Improved GMM Estimation of Panel VAR Models
30 Pages Posted: 18 Sep 2013 Last revised: 22 Mar 2015
Date Written: February 13, 2015
In this study, improved IV/GMM estimators for panel vector autoregressive models (VAR) are proposed by extending Hayakawa (2009b) ("A Simple Efficient Instrumental Variable Estimator in Panel AR(p) Models When Both N and T Are Large,'' Econometric Theory, 25, 873-890) in which an alternative form of instruments is suggested. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias-corrected fixed effects estimator of Hahn and Kuersteiner (2002) ("Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects When Both n and T Are Large,'' Econometrica, 70, 1639-1657) in the VAR(1) case when both N and T are large where N and T denote the sample sizes of cross section and time series, respectively. Since the proposed estimator is simply to change the form of instruments, it is very easy to implement in practice. As applications of the proposed estimators, we consider a panel Granger causality test and panel impulse response analysis in which the asymptotic distribution of generalized impulse response functions of Pesaran and Shin (1998) ("Generalized Impulse Response Analysis in Linear Multivariate Models,'' Economics Letters, 58, 17-29) is newly derived. Monte Carlo simulation results show that the proposed estimators have comparable or better finite sample properties than the conventional IV/GMM estimators using instruments in levels for moderate or large T.
Keywords: panel VAR, GMM
JEL Classification: C13
Suggested Citation: Suggested Citation