Credit Crunch in the Classroom: School District Financing Under Liquidity Constraints

• In Event: School Structure and Student Outcomes

Abstract

In this paper, I examine how municipal bond market credit ratings affect future funding and staffing decisions in the US public education system. Using a novel and comprehensive dataset of all municipal bonds issued by US public school districts since 1987, I apply machine learning techniques to identify districts near key credit rating thresholds. Leveraging a regression discontinuity design, I then estimate the causal impact of diminished credit access across these thresholds. Focusing on the AAA-AA margin, I find that a reduced credit rating results in approximately 6\% lower spending in the fiscal year following a ratings update. I show that this is primarily driven by decreases in capital expenditure, property tax revenue, and maintenance spending with the largest effects observed for mid-sized school districts.

Author

• Christopher Monjaras, University of Notre Dame
  Presenting Author