Effect of electricity policy uncertainty and carbon emission prices on electricity demand in China based on mixed-frequency data models

Wanbo Lu, Qibo Liu and Jie Wang

Utilities Policy, 2024, vol. 91, issue C

Abstract: This paper first constructs the electricity policy uncertainty (EPU) in China with textual methods and analyses the effect of the EPU and carbon emission prices (CEPs) on the total electricity demand. This paper also forecasts the demand for electricity in China with three mixed-frequency data models. The results show that the EPU index efficiently captures the uncertainty of China's electricity policy. The effects of EPU and CEPs on electricity demand are significant, and incorporating them into the forecasting model will improve the accuracy and timeliness. Moreover, compared with the ARMA model and LSTM neural networks, mixed-frequency data models perform better in electricity demand forecasting.

Keywords: Electricity demand; Policy uncertainty; Mixed-frequency data models (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0957178724001188
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:juipol:v:91:y:2024:i:c:s0957178724001188

DOI: 10.1016/j.jup.2024.101825

Access Statistics for this article

Utilities Policy is currently edited by Beecher, Janice

More articles in Utilities Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().