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Table 13 Controls and beauty, interaction (by subgroups)

From: Headscarf and job recruitment—lifting the veil of labour market discrimination

Decision maker

All

Male

Female

Age ≤ 22

Age ≥ 23

Turkish origin

0.031

− 0.008

0.087

0.015

0.044

 

(0.035)

(0.037)

(0.083)

(0.065)

(0.035)

Headscarf

− 0.189b

− 0.220a

− 0.127

− 0.100

− 0.256b

 

(0.072)

(0.078)

(0.090)

(0.142)

(0.105)

Headscarf × quality

0.078b

0.093b

0.054

0.084

0.068c

 

(0.035)

(0.044)

(0.038)

(0.091)

(0.034)

Headscarf × experience

0.054a

0.054b

0.051b

0.026

0.076b

 

(0.018)

(0.024)

(0.020)

(0.017)

(0.027)

Headscarf × education

0.042c

0.074a

0.006

0.075

0.024

 

(0.021)

(0.014)

(0.041)

(0.061)

(0.035)

Headscarf × english

0.054a

0.025

0.066b

0.021

0.076a

 

(0.013)

(0.019)

(0.028)

(0.039)

(0.022)

Headscarf × migrback

− 0.099

− 0.191a

− 0.039

− 0.152

− 0.067

 

(0.061)

(0.048)

(0.078)

(0.131)

(0.089)

Beauty

0.064a

0.051b

0.046a

0.069b

0.058a

 

(0.014)

(0.021)

(0.016)

(0.028)

(0.019)

Photo female

− 0.046b

− 0.049b

− 0.048

− 0.039

− 0.059b

 

(0.019)

(0.023)

(0.040)

(0.046)

(0.028)

Quality

0.110a

0.110a

0.109a

0.110a

0.109a

 

(0.014)

(0.018)

(0.024)

(0.020)

(0.019)

Experience

0.043a

0.031b

0.057a

0.048b

0.039a

 

(0.010)

(0.015)

(0.017)

(0.018)

(0.013)

Education

0.158a

0.165a

0.152a

0.166a

0.150a

 

(0.011)

(0.016)

(0.019)

(0.016)

(0.015)

English

0.018

0.015

0.024

0.032c

0.007

 

(0.013)

(0.016)

(0.021)

(0.018)

(0.018)

Unemployed

0.004

0.011

− 0.007

0.030c

− 0.017

 

(0.009)

(0.013)

(0.016)

(0.016)

(0.013)

Computer

0.045a

0.042a

0.049b

0.057a

0.035b

 

(0.011)

(0.015)

(0.018)

(0.014)

(0.016)

Wage

0.008

0.011

0.005

0.028c

− 0.007

 

(0.009)

(0.014)

(0.016)

(0.015)

(0.011)

Samegender

0.022

  

− 0.006

0.045

 

(0.018)

  

(0.026)

(0.026)

Samegender × beauty

− 0.041b

− 0.013

− 0.005

− 0.045

− 0.035

 

(0.020)

(0.033)

(0.039)

(0.028)

(0.029)

Time (photo)

0.234c

0.155

0.338c

0.123

0.357b

 

(0.128)

(0.186)

(0.183)

(0.231)

(0.144)

2nd position

0.001

0.016

− 0.020

0.024

− 0.019

 

(0.018)

(0.027)

(0.030)

(0.030)

(0.027)

3rd position

0.023

0.078b

− 0.045

0.023

0.021

 

(0.025)

(0.030)

(0.033)

(0.032)

(0.028)

4th position

0.039c

0.049

0.022

0.056c

0.025

 

(0.021)

(0.029)

(0.030)

(0.031)

(0.028)

Observations

3928

2168

1760

1712

2216

Adj. R2

0.077

0.089

0.065

0.068

0.083

  1. Notes: This table shows the relationship between applicant’s appearance and their characteristics and the chances that a CV is selected for a job interview. Turkish origin, headscarf, and photo female are dummy variables if the applicant is ethnic Turkish, wears a headscarf, or is female respectively. Beauty is a double-standardised beauty score of the photo. The variables quality, experience, education, english, unemployed, wage, and computer refer to the characteristics of each CV. They are rescaled so that a higher value is always better for the employer. Migrback is a dummy variable which is equal to 1 if the decision maker has a migration background. Samegender is a dummy variable which is equal to 1 if the decision maker and the applicant are of the same gender. Position refers to the order of appearence of a CV within the occupation. Robust standard errors clustered at the level of the applicant’s photo are in parentheses. All regressions are estimated using LPM (linear probability model). a, b, and c denote significance at the 1%, 5%, and 10% level, respectively