{"title":"Assessing School District Decision-Making: In-Person Schooling and COVID-19 Transmission","authors":"Alvin Christian, Brian Jacob, John D. Singleton","doi":"10.1162/edfp_a_00433","DOIUrl":null,"url":null,"abstract":"\n Recent controversies have highlighted the importance of local school district governance, but little empirical evidence exists evaluating the quality of district policymakers or policies. In this paper, we take a novel approach to assessing school district decision-making. We posit a model of rational decision-making under uncertainty that emphasizes districts learning over time. We test the predictions from the model using data on a set of highly visible and consequential decisions facing school district leaders—the choice of learning mode during the 2020-21 school year. We find that district behavior is consistent with a Bayesian learning process in several key respects. Districts respond on the margin to health risks: all else equal, a marginal increase in new cases reduces the probability that a district offers in-person instruction the next week. This negative response is magnified when the district was in-person the prior week and attenuates in magnitude over the school year, suggesting districts learn from experience about the effect of in-person learning on disease transmission in schools. We also find evidence that districts are influenced by the learning mode decisions of peer districts, but not their peers' experiences with in-person instruction and disease transmission, which implies that some important frictions exist.","PeriodicalId":46870,"journal":{"name":"Education Finance and Policy","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education Finance and Policy","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1162/edfp_a_00433","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Recent controversies have highlighted the importance of local school district governance, but little empirical evidence exists evaluating the quality of district policymakers or policies. In this paper, we take a novel approach to assessing school district decision-making. We posit a model of rational decision-making under uncertainty that emphasizes districts learning over time. We test the predictions from the model using data on a set of highly visible and consequential decisions facing school district leaders—the choice of learning mode during the 2020-21 school year. We find that district behavior is consistent with a Bayesian learning process in several key respects. Districts respond on the margin to health risks: all else equal, a marginal increase in new cases reduces the probability that a district offers in-person instruction the next week. This negative response is magnified when the district was in-person the prior week and attenuates in magnitude over the school year, suggesting districts learn from experience about the effect of in-person learning on disease transmission in schools. We also find evidence that districts are influenced by the learning mode decisions of peer districts, but not their peers' experiences with in-person instruction and disease transmission, which implies that some important frictions exist.