Peer group effects on the academic performance of Italian students

Abstract

We analyse peer effects among students of a middle-sized Italian public university. We explain students’ average grade in exams passed during their Second Level Degree course on the basis of their pre-determined measures of abilities, personal characteristics and peer group abilities. Thanks to a rich administrative data set, we are able to build a variety of definitions of peer groups, describing different kinds of students’ interaction, based on classes attended together or exams taken in the same session. Self-selection problems are handled through Two-Stage Least Squares estimations using as an instrument, the exogenous assignment of students to different teaching classes in the compulsory courses attended during their First Level Degree course. We find statistically significant positive peer group effects, which are robust to the different definitions of peer group and to different measures of abilities.

Acknowledgement

We would like to thank an anonymous referee, Mariarosaria Agostino, Francesco Aiello, Giovanni Anania, Giorgio Brunello and Paola Cardamone for useful suggestions and comments. We thank the administration of University of Calabria for allowing access to administrative dataset, and Maria Gabriele, Paolo Santolla and Antonio Ventriglia for helping with the use of data.

Notes

¹ As explained below, Italian University system is organized in two main levels: students first enrol in First Level Degree course and, after graduation, they may choose to enrol in a Second Level Degree course.

² In each academic year Italian students have available several dates to take a given exam (in fact, at University of Calabria seven sessions are available).

³ After Second Level Degree students can enrol in a Ph.D degree.

⁴ Each course typically gives five credits.

⁵ Provinces correspond to the Nuts 3 Eurostat classification.

⁶ Data do not provide information on socio-economic and family background.

⁷ The Final First Level Degree Grade is calculated on the basis of the average grade obtained at exams. In our regressions, we prefer to use AbilityFirst because the Final Grade compresses variability (typically each student with an average grade of 27.5 or more obtains the maximum final grade, ‘110 cum laude’).

⁸ These variables have been standardized in the principal component analysis.

⁹ Students have a certain freedom to choose courses in their Degree program, after some compulsory courses.

¹⁰ This is likely due to the high collinearity between AbilityHS and AbilityFirst (the correlation rate is 0.56). If we consider AbilityHS as the only measure of ability, it is highly significant with a p-value of 0.00 (not reported).

¹¹ We excluded students who have passed less than three exams.

¹² We do not consider differences among schools since all students in our sample accomplished their High School in public schools which differ from the program of study (Lyceums or Technical and vocational schools) but do not differ in terms of resources or teacher/pupil ratio, since the system is highly centralized and uniform.

¹³ The average number of peers according to this definition is 40.83.

On this aspect see also De Giorgi et al. (2006)

¹⁵ Unfortunately, we have data on passed exams only, as no information is available regards failed exams.

¹⁶ We also experimented with a measure of peer group which excludes from the peer group all students sitting together only once or twice (because this meetings could be due to pure chance). Results are similar to those reported.

¹⁷ Bayer et al. (2004) examine peer effects in criminal behaviour and build peer group as a weighted average of peer's characteristic, using as weight the time spent by individuals together in the same prison.

¹⁸ De Giorgi et al. (2006) examine for a prestigious Italian university the influence of peer groups on the choice of majors, rather than on academic performance.