Technology, routinization and wage inequality: gender differences in the case of Uruguay

Variable	2005/06				2014/15
	With imputation		Without imputation		With imputation		Without imputation
	Mean	s.e	Mean	s.e	Mean	s.e.	Mean	s.e.
All	3.632	(0.004)	3.658	(0.004)	4.213	(0.003)	4.228	(0.003)
Male	3.724	(0.005)	3.736	(0.005)	4.314	(0.004)	4.320	(0.004)
Female	3.537	(0.005)	3.572	(0.006)	4.114	(0.004)	4.134	(0.004)

[i] Notes: Number of observations: 2005/2006 38,522 2014/2015 41,893 without imputation and 43,022 and 45,063 with imputation in 2005 and 2015 respectevely.

[ii] Source: Compiled by authors based on ECH 2005, 2006 and 2014,2015 data.

Table 2

Descriptive statistics

Variable	2005/06		2014/15		Di · 2005 – 2015
Variable	With imputation	Without imputation	With imputation	Without imputation	With imputation	Without imputation
A: Men
Age	40.388	40.510	40.281	40.418	−0.108	−0.093
Education
6 years or less	0.290	0.286	0.212	0.209	−0.079	−0.077
7 to 9 years	0.327	0.325	0.289	0.288	−0.038	−0.037
10 to 12 years	0.243	0.246	0.331	0.333	0.088	0.087
13 to 16 years	0.067	0.067	0.084	0.084	0.018	0.017
16 and more years	0.074	0.076	0.084	0.085	0.010	0.009
Non – married	0.276	0.261	0.304	0.291	0.028	0.030
Resto of the country	0.492	0.491	0.473	0.473	−0.019	−0.018
Not registered	0.231	0.208	0.096	0.088	−0.134	−0.121
B: Women
Age	40.902	41.244	40.887	41.149	−0.015	−0.095
Education
6 years or less	0.261	0.250	0.185	0.177	−0.076	−0.073
7 to 9 years	0.270	0.262	0.233	0.225	−0.037	−0.037
10 to 12 years	0.270	0.275	0.352	0.357	0.082	0.082
13 to 16 years	0.097	0.101	0.107	0.111	0.010	0.010
16 and more years	0.102	0.112	0.122	0.129	0.020	0.017
Non – married	0.430	0.437	0.391	0.391	−0.038	−0.045
Rest of the country	0.455	0.440	0.466	0.461	0.010	0.021
Not registered	0.327	0.282	0.136	0.115	−0.191	−0.167

[i] Notes: Number of observations: 2005/2006 38,522 2014/2015 41,893 without imputation and 43,022 and 45,063 with imputation in 2005 and 2015 respectevely.

[ii] Source: Compiled by authors based on ECH 2005, 2006 and 2014,2015 data.

Log hourly wage change between 2005 and 2015, by gender
*Note*: i. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied. ii. Wages are expressed in real terms, 2010 prices.

Occupational category by gender
*Note*: Percentage of private workers by occupational category and gender in 2005 and 2015.

Information Task Content measure by Occupational Category
*Note*: Compiled by authors based on ECH-INE and National Center for O*NET Development. Blue bars correspond to men and violet ones to women.

Automation Task Content measure by Occupational Category
*Note*: Compiled by authors based on ECH-INE and National Center for O*NET Development. Blue bars correspond to men and violet ones to women.

Table 3

Average O*NET Indexes by Major Occupation Group 2005

A: WITH IMPUTATION	2005
	MEN		WOMEN
*ONet Indexes**	Information	Automation	Information	Automation
Overall Mean	0.596	0.739	0.602	0.732
Standard Deviation	0.118	0.062	0.112	0.061
Manager, Professionals, Technicians	0.788	0.702	0.771	0.676
Clerical support and sale workers	0.666	0.738	0.672	0.744
Plant and machines operators and assemblers	0.546	0.772	0.518	0.803
Agricultural, construction and transport workers	0.543	0.744	0.522	0.747
Service workers	0.530	0.713	0.531	0.726
B: WITHOUT IMPUTATION
Overall Mean	0.598	0.739	0.607	0.732
Standard Deviation	0.119	0.062	0.114	0.061
Manager, Professionals, Technicians	0.789	0.701	0.771	0.676
Clerical support and sale workers	0.667	0.738	0.675	0.747
Plant and machines operators and assemblers	0.547	0.772	0.518	0.804
Agricultural, construction and transport workers	0.544	0.744	0.531	0.750
Service workers	0.530	0.712	0.531	0.726

[i] Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

[ii] Note: The information content index is computed as ${IC}_{j} = \sum_{k = 1}^{5} I_{jk}^{\frac{2}{3}} * L_{jk}^{\frac{1}{3}}$ where k = work activities: Getting information, Processing information, Analyzing data or information, Interacting with computers, Documenting/Recording information. The automation content is defined as ${AC}_{j} = \sum_{l = 1}^{5} F_{jl} * V_{jl}$ where l = work context: Degree of automation, Importance of repeating same tasks, Structured versus unstructured work (reverse), Pace determined by speed of equipment, Spend time making repetitive motions. Task measures are normalized to range between zero and one.

