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The impact of growth, energy and financial development on environmental pollution in China: New evidence from a spatial econometric analysis

Zhao, Jing, Zhao, Ziru, Zhang, Huan·2021·Energy Economics

Abstract

Abstract This research examines data from 30 Chinese provinces from 1999 to 2017 to investigate the impacts of economic growth, energy consumption, and financial development on environmental pollution. Using spatial econometrics, we find that energy consumption has increased environmental pollution. Moreover, the direct effects of two indicators measuring financial development—financial depth and financial efficiency—on environmental pollution are directly negative and positive, respectively. Moreover, these two financial development indicators moderate the effects of technical progress and industry structure on environmental pollution differently. The “inverted N”-shaped environmental Kuznets curve relationship is well supported for SO2 and solid waste.

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Research works printed but not linked: 95

  1. Abbasi, 2016, CO2 emissions and financial development in an emerging economy: an augmented VAR approach, Energy Policy, 90, 102, 10.1016/j.enpol.2015.12.017 · DOI · Paper page
  2. Ahmed, 2016, Biomass energy, technological progress and the environmental Kuznets curve: evidence from selected European countries, Biomass Bioenergy, 90, 202, 10.1016/j.biombioe.2016.04.004 · DOI · Paper page
  3. Alam, 2012, Energy consumption, carbon emissions and economic growth nexus in Bangladesh: cointegration and dynamic causality analysis, Energy Policy, 45, 217, 10.1016/j.enpol.2012.02.022 · DOI · Paper page
  4. Albiman, 2015, The relationship between energy consumption, CO2 emissions and economic growth in Tanzania, International Journal of Energy Sector Management, 9, 361, 10.1108/IJESM-05-2014-0006 · DOI
  5. Al-Mulali, 2015, Does financial development reduce environmental degradation? Evidence from a panel study of 129 countries, Environ. Sci. Pollut. Res., 22, 14891, 10.1007/s11356-015-4726-x · DOI · Paper page
  6. Al-Mulali, 2016, Investigating the presence of the environmental Kuznets curve (EKC) hypothesis in Kenya: an autoregressive distributed lag (ARDL) approach, Nat. Hazards, 80, 1729, 10.1007/s11069-015-2050-x · DOI · Paper page
  7. Ang, 2008, Economic development, pollutant emissions and energy consumption in Malaysia, J. Policy Model, 30, 271, 10.1016/j.jpolmod.2007.04.010 · DOI · Paper page
  8. Aung, 2017, Economic growth and environmental pollution in Myanmar: an analysis of environmental Kuznets curve, Environ. Sci. Pollut. Res., 24, 1
  9. Balaguer, 2018, The role of education in the environmental Kuznets curve. Evidence from Australian data, Energy Econ., 70, 289, 10.1016/j.eneco.2018.01.021 · DOI
  10. Baron, 1986, The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations, J. Pers. Soc. Psychol., 51, 1173, 10.1037/0022-3514.51.6.1173 · DOI · Paper page
  11. Bekhet, 2017, CO2 emissions, energy consumption, economic growth, and financial development in GCC countries: dynamic simultaneous equation models, Renew. Sust. Energ. Rev., 70, 117, 10.1016/j.rser.2016.11.089 · DOI · Paper page
  12. Bi, 2014, Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model, Energy Policy, 66, 537, 10.1016/j.enpol.2013.10.056 · DOI · Paper page
  13. Birdsall, 1993, Trade policy and industrial pollution in Latin America: where are the pollution havens?, J. Environ. Dev., 2, 137, 10.1177/107049659300200107 · DOI · Paper page
