https://doi.org/10.1016/j.scs.2019.101593 doi: 10.1016/j.scs.2019.101593 |
[2] | T. C. Li, D. Han, S. Feng, L. Lei, Can Industrial inter-agglomeration between Producer Services and Manufacturing Reduce Carbon Intensity in China?, Sustainability, 11 (2019), 1–15. https://doi.org/10.3390/su11154024 doi: 10.11912/jws.2019.9.1.1-11 |
[3] | H. Yang, F. Zhang, Y. He, Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China, Environ. Dev. Sustain., 23 (2021), 16119–16144. https://doi.org/10.1016/j.jclepro.2020.121320 doi: 10.1007/s10668-021-01339-7 |
[4] | D. Z. Zeng, L. X. Zhao, Pollution Havens and Industrial Agglomeration, J. Environ. Econ. Mange., 58 (2009), 141–153. https://doi.org/10.1016/j.jeem.2008.09.003 doi: 10.1016/j.jeem.2008.09.003 |
[5] | G. Ellison, E. L. Glaeser, Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach, J. Polit. Econ., 105 (1997), 889–927. https://doi.org/10.1086/262098 doi: 10.1086/262098 |
[6] | Q. X. Gong, G. X. Guo, S. P. Li, X. D. Liang, Examining the Coupling Coordinated Relationship between Urban Industrial inter-agglomeration and Intensive Land Use, Land, 10 (2021), 1–12. https://doi.org/10.3390/land10050499 doi: 10.3390/land10050499 |
[7] | S. Ke, M. He, C. Yuan, Synergy and Co–agglomeration of Producer Services and Manufacturing: A Panel Data Analysis of Chinese Cities, Reg. Stud., 48 (2014), 1829–1841. https://doi.org/10.1080/00343404.2012.756580 doi: 10.1080/00343404.2012.756580 |
[8] | S. B. Billings, E. B. Johnson, Agglomeration within an Urban area. J. Urban Econ., 91 (2016), 13–25. https://doi.org/10.1016/j.jue.2015.11.002 doi: 10.1016/j.jue.2015.11.002 |
[9] | Z. Cheng, The Spatial Correlation and Interaction between Manufacturing Agglomeration and Environmental Pollution, Ecol. Indic., 61 (2016), 1024–1032. https://doi.org/10.1016/j.ecolind.2015.10.060 doi: 10.1016/j.ecolind.2015.10.060 |
[10] | K. Kanemoto, T. Hanaka, S. Kagawa, K. Nansai, Industrial clusters with substantial carbon–reduction potential, Econ. Syst. Res., 31 (2019), 248–266. https://doi.org/10.1080/09535314.2018.1492369 doi: 10.1080/09535314.2018.1492369 |
[11] | L. Brandt, T. Tombe, X. Zhu, Factor market distortions across time, space and sectors in China, Rev. Econ. Dyn., 16 (2013), 39–58. https://doi.org/10.1016/j.red.2012.10.002 doi: 10.1016/j.red.2012.10.002 |
[12] | W. Chen, X. Huang, Y. H. Liu, L. Xin, Y. Song, The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency-Evidence from the Yangtze River Economic Belt, Sustain., 11 (2019), 1–18. https://doi.org/10.1108/SAMPJ-09-2018-0248 doi: 10.1108/SAMPJ-09-2018-0248 |
[13] | M. Song, S. Wang, Can employment structure promote environment-biased technical progress?, Technol. Forecast. Soc. Change., 112 (2016), 285–292. https://doi.org/10.1016/j.techfore.2016.02.016 doi: 10.1016/j.techfore.2016.02.016 |
[14] | L. Ning, F. Wang, J. Li, Urban innovation, regional externalities of foreign direct investment and industrial agglomeration: Evidence from Chinese cities, Res. Policy., 45 (2016), 830–843. https://doi.org/10.1016/j.respol.2016.01.014 doi: 10.1016/j.respol.2016.01.014 |
