Gender differences in the STEM (Science Technology Engineering and Mathematics) disciplines are widespread in most OECD countries and mathematics is the only subject where typically girls tend to underperform with respect to boys. This paper describes the gender gap in math test scores in Italy, which is one of the countries displaying the largest differential between boys and girls according to the Programme for International Student Assessment (PISA). We use data from an Italian national level learning assessment, involving children in selected grades from second to tenth. We first analyse the magnitude of the gender gap using OLS regression and school fixedeffect models for each grade separately. Our results show that girls systematically underperform boys, even after controlling for an array of individual and family background characteristics, and that the average gap increases with children"s age. We then study the gender gap throughout the test scores distribution, using quantile regression and metric-free methods, and find that the differential is small at the lowest percentiles of the grade distribution, but large among top performing children. Finally, we estimate dynamic models relating math performance at two consecutive assessments. Lacking longitudinal data, we use a pseudo panel technique and find that girls" average test scores are consistently lower than those of boys at all school years, even conditional on previous scores. JEL: J16; I24; C31.
In this paper, we provide a picture of social selection throughout higher education in Italy, analysing a retrospective survey held in 2011 on the cohort of high school graduates 2007. We study enrolment, university system dropout and timely completion. Firstly, we model each outcome with separate logistic regressions, to examine the direct and indirect role of socioeconomic background via prior schooling. Secondly, we jointly analyse these results: by plotting the estimates of the retention probability (given enrolment) against the enrolment probability for subgroups of children by socio-demographic characteristics and prior schooling, we visualize the degree to which the disadvantage related to university enrolment also relates to retention, and acknowledge the existence of impressive inequalities. Thirdly, we jointly analyse retention and timely completion, and find that these two outcomes are affected differently by individual factors. Lastly, we examine the role of labour market conditions on higher education outcomes at the onset of the recent economic crisis: youth unemployment rates were negatively related to enrolment, timely completion and retention. The negative relation with retention suggests that there is little evidence in favour of explanations of dropout referring to labour market "pulling out" students from the university system.
This article provides an empirical assessment of the effect of immigrant concentration on student learning in Italian primary and lower secondary schools, using the data of a standardized learning assessment administered in 2010 to the entire student population of selected grades at the national level. Identification is accomplished by exploiting the within-school random variability observed in the share of immigrant students across classes. I estimate peer effects allowing for heterogeneous effects between native and immigrant background children, and among natives, between children of different socioeconomic status. The main finding is that the proportion of immigrant students has a weak effect on child learning outcomes, and that this effect is somewhat larger for children from disadvantaged backgrounds (immigrants and low socioeconomic status).
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