Instrumental Variable Estimation of Structural VAR Models Robust to Possible Non-Stationarity

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)33_Other conference paperpeer-review

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Detail(s)

Original languageEnglish
Pages1-35
Number of pages35
Publication statusPresented - 15 Aug 2019

Conference

Title2019 NBER-NSF Time Series Conference
LocationChinese University of Hong Kong
PlaceChina
CityHong Kong
Period14 - 15 August 2019

Abstract

This paper considers the estimation of dynamic causal effects using external instruments and a structural vector-autoregressive model with possibly non-stationary regressors. We provide general conditions under which the asymptotic normal approximation remains valid. In this case, the asymptotic variance depends on the persistence property of each series. We further provide a consistent asymptotic covariance matrix estimator that requires neither such knowledge nor pre-tests for nonstationarity. The proposed consistent covariance matrix estimator is robust and is easy to implement in practice.

Research Area(s)

  • external instruments, non-stationarity, robust inference, structural VAR

Bibliographic Note

Information for this record is supplemented by the author(s) concerned.

Citation Format(s)

Instrumental Variable Estimation of Structural VAR Models Robust to Possible Non-Stationarity. / HAN, Xu; INOUE, Atsushi; Cheng, Xu.

2019. 1-35 2019 NBER-NSF Time Series Conference, Hong Kong, China.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)33_Other conference paperpeer-review