Abstract
The study tests the EKC hypothesis, forecasts future paths, and models the dynamic relationship between ecological and economic variables in China. The problem of sustainable and green growth in China arises with the rebirth of the Belt and Road Initiative (BRI) program. Although there has been various research on the subject, the basic EKC model results are often conflicting. To obtain consistent parameter estimates, the basic EKC model was extended; the study’s contributions or novelties include avoiding the omitted variable bias by introducing urbanisation rate and international trade, which according to the literature, simultaneously influence pollution levels significantly. Also, more recent and robust estimation techniques including the Fourier ADF (FADF) unit root test, the time-varying bootstrap causality test, the Fourier ADL and Gregory-Hansen cointegration tests, fully modified ordinary least squares (FMOLS), vector error correction model (VECM), and the forecast error variance decomposition (FEVD) analysis were employed. The techniques mentioned earlier were confirmed using traditional methods such as the Johansen cointegration test and the traditional testing methods for unit root. The EKC is not valid in China. Cointegration and long-run relationships are established. Also, the future path of CO2 emissions continues to be on the rise. While economic growth, energy consumption and trade significantly increase CO2 emissions, urbanisation significantly lessens pollution from CO2 emissions in the long run. Policy recommendations include using new technologies, energy diversification, and the ultimate switch to clean energy use, including hydropower, wind power, solar energy, bio-energy, and tidal energy. Also, the need for increased urbanisation in China is critical to reducing CO2 emissions. It is partly because urban agglomeration allows for the same output to be produced using fewer resources.
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Availability of data and materials
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
Notes
The SDG 13 involves the responsible consumption and the production options of energy being essential to climate change mitigation.
For brevity, visual plots of the series from the ZA unit root tests depict the presence of structural breaks. These plots can be made available on request.
See Table 7
The lower section of Table 4 presents the residual diagnostic checks for the model.
For brevity, we make available only the point forecast for lnCO2 in Table 6 since the focus is on how the other variables explain lnCO2. Point forecast for the variables (lnGDP, lnGDP2, lnENRC, URB, TRADE) can be made available in a table form on request.
TRADE’s shock to lnCO2 causes lnCO2 to increase, thus, worsening the environment (see Table 5 and Table 7 for further evidence). The effect is that a switch to clean energy use will continue to promote international trade and maintain green economic growth; it will cause carbon dioxide emissions to lessen.
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The study sourced its funding from the National Natural Science Foundation of China number 71701082 and 71271103.
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MK: Conceptualisation, Data curation, Methodology, Formal analysis, Investigation, Software, Validation, Writing -original draft. HY: Funding, Supervision, Writing—review and editing. VY: Validation, Writing—review and editing.
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Kongkuah, M., Yao, H. & Yilanci, V. The relationship between energy consumption, economic growth, and CO2 emissions in China: the role of urbanisation and international trade. Environ Dev Sustain 24, 4684–4708 (2022). https://doi.org/10.1007/s10668-021-01628-1
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DOI: https://doi.org/10.1007/s10668-021-01628-1