[15] | Z. Huang, G. Liao, Z. Li, Loaning scale and government subsidy for promoting green innovation, Technol. Forecast. Soc. Change., 144 (2019), 148–156. https://doi.org/10.1016/j.techfore.2019.04.023 doi: 10.1016/j.techfore.2019.04.023 |
[16] | Z. Li, G. Liao, K. Albitar, Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation, Bus. Strateg. Environ., 29 (2020), 1045–1055. https://doi.org/10.1002/bse.2416 doi: 10.1002/bse.2416 |
[17] | S. J. Li, B. Sun, D. X. Hou, W. J. Jin, Y. Ji, Does Industrial Agglomeration or Foreign Direct Investment Matter for Environment Pollution of Public Health? Evidence From China, Front. Public Health, 9 (2021), 1–14. https://doi.org/10.3389/fpubh.2021.711033 doi: 10.3389/fpubh.2021.711033 |
[18] | M. W. Wang, R. Gu, M. Wang, J. Zhang, Research on the impact of finance on promoting technological innovation based on the state-space model, Green Financ., 3 (2021), 119–137. https://doi.org/10.3934/GF.2021007 doi: 10.3934/GF.2021007 |
[19] | X. Sun, L. Loh, Z. Chen, Effect of market fragmentation on ecological efficiency: evidence from environmental pollution in China, Environ. Sci. Pollut. Res., 27 (2020), 4944–4957. https://doi.org/10.1007/s11356-019-06548-2 doi: 10.1007/s11356-019-06548-2 |
[20] | B. Zhang, X. Chen, H. Guo, Doez es central supervision enhance local environmental enforcement? Quasi-experimental evidence from China, J. Public. Econ., 164 (2018), 70–90. https://doi.org/10.1016/j.jpubeco.2018.05.009 doi: 10.1016/j.jpubeco.2018.05.009 |
[21] | T. Li, X. Li, K. Albitar, Threshold effects of financialization on enterprise R & D innovation: comparison research on heterogeneity, Quant. Financ. Econ., 5 (2021), 496–515. https://doi.org/10.3934/QFE.202102 doi: 10.3934/QFE.2021022 |
[22] | X.Y. Li, Study on the impact of energy rebound effect on carbon emission reduction at different stages of urbanization in China, Ecol. Indic., 120 (2021), 1–8. https://doi.org/10.1016/j.ecolind.2020.106983 doi: 10.1016/j.ecolind.2020.106983 |
[23] | Z. Li, F. Zou, B. Mo, Does mandatory CSR disclosure affect enterprise total factor productivity? Ekon. Istraz., 35 (2021), 4902–4921. https://doi.org/10.1080/1331677X.2021.2019596 doi: 10.1080/1331677X.2021.2019596 |
[24] | 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. Financ. Econ., 26 (2021), 4386–4389. https://doi.org/10.1002/ijfe.2020 doi: 10.1002/ijfe.2020 |
[25] | E. L. Glaser, M. E. Kahn, The Greenness of Cites: Carbon Dioxide Emissions and Urban Development, J. Urban Econ., 67 (2010), 404–418. https://doi.org/10.1016/j.jue.2009.11.006 doi: 10.1016/j.jue.2009.11.006 |
[26] | S. Brakman, J. H. Garretsen, R. Gigengack, C. V. Marrewijk, R. Wagenvoort, Negative Feedbacks in the Economy and Industrial Location, J. Reg. Sci., 36 (1996), 631–651. https://doi.org/10.1111/j.1467-9787.1996.tb01122.x doi: 10.1111/j.1467-9787.1996.tb01122.x |
[27] | F. de Leeuw, N. Moussiopoulos, P. Sahm, A. Bartonova, Urban Air Quality in Larger Conurbations in the European Union, Environ. Modell. Softw., 16 (2001), 399–414. https://doi.org/10.1016/S1364-8152(01)00007-X doi: 10.1016/S1364-8152(01)00007-X |
[28] | W. Ren, Y. Zhong, J. Meligrana, B. Anderson, W. E. Watt, J. Chen, and H. L. Leung, Urbanization, Land Use, and Water Quality in Shanghai:1947–1996. Environ. Int., 29 (2003), 649–659. https://doi.org/10.1016/S0160-4120(03)00051-5 doi: 10.1016/S0160-4120(03)00051-5 |
