How to Design a State Education Aid Formula Using a Regression-based Estimate of the Cost-capacity Gap: The Case of Connecticut, USA

Bo Zhao

Journal of Education Finance2023https://doi.org/10.1353/jef.2023.a913132article
ABDC C
Weight
0.42

What the paper says

abstract: After being sued for inequity and inadequacy in school funding, many states in the US have reformed their education aid formulas but have still faced many criticisms. Using Connecticut as an example, this paper shows how to design a more equitable and adequate aid formula with tools to win broad support from communities and lawmakers. It develops a measure of the gap between education cost and revenue capacity as an indicator for each district’s need for state aid. Both education cost and revenue capacity are estimated using school district characteristics that are outside the direct control of local officials at any given point in time. This paper shows that Connecticut school districts have a wide range of cost-capacity gaps, due to disparities in cost factors and property tax base, and therefore have different needs for state aid. While larger-gap districts, on average, received more state aid per pupil than smaller-gap districts, many districts—especially the largest-gap ones—received less aid than they needed to close their cost-capacity gaps. Further analysis suggests that inadequate school funding could have a negative impact on student test performance. As a potential solution, this paper proposes a gap-based formula to allocate state aid and includes tools to make the formula more attractive to a wide range of school districts. The policy simulations show that the gap-based formulas can align aid with the gaps better than the existing formula does. However, applying tools to increase the formula’s attractiveness to small-gap districts would compromise the ability of state aid to eliminate inequity and inadequacy and would often require a larger state aid pool. This paper expands the academic community’s knowledge about the US education equity and adequacy by examining Connecticut’s school funding for the first time under the regression-based cost-capacity gap approach. This analysis can be relevant and useful for other states facing similar issues, as it provides a practical, step-by-step roadmap how to apply the sufficiently general research method and formula design to an individual state.

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https://doi.org/https://doi.org/10.1353/jef.2023.a913132

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@article{bo2023,
  title        = {{How to Design a State Education Aid Formula Using a Regression-based Estimate of the Cost-capacity Gap: The Case of Connecticut, USA}},
  author       = {Bo Zhao},
  journal      = {Journal of Education Finance},
  year         = {2023},
  doi          = {https://doi.org/https://doi.org/10.1353/jef.2023.a913132},
}

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Evidence weight

0.42

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.18 × 0.4 = 0.07
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.