Bayesian networks and the assessment of universities' value added

F. Cugnata, G. Perucca and Silvia Salini ()

Journal of Applied Statistics, 2017, vol. 44, issue 10, 1785-1806

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.

Date: 2017
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DOI: 10.1080/02664763.2016.1223839

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