[29] | T. Li, X. Li, G. Liao, Business cycles and energy intensity. Evidence from emerging economies, Borsa Istanbul Rev., 22 (2022), 560–570. https://doi.org/10.1016/j.bir.2021.07.005 doi: 10.1016/j.bir.2021.07.005 |
[30] | B. Wang, X. Nie, Industrial agglomeration and environmental governance: help or resistance--Evidence from quasi natural experiment in development zones, China Ind. Econ., 12 (2016), 75–89. (In Chinese). https://doi.org/10.19581/j.cnki.ciejournal.2016.12.006 doi: 10.19581/j.cnki.ciejournal.2016.12.006 |
[31] | S. X. Liu, Y. M. Zhu, K. Q. Du, The impact of industrial agglomeration on industrial pollutant emission: evidence from China under New Normal, Clean Technol. Environ. policy, 19 (2017), 2327–2334. https://doi.org/10.1007/s10098-017-1407-0 doi: 10.1007/s10098-017-1407-0 |
[32] | V. Erik, N. Peter, Urban Environmental Externalities, Agglomeration Forces, and the Technological 'Deus ex Machina', Environ. Plan. A., 40 (2008), 928–947. https://doi.org/10.1068/a38434 doi: 10.1068/a38434 |
[33] | C. C. Fan, A. J. Scott, Industrial Agglomeration and Development: A Survey of Spatial Economic Issues in East Asia and a Statistical Analysis of Chinese Regions, Econ. Geogr., 79 (2003), 295–319. https://doi.org/10.1111/j.1944-8287.2003.tb00213.x doi: 10.1111/j.1944-8287.2003.tb00213.x |
[34] | J. Lan, M. Kakinaka, X. Huang, Foreign Direct Investment, Human Capital and Environmental Pollution in China, Environ. Resour. Econ., 51 (2012), 255–275. https://doi.org/10.1007/s10640-011-9498-2 doi: 10.1007/s10640-011-9498-2 |
[35] | Y. Zhu, Y. Xia, The Impact of Industrial Agglomeration on Environmental Pollution: Evidence from China under New Urbanization, Energ. Environ., 30 (2018), 1010–1026. https://doi.org/10.1177/0958305X18802784 doi: 10.1177/0958305X18802784 |
[36] | Y. L. Ye, S. Ye, H. C. Yu, Can Industrial Collaborative Agglomeration Reduce Haze Pollution? City-Level Empirical Evidence from China, Int. J. Environ. Res. Public Health, 18 (2021), 1566–1585. https://doi.org/10.3390/ijerph18041566 doi: 10.3390/ijerph18041566 |
[37] | J. Gorelick, N. Walmsley, The greening of municipal infrastructure investments: technical assistance, instruments, and city champions, Green Financ., 2 (2020), 114–134. https://doi.org/10.3934/GF.2020007 doi: 10.3934/GF.2020007 |
[38] | K. Tanaka, S. Managi, Industrial agglomeration effect for energy efficiency in Japanese production plants, Energ. Policy, 156 (2021). https://doi.org/10.1016/j.enpol.2021.112442 doi: 10.1016/j.enpol.2021.112442 |
[39] | S. Naik, V. Bagodi, Energy conservation opportunities: evidences from three industrial clusters in India, Int. J. Energy Sect. Manag., 15 (2021), 600–627. https://doi.org/10.1108/IJESM-07-2020-0022 doi: 10.1108/IJESM-07-2020-0022 |
[40] | M. Yi, Y.Q. Wang, M. Y. Sheng, B. Sharp, Y. Zhang, Effects of heterogeneous technological progress on haze pollution: Evidence from China, Ecol. Econ., 169 (2020), 106533–106544. https://doi.org/10.1016/j.ecolecon.2019.106533 doi: 10.1016/j.ecolecon.2019.106533 |
