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The sheer scale of China’s urban renewal and CO2 emissions: multiple structural breaks, long-run relationship, and short-run dynamics

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Abstract

In the light of urban environmental transition (UET) theory, this study explores the relationship between carbon dioxide (CO2) emissions, economic growth, urbanization, and trade openness using updated Chinese data over the extended period (1971–2013). After confirming that all the underlying series are stationary and adjusted with single structural break point, the results of autoregressive distributed lag (ARDL) bounds test approach to cointegration confirm the cointegration between the variables. The long- and short-run dynamics reveal that urbanization reduces the CO2 emissions both in short and long runs, but statistically insignificant. These findings contrast with previous literature and sound the validation of urban environmental transition theory (UET). However, economic growth and trade openness contribute environmental degradation both in long- and short-run paths. The causality analysis reports bidirectional causal link between trade openness and urbanization in the short run. However, in the long-run, economic growth Granger causes carbon dioxide emissions, urbanization, and trade openness. Similarly, trade openness Granger causes carbon dioxide emissions, economic growth, and urbanization in the long run. The overall results imply that rural to urban immigration is still mostly driven by export-related manufacturing sectors. In addition, the higher GDP also contributes to urbanization as a feedback effect. In the end, stability of the model is also checked, model found stable, and findings are suitable for environmental policy control use.

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Notes

  1. National Development and Reforms Commission (NDRC), 2011. http://en.ndrc.gov.cn/(Accessed:10.10.2015).

  2. National Bureau of Statistics of China (NBSC), 2014. http://www.stats.gov.cn/enGLISH/PressRelease/201402/t20140224_515103.html (Accessed:10.10.2015).

  3. For details, see Sadorsky (2014).

  4. See for example the UK’s Environmental Policy (https://www.gov.uk/government/organisations/environment-agency)

  5. See for example the European Union’s Environmental Action Programme(s) (http://ec.europa.eu/environment/archives/action-programme/)

  6. World Bank’s WDIs. http://databank.worldbank.org/data/home.aspx (accessed March 9, 2015).

  7. The unit root test has become the standard procedure and the literature is also well-established. Therefore, LP unit root test equations are not mentioned, but are available upon request.

  8. Engle-Granger two-step residual-based method of cointegration developed in Engle and Granger (1987).

  9. Johansen-Juselius maximum likelihood approach to cointegration developed in Johansen and Juselius (1990).

  10. For recent studies using ARDL bounds testing approach to cointegration, see Solarin (2014), Ling et al. (2015), Al-Mulali et al. (2016), and Shahbaz et al. (2016).

  11. ECM is mainly used for cointegrated series, and their function is to estimate the speed at which a dependent variable return to its equilibrium position after a change occurs in an independent variable. ECM also helps to estimate the long- and short-run impacts between the series (for details, see Engle and Granger 1987; Banerjee et al. 1998).

  12. Similarly, the number of test equations will be equal to the number of variables. However, we just mentioned single equation to conserve the space.

  13. If the calculated F-statistics in column 4 of Table 4 lies above the upper bound I(1) value, the decision favors the rejection of null hypothesis and confirms the cointegration relationship. However, the value below the lower bound I(0) value and within the upper I(1) and lower I(0) bound values do not reject the null hypothesis (no cointegration relationship) and inconclusive relationship, respectively. For details, refer to Pesaran et al. (2001).

  14. 11th 5-year plan (2006–2010)

  15. 12th 5-year plan (2011–2015)

  16. The straight lines (i.e., red and green) in Figs. 7 and 8 represent the upper and lower bound limits, respectively.

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  1. Sukkur Institute of Business Administration, 65200, Sukkur, Sindh, Pakistan

    Khalid Ahmed

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  1. Khalid Ahmed
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Ahmed, K. The sheer scale of China’s urban renewal and CO2 emissions: multiple structural breaks, long-run relationship, and short-run dynamics. Environ Sci Pollut Res 23, 16115–16126 (2016). https://doi.org/10.1007/s11356-016-6765-3

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