Radmila Janković, I. Mihajlović, Alessia Amelio, I. Draganov
{"title":"预测生态足迹:以意大利、巴基斯坦和中国为例","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":"{\"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}","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}
Predicting the Ecological Footprint: A Case Study for Italy, Pakistan and China
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.