Modeling electricity demand in China based on macro and micro-level methods

Shaogang Chen and Zizhe Wang

Utilities Policy, 2025, vol. 96, issue C

Abstract: This study analyzes residential electricity demand in Chengdu from both micro and macro-level perspectives. Household survey data is used at the micro level to estimate demand functions and capture heterogeneity via corresponding random and fixed effect models and quantile regression. At the macro level, the Autoregressive Distributed Lag (ARDL) cointegration method examines the relationships between electricity demand, gross domestic product (GDP), and prices. Results show significant differences in price and income elasticity across households, and economic growth drives energy consumption. Combining macro and micro-level analyses helps better understand demand patterns and supports more effective policy decisions.

Keywords: Household electricity consumption; Quantile regression; Elasticity theory (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0957178725001092
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:96:y:2025:i:c:s0957178725001092

DOI: 10.1016/j.jup.2025.101994

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 ().