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

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 model...

Full description

Saved in:
Bibliographic Details
Published in:Utilities policy 2024-12, Vol.91, p.101825, Article 101825
Main Authors: Lu, Wanbo, Liu, Qibo, Wang, Jie
Format: Article
Language:English
Subjects:
Electricity demand
Mixed-frequency data models
Policy uncertainty
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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. •The EPU index efficiently captures the uncertainty of China's electricity policy.•The effects of electricity policy uncertainty and carbon emission prices on electricity demand are significant.•Mixed-frequency data models, especially MIDAS with ECM, perform better in electricity demand forecasting.
ISSN:0957-1787
DOI:10.1016/j.jup.2024.101825