Journal article
Nearly-efficient tuitions and subsidies in American public higher education
Economics of education review, Vol.55, pp.182-197
12/01/2016
DOI: 10.1016/j.econedurev.2016.09.003
Abstract
•Endogenous tuition and subsidy structures are determined for decentralized public universities.•Subsidies are optimally directed to support high net willingness to pay programs.•Inefficient restrictions placed on the subsidy structure reduce welfare and significantly redistribute value among resident and nonresident students and state taxpayers.•Tuitions and subsidies are determined to numerically replicate standard public university budgeting templates.•The formulations, as applied to the University of Iowa and to the University of Michigan, indicate that equity (fairness) dominates efficiency considerations.
A two-stage setting for determining subsidies and tuitions in a public university context is developed where fixed costs introduce an efficiency-enhancing role for taxpayer-financed appropriations. The optimal subsidy per enrollment is shown to be proportional to students’ maximum net willingness to pay. This result extends a well-known result associated with Ramsey pricing to include endogenous appropriations to public higher education. Realistic restrictions are imposed on the subsidy structure, and scenarios for determining tuitions are addressed and illustrated numerically, using budget data for the University of Iowa and the University of Michigan.
Details
- Title: Subtitle
- Nearly-efficient tuitions and subsidies in American public higher education
- Creators
- Samuel Burer - University of IowaGary Fethke - Professor Emeritus of Economics and Management Sciences, Tippie College of Business, University of Iowa, United States
- Resource Type
- Journal article
- Publication Details
- Economics of education review, Vol.55, pp.182-197
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.econedurev.2016.09.003
- ISSN
- 0272-7757
- eISSN
- 1873-7382
- Language
- English
- Date published
- 12/01/2016
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380520002771
Metrics
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