The relationship between energy consumption, economic growth, and CO2 emissions in China: the role of urbanisation and international trade


Kongkuah M., Yao H., Yilanci V.

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, vol.24, no.4, pp.4684-4708, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 4
  • Publication Date: 2022
  • Doi Number: 10.1007/s10668-021-01628-1
  • Journal Name: ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, PASCAL, ABI/INFORM, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Business Source Elite, Business Source Premier, CAB Abstracts, Geobase, Greenfile, Index Islamicus, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.4684-4708
  • Keywords: Energy consumption, CO2 emissions, Economic growth, EKC hypothesis, Time series, China, CARBON-DIOXIDE EMISSIONS, COINTEGRATION, DETERMINANTS, CAUSALITY, IMPACT, INCOME, BELT, PART
  • Çanakkale Onsekiz Mart University Affiliated: Yes

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.