  14. Boutabba, 2014, The impact of financial development, income, energy and trade on carbon emissions: evidence from the Indian economy, Econ. Model., 40, 33, 10.1016/j.econmod.2014.03.005 · DOI · Paper page
  15. Brajer, 2011, Searching for an environmental Kuznets curve in China's air pollution, China Econ. Rev., 22, 383, 10.1016/j.chieco.2011.05.001 · DOI
  16. Brännlund, 2007, Increased energy efficiency and the rebound effect: effects on consumption and emissions, Energy Econ., 29, 1, 10.1016/j.eneco.2005.09.003 · DOI · Paper page
  17. Chen, 2015, The estimation of environmental Kuznets curve in China: nonparametric panel approach, Comput. Econ., 46, 405, 10.1007/s10614-015-9486-7 · doi:10.1007/s10614-015-9486-7
  18. Cole, 2005, Industrial characteristics, environmental regulations and air pollution: an analysis of the UK manufacturing sector, J. Environ. Econ. Manag., 50, 121, 10.1016/j.jeem.2004.08.001 · DOI · Paper page
  19. Dhakal, 2009, Urban energy use and carbon emissions from cities in China and policy implications, Energy Policy, 37, 4208, 10.1016/j.enpol.2009.05.020 · DOI · Paper page
  20. Dasgupta, 2001, Pollution and capital markets in developing countries, J. Environ. Econ. Manag., 42, 310, 10.1006/jeem.2000.1161 · DOI · Paper page
  21. Debarsy, 2010, Testing for spatial autocorrelation in a fixed effects panel data model, Reg. Sci. Urban Econ., 40, 453, 10.1016/j.regsciurbeco.2010.06.001 · DOI
  22. Diao, 2009, EKC analysis for studying economic growth and environmental quality: a case study in China, J. Clean. Prod., 17, 541, 10.1016/j.jclepro.2008.09.007 · DOI · Paper page
  23. Dong, 2012, FDI and environmental regulation: pollution haven or a race to the top?, J. Regul. Econ., 41, 216, 10.1007/s11149-011-9162-3 · doi:10.1007/s11149-011-9162-3
  24. Du, 2012, Economic development and carbon dioxide emissions in China: provincial panel data analysis, China Econ. Rev., 23, 371, 10.1016/j.chieco.2012.02.004 · DOI · Paper page
  25. Elhorst, 2003, Specification and estimation of spatial panel data models, Int. Reg. Sci. Rev., 26, 244, 10.1177/0160017603253791 · DOI · Paper page
  26. Elhorst, 2010, Dynamic panels with endogenous interaction effects when is small, Reg. Sci. Urban Econ., 40, 272, 10.1016/j.regsciurbeco.2010.03.003 · DOI
  27. Elhorst, 2014, Matlab software for spatial panels, Int. Reg. Sci. Rev., 37, 389, 10.1177/0160017612452429 · DOI · Paper page
  28. Feng, 2015, Research on the impact of science-finance on technological innovation based on panel data model, China Soft Science, 6, 139
  29. Fodha, 2010, Economic growth and pollutant emissions in Tunisia: an empirical analysis of the environmental Kuznets curve, Energy Policy, 38, 1150, 10.1016/j.enpol.2009.11.002 · DOI · Paper page
  30. Frankel, 1999, Does trade cause growth?, Am. Econ. Rev., 89, 379, 10.1257/aer.89.3.379 · DOI · Paper page
  31. Frankel, 2002, An estimate of the effect of common currencies on trade and income, Q. J. Econ., 117, 437, 10.1162/003355302753650292 · DOI · Paper page
  32. García-Herrero, 2009, What explains the low profitability of Chinese banks?, J. Bank. Financ., 33, 2080, 10.1016/j.jbankfin.2009.05.005 · DOI · Paper page
  33. Ge, 2013, Quantifying the risk to crude oil imports in China: an improved portfolio approach, Energy Econ., 40, 72, 10.1016/j.eneco.2013.06.009 · DOI
  34. Govindaraju, 2013, The dynamic links between CO2 emissions, economic growth and coal consumption in China and India, Appl. Energy, 104, 310, 10.1016/j.apenergy.2012.10.042 · DOI · Paper page
  35. Gu, 2015, Inequality and saving: further evidence from integrated economies, Rev. Dev. Econ., 19, 15, 10.1111/rode.12125 · doi:10.1111/rode.12125
