Paper Title
Structural Error Correction Model For Forecasting Energy Demand

Abstract
This study devises a structural error correction model for forecasting China’s energy demand. China is the second largest consumer of energy products in the world. Forecasting China’s energy demand is crucial to forecasting the costs of energy and answering questions of when and what capacity to invest in energy infrastructures. Following two decades of rapid economic growth and rising demand for energy products, Chinese citizens are becoming more environmentally aware. Chinese policy makers recognized the need for cleaner sources of energy – oil and gas. As a result, the share of coal in China’s total energy consumption is declining, with the share of oil and gas increasing substantially. This study’s structural error correction model takes into consideration the substitutability between various traditional energy products (e.g., coal, oil, gas, etc.). Structural parameters governing such substitutability can be identified from the model. The model can also be extended to capture the substitutability between non-renewable and renewable energy products, which have implications on the government’s environmental policies. The same approach can be applied to forecasting the demand for other commodities with a large degree of substitutability.