Analysis of the impact of occupational sex-segregation on the wages of men and women and its significance in the gender pay gap: Russian case
The impact of horizontal occupational gender segregation on the hourly wages of men and women in Russia after the crisis. The main indicator of occupational segregation: the percentage of women in the industry, the so-called occupational feminization.
Рубрика | Экономика и экономическая теория |
Вид | дипломная работа |
Язык | английский |
Дата добавления | 18.07.2020 |
Размер файла | 966,1 K |
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(0.0937)
Marst_6
-0.241***
0.0472
-0.0304
0.0340
DIPLOM
(0.0914)
(0.136)
(0.107)
(0.128)
Diplom_3
0.0204
-0.154*
-0.120
0.0868
(0.106)
(0.0917)
(0.0950)
(0.160)
Diplom_4
-0.0537
-0.246***
-0.206**
0.0214
(0.0969)
(0.0907)
(0.0929)
(0.147)
Diplom_5
-0.0294
-0.158
-0.144
0.0459
(0.0977)
(0.108)
(0.103)
(0.158)
Diplom_6
0.259***
-0.0815
0.128
-0.0282
INDUSTRY
(0.0988)
(0.138)
(0.108)
(0.170)
Industry_2
-0.0944
0.194*
0.0971
0.00938
(0.0833)
(0.112)
(0.106)
(0.122)
Industry_3
-0.0265
0.271**
0.164
0.140
(0.0747)
(0.135)
(0.101)
(0.133)
Industry_4
0.191*
0.254**
0.224**
0.0551
(0.107)
(0.110)
(0.0994)
(0.116)
Industry_5
0.288***
0.265***
0.255***
0.169*
(0.0902)
(0.102)
(0.0926)
(0.0899)
Industry_6
0.311***
0.224**
0.247**
0.0159
(0.114)
(0.101)
(0.0991)
(0.106)
Industry_7
0.0217
0.106
0.0851
0.00582
(0.0840)
(0.0883)
(0.0831)
(0.0881)
Industry_8
-0.268***
0.0405
-0.0509
-0.0216
(0.0902)
(0.114)
(0.101)
(0.0985)
Industry_9
-0.194***
-0.0104
-0.0732
0.114
(0.0732)
(0.130)
(0.105)
(0.107)
Industry_10
-0.260**
-0.296**
-0.236**
-0.0816
(0.102)
(0.150)
(0.113)
(0.132)
Industry_11
-0.348***
-0.106
-0.186
0.0222
(0.0846)
(0.191)
(0.145)
(0.130)
Industry_12
-0.344***
-0.200
-0.257**
0.0212
(0.100)
(0.140)
(0.110)
(0.117)
Industry_13
-0.0986
-0.0837
-0.109
0.0282
(0.101)
(0.173)
(0.150)
(0.113)
Industry_14
-0.0693
-0.0463
-0.0630
0.0376
(0.0543)
(0.0736)
(0.0652)
(0.0687)
Industry_15
-0.111
-0.175
-0.164
-0.0199
(0.0893)
(0.126)
(0.112)
(0.108)
Industry_16
0.285***
0.455**
0.386***
0.180
(0.0840)
(0.188)
(0.120)
(0.129)
Industry_17
-0.246***
0.0787
-0.0191
-0.0141
(0.0683)
(0.132)
(0.109)
(0.0942)
Industry_18
0.0477
-0.166
-0.133
0.153
(0.141)
(0.141)
(0.0982)
(0.150)
Industry_19
-0.361**
-0.180
-0.247*
-0.00388
(0.164)
(0.148)
(0.130)
(0.168)
Industry_20
-0.0728
-0.130
-0.142
0.248**
(0.451)
(0.215)
(0.250)
(0.121)
Industry_21
-0.374**
0.328**
0.200**
0.367
(0.159)
(0.138)
(0.0806)
(0.242)
Industry_23
-0.267*
-0.0696
-0.115
-0.273
(0.161)
(0.179)
(0.187)
(0.248)
Industry_24
-1.152***
-0.765***
-0.846***
-0.955***
(0.0907)
(0.111)
(0.0970)
(0.133)
Industry_25
-0.437**
-0.405***
-0.426***
-0.228**
(0.221)
(0.129)
(0.147)
(0.109)
Industry_26
0.105
0.163
0.131
0.211*
(0.113)
(0.120)
(0.102)
(0.113)
Industry_27
-0.178
0.0644
-0.0304
0.0130
(0.200)
(0.132)
(0.132)
(0.153)
Industry_28
-0.761***
-1.551***
-1.406***
-0.661***
(0.151)
(0.151)
(0.140)
(0.138)
Industry_29
-0.407*
-0.167
-0.269
0.647
(0.221)
(0.356)
