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Table 4 Predicting graduates’ access to professional and managerial occupations 5 years after graduation

From: Privilege travels: migration and labour market outcomes of Southern Italian graduates

  Model 1 baseline Model 2 + migration study
Estimate S.E p value Estimate S.E p value
Parental education
 Both with higher education (ref)       
 At least one with education − 0.160 0.085 0.060 − 0.157 0.085 0.066
 At least one with high school − 0.287 0.077 0.000 − 0.282 0.077 0.000
 Both with less than high school − 0.327 0.084 0.000 − 0.319 0.084 0.000
Migration study     0.086 0.048 0.072
Field of Study
 Law (ref)       
 Agriculture − 0.268 0.168 0.111 − 0.276 0.168 0.102
 Architecture 0.229 0.124 0.065 0.218 0.124 0.080
 Chemistry and pharmacy 0.416 0.151 0.006 0.414 0.151 0.006
 Economics/statistics − 0.897 0.104 0.000 − 0.904 0.105 0.000
 Sports science and physical education − 1.293 0.214 0.000 1.311 0.214 0.000
 Biology and Geography 0.244 0.131 0.062 0.236 0.131 0.071
 Engineering 0.570 0.109 0.000 0.563 0.109 0.000
 Education − 1.336 0.166 0.000 − 1.341 0.166 0.000
 Literature − 0.366 0.120 0.002 − 0.381 0.121 0.002
 Linguistics − 0.555 0.129 0.000 − 0.566 0.129 0.000
 Medicine − 0.555 0.136 0.000 − 0.567 0.136 0.000
 Political science/social science − 1.150 0.107 0.000 − 1.171 0.107 0.000
 Psychology − 0.042 0.116 0.717 − 0.058 0.116 0.618
 Natural science/mathematics/physics 0.444 0.158 0.005 0.448 0.158 0.005
Gender
 Men (ref)       
 Women − 0.205 0.051 0.000 − 0.202 0.051 0.000
Constant 5.802 0.676 0.000 5.711 0.678 0.000
R-Squared 0.163   0.164  
N 11,192   11,192  
  1. Logistic regression models; All models control also for: age, degree type, secondary school, grades secondary school, grades university