Table 4

Avarage O*NET Indexes by Major Occupation Group 2015

A: WITH IMPUTATION	2015
	MEN		WOMEN
*ONet Indexes**	Information	Automation	Information	Automation
Overall Mean	0.608	0.738	0.621	0.732
Standard Deviation	0.117	0.063	0.114	0.061
Manager, Professionals, Technicians	0.799	0.706	0.776	0.685
Clerical support and sale workers	0.670	0.744	0.668	0.746
Plant and machines operators and assemblers	0.552	0.772	0.518	0.802
Agricultural, construction and transport workers	0.559	0.738	0.561	0.757
Service workers	0.536	0.713	0.545	0.725
B: WITHOUT IMPUTATION
Overall Mean	0.610	0.738	0.625	0.732
Standard Deviation	0.117	0.063	0.115	0.062
Manager, Professionals, Technicians	0.799	0.706	0.777	0.685
Clerical support and sale workers	0.671	0.744	0.671	0.748
Plant and machines operators and assemblers	0.552	0.772	0.519	0.804
Agricultural, construction and transport workers	0.560	0.737	0.576	0.761
Service workers	0.536	0.712	0.544	0.725

[i] Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

[ii] Note: The information content index is computed as ${IC}_{j} = \sum_{k = 1}^{5} I_{jk}^{\frac{2}{3}} * L_{jk}^{\frac{1}{3}}$ where where k = work activities: Getting information, Processing information, Analyzing data or information, Interacting with computers, Documenting/Recording information. The automation content is de ned as ${AC}_{j} = \sum_{l = 1}^{5} F_{jl} * V_{jl}$ where l = work context: Degree of automation, Importance of repeating same tasks, Structured versus unstructured work (reverse), Pace determined by speed of equipment, Spend time making repetitive motions. Task measures are normalized to range between zero and one.

Table 5

Percentage of Workers in the Top Quartile of Task Content Indexes by Major Occupation Group in 2005/2006 – 2014/2015 (with self selection correction)

Task Content Indexes	Percentage of workers		Technology
Task Content Indexes	Percentage of workers		Information		Automation
2005	Men	Women	Men	Women	Men	Women
Overall	100	100	20	25	26	23
Manager, Professionals, Technicians	13	12	87	84	0	0
Clerical support and sale workers	19	31	45	49	48	56
Plant and machines operators and assemblers	20	8	2	0	51	75
Agricultural, construction and transport workers	36	1	1	1	20	27
Service workers	13	48	0	0	2	0
2015
Overall	100	100	21	29	23	16
Manager, Professionals, Technicians	13	15	87	82	1	0
Clerical support and sale workers	20	36	44	48	23	30
Plant and machines operators and assemblers	20	6	2	0	49	69
Agricultural, construction and transport workers	33	2	1	0	24	38
Service workers	14	42	0	0	2	0

[i] Note: The numbers in each of the task content indexes columns indicate the percentage of workers in each major occupation by gender, which fall in the top 75 per cent of their category.

Table 6

Unconditional Quantile Partial Effects on Log Wages (2005 – 2015) - RIF Regression

