用时间序列分析预测印度及其邻国的GDP

Ankita Raj, S. K. Singh
{"title":"用时间序列分析预测印度及其邻国的GDP","authors":"Ankita Raj, S. K. Singh","doi":"10.1109/GlobConPT57482.2022.9938189","DOIUrl":null,"url":null,"abstract":"The gross domestic product (GDP), a key indicator of an economy's index, is a market estimate of all final services and items produced within a country. This research aims to analyze, compare, and forecast the GDP of India's neighboring countries (Pakistan, Nepal, Bangladesh, and China). As a result, this paper employs an autoregressive integrated moving average (ARIMA) model, Auto-ARIMA and regression model. These models used to do train with data to better compare with different countries and forecast future values. Performance is analyzed through RMDSPE, AE, MAPE, NRMSE and RMSPE, and forecasted the countries' GDP as mentioned above from 2021 to 2026. Further, policy implications are also suggested.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting GDP of India and its neighbouring countries using Time Series Analysis\",\"authors\":\"Ankita Raj, S. K. Singh\",\"doi\":\"10.1109/GlobConPT57482.2022.9938189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The gross domestic product (GDP), a key indicator of an economy's index, is a market estimate of all final services and items produced within a country. This research aims to analyze, compare, and forecast the GDP of India's neighboring countries (Pakistan, Nepal, Bangladesh, and China). As a result, this paper employs an autoregressive integrated moving average (ARIMA) model, Auto-ARIMA and regression model. These models used to do train with data to better compare with different countries and forecast future values. Performance is analyzed through RMDSPE, AE, MAPE, NRMSE and RMSPE, and forecasted the countries' GDP as mentioned above from 2021 to 2026. Further, policy implications are also suggested.\",\"PeriodicalId\":431406,\"journal\":{\"name\":\"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GlobConPT57482.2022.9938189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobConPT57482.2022.9938189","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

国内生产总值(GDP)是一个经济指数的关键指标,是一个国家生产的所有最终服务和项目的市场估计。本研究旨在分析、比较和预测印度周边国家(巴基斯坦、尼泊尔、孟加拉国和中国)的GDP。因此,本文采用自回归综合移动平均(ARIMA)模型、Auto-ARIMA模型和回归模型。这些模型使用数据进行训练,以便更好地与不同国家进行比较,并预测未来的价值。通过RMDSPE、AE、MAPE、NRMSE和RMSPE进行绩效分析,并对上述国家2021 - 2026年的GDP进行预测。此外,还提出了政策影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Forecasting GDP of India and its neighbouring countries using Time Series Analysis
The gross domestic product (GDP), a key indicator of an economy's index, is a market estimate of all final services and items produced within a country. This research aims to analyze, compare, and forecast the GDP of India's neighboring countries (Pakistan, Nepal, Bangladesh, and China). As a result, this paper employs an autoregressive integrated moving average (ARIMA) model, Auto-ARIMA and regression model. These models used to do train with data to better compare with different countries and forecast future values. Performance is analyzed through RMDSPE, AE, MAPE, NRMSE and RMSPE, and forecasted the countries' GDP as mentioned above from 2021 to 2026. Further, policy implications are also suggested.
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
期刊最新文献
MeDiFakeD: Medical Deepfake Detection using Convolutional Reservoir Networks Artificial Neural Networks as a Methodology for Optimal Location of Static Synchronous Series Compensator in Transmission Systems Electromagnetic Characterization of Multi-winding High Frequency Magnetic Link Under Non-sinusoidal Excitations Implementation of Various Modulation Techniques to a PV Fed Solar Inverter with High Gain DC-DC Converter in Standalone Applications Obstacle Free Robot Motion Planning and Intelligent Maneuvering Controller
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1