Conducting field experiments in education with Sally Sadoff and Andy Brownback

In this episode, we speak with Sally Sadoff from the Rady School of Management, UC San Diego, and Andy Brownback from the University of Arkansas, about their field work with community colleges. They discuss two recent papers they coauthored on the topic. The first paper, entitled “Improving College Instruction through Incentives,” investigates the effect of offering performance-based incentives to community college instructors on students’ achievement. The second paper studies the educational benefits of enrolling in college summer schools and whether students correctly perceive the potential returns.

Debate participation and electoral outcomes with Horacio Larreguy

In this episode, we talk with Horacio Larreguy from the Harvard Kennedy School about his paper “Who Debates,Wins? At-Scale Experimental Evidence on Debate Participation in a Liberian Election,” which he co-authored with Jeremy Bowles. They conduct a field experiment in Liberia to understand how the participation of legislative candidates in nationwide debate initiatives affects their electoral outcomes.

Dynamic Inconsistency in Food Choice with Anya Samek

In this episode, we talk with Anya Samek from the University of Southern California about her paper “Dynamic Inconsistency in Food Choice: Experimental Evidence from Two Food Deserts,” which she co-authored with Sally Sadoff and Charlie Sprenger. In the context of two home grocery delivery programs, this paper provides evidence of (i) dynamic inconsistency between immediate and advance choices of food and (ii) a surprising negative link between dynamic inconsistency and commitment demand to advance choices.

During this conversation, Anya also refers to two papers on the topic of field experiments:

Testing Bayesian Updating with Ned Augenblick

In this episode, we talk with Ned Augenblick from the University of Berkeley Haas School of Business about his paper with Matthew Rabin entitled “Belief Movement, Uncertainty Reduction, & Rational Updating”. This paper analyzes the relationship between (i) the movement in the beliefs of a Bayesian updater when new information arrives, and (ii) the associated reduction in his uncertainty. This relationship is used to develop statistical tests of rational updating that are then applied to datasets of beliefs.