This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Consistent Estimation of Global VAR Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Mutl, Jan (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

Additional information is available for the following registered author(s):

Abstract

In this paper, I propose an instrumental variable (IV) estimation procedure to estimate global VAR (GVAR) models and show that it leads to consistent and asymptotically normal estimates of the parameters. I also provide computationally simple conditions that guarantee that the GVAR model is stable.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.ihs.ac.at/publications/eco/es-234.pdf
File Format: application/pdf
File Function: First version, 2009
Download Restriction: no

Publisher Info
Paper provided by Institute for Advanced Studies in its series Economics Series with number 234.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 24 pages
Date of creation: Feb 2009
Date of revision:
Handle: RePEc:ihs:ihsesp:234

Contact details of provider:
Postal: Stumpergasse 56, A-1060 Vienna, Austria
Phone: ++43 - (0)1 - 599 91 - 0
Fax: ++43 - (0)1 - 599 91 - 555
Web page: http://www.ihs.ac.at/index.php3?id=310
More information through EDIRC

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

For technical questions regarding this item, or to correct its listing, contact: (Wolfgang Nessler).

Related research
Keywords: Global VAR; GVAR; Consistent estimation; Instrumental variables;

Find related papers by JEL classification:
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data

This paper has been announced in the following NEP Reports:

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. 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)
  2. 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.
  3. 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)
  4. M. Hashem Pesaran & Ron Smith, 2006. "Macroeconometric Modelling With A Global Perspective," Manchester School, University of Manchester, vol. 74(s1), pages 24-49, 09. [Downloadable!] (restricted)
    Other versions:
  5. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(04), pages 795-837, August. [Downloadable!]
    Other versions:
  6. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July. [Downloadable!] (restricted)
    Other versions:
  7. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August. [Downloadable!] (restricted)
    Other versions:
  8. Stephane Dees & Filippo di Mauro & M. Hashem Pesaran & L. Vanessa Smith, 2004. "Exploring the International Linkages of the Euro Area: A Global VAR Analysis," IEPR Working Papers 04.6, Institute of Economic Policy Research (IEPR). [Downloadable!]
    Other versions:
  9. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July. [Downloadable!] (restricted)
  10. Dr. Peter Kenning & Hilke Plassmann, 2004. "NeuroEconomics," Experimental 0412005, EconWPA. [Downloadable!]
  11. 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.
Full references

Statistics
Access and download statistics

Did you know? Authors can create their own profile with links to their works on the RePEc Author Service.

This page was last updated on 2009-11-27.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.