Regional Economic Disparities as Determinants of Students’ Achievement in Italy

Abstract

We use a statistical (multilevel) approach to study the relationship between Math Scores and individual-level and school-level factors. The sample contains data about 21,336 students sorted into 163 schools. Our results show that students attending schools in Northern Italy outperform their counterparts in the South. Moreover, the between-schools variance is much higher in Southern Italy than in Northern Italy, albeit it is not due to student sorting based on different socio-economic status (SES), as suggested by the traditional literature in this field. Finally, between-schools variance actually masks achievement differentials due to the different economic development of the Regions.

Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students

“…For example, it emerged that females have worse average results than males, 1 st and 2 nd generation immigrant students have lower average performances than native Italian students, being early/late-enrolled students decreases the average results, students with a high level of socioeconomical status have better performances than students with a lower one, and much more. Big differences exist between North, Center and South of Italy: students attending schools in the North obtain higher scores, all else equal, reinforcing the need for further exploring the differences across countries' geographical areas (see [4], [37] and [59]) -a topic that is explicitly modeled in the present paper. Moreover, despite the institutional organization of the Italian educational system is based on strong assumptions about its equality purposes, based on the presumption that all schools/classes provide similar educational standards, these studies empirically proved that this is not true and that actually the country's educational system is characterized by a 'learning divide'.…”

“…The chapter by Petracco-Giudici et al (2010, see [44]) describes how the role of students' socioeconomic background as a critical factor that affects students' test scores. Agasisti & Vittadini (2012, see [4]) merge the INVALSI data with TIMSS ones, and build an argument around the role of territorial socioeconomic differences between Provinces. Paccagnella & Sestito (2014, see [43]) discuss the measured cheating in INVALSI test scores as a variable that is correlated with measures of (geographically-based) social capital.…”

“…Some variables about size (number of students per class, average size of classes, number of students of the school) are also included to take eventual scale effects into account. Lastly, regarding geographical location, we include two dummies for schools located in Central and Southern Italy and the district in which the school is located; some previous literature, indeed, pointed at demonstrating that students attending the schools located in Northern Italy tend to have higher achievement scores than their counterparts in other regions, all else equal (see [4]). As we have the anonymous student ID, we have also the encrypted school and class IDs that allow us to identify and distinguish schools and classes.…”

Beyond the mean estimate: a quantile regression analysis of inequalities in educational outcomes using INVALSI survey data

“…PISA, and on the INVALSI national data (e.g. Agasisti and Vittadini 2012;Agasisti and Cordero-Ferrara 2013;INVALSI 2015a).…”

Heterogeneity, school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model

“…Put simply: even in the Italian "egalitarian" educational system, school matters-and attending the school A instead than the school B can have a strong correlation with achievement. This evidence is accompanied by a specific feature of the Italian educational system, namely a strong difference in educational attainment and results in different geographical macro areas (see Agasisti and Vittadini 2012), with students in Northern Italy obtaining (on average, and all else equal) higher scores than their counterparts in Central and Southern part of the country. While the determinants of this gap are still not completely clear-even though some authors also propose possible explanations based, for example, on different resources and/or social capital, see Bratti et al (2007)-the empirical evidence illustrates that also between-schools differences are stronger in the South than in the North.…”