Table 5 Wage regressions

Non-white

− .0353*** (.0069)

− .0378*** (.0064)

− .0017 (.0121)

− .0336*** (.0068)

− .0692*** (.0102)

Female

− .2211*** (.0169)

− .2197*** (.0169)

− .2214*** (.0203)

− .1771*** (.0179)

− .1933*** (.0164)

Married

.0945*** (.0075)

.0943*** (.0074)

.0773*** (.0125)

.0842*** (.0094)

.1229*** (.0064)

Age

.0511*** (.0024)

.0516*** (.0024)

.0614*** (.0040)

.0488*** (.0031)

.0519*** (.0026)

Age squared

− .0005*** (.0000)

− .0005*** (.0000)

− .0006*** (.0000)

− .0005*** (.0000)

− .0005*** (.0000)

High school

.1161*** (.0109)

.1166*** (.0105)

.0277 (.0323)

.0923*** (.0116)

.1588*** (.0095)

Some college

.1896*** (.0147)

.1886*** (.0135)

.1084*** (.0365)

.1686*** (.0132)

.2403*** (.0199)

College degree

.4644*** (.0226)

.4642*** (.0225)

.4750*** (.0349)

.3778*** (.0231)

.3442*** (.0427)

Non-routine cogn.

.0667*** (.0233)

.0710*** (.0222)

.1147* (.0624)

.1174*** (.0237)

.1280*** (.0185)

Non-routine manual

− .0180 (.0286)

− .0190 (.0292)

− .1225** (.0575)

− .0894** (.0438)

− .0074 (.0171)

Routine cognitive

.1029*** (.0222)

.0906*** (.0216)

 .1707*** (.0452)

.0646*** (.0197)

.0460*** (.0222)

Routine manual.

−.0928** (.0367)

−.0900*** (.0338)

.0191 (.0797)

−.1285*** (.0433)

−.0090 (.0190)

Risk

.1029*** (.0290)

.0949*** (.0286)

.0370 (.0445)

.1834*** (.0365)

.0657*** (.0179)

# Job-specific tools

.0387** (.0170)

.0734** (.0288)

.0406 (.0670)

.0720** (.0331)

Specific squared

− .0002 (.0009)

− .0011 (.0011)

− .0038 (.0093)

− .0101*** (.0029)

Total tools

− .0020 (.0074)

− .0181* (.0106)

− .0268 (.0178)

− .1082*** (.0363)

− .0006 (.0139)

Total tools squared

.0000 (.0001)

− .0001 (.0004)

.0000 (.0005)

.0075*** (.0026)

− .0002 (.0006)

Occupation indicators

Yes

Yes

No

No

No

Observations

1,041,239

1,041,239

295,419

497,121

248,699

R-squared

.326

.328

.285

.245

.210