Wagner's law and Italian disaggregated public spending: some empirical evidences

Cosimo Magazzino

MPRA Paper from University Library of Munich, Germany

Abstract: Wagner’s Law is the first model of public spending in the history of public finance. The aim of this article is to assess its empirical evidence in Italy for the period 1960-2008 at a disaggregated level, using a time-series approach. After a brief introduction, a survey of the economic literature on this issue is shown, before estimating the specifications of Wagner’s Law for some specific items of public spending (for interests, for final consumption, for labour dependent income, for grants on production, and for public investments). We found a cointegration relationship for three out of five items. Moreover, Granger causality tests results show evidence in favour of Wagner’s law only for spending for passive interests in the long-run, and for spending for dependent labour income in the short-run. Some notes on the policy implications of our empirical results conclude the paper.

Keywords: public spending; economic growth; Wagner’s Law; time-series; unit root; cointegration; causality; fiscal policy (search for similar items in EconPapers)
JEL-codes: C32 D60 H50 H60 N44 (search for similar items in EconPapers)
Date: 2010-11-10
New Economics Papers: this item is included in nep-his
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/26662/2/MPRA_paper_26662.pdf original version (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:pra:mprapa:26662

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().