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Female	−0.141^*** (0.005)	−0.158^*** (0.003)	−0.327^*** (0.004)	−0.203^*** (0.002)	−0.237^*** (0.002)	−0.272^*** (0.002)
Task content indexes (1st. quartile omitted)
Information content Q2	0.136^*** (0.009)	0.105^*** (0.009)	0.080^*** (0.006)	−0.001 (0.005)	−0.059^*** (0.003)	0.047^*** (0.003)
Information content Q3	0.105^*** (0.008)	0.220^*** (0.008)	0.061^*** (0.006)	0.005 (0.004)	0.004^*** (0.001)	−0.118^*** (0.002)
Information content Q4	0.185^*** (0.008)	0.543^*** (0.008)	1.013^*** (0.011)	0.071^*** (0.004)	0.230^*** (0.002)	0.514^*** (0.005)
Automation content Q2	−0.010 (0.009)	0.011 (0.009)	−0.112^*** (0.005)	0.045^*** (0.001)	0.002 (0.002)	−0.151^*** (0.005)
Automation content Q3	0.205^*** (0.009)	0.281^*** (0.009)	−0.125^*** (0.008)	0.101^*** (0.002)	0.11^*** (0.002)	−0.093^*** (0.003)
Automation content Q4	0.088^*** (0.008)	0.037^*** (0.008)	−0.304^*** (0.007)	0.1^*** (0.003)	0.045^*** (0.003)	−0.412^*** (0.004)
Education (6 years or less omitted)
From 7 to 9 years	0.167^*** (0.009)	0.141^*** (0.004)	0.093^*** (0.004)	0.148^*** (0.004)	0.105^*** (0.002)	0.064^*** (0.002)
From 10 to 12 years	0.243^*** (0.008)	0.278^*** (0.005)	0.356^*** (0.008)	0.281^*** (0.004)	0.294^*** (0.002)	0.267^*** (0.003)
From 13 to 15 years	0.243^*** (0.008)	0.278^*** (0.005)	0.356^*** (0.008)	0.281^*** (0.004)	0.294^*** (0.002)	0.267^*** (0.003)
16 and more years	0.296^*** (0.009)	0.525^*** (0.008)	0.978^*** (0.015)	0.359^*** (0.005)	0.566^*** (0.004)	0.765^*** (0.006)
Experience (15<Experience<20 omitted)
Experience<5	0.042^*** (0.012)	−0.079^*** (0.014)	−1.581^*** (0.034)	0.020^*** (0.004)	−0.099^*** (0.009)	−1.067^*** (0.017)
5<experience<10	0.023^** (0.010)	−0.130^*** (0.005)	−0.670^*** (0.009)	−0.017^*** (0.004)	−0.119^*** (0.003)	−0.436^*** (0.007)
10<experience<15	−0.051^*** (0.009)	−0.116^*** (0.004)	−0.153^*** (0.007)	−0.046^*** (0.004)	−0.088^*** (0.003)	−0.128^*** (0.003)
20<experience<25	0.035^*** (0.009)	0.102^*** (0.004)	0.118^*** (0.006)	0.031^*** (0.003)	0.031^*** (0.004)	0.074^*** (0.005)
25<experience<30	0.075^*** (0.008)	0.144^*** (0.003)	0.213^*** (0.007)	0.034^*** (0.004)	0.067^*** (0.003)	0.132^*** (0.003)
30<experience<35	0.056^*** (0.008)	0.16^*** (0.005)	0.232^*** (0.007)	0.049^*** (0.004)	0.089^*** (0.003)	0.202^*** (0.004)
35<experience<40	0.113^*** (0.010)	0.176^*** (0.006)	0.222^*** (0.005)	0.055^*** (0.005)	0.086^*** (0.003)	0.195^*** (0.003)
Experience>40	0.046^*** (0.008)	0.208^*** (0.004)	0.225^*** (0.006)	0.048^*** (0.004)	0.094^*** (0.003)	0.167^*** (0.004
Nonmarried	−0.073^*** (0.005)	−0.131^*** (0.004)	−0.149^*** (0.003)	−0.050^*** (0.002)	−0.101^*** (0.002)	−0.101^*** (0.001)
Region	−0.190^*** (0.003)	−0.161^*** (0.003)	−0.150^*** (0.004)	−0.086^*** (0.002)	−0.060^*** (0.001)	−0.059^*** (0.001)
Informal	−0.438^*** (0.007)	−0.244^*** (0.005)	−0.0220^*** (0.006)	−0.506^*** (0.008)	−0.196^*** (0.003)	0.001 (0.003)
Constant	2.750^*** (0.013)	3.334^*** (0.005)	4.358^*** (0.007)	3.450^*** (0.007)	4.008^*** (0.004)	4.834^*** (0.003)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 43,022; 2014/15: 45,063

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.34

Table 7

Unconditional Quantile Partial Effects on Male Log Wages (2005 – 2015) - RIF Regression

