Comparison of Local Projection Estimators for Proxy Vector Autoregressions

Martin Bruns, H. Luetkepohl
{"title":"Comparison of Local Projection Estimators for Proxy Vector Autoregressions","authors":"Martin Bruns, H. Luetkepohl","doi":"10.2139/ssrn.3855339","DOIUrl":null,"url":null,"abstract":"Different local projection (LP) estimators for structural impulse responses of proxy vector autoregressions are reviewed and compared algebraically andwith respect to their small sample suitability for inference. Conditions for numerical equivalence and similarities of some estimators are provided. A new LP type estimator is also proposed which is very easy to compute. Two generalized least squares (GLS) projection estimators are found to be more accurate than the other LP estimators in small samples. In particular, a lag-augmented GLS estimator tends to be superior to its competitors and to perform as well as a standard VAR estimator for sufficiently large samples.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Econometric & Statistical Methods - General eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3855339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Different local projection (LP) estimators for structural impulse responses of proxy vector autoregressions are reviewed and compared algebraically andwith respect to their small sample suitability for inference. Conditions for numerical equivalence and similarities of some estimators are provided. A new LP type estimator is also proposed which is very easy to compute. Two generalized least squares (GLS) projection estimators are found to be more accurate than the other LP estimators in small samples. In particular, a lag-augmented GLS estimator tends to be superior to its competitors and to perform as well as a standard VAR estimator for sufficiently large samples.
代理向量自回归的局部投影估计比较
对代理向量自回归结构脉冲响应的不同局部投影(LP)估计进行了综述,并从代数上比较了它们的小样本推理适用性,给出了一些估计的数值等价性和相似性的条件。本文还提出了一种新的易于计算的LP型估计器。在小样本情况下,发现两个广义最小二乘(GLS)投影估计器比其他LP估计器更准确。特别是,滞后增强的GLS估计器往往优于其竞争对手,并且在足够大的样本中表现得与标准VAR估计器一样好。
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:481959085
Book学术官方微信