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Schooling During the Great Recession: Patterns of School Spending and Student Achievement using Population Data

Version
V0
Resource Type
Dataset
Creator
  • Shores, Kenneth (University of Delaware)
  • Steinberg, Matthew (George Mason University)
Publication Date
2020-06-18
Description
  • Abstract

    The Great Recession was the most severe economic downturn in the United States since the Great Depression. Using data from the Stanford Education Data Archive (SEDA), we describe the patterns of math and English language arts (ELA) achievement for students attending schools in communities differentially affected by recession-induced employment shocks. Employing a difference-in-differences strategy that leverages both cross-county variation in the economic shock of the recession and within-county, cross-cohort variation in school-age years of exposure to the recession, we find that declines in student math and ELA achievement were greater for cohorts of students attending school during the Great Recession in communities most adversely affected by recession-induced employment shocks, relative to cohorts of students that entered school after the recession had officially ended. Moreover, declines in student achievement were larger in school districts serving more economically disadvantaged and minority students. We conclude by discussing potential policy responses.
Availability
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Relations
  • Is supplement to
    DOI: 10.1177/2332858419877431 (Text)
Publications
  • Shores, Kenneth, and Matthew P. Steinberg. “Schooling During the Great Recession: Patterns of School Spending and Student Achievement Using Population Data.” AERA Open 5, no. 3 (July 2019): 233285841987743. https://doi.org/10.1177/2332858419877431.
    • ID: 10.1177/2332858419877431 (DOI)

Update Metadata: 2020-06-18 | Issue Number: 1 | Registration Date: 2020-06-18

Shores, Kenneth; Steinberg, Matthew (2020): Schooling During the Great Recession: Patterns of School Spending and Student Achievement using Population Data. Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E119963