[41] | R. Tveteras, G. E. Battese, Agglomeration Externalities, Productivity and Technical Inefficiency, J. Reg. Sci., 46 (2006), 605–625. https://doi.org/10.1111/j.1467-9787.2006.00470.x doi: 10.1111/j.1467-9787.2006.00470.x |
[42] | A. Ciccone, R. E. Hall, Productivity and the Density of Economic Activity, Am. Econ. Rev., 86 (1996), 1–39. http://www.jstor.org/stable/2118255 |
[43] | J. H. Zhu, Z. H. Li, Can digital financial inclusion effectively stimulate technological Innovation of agricultural enterprises? --A case study on China, Natl. Account. Rev., 3 (2021), 398–421. https://doi.org/10.3934/NAR.2021021 doi: 10.3934/NAR.2021021 |
[44] | M. X. Wang, L. Li, H. Y. Lan, The measurement and analysis of technological innovation diffusion in China's manufacturing industry, Natl. Account. Rev., 3 (2021), 452–471. https://doi.org/10.3934/NAR.2021024 doi: 10.3934/NAR.2021024 |
[45] | Z. Li, H. Chen, B. Mo, Can digital finance promote urban innovation? Evidence from China, Borsa. Istanbul Rev., 2022, 1–12. https://doi.org/10.1016/j.bir.2022.10.006 doi: 10.1016/j.bir.2022.10.006 |
[46] | A. Martin, P. L. Johan, W. Joakim, The economic micro geography of diversity and specialization externalities-firm-level evidence from Swedish cities, Res. Policy, 48 (2019), 1385–1398. https://doi.org/10.1016/j.respol.2019.02.003 doi: 10.1016/j.respol.2019.02.003 |
[47] | Q. Y. Zheng, B. Q. Lin, Impact of industrial agglomeration on energy efficiency in China's paper industry, J. Clean. Prod., 184 (2019), 1072–1080. https://doi.org/10.1177/0958305X18802784 doi: 10.1177/0958305X18802784 |
[48] | M. Tahir, E. Ahmad, The relationship of energy intensity with economic growth: Evidence for European economies, Energy Strategy Rev., 20 (2018), 90–98. https://doi.org/10.1016/j.esr.2018.02.002 doi: 10.1016/j.esr.2018.02.002 |
[49] | M. He, B. Walheer, Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach, Natl. Account. Rev., 2 (2020), 110–137. https://doi.org/10.3934/NAR.2020007 doi: 10.3934/NAR.2020007 |
[50] | Y. Liu, P. Failler, Y. Ding, Enterprise financialization and technological innovation: Mechanism and heterogeneity, PLoS One, 17 (2022), 1–21. https://doi.org/10.1371/journal.pone.0275461 doi: 10.1371/journal.pone.0275461 |
[51] | X. H. Liu, Dynamic evolution, spatial spillover effect of technological innovation and haze pollution in China, Energy Environ., 29 (2018), 968–988. doi: 10.1177/0958305X18765249 |
[52] | L. M. Ma, X. Zhang, Spatial effects of China's haze and its impact on economic and energy structure, China Ind. Econ., 4 (2014), 19–31. |
[53] | C. Hua, J. J. Miao, W. P. Liu, G. Du, X. Wang, The impact mechanism of industrial agglomeration on energy efficiency-Evidence from producer service industry in China, Energ. Sources Part B, 16 (2021), 740–758 doi: 10.1080/15567249.2021.1966132 |
[54] | M. M. Rahman, K. Alam, The nexus between health status and health expenditure, energy consumption and environmental pollution: empirical evidence from SAARC-BIMSTEC regions, BMC Public Health, 21 (2021), 1–12. https://doi.org/10.21203/rs.3.rs-68393/v2 doi: 10.1186/s12889-020-10013-y |
