Panel VAR Models with Spatial Dependence
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.
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- Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005.
"Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration,"
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- Michael Binder, Cheng Hsiao, and M. Hashem Pesaran, 2001. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Computing in Economics and Finance 2001 36, Society for Computational Economics.
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- Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
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