Development and History
Development and Economic History
Members of the Development and Economic History Research Group combine archival data, lab-in-the-field experiments, randomized controlled trials, text analysis, survey and secondary data along with theoretical tools to study issues in development and economic history. Faculty and students work in the field in South Asia, China and Africa as well as doing archival work in libraries across Europe and Asia.
Almost all faculty are members of CAGE in the economics department and some are also members of Warwick Interdisciplinary Centre for International Development (WICID). There is a regular weekly external seminar, two weekly internal workshops, and high quality research students. We also organise international conferences on campus, or in Venice.
Our activities
Development and Economic History Research Group Workshop/Seminar
Monday: 1.00-2.00pm
For faculty and PhD students at Warwick and other top-level academic institutions across the world. For a detailed scheduled of speakers please follow the link below.
Organisers: Bishnupriya Gupta and Claudia Rei
People
Academics
Academics associated with the Development and Economic History Research Group are:
Bishnupriya Gupta
Co-ordinator
Anant Sudarshan
Deputy Co-ordinator
Research Students
Events
Econometrics Seminar - Francesca Molinari (Cornell)
Organisers: Mingli Chen and Giovanni Ricco
Title of paper is: Discrete choice under risk with limited consideration
Abstract: This paper is concerned with learning decision makers’ (DMs) preferences using data on observed choices from a finite set of risky alternatives with monetary outcomes. We propose a discrete choice model with unobserved heterogeneity in consideration sets (the collection of alternatives considered by DMs) and unobserved heterogeneity in standard risk aversion. In this framework, stochastic choice is driven both by different rankings of alternatives induced by unobserved heterogeneity in risk preferences and by different sets of alternatives considered. We obtain sufficient conditions for semi- nonparametric point identification of both the distribution of unobserved heterogeneity in preferences and the distribution of consideration sets. Our method yields an estimator that is easy to compute and that can be used in markets with a large number of alternatives. We apply our method to a dataset on property insurance purchases. We find that although households are on average strongly risk averse, they consider lower coverages more frequently than higher coverages. Finally, we estimate the monetary losses associated with limited consideration in our application.
Coauthors: Levon Barseghyan (Cornell) and Matthew Thirkettle (Cornell)