In many centralized school assignment systems, students are
required to submit ranked preference lists. Depending on the
system’s design, they may have incentives to fill out these
lists strategically. Using register data from Amsterdam, this
paper investigates how students respond to changes in strategic
incentives following previously unexplored design reforms. After
a 2016 reform that limited school priority to first-ranked
choices, I document a marked increase in the share of students
ranking their priority school first—an increase larger than
predicted by simulations assuming optimal strategic behavior. In
2018, the introduction of a placement guarantee created a new
incentive to manipulate rank-ordered lists. Yet, my analyses
suggest that few students, if any, responded to this opportunity
in a strategically sophisticated manner. My findings also
highlight the fragility of assignment mechanisms: even seemingly
modest policy changes can erode properties such as
strategy-proofness and produce unintended consequences.
Simulations illustrate that if a larger share of students were
to exploit the placement guarantee reform, the system could
experience a sharp rise in the number of unassigned students,
raising the risk of market collapse.
The Financial Literacy Puzzle: an Impact Evaluation of Financial
Education in Italy
I attempt to gauge the impact of the 2008-2010 Gelmini school
reform on Italian students’ educational achievement. The reform
aimed at cutting on educational spending by targeting teaching
staff expenditures, as well as boosting the overall efficiency
of the education system. I apply Synthetic Control methods (SCM)
to a panel dataset of six PISA international assessments for 25
countries, and carry out a case study of the reform. I find
large effects on mathematics performance, but no statistically
significant evidence of an impact on reading scores. The
inferential strategy based on placebo runs sets the p-value for
math treatment effect about the 10% threshold, meaning weak
statistical significance. The observed positive effect on math
scores may simply be the result of training for Invalsi tests
and teaching to the test. However, a conservative and
economically relevant conclusion can be drawn from my results:
the Gelmini school reform did not negatively affect Italian
students’ achievement in international tests. Contextual
questionnaires allow me to provide an interpretation for these
results. In robustness analysis, I experiment with changing the
matching period, the predictors, and the donor pool units.
Moreover, I directly address the scarcity of pre-intervention
observations by merging TIMSS data, and applying a recently
developed penalized Synthetic Control method. This is one of the
few studies that attempted to quantitatively assess the outcome
of the Gelmini reform. Moreover, to the best of my knowledge, my
analysis constitutes the first attempt to apply SCM to a merged
PISA-TIMSS database, and the first application of the penalized
SCM to international assessments data.
I use the PISA 2018 student-level achievement database, recently
made available, to estimate the impact of socio-economic
background on students’ school performance. Family background is
found to exert a strong positive effect on educational
achievement, which is estimated in an increase of one third of a
standard deviation in PISA test performance for each
one-standard deviation increase in student socio-economic index.
I use the estimated cross-country variation in family background
effect as a measure of inequality of educational opportunities
and search for cross-country differences in institutions that
may explain such variation. Further analysis provides evidence
of a potential trade-off between equality of educational
opportunities and efficiency in education production.
Non-Economics
Monitoring Faculty Development: with Data, beyond Data
[LINK]
Higher Education Learning Methodologies and Technologies Online
(Springer), 2024
Monitoring the reach of faculty development programs is needed
to effectively support efforts and design future actions.
However, evaluation requires careful integration into the
organisational culture and processes. The University of Padua
established the “Teaching4Learning@Unipd” (T4L) Faculty
Development program in 2016 and a Monitoring Group has been put
in place to oversee the program using various data sources. The
present paper presents findings from the Monitoring Group's
research. The study explored perceptions of teachers and
students about the use of active teaching methods: data from 241
academic teachers and 130 students was collected and analysed.
The results showed: Teachers trained in T4L were more likely to
use technology-mediated interactive methods than non-T4L
teachers. A positive correlation was found between teachers and
students’ perceptions of the implementation of active teaching
methods. T4L-trained teachers showed higher motivation and
self-reflection about their teaching skills. There was also a
perception of increased workload for teachers switching to
active teaching methods. The study's results emphasize the
significance of promoting, monitoring, and improving the
sustainability of a quality-focused, data-driven, and
participatory approach to teaching.