中国煤炭价格的长期预测:一种变化趋势时间序列方法

Baomin Dong, Xuefeng Li, Boqiang Lin
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引用次数: 17

摘要

本文研究了中国市场中长期煤炭实际价格的变化规律。这个问题非常重要,因为煤炭占中国能源结构的70%,而中国是世界第二大碳排放国。准确预测煤炭价格对于预测中国未来的能源消费结构以及私营部门与能源类型相关的投资决策至关重要。在估计和预测中,使用Robert Pindyck提出的移动趋势时间序列模型来捕捉计量经济学家无法观察到的技术进步。结果表明,具有价格水平和趋势连续随机变化的移动趋势模型优于普通ARIMA模型。有人认为,即使在能源价格受到相对严格的监管控制的转型经济中,平迪克假设的模型也是稳健的。提供了样本外预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Long-Run Coal Price in China: A Shifting Trend Time-Series Approach
The paper studies the behavior of mid- to long-run real coal price in the Chinese market. The problem is of great importance because the coal takes a 70% share in China's energy mix, and China is the world's second largest carbon emitter. An accurate forecast in coal price is crucial in predicting China's future energy consumption mix as well as the private sector's energy-type-related investment decisions. In estimation and forecasting, the shifting trend time-series model suggested by Robert Pindyck is used to capture the technological progress that is unobservable to the econometrician. It is found that the shifting trend model with continuous and random changes in price level and trend outperforms plain vanilla ARIMA models. It is argued that the model postulated by Pindyck is robust even in a transition economy where energy prices are subject to relatively rigid regulatory control. Out-of-sample forecasts are provided.
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