Caste, corruption and political competition in India
Avidit Acharya (),
John Roemer () and
Research in Economics, 2015, vol. 69, issue 3, 336-352
Voters in India are often perceived as being biased in favor of parties that claim to represent their caste. We incorporate this caste bias into voter preferences and examine its influence on the distributive policies and corruption practices of the two major political parties in the North Indian state of Uttar Pradesh (U.P.). We begin with a simple two-party, two-caste model to show that caste bias causes political parties to diverge in their policy platforms and has ambiguous effects on corruption. We then develop the model to make it correspond more closely to political reality by incorporating class-based redistributive policies. We use survey data from U.P. that we collected in 2008–2009 to calibrate voter preferences and other model parameters. We then numerically solve for the model׳s equilibria, and conduct a counterfactual analysis to estimate policies in the absence of caste bias. Our model predicts that the Bahujan Samaj Party (BSP), which was in power at the time of our survey, would be significantly less corrupt in a world without caste-based preferences.
Keywords: Corruption; Redistribution; Political bias; Multidimensional policy space; Indian politics; Caste (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: CASTE, CORRUPTION AND POLITICAL COMPETITION IN INDIA (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:reecon:v:69:y:2015:i:3:p:336-352
Access Statistics for this article
Research in Economics is currently edited by Federico Etro
More articles in Research in Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().