(0.344)
(0.506)
Industry_30
-0.213
0.129***
0.0603
0.243
(0.132)
(0.0476)
(0.0443)
(0.206)
Industry_31
-0.448**
-0.374***
-0.436***
0.143
(0.192)
(0.0888)
(0.0752)
(0.143)
Industry_31
-0.428**
-0.242
-0.291
-0.0477
REGION
(0.190)
(0.184)
(0.185)
(0.132)
Region_2
0.595***
-
0.593
-
(0.166)
(0.403)
Region_3
-0.340***
-
-0.327**
-
(0.0661)
(0.127)
Region_4
-0.0793
-
-0.0601
-
(0.0605)
(0.131)
Region_5
-0.315***
-
-0.358**
-
(0.0610)
(0.141)
Region_6
-0.572***
-
-0.572***
-
(0.0614)
(0.134)
Region_7
-0.433***
-
-0.430***
-
(0.0592)
(0.122)
Region_8
-0.202***
-
-0.183
-
(0.0578)
(0.131)
Region_9
-0.152
-
-0.166
-
(0.0965)
(0.175)
Region_10
-0.176***
-
-0.255**
-
(0.0674)
(0.126)
Region_11
-0.142
-
-0.140
-
(0.0931)
(0.170)
Region_12
-0.367***
-
-0.366***
-
(0.0623)
(0.135)
Region_13
-0.644***
-
-0.640***
-
(0.0681)
(0.133)
Region_14
-0.0111
-
0.0913
-
(0.102)
(0.112)
Region_15
0.101
-
0.0488
-
(0.0729)
(0.178)
Region_16
-0.124*
-
-0.132
-
(0.0692)
(0.141)
Region_17
0.0727
-
0.104
-
(0.0778)
(0.153)
Region_18
-0.163**
-
-0.204
-
(0.0806)
(0.149)
Region_19
-0.239***
-
-0.301***
-
(0.0693)
(0.114)
Region_20
-0.364***
-
-0.318**
-
(0.0931)
(0.161)
Region_21
0.675***
-
0.654
-
(0.166)
(0.400)
Region_22
0.802***
-
0.818***
-
(0.0775)
(0.126)
Region_23
-0.291***
-
-0.348**
-
(0.0650)
(0.143)
Region_24
-0.532***
-
-0.551***
-
(0.0678)
(0.152)
Region_25
-0.00947
-
0.0323
-
(0.149)
(0.111)
Region_26
-0.0519
-
-0.0304
-
(0.0767)
(0.188)
Region_27
-0.283***
-
-0.327**
-
(0.0682)
(0.146)
Region_28
0.139**
-
0.0961
-
(0.0641)
(0.123)
Region_29
-0.677***
-
-0.744***
-
(0.0555)
(0.125)
Region_30
-0.237***
-
-0.270**
-
(0.0546)
(0.126)
Region_31
-0.183**
-
-0.128
-
(0.0728)
(0.158)
Region_32
0.279**
-
0.358
-
(0.124)
(0.348)
Region_33
0.182*
-
0.201
-
(0.105)
(0.206)
Region_34
0.652***
-
0.659***
-
(0.0594)
(0.124)
Region_35
0.384***
-
0.371**
-
(0.0756)
(0.151)
Region_36
0.343***
-
0.338**
-
(0.0585)
(0.132)
Region_37
0.0377
-
0.0233
-
YEAR
(0.0708)
(0.117)
Year_2011
0.147***
0.148***
0.146***
0.129***
(0.0376)
(0.0377)
(0.0274)
(0.0366)
Year_2012
0.248***
0.251***
0.248***
0.219***
(0.0345)
(0.0541)
(0.0248)
(0.0616)
Year_2013
0.422***
0.429***
0.423***
0.381***
(0.0329)
(0.0788)
(0.0258)
(0.0887)
Year_2014
0.493***
0.497***
0.491***
0.429***
(0.0334)
(0.105)
(0.0285)
(0.116)
Year_2015
0.536***
0.546***
0.537***
0.464***
(0.0338)
(0.128)
(0.0274)
(0.140)
Year_2016
0.598***
0.619***
0.605***
0.511***
(0.0342)
(0.153)
(0.0300)
(0.166)
Year_2017
0.642***
0.664***
0.649***
0.542***
(0.0357)
(0.176)
(0.0309)
(0.192)
Year_2018
0.745***
0.776***
0.756***
0.631***
(0.0345)
(0.203)
(0.0329)
(0.220)
Constant
4.149***
4.184***
4.113***
-
(0.202)
(1.101)
(0.227)
Observations
3,729
3,729
3,729
3,303
R-squared
0.523
0.355
0.169
Number of idind
421
421
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Heteroscedasticity test
Modified Wald test for groupwise heteroscedasticity in fixed effect regression model |
|
H0: sigma(i)^2 = sigma^2 for all i |
|
chi2 (9839) = 52076.34 |
|
Prob>chi2 = 0.0000 |
