Gender stereotyping and wage discrimination among Italian graduates

Variable

Earnings equation (employees)

Female

Male

Coefficient

T-value

Coefficient

T-value

CONSTANT

6.451078

80.249

6.516929

89.401

Educational performance___________________

0.000950

4.031

0.001423

5.301

lambda________________________________

0.383831

6.319

0.414517

7.583

experience________________________________

-0.036356

-6.557

0.016100

1.465

experience2_______________________________

0.004010

5.722

-0.001348

-1.141

Sciences________________________________

0.189980

4.621

0.075470

2.594

Pharmacy____________________________

0.290410

6.725

0.150891

5.120

Natural sciences____________________________

0.130703

3.820

0.062717

1.939

Engineering_______________________________

0.360510

7.515

0.253378

7.238

Architecture___________________________________

0.183003

3.857

0.121772

3.219

Agricultural studies___________________________

0.138144

3.090

0.058937

1.561

Economics, business and statistics___________

0.246893

6.207

0.168118

5.653

Political sciences and sociology______________

0.203020

4.692

0.074503

2.384

Law________________________________

0.075950

2.721

0.042657

1.507

Humanities________________________________

0.131889

3.114

-0.077757

-2.105

Foreign languages_________________________

0.162961

3.879

0.016601

0.391

Teachers college__________________________

0.111559

2.432

0.056077

1.162

Psychology______________________________

0.082282

1.645

0.043418

0.979

Hours worked (Q2 21)____________________

0.008788

8.024

0.007432

6.449

University of North____________________________

-0.052636

-3.973

-0.011993

-0.804

University of Center_________________________

-0.010915

-0.766

0.043994

2.943

d Liceo_____________________________________

-0.017863

-1.904

0.002172

0.235

d Previously entered another degree course

0.005927

0.490

0.012281

0.894

d Studied in the hometown__________________

0.000538

0.068

0.003824

0.440

d Moved to attend university_________________

0.034356

3.784

0.032285

3.018

d Working student_________________________

0.096551

7.163

0.076887

6.731

Training_______________________________________

-0.090338

-6.441

-0.107812

-7.538

Married_____________________________________

0.005629

0.685

0.080510

6.880

Children____________________________________

-0.009754

-0.620

0.091021

4.602

d Father’s university degree_________________

0.030699

2.294

0.007577

0.509

d Father’s high school degree________________

0.018705

1.967

0.004630

0.421

d Mother’s degree_________________________

-0.002357

-0.162

0.009058

0.567

d High school______________________________

-0.005666

-0.598

0.011621

1.083

d Father’s occupation: manager_____________

0.015552

1.036

0.030424

1.903

d Father’s occupation: executive cadre_______

-0.003928

-0.280

0.027497

1.839

d Father’s occupation: white collar____________

-0.000960

-0.086

0.001874

0.154

d Mother’s occupation: executive cadre______

0.011883

0.812

-0.021382

-1.375

d Mother’s occupation: white collar___________

0.019560

1.942

0.006837

0.628

Erasmus_____________________________

0.031319

2.666

0.052507

4.020

Firm size____________________________________

0.089913

6.131

0.074524

3.547

d Attended private courses at university______

0.020647

0.995

0.001685

0.066

d Father employed________________________

0.004156

0.230

-0.000877

-0.041

d Father self-employed_____________________

0.023489

2.481

0.023034

2.074

Industrial sector________________________________

0.022993

2.527

0.037864

4.124

Paid training__________________________________

-0.145341

-5.817

-0.120088

-4.218

Region dummies________________________

X

X

Number of observations___________________

3744

3709

Rbar-squared____________________________

0.1480

0.1460

F_________________________________________

11.805 (0.00)

11.596 (0.0^5)~

Average wage women (ln)________________

7.1099409

Average wage men (ln)____________________

7.2269904