  36. Guariglia, 2008, Could financial distortions be no impediment to economic growth after all? Evidence from China, Social Science Electronic Publishing, 36, 633
  37. Halicioglu, 2009, An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey, Energy Policy, 37, 1156, 10.1016/j.enpol.2008.11.012 · DOI · Paper page
  38. Hao, 2016, Does the environmental Kuznets curve for coal consumption in China exist? New evidence from spatial econometric analysis, Energy, 114, 1214, 10.1016/j.energy.2016.08.075 · DOI
  39. Hao, 2016, Is CO2 emission a side effect of financial development? An empirical analysis for China, Environ. Sci. Pollut. Res., 23, 21041, 10.1007/s11356-016-7315-8 · DOI
  40. He, 2015, Environmental regulation, technology change, and air pollution: a panel study on Tianjin, Science of Science and Management of S.& T., 36, 51
  41. Ilyina, 2011, Technology and financial development, J. Money, Credit, Bank., 43, 899, 10.1111/j.1538-4616.2011.00401.x · DOI
  42. Jalil, 2011, The impact of growth, energy and financial development on the environment in China: a cointegration analysis, Energy Econ., 33, 284, 10.1016/j.eneco.2010.10.003 · DOI · Paper page
  43. Jalil, 2009, Environment Kuznets curve for co emissions: a cointegration analysis for China, Energy Policy, 37, 5167, 10.1016/j.enpol.2009.07.044 · DOI · Paper page
  44. Kaika, 2013, The environmental Kuznets curve (EKC) theory-part a: concept, causes and the CO2 emissions case, Energy Policy, 62, 1392, 10.1016/j.enpol.2013.07.131 · DOI · Paper page
  45. Kang, 2016, Environmental Kuznets curve for CO2 emissions in China: a spatial panel data approach, Ecol. Indic., 63, 231, 10.1016/j.ecolind.2015.12.011 · DOI · Paper page
  46. Katircioğlu, 2017, Testing the moderating role of financial development in an environmental Kuznets curve: empirical evidence from Turkey, Renew. Sust. Energ. Rev., 68, 572, 10.1016/j.rser.2016.09.127 · DOI · Paper page
  47. Kelejian, 1998, A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances, J. Real Estate Financ. Econ., 17, 99, 10.1023/A:1007707430416 · DOI · Paper page
  48. King, 1993, Finance and growth: Schumpeter might be right, Q. J. Econ., 108, 717, 10.2307/2118406 · DOI · Paper page
  49. Kwang, 2002, Dynamic process of technology spillover: a transfer function approach, Technovation, 22, 437, 10.1016/S0166-4972(01)00026-8 · doi:10.1016/s0166-4972(01)00026-8
  50. Lee, 2010, A spatial dynamic panel data model with both time and individual fixed effects, Econometric Theory, 26, 564, 10.1017/S0266466609100099 · doi:10.1017/s0266466609100099
  51. Li, 2016, Environmental Kuznets curve in China: new evidence from dynamic panel analysis, Energy Policy, 91, 138, 10.1016/j.enpol.2016.01.002 · DOI · Paper page
  52. Liu, 2018, From club convergence of per capita industrial pollutant emissions to industrial transfer effects: an empirical study across 285 cities in China, Energy Policy, 121, 300, 10.1016/j.enpol.2018.06.039 · DOI
  53. Llorca, 2009, SO2 emissions and the environmental Kuznets curve: the case of Chinese provinces, J. Chin. Econ. Bus. Stud., 7, 1, 10.1080/14765280802604656 · DOI
  54. Lundgren, 2003, A real options approach to abatement investments and green goodwill, Environ. Resour. Econ., 25, 17, 10.1023/A:1023602426857 · doi:10.1023/a:1023602426857
  55. Ma, 2008, China’s changing energy intensity trend: a decomposition analysis, Energy Econ., 30, 1037, 10.1016/j.eneco.2007.05.005 · DOI · Paper page
  56. Maddison, 2006, Environmental Kuznets curves: a spatial econometric approach, J. Environ. Econ. Manag., 51, 218, 10.1016/j.jeem.2005.07.002 · DOI · Paper page