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Task content indexes (1st. quartile omitted)
Information content Q2	0.071^*** (0.005)	0.087^*** (0.005)	−0.075^*** (0.007)	−0.022^** (0.009)	0.010^*** (0.003)	0.111^*** (0.004)
Information content Q3	0.031^*** (0.006)	0.081^*** (0.004)	0.007 (0.007)	0.005 (0.005)	−0.035^*** (0.002)	−0.133^*** (0.003)
Information content Q4	0.14^*** (0.006)	0.45^*** (0.006)	1.112^*** (0.011)	0.026^*** (0.006)	0.163^*** (0.002)	0.474^*** (0.008)
Automation content Q2	−0.259^*** (0.007)	−0.147^*** (0.004)	−0.171^*** (0.007)	−0.050^*** (0.003)	−0.035^*** (0.002)	−0.096^*** (0.004)
Automation content Q3	0.124^*** (0.008)	0.227^*** (0.010)	−0.142^*** (0.010)	0.057^*** (0.003)	0.129^*** (0.003)	−0.014^*** (0.004)
Automation content Q4	0.009^* (0.005)	−0.019^*** (0.005)	0.008 (0.008)	0.003 (0.003)	−0.02^*** (0.003)	−0.326^*** (0.003)
Education (6 years or less omitted)
From 7 to 9 years	0.193^*** (0.007)	0.164^*** (0.004)	0.101^*** (0.007)	0.173^*** (0.005)	0.112^*** (0.002)	0.096^*** (0.003)
From 10 to 12 years	0.274^*** (0.007)	0.331^*** (0.005)	0.460^*** (0.010)	0.269^*** (0.004)	0.311^*** (0.002)	0.345^*** (0.004)
From 13 to 15 years	0.328^*** (0.012)	0.535^*** (0.009)	1.257^*** (0.031)	0.353^*** (0.006)	0.524^*** (0.005)	0.899^*** (0.008)
16 and more years	0.312^*** (0.005)	0.649^*** (0.007)	2.751^*** (0.032)	0.403^*** (0.006)	0.691^*** (0.004)	1.953^*** (0.012)
Experience (15<Experience<20 omitted)
Experience<5	−0.024^** (0.011)	−0.090^*** (0.015)	−2.119^*** (0.044)	0.054^*** (0.006)	−0.077^*** (0.015)	−1.350^*** (0.036)
5<experience<10	0.008 (0.012)	−0.129^*** (0.011)	−0.916^*** (0.017)	−0.013^*** (0.004)	−0.128^*** (0.005)	−0.516^*** (0.009)
10<experience<15	−0.112^*** (0.013)	−0.138^*** (0.006)	−0.156^*** (0.010)	−0.039^*** (0.004)	−0.072^*** (0.003)	−0.147^*** (0.006)
20<experience<25	0.046^*** (0.009)	0.108^*** (0.007)	0.131^*** (0.008)	0.053^*** (0.004)	0.06^*** (0.003)	0.096^*** (0.005)
25<experience<30	0.075^*** (0.007)	0.147^*** (0.004)	0.26^*** (0.008)	0.065^*** (0.003)	0.094^*** (0.004)	0.156^*** (0.005)
30<experience<35	0.074^*** (0.008)	0.159^*** (0.006)	0.192^*** (0.010)	0.073^*** (0.003)	0.128^*** (0.001)	0.204^*** (0.005)
35<experience<40	0.096^*** (0.010)	0.153^*** (0.007)	0.202^*** (0.008)	0.092^*** (0.004)	0.129^*** (0.004)	0.243^*** (0.005)
Experience>40	0.052^*** (0.012)	0.165^*** (0.005)	0.235^*** (0.011)	0.091^*** (0.005)	0.091^*** (0.003)	0.192^*** (0.007)
Nonmarried	−0.083^*** (0.008)	−0.159^*** (0.003)	−0.158^*** (0.004)	−0.071^*** (0.002)	−0.111^*** (0.002)	−0.134^*** (0.003)
Region	−0.108^*** (0.004)	−0.097^*** (0.004)	−0.147^*** (0.007)	−0.054^*** (0.004)	−0.016^*** (0.002)	−0.029^*** (0.002)
Informal	−0.484^*** (0.011)	−0.325^*** (0.006)	−0.017^* (0.010)	−0.515^*** (0.008)	−0.255^*** (0.004)	0.008 (0.006)
Constant	2.853^*** (0.008)	3.458^*** (0.007)	4.327^*** (0.011)	3.504^*** (0.007)	4.021^*** (0.004)	4.725^*** (0.007)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 21,852; 2014/15: 22,183

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

Table 8

Unconditional Quantile Partial Effects on Female Log Wages (2005 – 2015) - RIF Regression

