Estimation of Panel Vector Autoregression in Stata: a Package of Programs
Michael Ralph Abrigo and
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Inessa Love: University of Hawaii at Manoa
No 201602, Working Papers from University of Hawaii at Manoa, Department of Economics
Panel vector autoregression (VAR) models have been increasingly used in applied research. While programs specifically designed to estimate time-series VAR models are often included as standard features in most statistical packages, panel VAR model estimation and inference are often implemented with general-use routines that require some programming dexterity. In this paper, we briefly discuss model selection, estimation and inference of homogeneous panel VAR models in a generalized method of moments (GMM) framework, and present a set of Stata programs to conveniently execute them. We illustrate the pvar package of programs by using standard Stata datasets.
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