Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2015 | OriginalPaper | Chapter

11. Family Origin and Early School Leaving in Italy: The Long-Term Effects of Internal Migration

Authors : Carmen Aina, Giorgia Casalone, Paolo Ghinetti

Published in: Geographical Labor Market Imbalances

Publisher: Springer Berlin Heidelberg

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The proportion of early school leavers in Italy is high by European Union standards. However, it is not uniformly distributed across the country: in Southern regions, it is almost double than in Centre-Northern area. This chapter goes beyond descriptive evidence and examines the conditional probability of leaving school with (at most) the compulsory schooling certificate in Italy using seven waves of Bank of Italy’s SHIW data, covering individuals born in the period from 1979 to 1995. Among various determinants, we focus on the role played by family origin. Our results show that youths born in the Centre-North with both parents from Southern Italy (second generation internal migrants) behave similarly to youths born and living in the South, so that they are more likely to drop out school earlier than comparable individuals born in the Centre-North with parents from the same area (natives). When only the household head is from the South, second generation migrants are similar to natives and the assimilation with native born in terms of schooling choices at the age of 14 is complete. Differences in family characteristics (education, financial conditions) are able to account for a large share of raw differences in education decisions between individuals born in Centre-North vs. South, as well as between natives and second generation migrants born in the Centre-North of Italy. The analysis of these dynamics over time shows that differences across groups of youths defined by their origin narrow since the mid-2000.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Explaining the Patenting Propensity: A Regional Analysis Using EPO-OECD Data
next chapter The Effect of University Costs and Institutional Incentives on Enrolments: Empirical Evidence for Italian Regions
Appendix
Available only for authorised users
Footnotes
1
The rate of early school leavers is defined as the proportion of the population aged 18–24 with only lower secondary education or less and no longer in education or training.
 
2
PISA surveys emphasise youths’ educational gaps amongst Northern and Southern Italy also in terms of skills acquired.
 
3
See the appendix for a brief overview of Italian internal migration.
 
4
When they talk about traits, they refer to abilities, preferences and expectations.
 
5
Baici et al. (2007) analyse early drop out from high school using a cohorts of youth living in the province of Novara. Their main finding is that family background—and in particular parental education—is a decisive factor in the educational failure of youngsters. Aina et al. (2013) use the same dataset to provide evidence of the effect of migration status on youth’s educational achievement in a province traditionally characterised by a remarkable migration inflow. Findings show that non-natives, especially male, are more likely to study less.
 
6
In principle, the definition of youth as individuals aged 15–25 at the time of each survey would imply the inclusion of all the cohorts born in the 1973–1995 period. However, we exclude the first five cohorts since an important covariate used in the empirical analysis, namely the gender-specific regional unemployment rate, at the time at which the education decision of dropping out after compulsory schooling—i.e. at the age of 14—is available only since 1993 (1979 + 14).
 
7
Since internal migration is mainly from the South to the Centre-North, youths born in the South have for the most part both parents from the same area. However, in order to improve the interpretation of our results in both cases, we have dropped the residual group of individuals living in the South but born elsewhere or from parents of different origins (one of the Centre-North and the other from the South).
 
8
Including parents’ employment status proxies in the estimates does not improve the results, as the corresponding coefficients are never statistically significant. This result is not surprising as parents’ education and households’ financial resources generally capture the whole effect of the family background.
 
9
For example, if parents of second generation migrants were low-income or low-educated individuals in their origin area, and this means something for the value given to education and for the amount of economic resources, they are willing to invest in the education of their offspring; OLS estimates are biased and inconsistent.
 
10
Despite it is very difficult to evaluate empirically these issues, in Tables 11.3 and 11.4, we analyse the sensitivity of results to the inclusion/exclusion of family variables, which is helpful to better understand how the drop-out decision of second generation migrants are affected by background characteristics (i.e. the direction of the selection bias).
Table 11.3
South to Centre-North Internal migration and the probability of early drop out from education system (linear probability models) - Youth born and living in Centre-North: migration status based on Household Head (HH) origin
 
All
Males
Females
Variables
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
HH born in Centre-North
−0.141***
−0.0577***
−0.0318*
−0.155***
−0.0588***
−0.0269
−0.125***
−0.0491***
−0.0152
(0.00971)
(0.00983)
(0.0164)
(0.0146)
(0.0148)
(0.0228)
(0.0124)
(0.0128)
(0.0217)
HH born in the South
−0.102***
−0.0559***
−0.0314
−0.123***
−0.0529**
−0.0236
−0.0739***
−0.0442*
−0.0107
(0.0166)
(0.0161)
(0.0194)
(0.0232)
(0.0223)
(0.0264)
(0.0233)
(0.0230)
(0.0269)
Female
−0.0718***
−0.0655***
−0.0771***
      
