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Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China

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Abstract

Based on the perspective of government-dominated and market-driven industrial co-agglomeration mode, the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control is explored by using spatial Durbin model, and the mediating effect of technological innovation is further tested. The results show that: (1) At the national level, the government-dominated industrial co-agglomeration only significantly promotes the local ecological environment pollution control, while the market-driven industrial co-agglomeration also can promote the ecological environment pollution control in the surrounding region through its spatial spillover effect. Moreover, there is a significant inverted “U-shaped” curve relationship between the economic development level and ecological environment pollution. Additionally, the environment regulation is also conducive to promoting the ecological environment pollution control, while the industrial structure and foreign direct investment will lead to more serious ecological environment pollution; (2) In the east region, the government-dominated and market-driven industrial co-agglomeration can promote the ecological environment pollution control in the local and surrounding regions, and the promotion effect and spatial spillover effect of market-driven industrial co-agglomeration are greater. However, in the central and west regions, the government-dominated industrial co-agglomeration and market-driven industrial co-agglomeration only promote the local ecological environment pollution control. (3) Technological innovation has partial mediating effect in the impact of government-dominated and market-driven industrial co-agglomeration on the ecological environment pollution control, namely that the government-dominated and market-driven industrial co-agglomeration not only can directly promote the ecological environment pollution control, but also can indirectly promote the ecological environment pollution control through the mediating effect of technological innovation.

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Abbreviations

EPI :

Ecological environment pollution index

Gov_Coagg :

Government-dominated producer services and manufacturing industrial co-agglomeration

Mar_Coagg :

Market-driven producer services and manufacturing industrial co-agglomeration

Pgdp :

Economic development level

Er :

Environment regulation

Is :

Industrial structure

FDI :

Foreign direct investment

W :

Spatial weight matrix

ρ:

Spatial lag coefficient

LogL :

Log-likelihood

Obs.:

Observation

VIF:

Variance inflation factor

SDM:

Spatial Durbin model

TI :

Technological innovation level

References

  • Akbostanci, E., Tunc, G. I., & Turutasik, S. (2007). Pollution haven hypothesis and the role of dirty industries in Turkey’s exports. Environment and Development Economics, 12(2), 297–322.

    Article  Google Scholar 

  • Akram, R., Chen, F., Khalid, F., Ye, Z., & Majeed, M. T. (2020). Heterogeneous effects of energy efficiency and renewable energy on carbon emissions: Evidence from develo** countries. Journal of Cleaner Production, 247, 119122.

    Article  Google Scholar 

  • Akram, Z., Engo, J., Akram, U., & Zafar, M. W. (2019). Identification and analysis of driving factors of CO2 emissions from economic growth in Pakistan. Environmental Science and Pollution Research, 26(19), 19481–19489.

    Article  CAS  Google Scholar 

  • Anis, O., & Tarek, B. H. (2020). Foreign investment and air pollution: Do good governance and technological innovation matter? Environmental Research, 185, 109469.

    Article  CAS  Google Scholar 

  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.

    Article  CAS  Google Scholar 

  • Cheng, Z. (2016). The spatial correlation and interaction between manufacturing agglomeration and environmental pollution. Ecological Indicators, 61, 1024–1032.

    Article  Google Scholar 

  • De Leeuw, F. A., Moussiopoulos, N., Sahm, P., & Bartonova, A. (2001). Urban air quality in larger conurbations in the European Union. Environmental Modelling & Software, 16(4), 399–414.

    Article  Google Scholar 

  • Dou, J., & Han, X. (2019). How does the industry mobility affect pollution industry transfer in China: Empirical test on pollution haven hypothesis and porter hypothesis. Journal of Cleaner Production, 217, 105–115.

    Article  Google Scholar 

  • Ehrenfeld, J. (2003). Putting a spotlight on metaphors and analogies in industrial ecology. Journal of Industrial Ecology, 7(1), 1–4.

    Article  Google Scholar 

  • Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 26(3), 244–268.

    Article  Google Scholar 

  • Ellison, G., Glaeser, E. L., & Kerr, W. R. (2010). What causes industry agglomeration? Evidence from coagglomeration patterns. American Economic Review, 100(3), 1195–1213.

    Article  Google Scholar 

  • Engo, J. (2020). Driving forces and decoupling indicators for carbon emissions from the industrial sector in Egypt, Morocco, Algeria, and Tunisia. Environmental Science and Pollution Research, 1–14.

