Published February 2019 | Version v1
Journal article

Will Trump's coal revival plan work? - Comparison of results based on the optimal combined forecasting technique and an extended IPAT forecasting technique

  • 1. Institute for Energy Economics and Policy, China University of Petroleum (East China), Qingdao, Shandong 266580 (China)
  • 2. School of Economics and Management, China University of Petroleum (East China), Qingdao, Shandong 266580 (China)
  • 3. School of Management & Economics, Beijing Institute of Technology, Haidian District, Beijing 100081 (China)

Description

Highlights: • The decisive factors for decline in the U.S. coal industry come from the demand side. • Three time-series forecasting technique are developed to forecast coal demand. • A combination econometric forecasting model is proposed to forecasting coal demand. • Results from three time-series and an econometric technique are similar. • We conclude that Trump's coal revival plan can not save the U.S. coal industry. -- Abstract: Discussions about United States President Trump's coal revival plan are dominated by qualitative analyses, few quantitative analyses have been conducted. To fill the research gap, this study analyzes the future coal demand of the United States from a market perspective. Both time-series and econometric forecasting techniques are developed to quantify the change of total coal consumption and coal consumption of electricity (sharing over 90% of total coal consumption) in the United States. The proposed time-series forecasting techniques are based on metabolic grey model, Autoregressive Integrated Moving Average Model-grey model, and induced ordered weighted geometric averaging operator. The mean absolute percent error of the proposed technique is less than 1%, indicating the proposed forecasting technique provides reliable information. The forecasting results obtained by time-series model show coal consumption and coal demand for electricity sector in U.S. will continue to decline in the next decade. The proposed econometric forecasting technique is based on the IPAT identity, grey model and Vector Auto-Regression. The combination econometric forecasting technique is used simultaneously to analyze the impact of various internal factors on coal consumption. The results from the proposed econometric technique also show the decline trend of coal demand in the U.S. Thus, the results from the time-series and econometric forecasting technique are consistent. Based on the quantitative analyses, this study contend that Trump's policy is unlikely to revive the coal industry.

Additional details

Identifiers

DOI
10.1016/j.energy.2018.12.045;
PII
S0360544218324113;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
169
Journal Page Range
p. 762-775
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55017950
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY; S01: COAL, LIGNITE, AND PEAT;
Descriptors DEI
COAL; COAL INDUSTRY; ECONOMETRICS; ELECTRICITY; ENERGY POLICY; ERRORS; GEOMETRY; MARKET; VECTORS
Descriptors DEC
CARBONACEOUS MATERIALS; ECONOMICS; ENERGY SOURCES; FOSSIL FUELS; FUELS; GOVERNMENT POLICIES; INDUSTRY; MATERIALS; MATHEMATICS; TENSORS

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.