(0.00898)
(0.00838)
(0.00959)
      
Number of children
 
0.0217***
0.0218***
 
0.0207***
0.0208***
 
0.0240***
0.0240***
 
(0.00549)
(0.00548)
 
(0.00753)
(0.00753)
 
(0.00784)
(0.00784)
Father vocat./upper second
 
−0.109***
−0.109***
 
−0.130***
−0.132***
 
−0.0817***
−0.0820***
 
(0.00882)
(0.00883)
 
(0.0131)
(0.0130)
 
(0.0118)
(0.0118)
Father univ. degree
 
−0.0864***
−0.0886***
 
−0.106***
−0.109***
 
−0.0504***
−0.0522***
 
(0.0107)
(0.0108)
 
(0.0158)
(0.0159)
 
(0.0144)
(0.0145)
Mother vocat./upper second
 
−0.0848***
−0.0858***
 
−0.116***
−0.116***
 
−0.0550***
−0.0567***
 
(0.00872)
(0.00878)
 
(0.0131)
(0.0132)
 
(0.0114)
(0.0114)
Mother univ. degree
 
−0.0879***
−0.0882***
 
−0.117***
−0.118***
 
−0.0565***
−0.0566***
 
(0.0101)
(0.0102)
 
(0.0149)
(0.0150)
 
(0.0133)
(0.0132)
Log (family equiv. income)
 
−0.0485***
−0.0466***
 
−0.0477***
−0.0453***
 
−0.0528***
−0.0503***
 
(0.00963)
(0.00971)
 
(0.0140)
(0.0140)
 
(0.0131)
(0.0132)
Family-owned house
 
−0.106***
−0.105***
 
−0.108***
−0.107***
 
−0.107***
−0.106***
 
(0.0122)
(0.0121)
 
(0.0178)
(0.0177)
 
(0.0162)
(0.0160)
Youths reg. unem. rate at age 14
  
0.00108*
  
0.00158*
  
0.00122*
  
(0.000558)
  
(0.000871)
  
(0.000722)
Constant
0.0228
0.524***
0.466***
−0.0909**
0.425***
0.343**
0.0370
0.544***
0.469***
(0.0335)
(0.0930)
(0.0974)
(0.0413)
(0.132)
(0.139)
(0.0395)
(0.132)
(0.138)
Observations
11,458
11,458
11,458
6,122
6,122
6,122
5,336
5,336
5,336
R 2
0.063
0.165
0.166
0.067
0.178
0.179
0.052
0.149
0.150
Note see also below. HH born in Centre-North are the Centre-North natives. HH born in the South are the 2nd generation internal migrants from the South to the Centre-North, ***p < 0.01, **p < 0.05, *p < 0.1
Table 11.4
South to Centre-North Internal migration and the probability of early drop-out from education system (linear probability models) - Youth born and living in Centre-North: migration status based on Household Head (HH) and his/her spouse (Sp) origin
 
All
Males
Females
Variables
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
HH and Sp born in Centre-North
−0.142***
−0.0569***
−0.0315*
−0.155***
−0.0558***
−0.0237
−0.127***
−0.0502***
−0.0166
(0.00981)
(0.00996)
(0.0166)
(0.0149)
(0.0150)
(0.0231)
(0.0125)
(0.0130)
(0.0218)
HH and Sp born in the South
−0.0577**
−0.0205
0.00303
−0.0676*
−0.00753
0.0217
−0.0419
−0.0225
0.0103
(0.0258)
(0.0244)
(0.0263)
(0.0352)
(0.0322)
(0.0345)
(0.0375)
(0.0373)
(0.0386)
HH and Sp born in differ. areas
−0.140***
−0.0844***
−0.0597***
−0.172***
−0.104***
−0.0732***
−0.0989***
−0.0524***
−0.0186
(0.0140)
(0.0139)
(0.0183)
(0.0197)
(0.0199)
(0.0251)
(0.0199)
(0.0192)
(0.0260)
Female
−0.0715***
−0.0654***
−0.0767***
      
(0.00898)
(0.00838)
(0.00959)
      