  • Erdogan, S. (2020). Analyzing the environmental Kuznets curve hypothesis: the role of disaggregated transport infrastructure investments. Sustainable Cities and Society, 61, 102338.

    Article  Google Scholar 

  • Farahbod, F. (2020). Practical investigation of usage of nano bottom in the production of fresh water from brackish wastewater in a closed shallow solar basin. Environmental Progress & Sustainable Energy, 40, e13496.

    Google Scholar 

  • Farahbod, F. (2020b). Simultaneous use of mass transfer and thermodynamics equations to estimate the amount of removed greenhouse gas from the environment by a stream of water. Environmental Modeling & Assessment, 1–7.

  • Feng, Y., & He, F. (2020). The effect of environmental information disclosure on environmental quality: Evidence from Chinese cities. Journal of Cleaner Production, 276, 124027.

    Article  Google Scholar 

  • Feng, Y., & Wang, X. (2020). Effects of urban sprawl on haze pollution in China based on dynamic spatial Durbin model during 2003–2016. Journal of Cleaner Production, 242, 118368.

    Article  Google Scholar 

  • Feng, Y., Wang, X., Du, W., Wu, H., & Wang, J. (2019). Effects of environmental regulation and FDI on urban innovation in China: A spatial Durbin econometric analysis. Journal of Cleaner Production, 235, 210–224.

    Article  Google Scholar 

  • Freire-González, J., Vivanco, D. F., & Puig-Ventosa, I. (2017). Economic structure and energy savings from energy efficiency in households. Ecological Economics, 131, 12–20.

    Article  Google Scholar 

  • Gao, Y., & Zhang, M. (2019). The measure of technical efficiency of China’s provinces with carbon emission factor and the analysis of the influence of structural variables. Structural Change and Economic Dynamics, 49, 120–129.

    Article  Google Scholar 

  • Han, F., **e, R., & Fang, J. (2018). Urban agglomeration economies and industrial energy efficiency. Energy, 162, 45–59.

    Article  Google Scholar 

  • He, C., Huang, Z., & Ye, X. (2014). Spatial heterogeneity of economic development and industrial pollution in urban China. Stochastic Environmental Research and Risk Assessment, 28(4), 767–781.

    Article  Google Scholar 

  • He, J. (2006). Pollution haven hypothesis and environmental impacts of foreign direct investment: The case of industrial emission of sulfur dioxide (SO2) in Chinese provinces. Ecological Economics, 60(1), 228–245.

    Article  Google Scholar 

  • He, W., Tan, L., Liu, Z. J., & Zhang, H. (2020). Property rights protection, environmental regulation and corporate financial performance: Revisiting the Porter Hypothesis. Journal of Cleaner Production, 264, 121615.

    Article  Google Scholar 

  • Hosoe, M., & Naito, T. (2006). Trans-boundary pollution transmission and regional agglomeration effects. Papers in Regional Science, 85(1), 99–120.

    Article  Google Scholar 

  • Hossain, M. A., Engo, J., & Chen, S. (2021). The main factors behind Cameroon’s CO2 emissions before, during and after the economic crisis of the 1980s. Environment, Development and Sustainability, 23, 4500–4520.

    Article  Google Scholar 

  • Howard, E., Newman, C., & Tarp, F. (2016). Measuring industry coagglomeration and identifying the driving forces. Journal of Economic Geography, 16(5), 1055–1078.

    Article  Google Scholar 

  • Huo, T., Ren, H., Zhang, X., Cai, W., Feng, W., Zhou, N., & Wang, X. (2018). China’s energy consumption in the building sector: A statistical yearbook-energy balance sheet based splitting method. Journal of Cleaner Production, 185, 665–679.

    Article  Google Scholar 

  • Huo, T., Tang, M., Cai, W., Ren, H., Liu, B., & Hu, X. (2020). Provincial total-factor energy efficiency considering floor space under construction: An empirical analysis of China’s construction industry. Journal of Cleaner Production, 244, 118749.

    Article  Google Scholar 

  • **, W., Zhang, H. Q., Liu, S. S., & Zhang, H. B. (2019). Technological innovation, environment regulation, and green total factor efficiency of industrial water resources. Journal of Cleaner Production, 211, 61–69.

