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Panel VAR Models with Spatial Dependence

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Author Info
Mutl, Jan (Department of Economics, Institute for Advanced Studies, Vienna, Austria)

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Abstract

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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File URL: http://www.ihs.ac.at/publications/eco/es-237.pdf
File Format: application/pdf
File Function: First version, 2009
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Publisher Info
Paper provided by Institute for Advanced Studies in its series Economics Series with number 237.

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Length: 38 pages
Date of creation: Mar 2009
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Handle: RePEc:ihs:ihsesp:237

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Postal: Institute for Advanced Studies - Library, Stumpergasse 56, A-1060 Vienna, Austria

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Related research
Keywords: Spatial PVAR; Multivariate dynamic panel data model; Spatial GM; Spatial Cochrane-Orcutt transformation; Constrained maximum likelihood estimation;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. O'Connell, Paul G. J., 1998. "The overvaluation of purchasing power parity," Journal of International Economics, Elsevier, vol. 44(1), pages 1-19, February. [Downloadable!] (restricted)
  2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July. [Downloadable!] (restricted)
  3. 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.
  4. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Blackwell Publishing, vol. 58(2), pages 277-97, April. [Downloadable!] (restricted)
  5. 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. [Downloadable!]
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  6. Hsaio, Cheng & Pesaran, M. Hashem & Tahmiscioglu, A. Kamil, 1998. "Maximum Likelihood Estimation of Fixed Effects Dynamic Panel Data Models Covering Short Time Periods," Cambridge Working Papers in Economics 9826, Faculty of Economics, University of Cambridge.
    Other versions:
  7. Yoosoon Chang, 2000. "Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency," CIRJE F-Series CIRJE-F-85, CIRJE, Faculty of Economics, University of Tokyo. [Downloadable!]
    Other versions:
  8. 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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This page was last updated on 2009-11-27.

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