Regression quantiles to assess higher education performance

From 2001 Italian university system has adopted the credits to mea-sure the workload of the students. The weighted mean of marks with credits asweights is used to measure the their performance. In our opinion it does notseem a proper way to measure. We suggest to adopt the median of the weightedmarks, because we are considering an ordinale variable, with a non-normal empir-ical distribution, and a®ected by outliers. Then, instead of using an OLS multipleregression, we investigate the determinants of the performance measured by themedian using a regression quantile for ordinal response. A real dataset concerning133 students of the Faculty of Economics of the University of Palermo is consid-ered. Results show how the quantile regression is more able than the OLS one tocatch the e®ect of each covariate on student performance.