Predicting University Dropouts: Evidence on the Value of Student Expectations and Motivation

Thomas Frank Epper, Kristoffer Ibsen, Alexander K Koch and Julia Nafziger

No 21263, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: University dropout is costly, making it a policy priority to identify factors that predict dropout. Using a survey experiment with incoming first-year students linked to long-run administrative outcomes, we assess which information improves dropout prediction beyond standard university records. A small number of targeted, study-specific survey items — especially motivation and expectations about degree completion — substantially improve predictive performance. By contrast, widely used measures of general preferences and traits (such as grit and self-control) add little incremental value — a result that we qualitatively replicate in a large population. Our findings suggest inexpensive, scalable ways to improve dropout predictions.

Keywords: Dropout; Non-cognitive skills; Motivation; Economic preferences; beliefs; Education; Machine learning (search for similar items in EconPapers)
JEL-codes: D91 I23 (search for similar items in EconPapers)
Date: 2026-03
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