Location of Repository

Micro-Level Determinants of Lecture Attendance and Additional Study-Hours

By Liam Delaney, Martin Ryan and Colm Harmon


This paper uses novel measures of individual differences that produce new insights about student inputs into the (higher) education production function. The inputs examined are lecture attendance and additional study-hours. The data were collected through a web-survey that the authors designed. The analysis includes the following measures: willingness to take risks, consideration of future consequences and non-cognitive ability traits. Besides age, gender and year of study, the main determinants of lecture attendance and additional study-hours are attitude to risk, future-orientation and conscientiousness. In addition, future-orientation, and in particular conscientiousness, determine lecture attendance to a greater extent than they determine additional study. Finally, we show that family income and financial transfers (from both parents and the state) do not determine any educational input. This study suggests that non-cognitive abilities may be more important than financial constraints in the determination of inputs related to educational production functions.higher education, education inputs, lecture attendance, hours of study, future-orientation, attitude to risk, non-cognitive ability, conscientiousness

OAI identifier:

Suggested articles



  1. A very brief measure of the Big-Five personality domains."
  2. Am I Missing Something? The Eects of Absence from Class on Student Performance." IZA Discussion Papers 3749, 2008, Institute for the Study of Labor
  3. (2008). Consideration of future consequences, ego-depletion, and self-control: Support for distinguishing between CFC-immediate and CFC-future sub-scales."
  4. Cross-sectional Earnings Risk and Occupational Sorting: The Role of Risk Attitudes."
  5. (2010). Direct Evidence on Risk Attitudes and Migration." The Review of Economics and Statistics,
  6. Do Students Go to Class? Should They?"
  7. (2007). Educational Production Functions." Palgrave Encyclopedia,
  8. (2008). Enhancing Noncognitive Skills to Boost Academic Achievement. Educational Testing in America: State Assessments, Achievement Gaps, National Policy and Innovations. Princeton Educational Testing Service,
  9. (2005). Financial Support, Students' Employment, and Academic Performance in College."
  10. (2005). Individual Risk Attitudes: New Evidence from a Large, Representative, Experimentally-Validated Survey."
  11. (2008). Parental Transfers, Student Achievement, and the Labour Supply of College Students." US Bureau of Labour Statistics (BLS) Working Papers,
  12. (2000). Policies to Foster Human Capital.
  13. (2006). Student Achievement and University Classes: Eects of Attendance, Size, Peers, and Teachers."
  14. (1991). The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement."
  15. (2007). The Causal Eect of Studying on Academic Performance."
  16. (2008). The Consideration Of Future Consequences Scale: An Assessment And Review." University of Agder Working Paper,
  17. (1994). The consideration of future consequences: weighing immediate and distant outcomes of behavior."
  18. (2008). The Economics and Psychology of Personality Traits."
  19. The Eective Use of Student Time: A Stochastic Frontier Production Function Case Study."
  20. (1995). The Eects of Attendance on Student Learning in Principles of Economics".
  21. (2002). The Evidence on Credit Constraints in Postsecondary Schooling.
  22. (1983). Who Maximizes What? A Study in Student Time Allocation".

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.