  57. Markandya, 2006, Energy intensity in transition economies: is there convergence towards the EU average?, Energy Econ., 28, 121, 10.1016/j.eneco.2005.10.005 · doi:10.1016/j.eneco.2005.10.005
  58. Narayan, 2010, Carbon dioxide emissions and economic growth: panel data evidence from developing countries, Energy Policy, 38, 661, 10.1016/j.enpol.2009.09.005 · DOI · Paper page
  59. Narayan, 2012, The energy consumption-real GDP nexus revisited: empirical evidence from 93 countries, Econ. Model., 29, 303, 10.1016/j.econmod.2011.10.016 · DOI
  60. Nasir, 2011, Environmental Kuznets curve for carbon emissions in Pakistan: an empirical investigation, Energy Policy, 39, 1857, 10.1016/j.enpol.2011.01.025 · DOI · Paper page
  61. Omri, 2015, Financial development, environmental quality, trade and economic growth: what causes what in MENA countries?, Energy Econ., 48, 242, 10.1016/j.eneco.2015.01.008 · DOI · Paper page
  62. Onafowora, 2014, Bounds testing approach to analysis of the environment Kuznets curve hypothesis, Energy Econ., 44, 47, 10.1016/j.eneco.2014.03.025 · DOI · Paper page
  63. Ozturk, 2013, The long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in Turkey, Energy Econ., 36, 262, 10.1016/j.eneco.2012.08.025 · DOI · Paper page
  64. Perman, 2003, Evidence from panel unit root and cointegration tests that the environmental Kuznets curve does not exist, Australian Journal of Agricultural & Resource Economics, 47, 325, 10.1111/1467-8489.00216 · DOI · Paper page
  65. Sadorsky, 2010, The impact of financial development on energy consumption in emerging economies, Energy Policy, 38, 2528, 10.1016/j.enpol.2009.12.048 · DOI · Paper page
  66. Shahbaz, 2012, Environmental Kuznets curve hypothesis in Pakistan: cointegration and Granger causality, Renew. Sust. Energ. Rev., 16, 2947, 10.1016/j.rser.2012.02.015 · DOI · Paper page
  67. Shahbaz, 2013, Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia, Renew. Sust. Energ. Rev., 25, 109, 10.1016/j.rser.2013.04.009 · DOI · Paper page
  68. Sharma, 2011, Determinants of carbon dioxide emissions: empirical evidence from 69 countries, Appl. Energy, 88, 376, 10.1016/j.apenergy.2010.07.022 · DOI · Paper page
  69. Song, 2008, An empirical test of the environmental Kuznets curve in China: a panel cointegration approach, China Econ. Rev., 19, 381, 10.1016/j.chieco.2007.10.001 · DOI · Paper page
  70. Song, 2011, Growing like China, Am. Econ. Rev., 101, 196, 10.1257/aer.101.1.196 · DOI · Paper page
  71. Song, 2013, Inflection point of environmental Kuznets curve in mainland China, Energy Policy, 57, 14, 10.1016/j.enpol.2012.04.036 · DOI
  72. Song, 2016, Public health in China: an environmental and socio-economic perspective, Atmos. Environ., 129, 9, 10.1016/j.atmosenv.2015.12.021 · DOI
  73. Tamazian, 2010, Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies, Energy Econ., 32, 137, 10.1016/j.eneco.2009.04.004 · DOI · Paper page
  74. Tamazian, 2009, Does higher economic and financial development lead to environmental degradation: evidence from BRIC countries, Energy Policy, 37, 246, 10.1016/j.enpol.2008.08.025 · DOI · Paper page
  75. Wang, 2013, The relationship between carbon dioxide emissions and economic growth: quantile panel-type analysis, Qual. Quant., 47, 1337, 10.1007/s11135-011-9594-y · DOI
  76. Wang, 2019, Spatial economic dependency in the environmental Kuznets curve of carbon dioxide: the case of China, J. Clean. Prod., 218, 498, 10.1016/j.jclepro.2019.01.318 · doi:10.1016/j.jclepro.2019.01.318
  77. Wang, 2007, Industrial ownership and environmental performance: evidence from China, Environ. Resour. Econ., 36, 255, 10.1007/s10640-006-9027-x · doi:10.1007/s10640-006-9027-x
