Panel VAR models with spatial dependence - Jan Mutl (Institute for Advanced Studies (IHS), 2009)
I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances characterized by a spatial autoregressive process. I propose a three-step estimation procedure. Its first step is an instrumental variable estimation that ignores the spatial correlation. In the second step, the estimated disturbances are used in a multivariate spatial generalized moments estimation to infer the degree of spatial correlation. The final step of the procedure uses transformed data and applies standard techniques for estimation of panel vector-autoregressive models. I compare the small-sample performance of various estimation strategies in a Monte Carlo study.
Keywords: C13; C31; C33; 330; spatial PVAR; multivariate dynamic panel data model; spatial GM; spatial Cochrane-Orcutt transformation; constrained maximum likelihood estimation; VAR-Modell; Panel; Momentenmethode; Maximum-Likelihood-Methode; Monte-Carlo-Methode