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Task content indexes (1st. quartile omitted)
Information content Q2	0.132^*** (0.019)	0.069^*** (0.005)	−0.018^** (0.007)	0.065^*** (0.009)	0.004 (0.006)	0.025^*** (0.006)
Information content Q3	0.136^*** (0.020)	0.384^*** (0.011)	0.010 (0.010)	0.008 (0.008)	0.103^*** (0.004)	−0.107^*** (0.006)
Information content Q4	0.602^*** (0.016)	0.607^*** (0.007)	0.886^*** (0.008)	0.103^*** (0.008)	0.374^*** (0.005)	0.587^*** (0.005)
Automation content Q2	0.162^*** (0.013)	0.169^*** (0.005)	−0.068^*** (0.006)	0.078^*** (0.008)	0.098^*** (0.005)	−0.143^*** (0.009)
Automation content Q3	0.171^*** (0.024)	0.178^*** (0.010)	−0.186^*** (0.014)	0.143^*** (0.006)	0.186^*** (0.005)	−0.211^*** (0.007)
Automation content Q4	0.096^*** (0.018)	0.041^*** (0.006)	0.012 (0.011)	0.006 (0.005)	0.106^*** (0.006)	−0.487^*** (0.009)
Education (6 years or less omitted)
From 7 to 9 years	0.176^*** (0.015)	0.115^*** (0.011)	0.043^*** (0.008)	0.133^*** (0.007)	0.07^*** (0.003)	0.019^*** (0.005)
From 10 to 12 years	0.285^*** (0.017)	0.248^*** (0.011)	0.18^*** (0.011)	0.31^*** (0.008)	0.313^*** (0.004)	0.138^*** (0.004)
From 13 to 15 years	0.352^*** (0.018)	0.492^*** (0.012)	0.705^*** (0.021)	0.39^*** (0.010)	0.581^*** (0.005)	0.599^*** (0.009)
16 and more years	0.364^*** (0.018)	0.648^*** (0.011)	1.857^*** (0.020)	0.424^*** (0.010)	0.74^*** (0.004)	1.712^*** (0.013)
Experience (15<Experience<20 omitted)
Experience<5	0.138^*** (0.027)	−0.03^* (0.016)	−1.239^*** (0.056)	0.053^*** (0.004)	−0.082^*** (0.009)	−0.957^*** (0.040)
5<experience<10	0.054^*** (0.021)	−0.09^*** (0.007)	−0.499^*** (0.018)	0.017^** (0.007)	−0.095^*** (0.005)	−0.372^*** (0.010)
10<experience<15	−0.003 (0.021)	−0.074^*** (0.006)	−0.159^*** (0.009)	−0.011 (0.009)	−0.081^*** (0.005)	−0.112^*** (0.006)
20<experience<25	0.048^*** (0.017)	0.08^*** (0.008)	0.102^*** (0.007)	0.066^*** (0.008)	0.012^* (0.007)	0.044^*** (0.009)
25<experience<30	0.105^*** (0.020)	0.118^*** (0.009)	0.117^*** (0.006)	0.056^*** (0.007)	0.056^*** (0.008)	0.085^*** (0.006)
30<experience<35	0.092^*** (0.015)	0.121^*** (0.009)	0.16^*** (0.009)	0.079^*** (0.008)	0.066^*** (0.007)	0.183^*** (0.009)
35<experience<40	0.134^*** (0.018)	0.149^*** (0.006)	0.154^*** (0.005)	0.078^*** (0.011)	0.06^*** (0.007)	0.137^*** (0.008)
Experience>40	0.08^*** (0.018)	0.196^*** (0.008)	0.163^*** (0.009)	0.048^*** (0.005)	0.048^*** (0.006)	0.098^*** (0.005)
Nonmarried	−0.082^*** (0.009)	−0.078^*** (0.004)	−0.105^*** (0.004)	−0.04^*** (0.003)	−0.066^*** (0.002)	−0.076^*** (0.003)
Region	−0.266^*** (0.008)	−0.228^*** (0.005)	−0.164^*** (0.005)	−0.1^*** (0.003)	−0.109^*** (0.002)	−0.094^*** (0.002)
Informal	−0.451^*** (0.022)	−0.156^*** (0.008)	−0.085^*** (0.007)	−0.525^*** (0.021)	−0.131^*** (0.006)	−0.01^** (0.005)
Constant	2.508^*** (0.036)	3.107^*** (0.008)	4.251^*** (0.008)	3.179^*** (0.013)	3.63^*** (0.007)	4.706^*** (0.011)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 21,170; 2014/15: 22,880

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

Unconditional Quantile Partial Effects: Occupational Task. Forth vs First Quartile of Task Content. Dependent variable: log hourly wages. 2005 and 2015.
*Notes*: i. Figures show the UQPE of the task indexes for the upper quartile when the bottom quartile is omitted. ii. Information/Automation covariates are defined as category variables that indicate the degree of information/automation task content of the job. Four quartiles are considered. iii. 2005 in red, 2015 in blue. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Unconditional Quantile Partial Effects: Selected Education Covariates (Dummy 6 Years of Schooling omitted). Dependent variable: log hourly wages. 2005 and 2015.
*Notes*: i. Figures show the UQPE of educational dummies, six years of education or less is omitted. ii. 2005 in red, 2015 in blue. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Aggregated decomposition of log hourly wages changes, 2005 and 2015.
*Notes*: i. Figures show the total change of wages by gender, as well as the aggregated decomposition into the structure and the composition effect. RIF-regression method is used to perform the decomposition. Covariates include: Information, Automation, Education, Experience, Informal worker, Region and Marital status. ii. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Table 9

