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The COVID-19 pandemic drew new attention to the role of school boards in the U.S. In this paper, we examine school districts' choices of learning modality -- whether and when to offer in-person, virtual, or hybrid instruction -- over the course of the 2020-21 pandemic school year. The analysis takes advantage of granular weekly data on learning mode and COVID-19 cases for Ohio school districts. We show that 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. Moreover, this negative response is magnified when the district was in-person the prior week and attenuates in magnitude over the school year. These findings are consistent with districts learning from experience about the effect of in-person learning on disease transmission in schools. We also find evidence that districts are influenced by the decisions of their peers.

In this paper, we study the role of expertise and independence on governing boards in the context of education. In particular, we examine the causal influence of professional educators elected to local school boards on education production. Educators may bring valuable human capital or experience to school district leadership, thereby improving student learning. Alternatively, the independence of educators may be distorted by interest groups. The key empirical challenge is that school board composition is endogenously determined through the electoral process. To overcome this, we develop and implement a novel research design that exploits California's randomized assignment of the order that candidates appear on election ballots. The insight of our empirical strategy is that ballot order effects generate quasi-random variation in the elected school board's composition. This approach is made possible by a unique dataset that combines election information about California school board candidates with district-level data on education inputs and outcomes. The results reveal that educators on the school board causally increase teacher salaries and reduce district enrollment in charter schools relative to other board members. We do not find accompanying effects on student test scores. We interpret these findings as consistent with educators on school boards shifting bargaining in favor of teachers' unions.

A significant criticism of the charter school movement is that funding for charter schools diverts money away from traditional public schools. As shown in prior work by Bifulco and Reback (2014) for two urban districts in New York, the magnitude of such adverse fiscal externalities depends in part on the nature of state and local funding policies. In this paper, we build on their approach to examine the fiscal effects of charter schools on both urban and non-urban school districts in North Carolina. We base our analysis on detailed balance sheet information for a sample of school districts that experienced significant charter entry since the statewide cap on charters was raised in 2011. This detailed budgetary information permits us to estimate a range of fiscal impacts using a variety of different assumptions. We find a large and negative fiscal impact from $500-$700 per pupil in our one urban school district and somewhat smaller, but still significant, fiscal externalities on the non-urban districts in our sample.

This paper develops and estimates an empirical framework that evaluates the impact of charter school choice on education quality in the aggregate. We estimate the model using student-level data from North Carolina. We find that North Carolina's lifting of its statewide charter school cap raised the average public school's value-added by around 0.01 standard deviations (on the student test score distribution). We calculate the total human capital returns of the expansion at above $100,000 per charter school enrollee. We further show that competition drives the aggregate gains; test score impacts on students induced into charter schools by the policy are negative.

The COVID-19 pandemic drew new attention to the role of school boards in the U.S. In this paper, we examine school districts' choices of learning modality--whether and when to offer in-person, virtual, or hybrid instruction--over the course of the 2020-21 pandemic school year. The analysis takes advantage of granular weekly data on learning mode and COVID-19 cases for Ohio school districts. We show that 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. Moreover, this negative response is magnified when the district was in-person the prior week and attenuates in magnitude over the school year. These findings are consistent with districts learning from experience about the effect of in-person learning on disease transmission in schools. We also find evidence that districts are influenced by the decisions of their peers.

In this paper, we show that the election of a new school board member causes home values in their neighborhood to rise. This increase is identified using narrowly-decided contests and is driven by non-Democratic members, whose neighborhoods appreciate about 4% on average relative to those of losing candidates. We find that student test scores in the neighborhood public schools of non-Democratic winners also relatively increase, but this effect is driven by changing student composition, including via the manipulation of attendance zones, rather than improvements in school quality (as measured by test score value-added). Notably, we detect no differential changes when comparing neighborhood or scholastic outcomes between winning and losing Democratic school board candidates. These results suggest that partisan affiliation is correlated with private motivations for seeking public office.

In this paper, we use a unique two-stage experiment that randomized access to school vouchers across both markets and students in rural India to estimate the revealed preference value of school choice. In the first step of the research design, we develop an empirical model of school choice subject to liquidity and credit constraints that is estimated using data from only the control markets. Based on this exercise, we estimate that the voucher generated welfare gains exceeding four times the average private school's annual tuition on average to the students induced into private schooling. The second step of the research design will validate the estimated welfare impacts by comparing model predictions for a simulated voucher program in control markets with the data from the treatment group. The results in this paper are based on the first step (using only control data) and this draft serves as a pre-commitment to the model estimates and predictions before examining the experimental data.

The tenth annual Recruiting Trends Survey conducted by Placement Services at Michigan State is presented, based on responses from a cross-section of business, government, and educational institutions. Job outlooks in the following fields and categories of 1980-81 graduates are offered: engineering, business, agriculture, science, liberal arts, education, women, minorities and handicapped. Other areas examined include: average starting salaries; campus recruiting activities; layoffs of college graduates; level of education required for job performance; withdrawal of job offers; average cost per new college hire; interviewee preparedness; summer jobs for 1981; recruiting problems; advice to freshmen and sophomores; and job search strategies. Results suggest that (1) employment opportunities for college graduates will be good for the class of 1981 compared to the overall job market; (2) of the nearly one million bachelors' degree graduates, about 90% will have jobs by graduation time; (3) there is a healthy market for engineers, business majors, agriculture, women graduates, and science graduates; (4) and liberal arts and education graduates will find the market in their areas a closed one, The main body of the report contains statistical data from the report. (LC)