Forecasting residential electricity demand in the Philippines using an error correction model

Angelo Gabrielle F. Santos
{"title":"Forecasting residential electricity demand in the Philippines using an error correction model","authors":"Angelo Gabrielle F. Santos","doi":"10.37907/6erp0202j","DOIUrl":null,"url":null,"abstract":"This study uses an Error Correction Model (ECM) to forecast residential electricity demand in the Philippines using household final consumption expenditure, residential electricity price, and temperature as explanatory variables. Results show that there is a long-run relationship between household final consumption expenditure and residential electricity demand. Estimates from the ECM are consistent with economic theory, and the model passed standard diagnostic and parameter stability tests. Forecast performance based on within-sample and out-of-sample forecasts of the ECM is also shown to be superior, relative to a benchmark Autoregressive Distributed Lag (ARDL) model. Simulations show that by 2040, residential electricity consumption will range from 42,500 gigawatthours (GWh) based on a weak income growth scenario and 62,000 GWh based on a combined changes scenario.","PeriodicalId":91420,"journal":{"name":"The Philippine review of economics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Philippine review of economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37907/6erp0202j","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This study uses an Error Correction Model (ECM) to forecast residential electricity demand in the Philippines using household final consumption expenditure, residential electricity price, and temperature as explanatory variables. Results show that there is a long-run relationship between household final consumption expenditure and residential electricity demand. Estimates from the ECM are consistent with economic theory, and the model passed standard diagnostic and parameter stability tests. Forecast performance based on within-sample and out-of-sample forecasts of the ECM is also shown to be superior, relative to a benchmark Autoregressive Distributed Lag (ARDL) model. Simulations show that by 2040, residential electricity consumption will range from 42,500 gigawatthours (GWh) based on a weak income growth scenario and 62,000 GWh based on a combined changes scenario.
使用误差修正模型预测菲律宾居民用电需求
本研究使用误差修正模型(ECM)来预测菲律宾的居民用电需求,使用家庭最终消费支出、居民电价和温度作为解释变量。结果表明,居民最终消费支出与居民用电需求之间存在着长期的关系。ECM的估计与经济理论一致,模型通过了标准诊断和参数稳定性测试。相对于基准的自回归分布滞后(ARDL)模型,基于样本内和样本外预测的ECM预测性能也显示出优越性。模拟显示,到2040年,住宅用电量将从基于弱收入增长情景的42,500千兆瓦时(GWh)和基于综合变化情景的62,000千兆瓦时不等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信