| |
Male
|
Female
|
Service
|
Sales
|
Admin
|
|---|
|
# Job-specific tools
|
.0341* (.0184)
|
.0403** (.0193)
|
.0350 (.0558)
|
2.9851*** (.4202)
|
.1529 (.2660)
|
|
Specific squared
|
− .0001 (.0008)
|
− .0001 (.0010)
|
− .0023 (.0088)
|
− 4.2719*** (.7879)
|
− .1347 (.2012)
|
|
Total tools
|
− .0134 (.0114)
|
− .0220* (.0119)
|
− .0653* (.0340)
|
− .2292 (.1671)
|
− .2177* (.1077)
|
|
Total tools squared
|
− .0002 (.0004)
|
− .0000 (.0004)
|
.0034 (.0028)
|
− .1412** (.0460)
|
.0498* (.0268)
|
|
Number of clusters
|
300
|
300
|
39
|
13
|
24
|
|
Observations
|
525,898
|
515,341
|
207,764
|
132,593
|
156,764
|
|
R-squared
|
.344
|
.296
|
.187
|
.317
|
.178
|
| |
Construction
|
Installation and repair
|
Production
|
Transportation
| |
|---|
|
# Job-specific tools
|
.0884 (.0808)
|
− .0666 (.1188)
|
− .0849* (.0443)
|
.3589*** (.0743)
| |
|
Specific squared
|
− .0250** (.0104)
|
.0051 (.0214)
|
.0089 (.0057)
|
− .0739*** (.0187)
| |
|
Total tools
|
.0044 (.0295)
|
.0955* (.0532)
|
.0635** (.0255)
|
.0274 (.1053)
| |
|
Total tools squared
|
.0010 (.0010)
|
− .0046 (.0029)
|
− .0022* (.0011)
|
− .0059 (.0128)
| |
|
Number of clusters
|
31
|
23
|
31
|
21
| |
|
Observations
|
58,020
|
39,144
|
56,848
|
81,993
| |
|
R-squared
|
.161
|
.194
|
.237
|
.187
| |
- Dependent variable is natural log of earnings. Robust standard errors in parentheses. Each regression includes full set of control variables, as in Table 5. Male and Female samples include occupation indicators to control for 10 major occupation groups. Tools measured in 10 tool increments
- *** p < .01, ** p < .05, * p < .1
