The determination of public tuition fees in a mixed education system: A majority voting model - Aix-Marseille Université Accéder directement au contenu
Article Dans Une Revue Journal of Public Economic Theory Année : 2019

The determination of public tuition fees in a mixed education system: A majority voting model

Résumé

We study the determination of public tuition fees through majority voting in a vertical differentiation model where agents' returns on educational investment differ and public and private universities coexist and compete in tuition fees. The private university offers higher educational quality than its competitor, incurring higher unit cost per trained student. The tuition fee for the state university is fixed by majority voting while that for the private follows from profit maximization. Then agents choose to train at the public university or the private one or to remain uneducated. The tax per head adjusts in order to balance the state budget. Because there is a private alternative, preferences for education are not single-peaked and no single-crossing condition holds. An equilibrium is shown to exist, which is one of three types: high tuition fee (the “ends” are a majority), low tuition fee (the “middle” is a majority), or mixed (votes tie). The cost structure determines which equilibrium obtains. The equilibrium tuition is either greater (majority at the ends) or smaller (majority at the middle) than the optimal one.
Fichier principal
Vignette du fichier
The determination of Public Tuition Fees in aMixed Education System.pdf (587.15 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01992143 , version 1 (12-02-2020)

Identifiants

Citer

Hejer Lasram, Didier Laussel. The determination of public tuition fees in a mixed education system: A majority voting model. Journal of Public Economic Theory, 2019, 21 (6), pp.1056-1073. ⟨10.1111/jpet.12317⟩. ⟨hal-01992143⟩
76 Consultations
205 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More