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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"Maximum Likelihood Estimation of Fixed Effects Dynamic Panel Data Models Covering Short Time Periods,"
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9826, Faculty of Economics, University of Cambridge.
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36, Society for Computational Economics.
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- Michael Binder & Cheng Hsiao & Jan Mutl & M. Hashem Pesaran, 2002. "Computational Issues in the Estimation of Higher-Order Panel Vector Autoregressions," Computing in Economics and Finance 2002 345, Society for Computational Economics.
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