Table 5 Regression result of salary equation’s OLS

Male

.093^***

.084^***

.19^***

.18^***

(.0053)

(.0052)

(.0026)

(.0026)

Year of education

.16^***

.15^***

.084^***

.083^***

(.0011)

(.0011)

(.00063)

(.00063)

Age

.081^***

.084^***

.004^***

.0076^***

(.0021)

(.002)

(.0011)

(.0011)

Square of age

−.00079^***

−.00083^***

.000014

−.000021

(.000028)

(.000027)

(.000016)

(.000016)

Eastern region

.48^***

.31^***

.19^***

.22^***

(.0068)

(.0076)

(.0053)

(.0059)

Central region

.15^***

.039^***

−.032^***

.019^**

(.0087)

(.0088)

(.0058)

(.0064)

Management personnel

−.093^***

−.071^***

.26^***

.26^***

(.0079)

(.0078)

(.0044)

(.0043)

Professional qualifications

−.1^***

−.079^***

.054^***

.044^***

(.0055)

(.0053)

(.0027)

(.0026)

Per capita profits

.00053^***

−.00039^***

(.000017)

(.000044)

Per capita sales

−.00013^***

.00006^***

(4.2e−06)

(6.5e−06)

With or without losses

−.34^***

−.23^***

(.0055)

(.003)

Constant term

−1.5^***

−1.2^***

.89^***

.85^***

(.042)

(.041)

(.022)

(.022)

N

74,274

74,274

198,970

198,970

R ²

.27

.31

.22

.24