一个用局部投影估计脉冲响应函数的R包

P. Adämmer
{"title":"一个用局部投影估计脉冲响应函数的R包","authors":"P. Adämmer","doi":"10.32614/RJ-2019-052","DOIUrl":null,"url":null,"abstract":"Impulse response analysis is a cornerstone in applied (macro-)econometrics. Estimating impulse response functions using local projections (LPs) has become an appealing alternative to the traditional structural vector autoregressive (SVAR) approach. Despite its growing popularity and applications, however, no R package yet exists that makes this method available. In this paper, I introduce lpirfs, a fast and flexible R package that provides a broad framework to compute and visualize impulse response functions using LPs for a variety of data sets.","PeriodicalId":438593,"journal":{"name":"ERN: Econometric Software (Topic)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"lpirfs: An R Package to Estimate Impulse Response Functions by Local Projections\",\"authors\":\"P. Adämmer\",\"doi\":\"10.32614/RJ-2019-052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Impulse response analysis is a cornerstone in applied (macro-)econometrics. Estimating impulse response functions using local projections (LPs) has become an appealing alternative to the traditional structural vector autoregressive (SVAR) approach. Despite its growing popularity and applications, however, no R package yet exists that makes this method available. In this paper, I introduce lpirfs, a fast and flexible R package that provides a broad framework to compute and visualize impulse response functions using LPs for a variety of data sets.\",\"PeriodicalId\":438593,\"journal\":{\"name\":\"ERN: Econometric Software (Topic)\",\"volume\":\"130 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Econometric Software (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32614/RJ-2019-052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Econometric Software (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32614/RJ-2019-052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

摘要

脉冲响应分析是应用(宏观)计量经济学的基础。利用局部投影(lp)估计脉冲响应函数已成为传统结构向量自回归(SVAR)方法的一种有吸引力的替代方法。尽管它越来越流行,应用程序也越来越多,但是,目前还没有R包支持这种方法。在本文中,我介绍了lpirfs,这是一个快速灵活的R包,它提供了一个广泛的框架,可以使用lp计算和可视化各种数据集的脉冲响应函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
lpirfs: An R Package to Estimate Impulse Response Functions by Local Projections
Impulse response analysis is a cornerstone in applied (macro-)econometrics. Estimating impulse response functions using local projections (LPs) has become an appealing alternative to the traditional structural vector autoregressive (SVAR) approach. Despite its growing popularity and applications, however, no R package yet exists that makes this method available. In this paper, I introduce lpirfs, a fast and flexible R package that provides a broad framework to compute and visualize impulse response functions using LPs for a variety of data sets.
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:481959085
Book学术官方微信