[55] | X. Sun, B. K. Zhu, S. Zhang, H. Zeng, K. Li, B. Wang, Z. F. Dong, C. C. Zhou, New indices system for quantifying the nexus between economic-social development, natural resources consumption, and environmental pollution in China during 1978–2018, Sci. Total Environ., 804 (2021), 150180. https://doi.org/10.1016/j.scitotenv.2021.150180 doi: 10.1016/j.scitotenv.2021.150180 |
[56] | D. Federica, C. Antonio, B. M. Silvio Servitization and sustainability actions, Evidence from European manufacturing companies, J. Environ. Manage., 234 (2019), 367–378. https://doi.org/10.1016/j.jenvman.2019.01.004 doi: 10.1016/j.jenvman.2019.01.004 |
[57] | M. M. Faisal, K. Afra, Energy consumption, carbon emissions and economic growth in Pakistan: Dynamic causality analysis, Renew. Sust. Energ. Rev., 72 (2016), 1233–1240. https://doi.org/10.1016/j.rser.2016.10.081 doi: 10.1016/j.rser.2016.10.081 |
[58] | C. Huang, J. W. Wang, C. M. Wang, J. H. Cheng, J. Dai, Does tourism industry agglomeration reduce carbon emissions? Environ. Sci. Pollut. Res., 28 (2021), 30278–30293. https://doi.org/10.1007/s11356-021-12706-2 doi: 10.1007/s11356-021-12706-2 |
[59] | Z. Huang, H. Dong, S. Jia, Equilibrium pricing for carbon emission in response to the target of carbon emission peaking, Energy Econ., 112 (2022), 106160–106175. https://doi.org/10.1016/j.eneco.2022.106160 doi: 10.1016/j.eneco.2022.106160 |
[60] | X. Y. Li, H. Z. Xu, The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from China's 35 industrial sectors, Energy Econ., 86 (2020), 10462–10476. https://doi.org/10.1016/j.eneco.2019.104628 doi: 10.1016/j.eneco.2019.104628 |
[61] | P. G. Saculsan, T. Kanamura, Examining risk and return profiles of renewable energy investment in developing countries: the case of the Philippines, Green Financ., 2 (2019), 135–150. https://doi.org/10.3934/GF.2020008 doi: 10.3934/GF.2020008 |
[62] | O. Sukharev, V. Ekaterina, Financial and non-financial investments: comparative econometric analysis of the impact on economic dynamics, Quant. Financ. Econ., 4 (2020), 382–411. https://doi.org/10.3934/QFE.2020018 doi: 10.3934/QFE.2020018 |
[63] | G. Carvalho, P. Roberto, S. Joelson, Venture capital backing: financial policies and persistence over time, Quant. Financ. Econ., 5 (2021), 640–663. https://doi.org/10.3934/QFE.2021029 doi: 10.3934/QFE.2021029 |
[64] | T. Li, J. Zhong, Z. Huang, Potential Dependence of Financial Cycles between Emerging and Developed Countries: Based on ARIMA-GARCH Copula Model, Emerg. Mark. Finance Trade, 56 (2019), 1237–1250. https://doi.org/10.1080/1540496x.2019.1611559 doi: 10.1080/1540496x.2019.1611559 |
[65] | Y. Liu, Z. Li, M. Xu, The influential factors of financial cycle spillover: evidence from China, Emerg. Mark. Financ. Trade, 56 (2020), 1336–1350. https://doi.org/10.1080/1540496x.2019.1658076 doi: 10.1080/1540496X.2019.1658076 |
[66] | Z. Li, C. Yang, Z. Huang, How does the fintech sector react to signals from central bank digital currencies?, Finance Res. Lett., 50 (2022), 103308–103313. https://doi.org/10.1016/j.frl.2022.103308 doi: 10.1016/j.frl.2022.103308 |
[67] | Y. Wang, S. Yin, X. Fang, W. Chen, Interaction of economic agglomeration, energy conservation and emission reduction: Evidence from three major urban agglomerations in China, Energy, 241 (2022), 122519–122532. https://doi.org/10.1016/j.energy.2021.122519 doi: 10.1016/j.energy.2021.122519 |
