@TechReport{iza:izadps:dp18439,
            	author={Epper, Thomas and Ibsen, Kristoffer and Koch, Alexander K. and Nafziger, Julia},
            	title={Predicting University Dropouts: Evidence on the Value of Student Expectations and Motivation},
            	year={2026},
	month={Mar},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={18439},
            	url={https://www.iza.org/publications/dp18439},
	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},
            }