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Analyzing and Predicting the Economic Growth, Energy Consumption and CO2 Emissions in Shanghai

机译：分析和预测上海的经济增长，能源消耗和二氧化碳排放量

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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%.
机译：基于1978-2010年的数据，采用协整和矢量误差校正方法，分析了上海市碳排放，能源消耗与经济增长之间的因果关系。运用灰色预测模型对2011年至2020年的三个变量进行了预测。实证结果表明，在长期均衡中，上海的碳排放量与能源消耗之间存在长期的正相关关系。 。但是，碳排放量与实际GDP之间存在负相关关系。此外，在短期均衡中，能源消耗是碳排放的重要影响。因果关系结果表明，碳排放，实际GDP与能源消耗之间存在双向因果关系。为了减少碳排放并且不对经济增长产生不利影响，上海应该优化能源消费结构并开发新能源。此外，真实GDP，能源消耗和碳排放的最佳预测模型具有良好的预测精度，MAPE小于3％。

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