分析土耳其总用电量和工业用电量空间模式的决定因素

Semra Türkan
{"title":"分析土耳其总用电量和工业用电量空间模式的决定因素","authors":"Semra Türkan","doi":"10.54694/stat.2024.2","DOIUrl":null,"url":null,"abstract":"This research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted regression, and multi-stage geographically weighted regression. The primary goal is to illustrate the presence of spatial effects in the connection between electricity consumption and economic growth. In this context, this study made for Turkey distinguishes itself from previous research by utilizing the multi-stage spatially weighted regression model to examine this relationship. The findings reveal that the multi-scale spatial regression model is the most effective in explaining the relation between economic growth at the provincial level and per capita electricity consumption and per capita industrial electricity consumption. Moreover, the study emphasizes that per capita Gross Domestic Product emerges as the most influential regional economic indicator when assessing its impact on per capita electricity consumption and per capita industrial electricity consumption.","PeriodicalId":508966,"journal":{"name":"Statistika: Statistics and Economy Journal","volume":"56 41","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing Determinants of Spatial Patterns in Total and Industrial Electricity Consumption in Turkey\",\"authors\":\"Semra Türkan\",\"doi\":\"10.54694/stat.2024.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted regression, and multi-stage geographically weighted regression. The primary goal is to illustrate the presence of spatial effects in the connection between electricity consumption and economic growth. In this context, this study made for Turkey distinguishes itself from previous research by utilizing the multi-stage spatially weighted regression model to examine this relationship. The findings reveal that the multi-scale spatial regression model is the most effective in explaining the relation between economic growth at the provincial level and per capita electricity consumption and per capita industrial electricity consumption. Moreover, the study emphasizes that per capita Gross Domestic Product emerges as the most influential regional economic indicator when assessing its impact on per capita electricity consumption and per capita industrial electricity consumption.\",\"PeriodicalId\":508966,\"journal\":{\"name\":\"Statistika: Statistics and Economy Journal\",\"volume\":\"56 41\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistika: Statistics and Economy Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54694/stat.2024.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistika: Statistics and Economy Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54694/stat.2024.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究采用线性回归、地理加权回归和多阶段地理加权回归等多种回归模型,研究人均用电量、人均工业用电量和经济增长之间的空间相关性。其主要目的是说明电力消费与经济增长之间的联系存在空间效应。在这种情况下,针对土耳其的这项研究有别于以往的研究,采用了多阶段空间加权回归模型来研究这种关系。研究结果表明,多尺度空间回归模型能最有效地解释省级经济增长与人均用电量和人均工业用电量之间的关系。此外,研究还强调,在评估人均国内生产总值对人均用电量和人均工业用电量的影响时,人均国内生产总值是最具影响力的区域经济指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing Determinants of Spatial Patterns in Total and Industrial Electricity Consumption in Turkey
This research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted regression, and multi-stage geographically weighted regression. The primary goal is to illustrate the presence of spatial effects in the connection between electricity consumption and economic growth. In this context, this study made for Turkey distinguishes itself from previous research by utilizing the multi-stage spatially weighted regression model to examine this relationship. The findings reveal that the multi-scale spatial regression model is the most effective in explaining the relation between economic growth at the provincial level and per capita electricity consumption and per capita industrial electricity consumption. Moreover, the study emphasizes that per capita Gross Domestic Product emerges as the most influential regional economic indicator when assessing its impact on per capita electricity consumption and per capita industrial electricity consumption.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:604180095
Book学术官方微信