Chicago Booth Review
March 12, 2024
Jesse Bruhn, Christopher Campos, Eric Chyn, and Anh Tran
March 2025
The authors study the distributional effects of remote learning using a novel approach that combines preference data from a conjoint survey experiment with administrative student records. The experimentally derived preference data allow us to account for selection into remote learning while also studying selection patterns and treatment effect heterogeneity. The authors validate the approach using random variation from school choice lotteries. The authors’ analysis of the average impacts of remote learning finds negative effects on reading (–0.13σ) and math (–0.14σ) achievement. Notably, they find evidence of positive learning effects for children whose parents have the strongest demand for remote learning. Parental concerns related to bullying appear to be an important driver of the demand for remote learning. Moreover, the authors find that across-the-board positive impacts of remote learning on bullying outcomes operate as a compensating differential for negative impacts on learning. Their results suggest that an important subset of students who currently sort into post-pandemic remote learning benefit from expanded choice.
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