Abstract
Based on the data from 1978-2010, this paper analyzes the causal relationships between carbon emissions, energy consumption, and economic growth in Shanghai, adopting the co-integration and vector error correction methods. The Grey prediction model is applied to forecast three variables for the period between 2011 and 2020. As the empirical results showed, in the long-run equilibrium, there is a positive relationship of a long-term equilibrium between carbon emission and energy consumption in Shanghai. However, between carbon emission and real GDP, there is a negative correlation. Besides, in the short-run equilibrium, energy consumption is the important impact on carbon emission. The causality results show that there is a bidirectional causality relationship between carbon emission, real GDP and energy consumption. For the purposes of reducing carbon emissions and not adversely affecting economic growth, Shanghai should optimize the structure of energy consumption and develop new energy. In addition, the optimal forecasting models of real GDP, energy consumption and carbon emissions have good prediction precision with MAPEs of less than 3%.
Highlights
For the last 30 years, China’s economy grows rapidly and ranks second in the world
Soytas et al (2007) combined several techniques such as Granger causality test and forecast variance decomposition analysis to conduct a study on the dynamic relationship between economic growth, energy consumption and CO2 emissions in the years from 1960 to 2004 in America.The analysis showed that no obvious causal relationship existed between output and CO2 emissions or between output and energy consumption, but energy consumption does cause CO2 emissions
In the long-run equilibrium, carbon emission was positively correlated with energy consumption, which implies that an increase in energy consumption leads to an increase in carbon emissions
Summary
For the last 30 years, China’s economy grows rapidly and ranks second in the world. economic growth is mainly driven by investment, which brings a lot of energy consumption and greenhouse gas emissions. Soytas et al (2007) combined several techniques such as Granger causality test and forecast variance decomposition analysis to conduct a study on the dynamic relationship between economic growth, energy consumption and CO2 emissions in the years from 1960 to 2004 in America.The analysis showed that no obvious causal relationship existed between output and CO2 emissions or between output and energy consumption, but energy consumption does cause CO2 emissions. Soytas and Sari (2009) employed Granger causality test and a few other techniques to observe the mutual influence among economic growth, energy consumption and CO2 emissions in the years from 1960 to 2000 in Turkey. It indicated that there was a one-way Granger causality from CO2 emissions to energy consumption. The study and prediction of CO2 emissions, energy consumption and economic development comprise a vital part of Shanghai’s environment energy policy
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