Value for Money? Community Targeting in Vote-Buying and Politician Accountability

Jessica Leight, Dana Foarta, Rohini Pande and Laura Ralston
Additional contact information
Rohini Pande: Harvard University
Laura Ralston: World Bank

Research Papers from Stanford University, Graduate School of Business

Abstract: Community targeting of vote payments--defined as the saturation of entire neighborhoods with cash prior to elections--is widespread in the developing world. In this paper, we utilize laboratory experiments conducted in the U.S. and Kenya to demonstrate that, relative to individual targeting, a vote-buying regime that distributes payments widely renders voters more tolerant of politician rent-seeking, and increases the level of politician rent-seeking observed in equilibrium. The most parsimonious model of preferences consistent with these patterns is a model in which both politicians and voters are characterized by multifaceted social preferences, encompassing reciprocity, altruism, and inequality aversion.

Date: 2017-12
New Economics Papers: this item is included in nep-pol and nep-ure
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/445276
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
Journal Article: Value for money? Vote-buying and politician accountability (2020)
Working Paper: Value for Money? Community Targeting in Vote-Buying and Politician Accountability (2018)
Working Paper: Value for Money? Community Targeting in Vote-Buying and Politician Accountability (2018)
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:ecl:stabus:repec:ecl:stabus:3613

Access Statistics for this paper

More papers in Research Papers from Stanford University, Graduate School of Business Contact information at EDIRC.
Bibliographic data for series maintained by ().