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Regional Economic Disparities as Determinants of Students’ Achievement in Italy: Analyses by macroareas

When adding school-level variables, the between-schools variance decreases of about 5%, suggesting that the socio-economic composition of the student body matters for achievement. However, this effect is no more statistically significant when dummies about macro-areas are included (sixth column). Here, the explanatory power is captured by Southern Italy (the negative difference with Northern Italy is of about 11 points). The lack of statistical power associated to the school-average SES should be interpreted as follows: school-average SES is not a factor contributing to explain (i) schools’ performances and (ii) between-schools variance in Math_Score. The potential explanation is that the school-level SES actually masks a “location” effect, that is schools location in the Southern Italy is responsible for worse performance – for instance, because best teachers are attracted by living in Northern Italy, or other alternative reasons.
To further deepen the understanding of socioeconomic variables related to different geographical areas, we applied a multilevel analysis separately for the three macroareas (North, Central and South). The results are presented in the table 3.
The first evidence is that individual-level variables’ effects are confirmed: female students perform worse than males, disabled status is strongly negatively associated with performance (around 12 points), as well as being a foreign student (-4 points) or a student who repeated one or more years (around 10 points). Computer usage

When looking at school-level factors, findings obtained by Invalsi are confirmed: the between-schools variance is much higher in the South than in the North (21% vs 4%, respectively). Thus, there should be a mechanism that explains student sorting among schools, and/or schools’ characteristics, which act in the South but not in Northern Italy. The second evidence is that such mechanism is not the school-average SES: this variable is not statistically related to the Math_score. Other factors seem to play a role instead: (i) the community in which the school is located, and (ii) the shortage of instructional materials. In the former case, it looks like the schools located in cities benefited of a positive advantage in Math_Score (from 4 points in the North to 12.5 points in the South). It could be the case that higher social and cultural development of the cities (in comparison with towns and rural areas) acts both directly (higher educational level of the population) and indirectly (higher cultural stimulus for the school’s educational work): such effect appears stronger in the South. In the context of the Southern Italy, also the shortage of instructional materials appears as a critical factor: the coefficient is -7.2 and statistically related to (lower indeed) Math_Scores. Overall, these findings claim for a renewed attention to the school factors affecting performances, as the (traditional) explanation related to the SES is not satisfactory in interpreting our results.

Table 3: Results of the multilevel analysis (Math Scores), by macroarea

Empty model Individual level variables Individual and school level variables
Variable NorthernItaly Central Italy SouthernItaly NorthernItaly Central Italy SouthernItaly NorthernItaly Central Italy SouthernItaly
female -3.464 -1.301 -0.755 -3.414 -1.503 -0.620
0.000 0.024 0.102 0.000 0.014 0.195
disabled -12.283 -12.817 -10.692 -12.462 -13.805 -10.683
0.000 0.002 0.228 0.000 0.008 0.228
foreign -4.799 -0.276 -3.657 -4.640 -1.238 -3.607
0.000 0.830 0.058 0.000 0.361 0.062
early 0.784 3.941 0.834 0.587 4.072 1.026
0.759 0.026 0.322 0.821 0.029 0.252
late -10.432 -10.087 -3.768 -10.318 -10.351 -3.905
0.000 0.000 0.000 0.000 0.000 0.000
Disadvantaged (010%) 5.489 5.380 1.783
0.126 0.457 0.684
Disadvantaged (1125%) 4.493 7.278 -1.829
0.211 0.341 0.687
Disadvataged (2650%) 1.881 2.175 -1.952
0.616 0.768 0.671
High Shortage ofInstructionalmaterial 1.750 7.972 -7.243
0.247 0.189 0.053
Some Shortage ofInstructionalmaterial 3.129 3.279 8.074
0.199 0.674 0.374
Community_ big city 4.202 -0.829 12.502
0.033 0.913 0.100
Community_city 5.180 -4.259 11.928
0.005 0.559 0.096
Community_town -4.779 -7.259
0.403 0.379
Constant 67.113 65.241 56.219 70.668 66.751 56.845 61.289 63.904 47.344
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Random e fects
Between-schoolsvariance 13.694 36.154 123.451 12.011 33.734 123.061 9.362 38.707 122.230
Within-schoolvariance 310.135 367.219 468.410 288.668 358.212 467.271 290.957 342.541 466.388
% Between 4.23% 8.96% 20.86% 3.99% 8.61% 20.85% 3.12% 10.15% 20.77%
This post was written by , posted on January 11, 2014 Saturday at 12:12 pm