[68] | H. Baydoun, M, Age, The Effect of Energy Consumption and Economic Growth on Environmental Sustainability in the GCC Countries: Does Financial Development Matter?, Energies, 14 (2021), 5897–5915. https://doi.org/10.3390/en14185897 doi: 10.3390/en14185897 |
[69] | H. X. Liu, K. R. Du, J. Li, An improved approach to estimate direct rebound effect by incorporating energy efficiency: A revisit of China's industrial energy demand, Energ. Econ., 80 (2019), 720–730. https://doi.org/10.1016/j.eneco.2019.02.012 doi: 10.1016/j.eneco.2019.02.012 |
[70] | Y. J. Zhang, H. R. Peng, B. Su, Energy rebound effect in China's Industry: An aggregate and dis-aggregate analysis, Energ. Econ., 61 (2017), 199–208. https://doi.org/10.1016/j.eneco.2016.11.011 doi: 10.1016/j.eneco.2016.11.011 |
[71] | M. M. Xu, B. Q. Lin, S. Q. Wang, Towards energy conservation by improving energy efficiency? Evidence from China's metallurgical industry. Energy, 216 (2021), 119255–119355. https://doi.org/10.1016/j.energy.2020.119255 doi: 10.1016/j.energy.2020.119255 |
[72] | Y. Ushifusa, A. Tomohara, Productivity and Labor Density: Agglomeration Effects over Time, Atl. Econ. J., 41 (2013), 123–132. https://doi.org/10.1007/s11293-012-9354-y doi: 10.1007/s11293-012-9354-y |
[73] | P. H. Berkhout, J. C. Muskens, J. W. Velthuijsen, Defining the Rebound Effect, Energy Policy, 28 (2000), 425–432. https://doi.org/10.1016/S0301-4215(00)00022-7 doi: 10.1016/S0301-4215(00)00022-7 |
[74] | S. R. Mudakkar, K. Zamank, M. M. Khan, M. Ahmad, Energy for Economic Growth, Industrialization, Environment and Nature Resources: Living Is Just Enough, Renew. Sust. Energ. Rev., 25 (2013), 580–595. https://doi.org/10.1016/j.rser.2013.05.024 doi: 10.1016/j.rser.2013.05.024 |
[75] | D. Liu, B. Xiao, Can China achieve its carbon emission peaking? A scenario analysis based on STIRPAT and system dynamics model, Ecol. Indic., 93 (2018), 647–657. https://doi.org/10.1016/j.ecolind.2018.05.049 doi: 10.1016/j.ecolind.2018.05.049 |
[76] | Y. L. Chen, Z. Wang, Z. Q. Zhong, CO2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in China, Renew. Energ., 131 (2019), 208–216. https://doi.org/10.1016/j.renene.2018.07.047 doi: 10.1016/j.renene.2018.07.047 |
[77] | Q. Zhang, R. Brouwer, Is China Affected by the Resource Curse? A Critical Review of the Chinese Literature, J. Policy Model, 42 (2020), 133–152. https://doi.org/10.1016/j.jpolmod.2019.06.005 doi: 10.1016/j.jpolmod.2019.06.005 |
[78] | S. Chen, Y. Wang, K. Albitar, Z. Huang, Does ownership concentration affect corporate environmental responsibility engagement? The mediating role of corporate leverage, Borsa Istanbul Rev., 21 (2021), 13–24. https://doi.org/10.1016/j.bir.2021.02.001 doi: 10.1016/j.bir.2021.02.001 |
[79] | J. Hou, Y. Hou, Q. Wang, N. Yue, Can industrial agglomeration improve energy efficiency? Empirical evidence based on China's energy-intensive industries, Environ. Sci. Pollut. Res., 29 (2022), 80297–80311. https://doi.org/10.1007/s11356-022-21429-x doi: 10.1007/s11356-022-21429-x |
