Predicting the Ecological Footprint: A Case Study for Italy, Pakistan and China

Radmila Janković, I. Mihajlović, Alessia Amelio, I. Draganov
{"title":"Predicting the Ecological Footprint: A Case Study for Italy, Pakistan and China","authors":"Radmila Janković, I. Mihajlović, Alessia Amelio, I. Draganov","doi":"10.1109/ICEST52640.2021.9483528","DOIUrl":null,"url":null,"abstract":"This paper introduces a new prediction model of the ecological footprint from energy parameters based on time series vector autoregression. The experiment employs global yearly observations of the variables in the period 1971–2014 for three countries: (i) Italy, (ii) Pakistan, and (iii) China. A prediction is performed for each variable adopted in the model from 2015 to 2024. The obtained results indicate that the total ecological footprint of consumption will increase for China and Pakistan, and decrease for Italy.","PeriodicalId":308948,"journal":{"name":"2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEST52640.2021.9483528","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper introduces a new prediction model of the ecological footprint from energy parameters based on time series vector autoregression. The experiment employs global yearly observations of the variables in the period 1971–2014 for three countries: (i) Italy, (ii) Pakistan, and (iii) China. A prediction is performed for each variable adopted in the model from 2015 to 2024. The obtained results indicate that the total ecological footprint of consumption will increase for China and Pakistan, and decrease for Italy.
预测生态足迹:以意大利、巴基斯坦和中国为例
本文提出了一种基于时间序列向量自回归的能量参数生态足迹预测模型。该实验采用1971-2014年三个国家(i)意大利、(ii)巴基斯坦和(iii)中国对变量的全球年度观测。对模型中采用的每个变量在2015 - 2024年间进行预测。结果表明,中国和巴基斯坦的消费总生态足迹将增加,意大利的消费总生态足迹将减少。
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:604180095
Book学术官方微信