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Political Economy and Public Economics

Political Economy and Public Economics

The Department of Economics at the University of Warwick has an active Political Economy and Public Economics (PEPE) Research Group. These two disciplines have natural complementarities. Political Economy focuses more on the political feasibility of certain policies by looking at which policies are more likely to enjoy public support and thus succeed in an electoral contest. Public economics looks more at determining which policies are optimal in every environment, but is less concerned about their political approval or feasibility.

Recent world events such as the public backlash against globalization and inequality have raised awareness for the need for more integration between these two approaches as political resistance to the adoption of potentially beneficial policies has become ever more salient. Hence by their very nature these two disciplines transcend traditional field divisions such as micro and macroeconomics: they use theoretical, empirical and experimental methods to obtain conclusions, thus generating synergies with various other groups in our department from development to experimental to history to macroeconomics to economic theory.

Our activities

PEPE Research Group Seminar

Thursday: 11.15am-12.30pm
A weekly seminar is organised that brings top economists and political scientist speakers every week for a double-feature seminar in coordination with the LSE.

For a detailed scheduled of speakers please follow the link below:

https://warwick.ac.uk/fac/soc/economics/seminars/seminars/political-economy 

Organisers: Michela Redoano and Mateusz Stalinski

PEPE Research Group Annual Conference

In collaboration with colleagues from Princeton and Yale, and with the support of CEPR, the PEPE Research Group organises an annual conference which has become a central meeting of political economists in Europe. Having taken place in previous years in Venice and Rome, it attracts over 70 delegates attending from leading institutions in the US, EU and the UK. Every year, several of our PhD students get to participate in a fully funded conference with an opportunity to engage with leading scholars.

Find out more about this year's conference which will take place 26-27 April 2024 in Rome.

Organisers: Helios Herrera, Mateusz Stalinski

People

Academics

Academics associated with the Reseach Group Name research group are:


Michela Redoano

Co-ordinator

Helios Herrera

Deputy Co-ordinator

Events

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Applied Economics, Econometrics & Public Policy (CAGE) Seminar - Abhijeet Singh (HHS).

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Location: S2.79

Title: The incidence of affirmative action: Evidence from quotas in private schools in India (with Maricio Romero)

Abstract: The incidence of redistributive policies is central to whether they meet their stated goals. We study this in the context of one of the world's largest programs to improve social equity in schooling: a 25% quota in all Indian private schools for students from disadvantaged groups. We use lottery-based estimates to show that, although students admitted under the quota attend more expensive and preferred schools on average, the distribution of program benefits is very regressive. Program applicants are concentrated among more-educated and better-off households. Consequently, 7.4% of the program spending accrues to the bottom socioeconomic quintile, compared to 24.3% to the top quintile. We use rich survey data to show that low application rates for poorer children are not driven by preferences and beliefs. Instead, information constraints and application frictions appear to be key. Finally, we use a randomized intervention to confirm the importance of these frictions and further demonstrate that alleviating a single constraint (e.g., information) may not reduce regressive selection, even if it boosts application rates substantially. Our results demonstrate how constraints facing potential applicants can make redistributive policies regressive in practice. Appropriate policy interventions must consider the joint incidence of these constraints to reduce regressivity.

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