Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Most university departments aspire to increase their quantity of students. The objective of this empirical study is to ascertain whether it is possible to identify students who would demand more economics study. Using data on student perceptions of economics and the application of logistic regression, two step autoclustering, <italic>K</italic> means clustering, analysis of variance and Tukey's honestly significant difference statistical techniques, we reveal distinct clusters of students, including a small cluster of students who appear to be more open to further study.