    Article  Google Scholar 

  • Ke, S., He, M., & Yuan, C. (2014). Synergy and co-agglomeration of producer services and manufacturing: A panel data analysis of Chinese cities. Regional Studies, 48(11), 1829–1841.

    Article  Google Scholar 

  • Lin, B., & Chen, Y. (2019). Will economic infrastructure development affect the energy intensity of China’s manufacturing industry? Energy Policy, 132, 122–131.

    Article  Google Scholar 

  • Liu, J., Cheng, Z., & Zhang, H. (2017). Does industrial agglomeration promote the increase of energy efficiency in China? Journal of Cleaner Production, 164, 30–37.

    Article  Google Scholar 

  • Liu, J., Qu, J., & Zhao, K. (2019). Is China’s development conforms to the Environmental Kuznets Curve hypothesis and the pollution haven hypothesis? Journal of Cleaner Production, 234, 787–796.

    Article  Google Scholar 

  • Mi, Z., Zeng, G., **n, X., Shang, Y., & Hai, J. (2018). The extension of the Porter hypothesis: Can the role of environment regulation on economic development be affected by other dimensional regulations? Journal of Cleaner Production, 203, 933–942.

    Article  Google Scholar 

  • Musah, M., Kong, Y., Mensah, I. A., Antwi, S. K., & Donkor, M. (2020). The connection between urbanization and carbon emissions: A panel evidence from West Africa (pp. 1–28). Environment.

    Google Scholar 

  • Ouyang, X., Mao, X., Sun, C., & Du, K. (2019). Industrial energy efficiency and driving forces behind efficiency improvement: Evidence from the Pearl River Delta urban agglomeration in China. Journal of Cleaner Production, 220, 899–909.

    Article  Google Scholar 

  • Pan, X., Guo, S., Han, C., Wang, M., Song, J., & Liao, X. (2020). Influence of FDI quality on energy efficiency in China based on seemingly unrelated regression method. Energy, 192, 116463.

    Article  Google Scholar 

  • Porter, M. E., & Van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. Journal of Economic Perspectives, 9(4), 97–118.

    Article  Google Scholar 

  • Sarkodie, S. A., & Ozturk, I. (2020). Investigating the environmental Kuznets curve hypothesis in Kenya: A multivariate analysis. Renewable and Sustainable Energy Reviews, 117, 109481.

    Article  Google Scholar 

  • Sarkodie, S. A., & Strezov, V. (2019). A review on environmental Kuznets curve hypothesis using bibliometric and meta-analysis. Science of the Total Environment, 649, 128–145.

    Article  CAS  Google Scholar 

  • Shao, Q., Wang, X., Zhou, Q., & Balogh, L. (2019). Pollution haven hypothesis revisited: a comparison of the BRICS and MINT countries based on VECM approach. Journal of Cleaner Production, 227, 724–738.

    Article  Google Scholar 

  • Shen, J., Wang, S., Liu, W., & Chu, J. (2019). Does migration of pollution-intensive industries impact environmental efficiency? Evidence supporting “Pollution Haven Hypothesis.” Journal of Environmental Management, 242, 142–152.

    Article  Google Scholar 

  • Song, M., Wang, S., & Sun, J. (2018). Environmental regulations, staff quality, green technology, R&D efficiency, and profit in manufacturing. Technological Forecasting and Social Change, 133, 1–14.

    Article  Google Scholar 

  • Song, Y., Yang, T., Li, Z., Zhang, X., & Zhang, M. (2020). Research on the direct and indirect effects of environmental regulation on environmental pollution: Empirical evidence from 253 prefecture-level cities in China. Journal of Cleaner Production, 269, 122425.

    Article  Google Scholar 

  • Taherizadeh, M., Farahbod, F., & Ilkhani, A. (2020). Empirical evaluation of proposed treatment unit for saline wastewater softening. Journal of Applied Water Engineering and Research, 1–18.

  • Van Oort, F. G. (2017). Urban growth and innovation: Spatially bounded externalities in the Netherlands. Milton Park: Routledge.

    Book  Google Scholar 

  • Verhoef, E. T., & Nijkamp, P. (2002). Externalities in urban sustainability: environmental versus localization-type agglomeration externalities in a general spatial equilibrium model of a single-sector monocentric industrial city. Ecological Economics, 40(2), 157–179.

    Article  Google Scholar 

  • Wang, N., Zhu, Y., & Yang, T. (2020). The impact of transportation infrastructure and industrial agglomeration on energy efficiency: Evidence from China’s industrial sectors. Journal of Cleaner Production, 244, 118708.

