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INSTRUMENTAL VARIABLE ESTIMATION OF STRUCTURAL VAR MODELS ROBUST TO POSSIBLE NONSTATIONARITY

Published online by Cambridge University Press:  11 January 2021

Xu Cheng,
Xu Han and
Atsushi Inoue
Xu Cheng*
Affiliation:
University of Pennsylvania
Xu Han
Affiliation:
City University of Hong Kong
Atsushi Inoue
Affiliation:
Vanderbilt University
*
Address correspondence to Xu Cheng, Department of Economics, University of Pennsylvania, Philadelphia, PA 19104, USA; e-mail: xucheng@upenn.edu.
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Abstract

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This paper considers the estimation of dynamic causal effects using a proxy structural vector-autoregressive model with possibly nonstationary 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 knowledge of the presistence properties of the variables nor pretests for nonstationarity. The proposed consistent covariance matrix estimator is robust and is easy to implement in practice. When all regressors are indeed stationary, the method becomes the same as the standard procedure.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 38 , Issue 5: YALE 2018 CONFERENCE IN HONOR OF PETER C. B. PHILLIPS: PART I , October 2022, pp. 845 - 874
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Footnotes

We thank Donald Andrews, Peter Phillips, and two anonymous referees for their helpful comments. Xu Han would like to acknowledge the financial support by the GRF grant 11505515 from the Research Grants Council of Hong Kong S.A.R.

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