Information Policies in Secondary and Higher Education
Friday, Jan. 6, 2023 8:00 AM - 10:00 AM (CST)
- Chair: Christopher Neilson, Princeton University
Social Interactions and Preferences for Schools:Experimental Evidence from Los Angeles
AbstractUnlike conventional markets, the notion of quality in education markets is vastly more ambiguous and challenging to observe. In addition, there is a considerable amount of debate surrounding the margins of quality that govern how parents select schools, and in a setting with imperfect information, parents may resort to other parents’ private signals to make decisions. Therefore, inadequate information, preferences, and social interactions may each play different roles in distorting school incentives. I design an information provision experiment that allows me to study these various factors among parents making schooling decisions in Los Angeles. To study relative preferences for school and peer quality, I cross-randomize two margins of information, and to study social interactions, I use a spillover design that allows me to detect treatment effects for untreated parents in treated schools. I find that receiving information on either quality margin changes parents’ decisions, suggesting parents are imperfectly informed about both. I then show that social interactions are prevalent, generating treatment effects for untreated parents in treated schools similar to treated parents. The social interactions are sufficiently large to generate market-level consensuses uniformly moving demand toward higher value-added schools coupled with a systematic shift toward schools with lower quality peers. These findings suggest that when parents are perfectly informed about both school and peer quality, parental interactions are essential for interpreting the information and that demand moves in a way consistent with parents rewarding effective schools, providing schools incentives that are more aligned with improving student learning. The experiment ran again in Fall 2021 and results for the second iteration are forthcoming.
Application Mistakes and Information frictions in College Admissions
AbstractWe analyze the prevalence and relevance of application mistakes in a seemingly strategy-proof centralized college admissions system. We use data from Chile and exploit institutional features to identify a common type of application mistake: applying to programs without meeting all requirements (admissibility mistakes). We find that the growth of admissibility mistakes over time is driven primarily by growth on active score requirements. However, this effect fades out over time, suggesting that students might adapt to the new set of requirements but not immediately. To analyze application mistakes that are not observed in the data, we design nationwide surveys and collect information about students’ true preferences, their subjective beliefs about admission probabilities, and their level of knowledge about admission requirements and admissibility mistakes. We find that between 2% - 4% of students do not list their true most preferred program, even though they face a strictly positive admission probability, and only a fraction of this skipping behavior can be rationalized by biases on students’ subjective beliefs. In addition, we find a pull-to-center effect on beliefs, i.e., students tend to attenuate the probability of extreme events and under-predict the risk of not being assigned to the system. We use these insights to design and implement a large-scale information policy to reduce application mistakes. We find that showing personalized information about admission probabilities has a causal effect on improving students’ outcomes, significantly reducing the risk of not being assigned to the centralized system and the incidence of admissibility mistakes. Our results suggest that information frictions play a significant role in affecting the performance of centralized college admissions systems, even when students do not face clear strategic incentives to misreport their preferences.
Identifying The Spillover and Congestion Effects of Large Scale Information Interventions
AbstractThis paper studies how the effects of information provision vary with the scale of the intervention, in terms of the number of treated people. To do so, we evaluate the effects of an intervention that provides information of product availability and characteristics on consumer demand. We study these issues in the context of school choice where consumers are families that submit a ranked ordered list to a centralized assignment mechanism and are later assigned to schools depending on a specific set of rules, capacities, and overall demand. This allows for the design of an experiment where we can, in theory, disentangle the spillover effects of the information intervention on choices separately from the congestion effects that occur when aggregate demand changes prior to any supply side adjustments. We provide individual families as well as entire neighborhood markets with information about the schools that are nearby. We observe their applications, assignments, and matriculation choices and therefore we can test whether the intervention changed their applications as well as their later assignments. We implement this study in the population of all parents from dense urban areas (i.e., those with many schooling options) who participate in the centralized school choice process for the academic year 2021 in Chile. Our goal is to help determine where information provision at scale can be helpful at improving match quality and reducing segregation while also taking into account that a scaled-up intervention could have adverse effects on some applicants due to increased congestion in the short run.
- I2 - Education and Research Institutions