Real government size, automatic feedback rules and the measured effectiveness of fiscal policy
J. Stephen Ferris
Applied Economics, 1998, vol. 30, issue 3, 365-373
Abstract:
This paper argues that as intervention, fiscal policy means more than simply any change in government spending and this requires of fiscal analysis a measure that separates the allocative from the counter-cyclical activities of government. Defining intervention as an optimal policy rule that responds automatically to privately unanticipated variations in output, a general equilibrium model is built to separate the supply side effects of desired changes in the size of government from demand side interventions designed to stimulate aggregate demand. The model is tested using the results of a public choice investigation of the real size of government (Ferris and West, 1996). That exercise produces a measure of desired size and, through its residual, an implicit measure of intervention. The paper tests the prediction that increases in desired size increase aggregate supply and that ex post measures of fiscal intervention can be recovered and tested for their effect on aggregate output. The test uses CITIBASE US annual data from 1959 through 1989.
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/000368498325886 (text/html)
Access to full text is restricted to subscribers.
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:taf:applec:v:30:y:1998:i:3:p:365-373
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/000368498325886
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().