Advanced estimates of regional accounts: an alternative approach by spatial panels

Riccardo Corradini ()

No 287, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: The policies related to regional economic activity developed by European Union (EU) and the role played by regions as economic subject have determined a bigger set of disaggregated statistics at macroeconomic level. The methodologies used nowadays by the Italian national institute of statistics (ISTAT) are based on an information set build on the basis of inner statistical surveys and other external sources. The estimates of regional accounts carried out on the complete information set require an amount of time bigger than the one expected for the already mentioned aims. A strong need to carry out advanced estimates of regional accounts in a quicker time has emerged. The Kalman filter could be the right tool if we use a short time series span. Since it is available a larger data set from ISTAT web site (www.istat.it) from 1980 up to 2004, a different approach will be performed here, and is mainly based on Spatial Panel recently used by Elhorst and Baltagi. SAR (simultaneous autocorrelation model) and SEM (simultaneous error model) will be used. In a similar fashion the first log differences of ULA (units of labour) will be used to forecast the first log differences of four value added branches at constant prices. Finally some conclusions will be drawn on the performances of SAR and SEM

Keywords: spatial panel data models; regional accounts (search for similar items in EconPapers)
JEL-codes: C21 C22 C23 (search for similar items in EconPapers)
Date: 2006-07-04
New Economics Papers: this item is included in nep-geo
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://repec.org/sce2006/up.18498.1141058846.pdf (application/pdf)

Related works:
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: https://EconPapers.repec.org/RePEc:sce:scecfa:287

Access Statistics for this paper

More papers in Computing in Economics and Finance 2006 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().