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Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China

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Abstract

There has been a growing concern regarding the regulation of environmental pollution in the face of a growing population, global warming, and climate change. Governments around the world have devised various mechanisms and policy strategies to ameliorate the worsening condition of natural environment around the world. Similar to the developed world, in China, the government is also aware of deteriorating environmental conditions. Hence, the existing abatement instruments include pollution discharge fees and several other policy strategies. This research is conducted to investigate the association between pollution intensity and its determinants, i.e., pollutant discharge fees and urban population, third industry structure, and total retail goods consumption. The secondary data of 29 provinces is used for empirical analysis. The principal component analysis is used to develop a single index called pollution intensity, and panel autoregressive distributed lags model (ARDL), or pooled mean group (PMG) analysis, is employed to find long-run and short-run relationship. The empirical findings show that pollution discharge fees negatively affects pollution intensity. Total retail good consumption and urban population increase pollution intensity. However, third industry structure helps to control pollution intensity. These results suggest reforms in the existing environmental regulations policy by targeting more pollutant intensive provinces.

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Notes

  1. For instance, see also, Jordaan et al. (2017), Almutairi and Elhedhli (2014), Scrimgeour et al. (2005), Li and Zhao (2017), Xiao et al. (2015), and Guo et al. (2018).

  2. See, for instance, Jin et al. (2017), Abolhosseini et al. (2014), Lee et al. (2015), Fernández et al. (2018), Shaari et al. (2016), and Lee et al. (2015).

  3. List of provinces are given in Appendix 1.

  4. PCA results are given in Appendix 2.

  5. Figure-1A provides provincial level pollutant discharge fee in the Appendix.

  6. Figure-3A provides provincial wise total retail goods consumption in the Appendix.

  7. Figure-2A provides provincial wise population growth in the Appendix.

  8. The results are available upon request from authors.

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Authors and Affiliations

  1. School of Economics and Management (SEM), Tsinghua University, Beijing, China

    Zeeshan Khan & Yang Siqun

  2. Montpellier Business School, Montpellier, France

    Muhammad Shahbaz

  3. School of Economics, Department of Industrial Economics, Nanjing University, Nanjing, China

    Manzoor Ahmad

  4. Department of Economics, Abdul Wali Khan University Mardan, Mardan, Pakistan

    Manzoor Ahmad

  5. Department of Economics and Development Studies, University of Swat, Swat, Pakistan

    Fazli Rabbi

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  1. Zeeshan Khan
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  2. Muhammad Shahbaz
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  4. Fazli Rabbi
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Correspondence to Manzoor Ahmad.

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Appendices

Appendix 1

Fig. 1
figure 1

PDF statistics at provincial level

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Fig. 2
figure 2

China provincial population growth

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Fig. 3
figure 3

TRGC at provincial level

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Table 12 List of provinces
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Appendix 2

Table 13 Principal component analysis
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Khan, Z., Shahbaz, M., Ahmad, M. et al. Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China. Environ Sci Pollut Res 26, 32224–32242 (2019). https://doi.org/10.1007/s11356-019-06326-0

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