Aggregate Decomposition of wage change between 2005 and 2015

	90–10	90–50	50–10
A. All
Total Change	−0.453^*** (0.004)	−0.255^*** (0.002)	−0.197^*** (0.002)
Composition	−0.066^*** (0.003)	−0.067^*** (0.002)	0.001 (0.002)
Structure	−0.387^*** (0.003)	−0.188^*** (0.002)	−0.198^*** (0.003)
B. Males
Total Change	−0.582^*** (0.005)	−0.34^*** (0.002)	−0.242^*** (0.004)
Composition	−0.02^*** (0.002)	−0.015^*** (0.002)	−0.005^*** (0.002)
Structure	−0.562^*** (0.005)	−0.326^*** (0.002)	−0.236^*** (0.004)
C. Females
Total Change	−0.418^*** (0.012)	−0.184^*** (0.004)	−0.233^*** (0.009)
Composition	−0.052^*** (0.01)	−0.038^*** (0.006)	−0.014^** (0.006)
Structure	−0.365^*** (0.01)	−0.146^*** (0.006)	−0.219^*** (0.008)

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data. 32

Table 10

Detailed Decomposition of the composition effect, based on Unconditional Quantile Partial Effects

Inequality measure	All			Males			Females
Inequality measure	90-10	90-50	50-10	90-10	90-50	50-10	90-10	90-50	50-10
Female	−0.002^*** (0.00007)	−0.002^*** (0.00005)	−0.00016^*** (0.00004)
Information	0.018^*** (0.0009)	0.000 (0.0007)	0.018^*** (0.0005)	0.001 (0.0008)	−0.005^*** (0.0008)	0.006^*** (0.0006)	0.040^*** (0.002)	0.003^*** (0.001)	0.037^*** (0.001)
Automation	−0.041^*** (0.00146)	−0.048^*** (0.00087)	0.007^*** (0.0015)	0.012^*** (0.0008)	0.00667^*** (0.001)	0.006^*** (0.0009)	−0.036^*** (0.006)	−0.03539^*** (0.005)	−0.00058 (0.005)
Education	0.042^*** (0.001)	0.032^*** (0.0007)	0.011^*** (0.0005)	0.057^*** (0.0018)	0.045^*** (0.0014)	0.013^*** (0.0012)	0.019^*** (0.001)	0.015^*** (0.001)	0.004^*** (0.001)
Experience	−0.020^*** (0.0003)	−0.015^*** (0.0003)	−0.005^*** (0.0002)	−0.025^*** (0.00054)	−0.020^*** (0.00051)	−0.005^*** (0.0003)	−0.013^*** (0.001)	−0.010^*** (0.001)	−0.003^*** (0.001)
Other	−0.064^*** (0.002)	−0.035^*** (0.001)	−0.030^*** (0.001)	−0.065^*** (0.0018)	−0.041^*** (0.0015)	−0.024^*** (0.0013)	−0.062^*** (0.004)	−0.010^*** (0.002)	−0.051^*** (0.003)
Total Composition Effect	−0.066^*** (0.003)	−0.067^*** (0.002)	0.001 (0.002)	−0.020^*** (0.0024)	−0.015^*** (0.0022)	−0.005^*** (0.0015)	−0.052^*** (0.01)	−0.038^*** (0.006)	−0.014^** (0.006)

*** p < 0.01,

** p < 0.05,

* p < 0.1.

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data.

Table 11

Detailed Decomposition of the structure effect, wage variation between 2005 and 2015, based on Unconditional Quantile Partial Effects

Inequality measure	All			Males			Females
Inequality measure	90-10	90-50	50-10	90-10	90-50	50-10	90-10	90-50	50-10
Female	0.063^*** (0.0043)	0.072^*** (0.0032)	−0.00909^*** (0.0024)
Information	−0.112^*** (0.0086)	−0.015^** (0.0058)	−0.09663^*** (0.0071)	−0.159^*** (0.008)	−0.08^*** (0.006)	−0.079^*** (0.005)	−0.062^*** (0.018)	0.012 (0.01)	−0.074^*** (0.017)
Automation	−0.021^** (0.01)	0.012^*** (0.0047)	−0.03344^*** (0.0078)	−0.060^*** (0.007)	−0.009 (0.006)	−0.051^*** (0.005)	−0.034^** (0.016)	−0.060^*** (0.009)	0.026^** (0.013)
Education	−0.121^*** (0.0082)	−0.103^*** (0.0057)	−0.01804^*** (0.0049)	−0.136^*** (0.013)	−0.114^*** (0.009)	−0.021^** (0.009)	−0.052^*** (0.014)	−0.073^*** (0.01)	0.021 (0.014)
Experience	0.013^** (0.0053)	0.046^*** (0.0057)	−0.0334^*** (0.0068)	0.006 (0.008)	0.037^*** (0.008)	−0.031^*** (0.008)	0.021 (0.014)	0.052^*** (0.009)	−0.031^*** (0.012)
Other	0.015^*** (0.0044)	−0.003 (0.0035)	0.01813^*** (0.0044)	0.040^*** (0.005)	0.005 (0.003)	0.035^*** (0.004)	−0.023^** (0.011)	−0.008 (0.006)	−0.014 (0.01)
Constant	−0.224^*** (0.0176)	−0.198^*** (0.0075)	−0.02593 (0.0177)	−0.253^*** (0.014)	−0.165^*** (0.014)	−0.089^*** (0.012)	−0.216^*** (0.043)	−0.068^*** (0.015)	−0.148^*** (0.037)
Total Structure Effect	−0.387^*** (0.0033)	−0.188^*** (0.0016)	−0.1984^*** (0.0026)	−0.562^*** (0.005)	−0.326^*** (0.002)	−0.236^*** (0.004)	−0.365^*** (0.01)	−0.146^*** (0.006)	−0.219^*** (0.008)