    Article  Google Scholar 

  • Wang, X., & Luo, Y. (2020). Has technological innovation capability addressed environmental pollution from the dual perspective of FDI quantity and quality? Evidence from China. Journal of Cleaner Production, 258, 120941.

    Article  Google Scholar 

  • Wang, Y., Sun, X., & Guo, X. (2019). Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors. Energy Policy, 132, 611–619.

    Article  Google Scholar 

  • **n, D., & Zhang, Y. (2020). Threshold effect of OFDI on China’s provincial environmental pollution. Journal of Cleaner Production, 258, 120608.

    Article  CAS  Google Scholar 

  • Yang, H., Lu, F., & Zhang, F. (2020). Exploring the effect of producer services agglomeration on China’s energy efficiency under environmental constraints. Journal of Cleaner Production, 263, 121320.

    Article  Google Scholar 

  • Yang, Z., & Wei, X. (2019). The measurement and influences of China’s urban total factor energy efficiency under environmental pollution: Based on the game cross-efficiency DEA. Journal of Cleaner Production, 209, 439–450.

    Article  Google Scholar 

  • Yilanci, V., Bozoklu, S., & Gorus, M. S. (2020). Are BRICS countries pollution havens? Evidence from a bootstrap ARDL bounds testing approach with a Fourier function. Sustainable Cities and Society, 55, 102035.

    Article  Google Scholar 

  • Yu, H., Zheng, S., Zhao, M., Wu, H., Guo, Y., & Li, Y. (2020). Reexamining the relationships among urbanization, industrial structure, and environmental pollution in China—New evidence using the dynamic threshold panel model. Energy Reports, 6, 28–39.

    Article  Google Scholar 

  • Yuan, B., & Zhang, Y. (2020). Flexible environmental policy, technological innovation and sustainable development of China’s industry: The moderating effect of environment regulatory enforcement. Journal of Cleaner Production, 243, 118543.

    Article  Google Scholar 

  • Zeng, D. Z., & Zhao, L. (2009). Pollution havens and industrial agglomeration. Journal of Environmental Economics and Management, 58(2), 141–153.

    Article  Google Scholar 

  • Zhang, B., Wang, B., & Wang, Z. (2017). Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan. Journal of Cleaner Production, 156, 855–864.

    Article  Google Scholar 

  • Zhao, H., & Lin, B. (2020). Impact of foreign trade on energy efficiency in China’s textile industry. Journal of Cleaner Production, 245, 118878.

    Article  Google Scholar 

  • Zhao, H., & Lin, B. (2019). Will agglomeration improve the energy efficiency in China’s textile industry: Evidence and policy implications. Applied Energy, 237, 326–337.

    Article  Google Scholar 

  • Zhao, X., & Li, P. (2020). Is the energy efficiency improvement conducive to the saving of residential electricity consumption in China? Journal of Cleaner Production, 249, 119339.

    Article  Google Scholar 

  • Zheng, Q., & Lin, B. (2018). Impact of industrial agglomeration on energy efficiency in China’s paper industry. Journal of Cleaner Production, 184, 1072–1080.

    Article  Google Scholar 

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Acknowledgements

We are grateful to three anonymous reviewers who contribute in ameliorating the original version of this manuscript in the peer review of this work.

Funding

This study was funded by the National Natural Science Foundation of China (Grant No. 72004087; Grant No. 71673145; Grant No. 41661116; Grant No. 72064017), the Humanities and Social Science Fund of Ministry of Education of China (Grant No. 20YJC790161), the Research Project of Humanities and Social Sciences in Universities of Jiangxi Province (Grant No. JJ20209), the Major Program of National Fund of Philosophy and Social Science of China (Grant No. 16ZDA047; Grant No. 18ZDA047) and the Education Science Planning Project of Jiangxi Province (Grant No. 20ZD004).

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Authors and Affiliations

  1. School of Economics and Management, Nanchang University, Nanchang, 330031, China

    Haochang Yang

  2. School of Business, Guilin University of Electronic Technology, Guilin, 541004, China

    Faming Zhang

  3. School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Yixin He

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  1. Haochang Yang
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Yang, H., Zhang, F. & He, Y. Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China. Environ Dev Sustain 23, 16119–16144 (2021). https://doi.org/10.1007/s10668-021-01339-7

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