Financing public goods and attitudes toward immigration

Inigo Iturbe-Ormaetxe and José Romero Ciavatto

European Journal of Political Economy, 2016, vol. 44, issue C, 159-178

Abstract: We study a model where individuals choose both the level of provision of a public good and the quota of low-skilled immigrants that are allowed into the country. Individuals can supplement the public good in the private market. Immigrants affect natives through three channels: (i) the labor market; (ii) tax collection; (iii) the quality of the public good. We find that the higher the political weight of the rich (highly skilled) is, the less tolerant the poor and the middle-class are toward immigration and the more demanding they are toward increasing public spending. The rich are the most favorable to immigration. As they have more weight, the political outcome is closer to their preferences and further from the preferences of the other groups. We use data from the European Social Survey to test the implications of our model.

Keywords: Probabilistic voting model; Public goods; Immigration (search for similar items in EconPapers)
JEL-codes: D72 H41 J61 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0176268016300805
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Financing public goods and attitudes toward immigration (2013)
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:eee:poleco:v:44:y:2016:i:c:p:159-178

DOI: 10.1016/j.ejpoleco.2016.07.006

Access Statistics for this article

European Journal of Political Economy is currently edited by J. De Haan, A. L. Hillman and H. W. Ursprung

More articles in European Journal of Political Economy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().