*** p < 0.01,

** p < 0.05,

* p < 0.1.

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data.

Log-hourly wages gender gap, 2005 and 2015.
*Notes*: i. The gender gap is calculated by subtracting men’s wages minus women’s wages. ii. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied. iii. Estimates of the gender gap without correction for self-selection are reported in the Supplementary Appendix.

Log-hourly wages gender gap variation between 2005 and 2015, unconditional and after controlling for observed characteristics. With correction for selection bias.
*Notes*: i. Figures correspond to the estimation of the variation of the gender gap using an approach analogous to the diff in diff estimator. Unconditional stands for the estimation without any controls. Figure (a) compares the unconditional variation of the gap with respect to that which control for all selected characteristics (Information, Automation, Education, Experience, Informal worker, Region and Marital status). Figures (b) to (e) compares the model with all regressors with those excluding indicated variables. iii. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Aggregated decomposition of the gender wage gap and the gender gap change.
*Notes*: i. Figure (a) shows the aggregated composition and structure effects of gender wage gap in 2005 and 2015. Covariates include: Information, Automation, Education, Experience, Informal worker, Region and Marital status. ii. Figure (b) decompose gender wage gap change between 2005 and 2015 into the aggregated composition, structure and interaction effects, as defined in section 6) iii. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Detailed decomposition of the gender gap change
*Notes*: Figures show the composition, structure and total effects of covariates Information, Automation and Education to the change of the gender wage gap between 2005 and 2015 as defined in section 6). ii. Solid lines are point estimates, dashed lines indicate the lower and upper bound of the 95 confidence interval. Bootstrapped standard errors are calculated (200 replicates) within each 10 imputed data sets and then Rubin’s rules are applied.

Table A1

Unconditional Quantile Partial Effects on Log Wages (2005 – 2015) - RIF Regression (Without correction for selection bias)