[80] | C. Fan, A. J. Scott, Industrial Agglomeration and Development: A Survey of Spatial Economic Issues in East Asia and A Statistical Analysis of Chinese Regions, Econ. Geogr., 79 (2003), 295–319. https://www.tandfonline.com/doi/abs/10.1111/j.19448287.2003.tb00213.x doi: 10.1111/j.19448287.2003.tb00213.x |
[81] | M. E. Porter, C. Linde, Toward a New Conception of the Environment- Competitiveness Relationship, J. Econ. Perspect, 9 (1995), 97–118. https://doi.org/10.1257/jep.9.4.97 doi: 10.1257/jep.9.4.97 |
[82] | 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, Int. J. Environ. Res. Public Health, 18 (2021), 8535–8561. https://doi.org/10.3390/ijerph18168535 doi: 10.3390/ijerph18168535 |
[83] | H. Zhao, B. Lin, Will agglomeration improve the energy efficiency in China's textile industry: Evidence and policy implications. Appl. Energy, 237 (2018), 326–337. https://doi.org/10.1016/j.apenergy.2018.12.068 doi: 10.1016/j.apenergy.2018.12.068 |
[84] | J. Wang, J. Ma, Has tourism industry agglomeration improved the total factor productivity of Chinese urban agglomerations?--The moderating effect of public epidemic, Front. Public Health, 525 (2022), 854681–854691. https://doi.org/10.3389/fpubh.2022.854681 doi: 10.3389/fpubh.2022.854681 |
[85] | J. He, Pollution haven hypothesis and environmental impacts of foreign direct investment: The case of industrial emission of sulfur dioxide (SO2) in Chinese provinces, Ecol. Econ., 60 (2006), 228–245. https://doi.org/10.1016/j.ecolecon.2005.12.008 doi: 10.1016/j.ecolecon.2005.12.008 |
[86] | H. Wu, Y. Hao, S. Ren, How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China, Energy Econ., 91 (2020), 104880–104898. https://doi.org/10.1016/j.eneco.2020.104880 doi: 10.1016/j.eneco.2020.104880 |
[87] | K. Dong, M. Shahbaz, J. Zhao, How do pollution fees affect environmental quality in China? Energ. Policy, 160 (2022), 112695–112709. https://doi.org/10.1016/j.enpol.2021.112695 doi: 10.1016/j.enpol.2021.112695 |
[88] | Z. Yang, Z. Xiong, W. Xue, Y. Zhou, The Impact of Pollution Fee Reform on the Emission of Water Pollutants: Evidence from Manufacturing Enterprises in China, Int. J. Environ. Res. Public Health, 19 (2022), 10660–10677. https://doi.org/10.3390/ijerph191710660 doi: 10.3390/ijerph191710660 |
[89] | C. Qu, J. Shao, Z. Shi, Does financial agglomeration promote the increase of energy efficiency in China? Energy Policy, 146 (2020), 111810–111825. https://doi.org/10.1016/j.enpol.2020.111810 doi: 10.1016/j.enpol.2020.111810 |
[90] | F. Han, R. Xie, J. Y. Fang, Y. Liu, The effects of urban agglomeration economies on carbon emissions: Evidence from Chinese cities, J. Clean. Prod., 172 (2018), 1096–1110. https://doi.org/10.1016/j.jclepro.2017.09.273 doi: 10.1016/j.jclepro.2017.09.273 |
[91] | H. Xie, Q. Chen, F. Lu, W. Wang, G. Yao, J. Yu, Spatial-temporal disparities and influencing factors of total-factor green use efficiency of industrial land in China, J. Clean. Prod., 207 (2019), 1047–1058. https://doi.org/10.1016/j.jclepro.2018.10.087 doi: 10.1016/j.jclepro.2018.10.087 |
[92] | X. Li, X. Lai, F. Zhang, Research on green innovation effect of industrial agglomeration from perspective of environmental regulation: Evidence in China, J. Clean. Prod., 288 (2021), 125583–125595. https://doi.org/10.1016/j.jclepro.2020.125583 doi: 10.1016/j.jclepro.2020.125583 |
