Measuring links between labor monopsony and the gender pay gap in Brazil

Table 9 Female characteristics and gender differences, by region and sector

	Age 20–29	High school/	Prof./mgr./	Potential	Firm no.	Firm %
		college	tech. ^a	experience (years)	workers	white
				Female (Mean)		collar
All	0.25	0.55	0.54	19.77	5.40	0.68
Midwest	0.25	0.50	0.58	19.81	5.60	0.72
North	0.23	0.61	0.64	19.81	5.86	0.75
Northeast	0.22	0.61	0.60	20.08	5.62	0.72
Southeast	0.26	0.55	0.52	19.56	5.39	0.68
South	0.25	0.48	0.50	20.05	5.00	0.63
All industry	0.30	0.30	0.20	20.54	4.47	0.27
Construction	0.29	0.54	0.46	19.36	4.53	0.39
Retail trade	0.40	0.50	0.57	17.55	2.49	0.72
Wholesale trade	0.35	0.56	0.54	17.70	3.19	0.68
Finance	0.23	0.92	0.73	16.59	4.17	0.99
Real estate	0.35	0.58	0.44	18.02	4.25	0.72
Transport	0.28	0.62	0.40	18.79	5.03	0.68
Hotel and service	0.26	0.33	0.28	21.38	3.93	0.66
Medical	0.25	0.60	0.58	19.11	4.53	0.86
Education	0.24	0.80	0.74	17.27	4.42	0.88
Pub. admin.	0.13	0.70	0.79	20.70	8.55	0.82
Agriculture	0.24	0.10	0.09	25.38	3.65	0.14

Source: Brazilian RAIS, 2001. N=2,169,365
^aProf./mgr./tech. indicates the differences in rates of workers holding a professional, managerial, technical, or supervisory occupation
Employed, formal-sector workers, ages 20–49 years