Skip to main content

Table 4 Wage elasticity and implied and actual wage gaps, by region and sector

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

  Observations ε l,w =−2β vs Gaps
Parameter Male Female Male Female p value Implied Actual
All 1,338,108 831,257 1.62 0.92 0.00 0.291 0.357
    (.028) (.036)   (.028) (.0009)
Midwest 111,426 62,718 1.515 0.528 0.00 0.744 0.362
    (.084) (.098)   (.216) (.003)
North 57,905 38,911 1.012 0.638 0.128 0.292 0.302
    (.133) (.207)   (.269) (.004)
Northeast 215,370 144,418 1.045 0.089 0.00 5.237 0.315
    (.1) (.127)   (8.135) (.002)
Southeast 724,193 432,573 1.656 0.983 0.00 0.258 0.354
    (.037) (.047)   (.032) (.001)
South 229,214 152,637 1.893 1.342 0.00 0.142 0.378
    (.071) (.09)   (.036) (.002)
All industry 297,420 121,131 2.129 2.086 0.752 0.007 0.399
    (.072) (.115)   (.021) (.002)
Construction 117,959 7,413 1.452 0.279 0.001 1.715 0.198
    (.098) (.352)   (2.68) (.006)
Retail trade 169,832 105,032 .883 0.79 0.446 0.063 0.197
    (.076) (.096)   (.087) (.002)
Wholesale trade 44,316 15,901 1.205 0.899 0.256 0.154 0.225
    (.153) (.222)   (.164) (.005)
Finance 25,970 20,297 2.25 1.873 0.319 0.062 0.191
    (.258) (.275)   (.066) (.005)
Real estate 156,122 63,450 1.737 0.707 0.00 0.533 0.283
    (.075) (.095)   (.123) (.003)
Transport 104,971 19,507 2.163 1.765 0.179 0.071 0.233
    (.131) (.265)   (.062) (.004)
Hotel and service 88,483 101,133 1.029 0.675 0.009 0.259 0.229
    (.097) (.094)   (.12) (.002)
Medical 16,506 55,576 .774 0.935 0.582 −0.097 0.174
    (.244) (.161)   (.179) (.004)
Education 21,341 39,447 .941 0.844 0.662 0.059 0.139
    (.176) (.137)   (.138) (.005)
Pub. admin. 184,085 261,556 .583 0.248 0.01 0.856 0.383
    (.098) (.086)   (.551) (.002)
Agriculture 90,639 16,768 1.88 1.094 0.005 0.249 0.272
    (.092) (.262)   (.145) (.004)
  1. Source: Brazilian RAIS, 2001
  2. Asterisks denote levels of significance: * p<0.05 and ** p<0.01