Panel VAR Models with Spatial Dependence

Jan Mutl ()

No 237, Economics Series from Institute for Advanced Studies

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.

Keywords: Spatial PVAR; Multivariate dynamic panel data model; Spatial GM; Spatial Cochrane-Orcutt transformation; Constrained maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: C13 C31 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
Date: 2009-03

Downloads: (external link)
http://www.ihs.ac.at/publications/eco/es-237.pdf First version, 2009 (application/pdf)

Related works:
Working Paper: Panel VAR Models with Spatial Dependence (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:ihs:ihsesp:237

Ordering information: This working paper can be ordered from
Institute for Advanced Studies - Library, Stumpergasse 56, A-1060 Vienna, Austria

Access Statistics for this paper

More papers in Economics Series from Institute for Advanced Studies
Address: Stumpergasse 56, A-1060 Vienna, Austria
Contact information at EDIRC.
Series data maintained by Wolfgang Nessler ().