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

Leckcivilize, Attakrit; Straub, Alexander

doi:10.1186/s40172-018-0071-x

Table 8 Controls and beauty, interaction effects

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

Type of occupation	All		No contact		Contact		Low skill		High skill
	1st choice	2nd choice	1st choice	2nd choice	1st choice	2nd choice	1st choice	2nd choice	1st choice	2nd choice
Turkish origin	0.027	0.022	− 0.021	0.047	0.084^b	0.006	0.045	0.106	0.005	− 0.059
	(0.026)	(0.041)	(0.022)	(0.048)	(0.038)	(0.058)	(0.048)	(0.080)	(0.039)	(0.042)
Headscarf	− 0.064	− 0.204^a	− 0.155	− 0.149	− 0.014	− 0.247^a	0.008	− 0.211^b	− 0.098	− 0.191^a
	(0.084)	(0.055)	(0.125)	(0.088)	(0.062)	(0.054)	(0.073)	(0.098)	(0.100)	(0.047)
Headscarf × quality	0.014	0.087^b	0.062^a	0.123^a	− 0.024	0.054	− 0.008	0.078^a	0.027	0.117^b
	(0.009)	(0.037)	(0.015)	(0.034)	(0.022)	(0.041)	(0.019)	(0.025)	(0.021)	(0.051)
Headscarf × experience	0.012	0.065^a	0.023	0.049	0.011	0.066^a	− 0.026	0.087^a	0.044	0.034^b
	(0.034)	(0.015)	(0.051)	(0.033)	(0.019)	(0.014)	(0.031)	(0.031)	(0.039)	(0.016)
Headscarf × education	0.006	0.044^a	0.066^b	0.056^c	− 0.037^c	0.035	− 0.007	0.010	0.013	0.072^c
	(0.020)	(0.014)	(0.026)	(0.033)	(0.019)	(0.021)	(0.030)	(0.027)	(0.024)	(0.037)
Headscarf × english	0.022	0.038	0.007	0.011	0.030	0.067^b	− 0.001	− 0.005	0.041	0.082^b
	(0.016)	(0.023)	(0.022)	(0.017)	(0.018)	(0.032)	(0.032)	(0.021)	(0.039)	(0.039)
Beauty	0.035^a	0.052^a	0.013	0.072^a	0.056^a	0.034	0.022	0.046	0.047^b	0.058^b
	(0.011)	(0.015)	(0.012)	(0.021)	(0.014)	(0.026)	(0.020)	(0.034)	(0.020)	(0.023)
Photo female	− 0.012	− 0.049^c	− 0.011	− 0.099^a	− 0.019	− 0.004	0.022	− 0.086	− 0.048	− 0.013
	(0.015)	(0.025)	(0.014)	(0.021)	(0.022)	(0.042)	(0.039)	(0.061)	(0.029)	(0.032)
Quality	0.090^a	0.069^a	0.096^a	0.051^a	0.084^a	0.092^a	0.140^a	0.111^a	0.044^a	0.032^b
	(0.009)	(0.015)	(0.015)	(0.017)	(0.014)	(0.024)	(0.014)	(0.020)	(0.011)	(0.015)
Experience	0.048^a	0.014	0.044^a	0.002	0.052^a	0.029	0.055^a	0.020	0.049^a	0.018
	(0.010)	(0.011)	(0.012)	(0.014)	(0.012)	(0.019)	(0.014)	(0.016)	(0.010)	(0.013)
Education	0.113^a	0.111^a	0.097^a	0.106^a	0.129^a	0.121^a	0.100^a	0.104^a	0.134^a	0.126^a
	(0.008)	(0.014)	(0.012)	(0.016)	(0.011)	(0.025)	(0.015)	(0.021)	(0.010)	(0.018)
English	0.015	0.010	− 0.008	− 0.011	0.039^a	0.032	0.019	0.006	0.016	0.018
	(0.010)	(0.013)	(0.016)	(0.017)	(0.011)	(0.020)	(0.014)	(0.018)	(0.013)	(0.016)
Unemployed	0.009	− 0.003	− 0.001	− 0.025^c	0.019	0.019	0.001	0.017	0.023^c	− 0.019
	(0.010)	(0.007)	(0.015)	(0.013)	(0.013)	(0.016)	(0.012)	(0.014)	(0.013)	(0.012)
Computer	0.033^a	0.031^b	0.041^a	0.047^a	0.029^b	0.015	0.019	0.019	0.053^a	0.052^a
	(0.008)	(0.012)	(0.014)	(0.014)	(0.011)	(0.018)	(0.012)	(0.015)	(0.011)	(0.016)
Wage	0.005	0.007	0.011	0.008	− 0.000	0.008	0.018	0.015	− 0.001	0.004
	(0.006)	(0.011)	(0.009)	(0.013)	(0.013)	(0.021)	(0.011)	(0.013)	(0.010)	(0.015)
Samegender	0.018	0.012	0.013	0.026	0.022	− 0.004	0.021	− 0.013	0.014	0.031
	(0.013)	(0.018)	(0.016)	(0.024)	(0.020)	(0.020)	(0.016)	(0.028)	(0.021)	(0.024)
Samegender × beauty	− 0.020	− 0.034^c	− 0.004	− 0.045^c	− 0.031	− 0.021	− 0.028	− 0.026	− 0.012	− 0.038
	(0.014)	(0.019)	(0.016)	(0.025)	(0.020)	(0.024)	(0.017)	(0.021)	(0.021)	(0.028)
Time (photo)	0.094	0.190	0.065	0.067	0.139	0.363	0.119	0.189	0.073	0.207
	(0.118)	(0.149)	(0.160)	(0.154)	(0.162)	(0.234)	(0.176)	(0.191)	(0.143)	(0.187)
2nd position	0.003	0.005	0.045^c	0.020	− 0.036	− 0.009	− 0.024	0.018	0.028	− 0.006
	(0.018)	(0.022)	(0.024)	(0.038)	(0.029)	(0.027)	(0.021)	(0.030)	(0.030)	(0.032)
3rd position	0.009	0.027	0.043^c	0.026	− 0.027	0.025	− 0.000	0.001	0.018	0.057
	(0.017)	(0.027)	(0.023)	(0.040)	(0.027)	(0.033)	(0.029)	(0.037)	(0.023)	(0.037)
4th position	− 0.079^a	0.117^a	− 0.050^c	0.162^a	− 0.108^a	0.066^c	− 0.105^a	0.086^a	− 0.057^b	0.151^a
	(0.016)	(0.024)	(0.026)	(0.038)	(0.025)	(0.034)	(0.024)	(0.024)	(0.026)	(0.035)
Observations	3928	2946	1960	1470	1968	1476	1944	1458	1984	1488
Adj. R²	0.057	0.053	0.056	0.067	0.064	0.044	0.070	0.043	0.066	0.078

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 as 1st choice or 2nd choice respectively. The number of observations for 2nd choice decreases because CV’s which were selected as first preference are excluded from these estimations. 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

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