Number of children
 
0.0212***
0.0213***
 
0.0199***
0.0200***
 
0.0240***
0.0239***
 
(0.00549)
(0.00549)
 
(0.00754)
(0.00753)
 
(0.00785)
(0.00786)
Father vocat./upper second
 
−0.109***
−0.110***
 
−0.132***
−0.133***
 
−0.0816***
−0.0819***
 
(0.00885)
(0.00886)
 
(0.0132)
(0.0131)
 
(0.0118)
(0.0118)
Father univ. degree
 
−0.0871***
−0.0892***
 
−0.107***
−0.110***
 
−0.0504***
−0.0522***
 
(0.0107)
(0.0108)
 
(0.0158)
(0.0159)
 
(0.0144)
(0.0144)
Mother vocat./upper second.
 
−0.0838***
−0.0849***
 
−0.115***
−0.115***
 
−0.0543***
−0.0560***
 
(0.00872)
(0.00878)
 
(0.0132)
(0.0133)
 
(0.0113)
(0.0114)
Mother univ. degree
 
−0.0864***
−0.0867***
 
−0.114***
−0.116***
 
−0.0559***
−0.0560***
 
(0.0101)
(0.0102)
 
(0.0149)
(0.0151)
 
(0.0132)
(0.0132)
Log (family equiv. income)
 
−0.0487***
−0.0468***
 
−0.0478***
−0.0455***
 
−0.0529***
−0.0504***
 
(0.00963)
(0.00971)
 
(0.0140)
(0.0140)
 
(0.0131)
(0.0133)
Family-owned house
 
−0.106***
−0.105***
 
−0.109***
−0.107***
 
−0.107***
−0.105***
 
(0.0122)
(0.0121)
 
(0.0178)
(0.0177)
 
(0.0162)
(0.0160)
Youths reg. unem. rate at age 14
  
0.00106*
  
0.00159*
  
0.00121*
  
(0.000558)
  
(0.000871)
  
(0.000723)
Constant
0.0253
0.530***
0.473***
−0.0870**
0.433***
0.351**
0.0391
0.546***
0.471***
(0.0334)
(0.0929)
(0.0973)
(0.0414)
(0.132)
(0.139)
(0.0391)
(0.132)
(0.138)
Observations
11,458
11,458
11,458
6,122
6,122
6,122
5,336
5,336
5,336
R 2
0.065
0.166
0.167
0.068
0.180
0.180
0.053
0.149
0.150
Note The binary dep. var. is 1 when the individual achieves at most the lower second degree. All the regressions include a set of 16 cohort dummies for the year of birth and six time dummies for the survey’s years. Excluded categories: born in Southern Italy, mother lower secondary or less and father lower secondary or less. HH and Sp born in Centre-North are the Centre-North natives. HH and Sp born in the South are the 2nd generation internal migrants from South to Centre-North. HH and Sp born in differ. areas are the youths with ‘mixed’ origin. Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1
 
11
In alternative to the (regional and gender-specific) youth unemployment rate, other measures of unemployment may capture different features of labour market conditions. For example, one could use the ratio between rates of youth and adult (over 25 years old) unemployment. Unfortunately, the time series of the latter were not available by region and gender until recently and cannot be used for our purposes. We experimented by estimating specifications that included alternative measures of unemployment: either the absolute overall regional unemployment rate or the relative youth unemployment rate (ratio between the youth unemployment rate and the overall unemployment rate) instead of the absolute youth unemployment rate. None of the two definitions turned out to play any statistically significant role in the estimates. One problem with the relative youth unemployment rate is that it varies much less than its absolute value, leading di per se to less precise estimates. Overall, it seems that in a segmented labour market as the Italian one, the educational choices of young individuals are more influenced by the conditions of the youth’s labour market, than by its overall performance.
 
12
The migration status may correlate with unobservable school-leaving determinants such as ability or motivation. In our sample, the migration decision has been taken not by the individuals but by their parents. This is likely to attenuate endogeneity problems to the extent to which they are due to the family characteristics included in the analysis.
 
