Work Description

Title: Dataset and Associated Code to Assess the Educational Benefits of the US EPA School Bus Rebate Program Open Access Deposited

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Attribute Value
Methodology
  • We obtained data on all applicants for the 2012 through 2016 lotteries from the US EPA under a Freedom of Information Act (FOIA) request. The data for all applicants included: the lottery selection status, school district served, number of buses requested to be replaced, and funding requested. For districts that were awarded funding, we additionally received information on the number of buses/engines replaced or retrofitted, as well as engine model year of the replaced (i.e., baseline) buses, although this information was most often averaged across all replaced buses in a district. School district information came from the US Department of Education’s (ED) yearly Local Education Agency (School District) Universe Survey Data. These publicly available data include the number of students (total and by grade and race/ethnicity), number of schools, and urbanicity (i.e., city, suburb, town, rural) of each district. The land area of each school district was provided in the National Center for Education Statistics School District Geographic Relationship files for the school years of 2013-2014, 2015-2016, and 2017-2018. As a proxy for district socioeconomic status, we used data on the number of students in a school who were eligible for the free or reduced-price lunch program during the baseline school year from the US ED yearly Public Elementary/Secondary School Universe Survey Data, which we aggregated to the district level. We obtained data on all applicants for the 2012 through 2017 lotteries from the US EPA under a Freedom of Information Act (FOIA) request. The data for all applicants included: the lottery selection status, school district served, number of buses requested to be replaced, and funding requested. For districts that were awarded funding, we additionally received information on the number of buses/engines replaced or retrofitted, as well as engine model year of the replaced (i.e., baseline) buses, although this information was most often averaged across all replaced buses in a district. School district information came from the US Department of Education’s (ED) yearly Local Education Agency (School District) Universe Survey Data. These publicly available data include the number of students (total and by grade and race/ethnicity), number of schools, and urbanicity (i.e., city, suburb, town, rural) of each district. The land area of each school district was provided in the National Center for Education Statistics School District Geographic Relationship files for the school years of 2013-2014, 2015-2016, and 2017-2018. As a proxy for district socioeconomic status, we used data on the number of students in a school who were eligible for the free or reduced-price lunch program during the baseline school year from the US ED yearly Public Elementary/Secondary School Universe Survey Data, which we aggregated to the district level. We obtained school district test score data for math and reading and language arts (RLA) for children in grades 3 through 8 from the Stanford Education Data Archive (SEDA). We averaged SEDA data across grades by district and year. We linked annual standardized testing data for both the school year before and after the purchase of new buses to EPA entrants to have the most proximate data to an entrant’s lottery selection status inform the analysis and to reduce the influence of trends.
Description
  • In this study, we took advantage of the randomized allocation of the US EPA's funding for school bus replacements and retrofits to causally assess the impacts of upgrading buses on students' educational performance through the EPA’s national School Bus Rebate Program. Specifically, we used classical intent-to-treat analyses for randomized controlled trials to compare the change in school district level reading and language arts and math standardized test scores after vs before the 2012 through 2016 lotteries by funding selection status . We used overall district average standardized test scores since rates were not available for only school-bus riders.
Creator
Creator ORCID
Depositor
  • mpedde@umich.edu
Contact information
Discipline
Funding agency
  • Other Funding Agency
Other Funding agency
  • Health Effects Institute
ORSP grant number
  • AWD014294
Keyword
Date coverage
  • 2012-09-01 to 2018-06-30
Citations to related material
Resource type
Last modified
  • 05/09/2024
Published
  • 05/09/2024
Language
DOI
  • https://doi.org/10.7302/qx56-7c50
License
To Cite this Work:
Pedde, M. (2024). Dataset and Associated Code to Assess the Educational Benefits of the US EPA School Bus Rebate Program [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/qx56-7c50

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Files (Count: 4; Size: 986 KB)

Thumbnailthumbnail-column Title Original Upload Last Modified File Size Access Actions
read_me_for_Educational_Benefits...s.txt 2024-03-20 2024-03-20 3.54 KB Open Access
Bus_Funding_Education_Results_an...n.sas 2024-03-20 2024-03-20 20 KB Open Access
DERA_Lottery_All_final_Education...y.csv 2024-03-20 2024-03-20 6.32 KB Open Access
DERA_Lottery_All_final_Education.csv 2024-03-20 2024-03-20 956 KB Open Access

Date: 20 March, 2024

Dataset Title: Dataset to Assess the Educational Benefits of the US EPA School Bus Rebate Program

Dataset Creators: M. Pedde, A. Szpiro, R. Hirth, S.D. Adar

Dataset Contact: Meredith Pedde mpedde@umich.edu

Funding: 966-RFA18-1/19 (Health Effects Institute)

Key Points:
- Older school buses can expose students to high levels of diesel exhaust.
- This exposure can adversely impact health and school attendance, which may lower educational performance.
- EPA has spent millions of dollars to hasten the transition of school bus fleets to cleaner vehicles.
- We find that this EPA clean bus funding program did not improve district-average student test scores in reading and language arts and math among selected districts overall. In secondary analyses, however, districts that were
awarded funding to replace the oldest and highest-polluting buses experienced significantly greater improvements in district-average student test scores compared with those not selected for replacement funding.
- EPA distributed this funding randomly, allowing us to causally assess the educational impacts of school districts switching to cleaner buses.

Research Overview:
Approximately 25 million children ride buses to school in the United States (US). While school buses remain the safest school transport from an accident perspective, older buses often expose students to high levels of diesel exhaust. Since these exposures can adversely impact health and attendance, which may lower educational performance, the US EPA has spent millions of dollars to hasten the transition of school bus fleets to cleaner vehicles.
Here, we leveraged the randomized allocation of the EPA’s 2012-2016 School Bus Rebate Program funding to causally assess the district educational impacts of upgrading buses.
Districts randomly selected for School Bus Rebate Program funding had comparable changes in educational test scores for RLA and math in the year after the lottery to districts not selected for funding (mean SD changes in scores, 0.005 [95% CI, -0.007 to 0.018] higher for RLA and -0.001 [95% CI, -0.011 to 0.010] lower for math).
For districts replacing the oldest buses (pre-1990 models), however, we observed significantly larger SD improvements in mean RLA test scores of 0.062 (95% CI, 0.050-0.074) and math test scores of 0.025 (95% CI, 0.011-0.039) compared with districts without replacements.
These findings support prioritizing clean bus replacement of the oldest buses as an actionable way for improving students' educational performance.

Methodology:
The data are used to assess the educational impacts of the US EPA's School Bus Rebate Program. All analyses were conducted in SAS v9.4.

Instrument and/or Software specifications: NA

Files contained here:
The dataset and SAS code shared here were used to assess the educational benefits of the US EPA's School Bus Rebate Program.
- DERA_Lottery_All_final.xlsx: analyses data used in this publication
- Bus_Funding_Education_Results_and_Tables_JAMA_Network_Open.sas: code to reproduce all results in this publication using the datset listed above

Related publication(s):
Pedde, M., Szpiro, A., Hirth, R., Adar, S.D. (2024). School Bus Rebate Program and Student Educational Performance Test Scores. JAMA Network Open. https://doi.org/10.1001/jamanetworkopen.2024.3121

Use and Access:

To Cite Data:
Pedde, M., Szpiro, A., Hirth, R., Adar, S.D. (2024). Dataset to Assess the Educational Benefits of the US EPA School Bus Rebate Program [Data set]. University of Michigan - Deep Blue.

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