[93] | S. Sorrell, J. Dimitropoulos, The rebound effect: Microeconomic definitions, limitations and extensions, Ecol. Econ., 65 (2008), 636–649. https://doi.org/10.1016/j.ecolecon.2007.08.013 doi: 10.1016/j.ecolecon.2007.08.013 |
[94] | S. Shao, K. Zhang, J. M. Dou, Energy conservation and emission reduction effect of economic agglomeration: Theory and Chinese experience, Manage. World, 35 (2019), 36–60. (In Chinese). https://doi.org/10.19744/j.cnki.11-1235/f.2019.0005. doi: 10.19744/j.cnki.11-1235/f.2019.0005 |
[95] | T. Jaynes, On the rationale of maximum-entropy methods, Proc. IEEE. Inst. Electr. Electron Eng., 70 (1982), 939–952. https://doi.org/10.1109/PROC.1982.12425 doi: 10.1109/PROC.1982.12425 |
[96] | B. Q. Lin, and R. P. Tan, Chinese Economic Cluster and Green Economic Efficiency, Econ. Res., 54 (2019), 119–132. (In Chinese) |
[97] | H. Abdi, L. J. Williams, Principal component analysis, Wiley interdiscip. Rev. comput. Stat., 2 (2010), 433–459. https://doi.org/10.1002/wics.101 doi: 10.1002/wics.101 |
[98] | Y. M. Zhu, S. X. Liu, Y. J. Li, Y. Pei, H. Q. Qiao, The mitigation effect of industrial agglomeration on environmental pollution: the theory and the empirical evidence, Environ. Econ. Res., 4 (2019), 86–107. (In Chinese). https://doi.org/10.19511/j.cnki.jee.2019.01.007 doi: 10.19511/j.cnki.jee.2019.01.007 |
[99] | T. H. Chang, P. J. Klenow, Misallocation and Manufacturing TFP in China and India, Q. J. Econ., 124 (2009), 1403–1448. https://doi.org/10.1162/qjec.2009.124.4.1403 doi: 10.1162/qjec.2009.124.4.1403 |
[100] | H. W. Wen, C. C. Lee, Z. Y. Song, Digitization 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 |
[101] | X. E. Qu, Empirical Analysis of Comprehensive Evaluation of Environmental Pollution in China, Ind. Econ. Res., 04 (2014), 51–102. (In Chinese). https://doi.org/10.13269/j.cnki.ier.2014.04.006 doi: 10.13269/j.cnki.ier.2014.04.006 |
[102] | Y. Sun, Y. Li, T. Yu, X. Zhang, L. Liu, P. Zhuang, Resource extraction, environmental pollution and economic development: Evidence from prefecture-level cities in China, Resour. Policy, 74 (2021), 102330–102342. https://doi.org/10.1016/j.resourpol.2021.102330 doi: 10.1016/j.resourpol.2021.102330 |
[103] | Z. H. Li, J. H. Zhu, J. J. He, The effects of digital financial inclusion on innovation and entrepreneurship: A network perspective, Electron. Res. Arch., 30 (2022), 4697–4715. https://doi.org/10.3934/era.2022238 doi: 10.3934/era.2022238 |
[104] | T. H. Li, J. Y. Wen, D. W. 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 |
[105] | Y. Liu, P. Failler, Y. Ding, Enterprise financialization and technological innovation: Mechanism and heterogeneity, PLoS One, 17 (2022), 1–21. https://doi.org/10.1371/journal.pone.0275461 doi: 10.1371/journal.pone.0275461 |
[106] | Y. Liu, P. Failler, Z. Y. Liu, Impact of Environmental Regulations on Energy Efficiency: A Case Study of China's Air Pollution Prevention and Control Action Plan, Sustainability, 14 (2022), 1–21. https://doi.org/10.3390/su14063168 doi: 10.3390/su14063168 |
mbe-20-04-307 S1.pdf |