Literature
Aina, C., Casalone, G., & Ghinetti, P. (2013). Internal migration and educational outcomes in Italy: Evidence from a cohort of youths (Papers in Regional Science). doi:10.​1111/​pirs.​12071.
Baici, E., Cappellari, L., & Comi, S. (2007). Carriera scolastica ed esiti occupazionali di una generazione di giovani novaresi. Economia e Lavoro, 41(2), 79–97.
Bank of Italy. (several years). Survey on household income and wealth (SHIW). Rome: Bank of Italy.
Boeri, T. (2000). Structural change, welfare systems, and labour reallocation. Oxford: Oxford University Press.
Bonaguidi, A., & Terra Abrami, V. (1996). The pattern of internal migration: The Italian case. In P. Rees, J. Stillwell, A. Convey, & M. Kupiszewski (Eds.), Population migration in the European Union. London: Wiley.
Bonifazi, C. (1992). Saldi migratori e studio delle migrazioni interregionali: Osservazioni sul caso italiano. Genus, 1–2, 47–67.
Bonifazi, C., & Heins, F. (2000). Long-term trends of internal migration in Italy. International Journal of Population Geography, 6(2), 111–131.CrossRef
Bonifazi, C., Chieppa, A., & Heins, F. (1999). Le migrazioni interne meridionali: Un’analisi a livello provinciale. In C. Bonifazi (Ed.), Mezzogiorno e Migrazioni Interne. Rome: IRP-CNR 10.
Borjas, G. J. (1994). The economics of immigration. Journal of Economic Literature, 32(4), 1667–1717.
Bozick, R. (2009). Job opportunities, economic resources, and the postsecondary destinations of American youth. Demography, 46(3), 493–512.CrossRef
Bratti, M. (2007). Parents’ income and children’s school drop-out at 16 in England and Wales: Evidence from the 1970 British cohort study. Review of Economic Household, 5, 15–40.CrossRef
Casarico, A., Profeta, P., & Pronzato, C. (2011). Great expectations: The determinants of female university enrolment in Europe (CESifo Working Paper Nr. 3406). Munich: CESifo.
Clark, D. (2009). Do recessions keep students in school? The impact of youth unemployment on enrolment in post-compulsory education in England. Economica, 78(311), 523–545.
Dearden, L., Emmerson, C., Frayne, C., & Meghir, C. (2005). Education subsidies and school drop-out rates (IFS Working Paper Nr.05/11). London: The Institute for Fiscal Studies.
Dustmann, C., Hutton, T., & Preston, I. (2005). The labour market effects of immigration. The Economic Journal, 115, F297–F299.CrossRef
Eckstein, Z., & Wolpin, K. I. (1999). Why youths drop out of high school: The impact of preferences, opportunities and abilities. Econometrica, 67, 1295–1339.CrossRef
Eurostat. (2012). Eurostat structural indicators. Eurostat.
Gabrielli, G., Paterno, A., & White, M. (2007). The impact of origin region and internal migration on Italian fertility. Demographic Research, 17(24), 705–740.CrossRef
Haveman, R., & Wolfe, B. (1995). The determinants of children’s attainments: A review of methods and findings. Journal of Economic Literature, 33, 1829–1878.
Micklewright, J., Pearson, M., & Smith, S. (1990). Unemployment and early school leaving. The Economic Journal, 100(400), 163–169.CrossRef
Mocetti, S., & Porello, C. (2010). Labour mobility in Italy: New evidence on migration trends, Questioni di Economia e Finanza (Occasional Papers Nr. 61). Bank of Italy, Economic Research Department.
Oreopoulos, P. (2003). Do dropouts drop out too soon? Evidence from changes in school-leaving laws (NBER Working Paper Nr. 10155). Cambridge, MA: National Bureau of Economic Research.
Pastore, F. (2012). To study or to work? Education and labor-market participation of young people in Poland. Eastern European Economics, 50(3), 49–78.CrossRef
Petrongolo, B., & San-Segundo, M. (2002). Staying-on at school at 16: The impact of labor market conditions in Spain. Economics of Education Review, 21, 353–365.CrossRef
Pissarides, C. A. (1981). Staying-on at school in England and Wales. Economica, 48(192), 345–363.
Rice, P. (1999). The impact of local labour markets on investment in further education: evidence from the England and Wales youth cohort Studies. Journal of Population Economics, 12(2), 287–312.
Metadata
Title
Family Origin and Early School Leaving in Italy: The Long-Term Effects of Internal Migration
Authors
Carmen Aina
Giorgia Casalone
Paolo Ghinetti
Copyright Year
2015
Publisher
Springer Berlin Heidelberg
Book
Geographical Labor Market Imbalances

Print ISBN: 978-3-642-55202-1

Electronic ISBN: 978-3-642-55203-8

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-642-55203-8_11