Bayesian networks and the assessment of universities' value added

ABSTRACT

A broad literature focused on the effectiveness of tertiary education. In classical models, a performance indicator is regressed on a set of characteristics of the individuals and fixed effects at the institution level. The FE coefficients are interpreted as the pure value added of the universities. The innovative contribution of the present paper resides in the use of Bayesian network (BN) analysis to assess the effectiveness of tertiary education. The results of an empirical study focused on Italian universities are discussed, to present the use of BN as a decision support tool for policy-making purposes.

KEYWORDS:

• VAM models
• economics of education
• casual models
• do-calculus

Acknowledgments

We thank MIUR PRIN MISURA (Multivariate models for risk assessment) for financial support of the project.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCiD

S. Salini http://orcid.org/0000-0001-6106-9835

Notes

1. We use the bnlearn library [35,41] and the gRain library [29] to perform the inference required to calculate the conditional probabilities.

2. The categories of yearly income are the following ones: 0, (0, 12,000€], (12,000€, 18,000€], (18,000€, 24,000€], >24,000€.