An extension of the Tiebout hypothesis of voting with one's feet: the Medicaid magnet hypothesis
Richard Cebula () and
J. R. Clark
Applied Economics, 2013, vol. 45, issue 32, 4575-4583
Abstract:
This study empirically extends the Tiebout hypothesis of 'voting with one's feet' in two ways. First, it provides updated estimates using net migration data for the period 2000--2008. Second, in addition to investigating variables reflecting public education outlays, property taxation and income taxation, it investigates whether migrants are attracted to states with higher Medicaid benefits per recipient. The latter hypothesis is referred to as the 'Medicaid magnet hypothesis'. The analysis includes three economic variables, three quality of life variables and three Tiebout-type factors in addition to Medicaid benefits. Results indicate that consumer voters were attracted to states with higher per pupil public school spending, lower property and income tax rates , and that certain consumer-voters may be attracted to states that offer higher levels of Medicaid benefits.
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2013.795278 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: An Extension of the Tiebout Hypothesis of Voting with One's Feet: The Medicaid Magnet Hypothesis (2012) 
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:45:y:2013:i:32:p:4575-4583
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2013.795278
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 ().