Panel VAR Models with Spatial Dependence
AbstractI 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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Bibliographic InfoPaper provided by Institute for Advanced Studies in its series Economics Series with number 237.
Length: 38 pages
Date of creation: Mar 2009
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Other versions of this item:
- Jan Mutl, 2002. "Panel VAR Models with Spatial Dependence," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A5-2, International Conferences on Panel Data.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-23 (All new papers)
- NEP-ECM-2009-05-23 (Econometrics)
- NEP-GEO-2009-05-23 (Economic Geography)
- NEP-URE-2009-05-23 (Urban & Real Estate Economics)
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