  78. Wang, 2013, Estimating the environmental Kuznets curve for ecological footprint at the global level: a spatial econometric approach, Ecol. Indic., 34, 15, 10.1016/j.ecolind.2013.03.021 · DOI
  79. Wei, 2014, Industrial SO2 pollution and agricultural losses in China: evidence from heavy air polluters, J. Clean. Prod., 64, 404, 10.1016/j.jclepro.2013.10.027 · DOI
  80. Xia, 2017, The association between air pollution and population health risk for respiratory infection: a case study of Shenzhen, China, Int. J. Environ. Res. Public Health, 14, 950, 10.3390/ijerph14090950 · DOI
  81. Xiong, 2018, Financial development and carbon emissions in Chinese provinces: a spatial panel data analysis, The Singapore Economic Review, 63, 447, 10.1142/S0217590817400203 · DOI
  82. Xu, 2018, Investigating environmental Kuznets curve in China–aggregation bias and policy implications, Energy Policy, 114, 315, 10.1016/j.enpol.2017.12.027 · DOI
  83. Yang, 2012, Whether economic growth will automatically solve the environmental problems? China population, Resources and Environment, 22, 160
  84. Yang, 2015, Study on the impact of economic growth and financial development on the environment in China, Journal of Systems Science and Information, 3, 334, 10.1515/JSSI-2015-0334 · doi:10.1515/jssi-2015-0334
  85. Yang, 2015, The fragility of the environmental Kuznets curve: revisiting the hypothesis with Chinese data via an “extreme bound analysis”, Ecol. Econ., 109, 41, 10.1016/j.ecolecon.2014.10.023 · DOI
  86. Yin, 2015, The effects of environmental regulation and technical progress on CO2 Kuznets curve: an evidence from China, Energy Policy, 77, 97, 10.1016/j.enpol.2014.11.008 · DOI · Paper page
  87. Yuxiang, 2011, Financial development and environmental performance: evidence from China, Environ. Dev. Econ., 16, 93, 10.1017/S1355770X10000422 · DOI
  88. Zhang, 2011, The impact of financial development on carbon emissions: an empirical analysis in China, Energy Policy, 39, 2197, 10.1016/j.enpol.2011.02.026 · DOI · Paper page
  89. Zhang, 2016, Exploring the impact of environmental regulation on economic growth, energy use, and CO2 emissions nexus in China, Nat. Hazards, 84, 213, 10.1007/s11069-016-2417-7 · doi:10.1007/s11069-016-2417-7
  90. Zhang, 2012, Financial development and economic growth: recent evidence from China, J. Comp. Econ., 40, 393, 10.1016/j.jce.2012.01.001 · DOI · Paper page
  91. Zhang, 2014, Long-term exposure to high particulate matter pollution and cardiovascular mortality: a 12-year cohort study in four cities in northern China, Environ. Int., 62, 41, 10.1016/j.envint.2013.09.012 · DOI
  92. Zhang, 2016, Non-performing loans, moral hazard and regulation of the Chinese commercial banking system, J. Bank. Financ., 63, 48, 10.1016/j.jbankfin.2015.11.010 · DOI
  93. Zhao, 2015, Impact of environmental regulations on the efficiency and CO2 emissions of power plants in China, Appl. Energy, 149, 238, 10.1016/j.apenergy.2015.03.112 · DOI · Paper page
  94. Zhou, 2013, Efficiency of financial development on improving technological innovation: interactions with carbon markets, J. Appl. Sci., 13, 40, 10.3923/jas.2013.5700.5707 · DOI
  95. Zhou, 2017, The impacts of technical progress on sulfur dioxide Kuznets curve in China: a spatial panel data approach, Sustainability, 9, 674, 10.3390/su9040674 · DOI

Metadata

Authors
Zhao, J., Zhao, Z., & Zhang, H.
Venue
Energy Economics
Publisher
Elsevier BV
Published
2021-01
Volume
93
Pages
104506
ISSN
0140-9883 (ISSN-L)
OpenAlex
W2971691957
Cited by
261
References
4
FWCI
32.11
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)
Funders
National Planning Office of Philosophy and Social Science

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