Measurement of the Price Distortion Degree for Exhaustible Energy Resources in China: A Discount Rate Perspective

ABSTRACT

This paper uses the marginal opportunity cost (MOC) pricing method to calculate theoretical prices of energy resources (namely coal, crude oil, and natural gas). The theoretical price encompasses the marginal production cost (MPC) for exploitation, marginal user cost (MUC) for the scarcity of the exhaustible resources, and the marginal external cost (MEC) for environmental impacts. Compared with the existing compensation mechanism, this study estimates the degree of energy price distortions under different discount rates. The results show that each resource price presents different degrees of distortion with varying causes for the distortions. The crude oil price had the highest distortion degree, followed by coal and natural gas, and the lower the discount rate, the more serious is the energy price distortion.

KEY WORDS:

• Discount rate
• energy price distortion
• exhaustible energy resources
• marginal opportunity cost

JEL:

• P19
• P23
• P28

Supplementary material

Supplemental data for this article can be accessed here.

Notes

1. China Shenhua Energy Company (CSEC).

2. China National Petroleum Corporation (CNPC).

3. The detailed MPC and actual price of three resources can be seen in Table S2. See the Supplementary Material, available online.

4. According to the average exchange rate every year.

5. For the detailed resource taxes information of China’s companies, please see Table S3 in the “Supplementary Material”, available online.

6. Since December 1, 2014, Shenhua Coal Ltd. changed the resource tax from metering to ad valorem, with tax rates of 6%, 8%, and 9%, we chose 8% in this study. Before December 1, 2014, the resource tax was calculated on the basis of coal sales, and the tax rate was 3.2 yuan/ton.

7. For more detailed calculation process, please see Appendix D in the “Supplementary Materials”, available online.

Additional information

Funding

This work is partially supported by grants from the National Natural Science Foundation of China [Grant nos. 71874073, 71834003 and 71573186]; Key Projects of Philosophy and Social Science Research in Universities of Jiangsu Province [Grant no. 2017ZDIXM046]; Six talent peaks project in Jiangsu Province [Grant no. JNHB-024]; International Clean Energy Top Talents Program (iCET 2018) funded by China Scholarship Council (CSC); Outstanding young backbone teachers of Qinglan Project in Jiangsu Province; and Deep-Blue-Scholar program funded by Jiangsu University of Science and Technology.