Hausman (1978) specification test
Coef. |
||
Chi-square test value |
92.87 |
|
P-value |
0.0019 |
Sample 4. Without skills
(1) |
(2) |
(3) |
(4) |
||
VARIABLES |
OLS |
FE |
RE |
FD |
|
fem |
0.480* |
0.669*** |
0.626*** |
0.0140 |
|
(0.265) |
(0.241) |
(0.233) |
(0.224) |
||
fem_gender |
-0.0868 |
-0.165 |
-0.176 |
0.159 |
|
(0.0883) |
(0.183) |
(0.150) |
(0.173) |
Appendix 3. Contribution of occupational feminization to the gender wage gap (Detailed)
(1) |
(2) |
(3) |
(4) |
||
Samples |
OLS |
FE |
RE |
FD |
|
Sample 1 |
|||||
a |
-0,000154 |
-0,11966 |
-0,0846 |
0,019978 |
|
b |
0,02039463 |
-0,13943 |
-0,08647 |
-0,03455 |
|
Coefficients of feminization (a) |
0,000148 |
0,115 |
0,0813 |
-0,0192 |
|
Coefficients of feminization (b) |
-0,0196 |
0,134 |
0,0831 |
0,0332 |
|
Average feminization (for women) |
0.6388849 |
0.6388849 |
0.6388849 |
0.6388849 |
|
Average feminization (for men) |
0.4380794 |
0.4380794 |
0.4380794 |
0.4380794 |
|
Log of average hourly wage (for women) |
4.79583269 |
4.795833 |
4.795833 |
4.795833 |
|
Log of average hourly wage (for men) |
4.98881427 |
4.988814 |
4.988814 |
4.988814 |
|
Sample 2 |
|||||
a |
0,04785 |
-0,10886 |
-0,05240 |
0,07836 |
|
b |
0,07836 |
-0,13518 |
-0,07082 |
0,01280 |
|
Coefficients of feminization (a) |
-0,04 |
0,091 |
0,0438 |
-0,0655 |
|
Coefficients of feminization (b) |
-0,0655 |
0,113 |
0,0592 |
-0,0107 |
|
Average feminization (for women) |
0.6419432 |
0.641943 |
0.641943 |
0.641943 |
|
Average feminization (for men) |
0.4268734 |
0.426873 |
0.426873 |
0.426873 |
|
Log of average hourly wage (for women) |
4.808376301 |
4.808376 |
4.808376 |
4.808376 |
|
Log of average hourly wage (for men) |
4.988161302 |
4.988161 |
4.988161 |
4.988161 |
|
Sample 3 |
|||||
a |
-0,16425277 |
-0,20399** |
-0,18015* |
0,062654 |
|
b |
-0,15895429 |
-0,23181** |
-0,20002* |
-0,01246 |
|
Coefficients of feminization (a) |
0,124 |
0,154** |
0,136* |
-0,0473 |
|
Coefficients of feminization (b) |
0,12 |
0,175** |
0,151* |
0,00941 |
|
Average feminization (for women) |
0.6423629 |
0.642363 |
0.642363 |
0.642363 |
|
Average feminization (for men) |
0.4261113 |
0.426111 |
0.426111 |
0.426111 |
|
Log of average hourly wage (for women) |
4.784450456 |
4.78445 |
4.78445 |
4.78445 |
|
Log of average hourly wage (for men) |
4.947706144 |
4.947706 |
4.947706 |
4.947706 |
|
Sample 4 |
|||||
a |
-0,66301656* |
-0,80005*** |
-0,73776** |
-0,14119 |
|
b |
-0,64363821* |
-0,68378** |
-0,6561** |
0,037788 |
|
Coefficients of feminization (a) |
0,479* |
0,578*** |
0,533** |
0,102 |
|
Coefficients of feminization (b) |
0,465* |
0,494** |
0,474** |
-0,0273 |
|
Average feminization (for women) |
0.66998 |
0.66998 |
0.66998 |
0.66998 |
|
Average feminization (for men) |
0.4296647 |
0.429665 |
0.429665 |
0.429665 |
|
Log of average hourly wage (for women) |
4.826975242 |
4.826975 |
4.826975 |
4.826975 |
|
Log of average hourly wage (for men) |
5.000592366 |
5.000592 |
5.000592 |
5.000592 |
*** p<0.01, ** p<0.05, * p<0.1
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