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Female	−0.141^*** (0.001)	−0.166^*** (0.001)	−0.337^*** (0.002)	−0.210^*** (0.001)	−0.234^*** (0.0005)	−0.284^*** (0.001)
Task content indexes (1st. quartile omitted)
Information content Q2	0.143^*** (0.001)	0.097^*** (0.001)	0.0190^*** (0.001)	0.009^*** (0.001)	−0.089^*** (0.001)	−0.033^*** (0.001)
Information content Q3	0.108^*** (0.001)	0.2190^*** (0.001)	−0.026^*** (0.001)	−0.009^*** (0.001)	0.024^*** (0.001)	−0.044^*** (0.001)
Information content Q4	0.166^*** (0.001)	0.512^*** (0.001)	0.988^*** (0.003)	0.109^*** (0.001)	0.336^*** (0.001)	0.578^*** (0.001)
Automation content Q2	−0.017^*** (0.001)	−0.000 (0.001)	−0.147^*** (0.001)	0.042^*** (0.001)	−0.030^*** (0.001)	−0.135^*** (0.001)
Automation content Q3	0.192^*** (0.001)	0.217^*** (0.001)	−0.390^*** (0.002)	0.089^*** (0.001)	0.100^*** (0.001)	−0.014^*** (0.001)
Automation content Q4	0.100^*** (0.001)	0.044^*** (0.001)	−0.192^*** (0.002)	0.098^*** (0.001)	0.019^*** (0.001)	−0.324^*** (0.001)
Education (6 years or less omitted)
From 7 to 9 years	0.166^*** (0.001)	0.145^*** (0.001)	0.097^*** (0.001)	0.150^*** (0.001)	0.103^*** (0.001)	0.055^*** (0.001)
From 10 to 12 years	0.235^*** (0.001)	0.280^*** (0.001)	0.363^*** (0.001)	0.268^*** (0.001)	0.259^*** (0.001)	0.215^*** (0.001)
From 13 to 15 years	0.235^*** (0.001)	0.280^*** (0.001)	0.363^*** (0.001)	0.268^*** (0.001)	0.259^*** (0.001)	0.215^*** (0.001)
16 and more years	0.280^*** (0.001)	0.541^*** (0.001)	0.954^*** (0.004)	0.331^*** (0.001)	0.49^*** (0.001)	0.659^*** (0.002)
Experience (15<Experience<20 omitted)
Experience<5	0.027^*** (0.002)	−0.090^*** (0.002)	−1.658^*** (0.009)	0.015^*** (0.001)	−0.112^*** (0.001)	−1.096^*** (0.005)
5<experience<10	0.022^*** (0.001)	−0.134^*** (0.001)	−0.662^*** (0.003)	−0.015^*** (0.001)	−0.124^*** (0.001)	−0.435^*** (0.002)
10<experience<15	−0.057^*** (0.001)	−0.123^*** (0.001)	−0.154^*** (0.001)	−0.046^*** (0.001)	−0.089^*** (0.001)	−0.13^*** (0.001)
20<experience<25	0.019^*** (0.001)	0.099^*** (0.001)	0.123^*** (0.002)	0.022^*** (0.001)	0.026^*** (0.001)	0.077^*** (0.001)
25<experience<30	0.058^*** (0.001)	0.142^*** (0.001)	0.223^*** (0.002)	0.023^*** (0.001)	0.057^*** (0.001)	0.134^*** (0.001)
30<experience<35	0.050^*** (0.002)	0.160^*** (0.001)	0.234^*** (0.002)	0.034^*** (0.001)	0.077^*** (0.001)	0.198^*** (0.001)
35<experience<40	0.100^*** (0.001)	0.178^*** (0.001)	0.220^*** (0.002)	0.041^*** (0.001)	0.077^*** (0.001)	0.197^*** (0.001)
Experience>40	0.032^*** (0.001)	0.202^*** (0.001)	0.234^*** (0.002)	0.027^*** (0.001)	0.076^*** (0.001)	0.155^*** (0.001)
Nonmarried	−0.082^*** (0.001)	−0.146^*** (0.001)	−0.157^*** (0.001)	−0.0550^*** (0.001)	−0.099^*** (0.0004)	−0.095^*** (0.001)
Region	−0.198^*** (0.001)	−0.159^*** (0.001)	−0.150^*** (0.001)	−0.088^*** (0.001)	−0.058^*** (0.0004)	−0.065^*** (0.001)
Informal	−0.480^*** (0.001)	−0.239^*** (0.001)	0.004^*** (0.001)	−0.550^*** (0.001)	−0.185^*** (0.001)	0.038^*** (0.001)
Constant	2.775^*** (0.002)	3.351^*** (0.001)	4.425^*** (0.002)	3.476^*** (0.001)	4.041^*** (0.001)	4.819^*** (0.001)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 38,522; 2014/15: 41,893

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

Table A2

Unconditional Quantile Partial Effects on Male Log Wages (2005 – 2015) - RIF Regression (Without correction for selection bias)

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Task content indexes (1st. quartile omitted)
Information content Q2	0.021^*** (0.001)	0.064^*** (0.001)	0.067^*** (0.001)	−0.072^*** (0.001)	−0.042^*** (0.001)	−0.070^*** (0.001)
Information content Q3	0.033^*** (0.001)	0.030^*** (0.002)	0.001 (0.001)	0.001 (0.001)	−0.002^* (0.001)	−0.023^*** (0.001)
Information content Q4	0.479^*** (0.001)	0.124^*** (0.001)	0.390^*** (0.001)	0.322^*** (0.001)	0.106^*** (0.001)	0.296^*** (0.001)
Automation content Q2	−0.199^*** (0.001)	−0.281^*** (0.002)	−0.160^*** (0.001)	−0.066^*** (0.001)	−0.072^*** (0.001)	−0.049^*** (0.001)
Automation content Q3	0.017^*** (0.001)	0.104^*** (0.001)	0.179^*** (0.001)	0.062^*** (0.001)	0.032^*** (0.001)	0.122^*** (0.001)
Automation content Q4	−0.044^*** (0.002)	0.017^*** (0.001)	0.001 (0.001)	0.001 (0.001)	0.012^*** (0.001)	−0.007^*** (0.001)
Education (6 years or less omitted)
From 7 to 9 years	0.162^*** (0.001)	0.188^*** (0.001)	0.167^*** (0.001)	0.118^*** (0.001)	0.175^*** (0.001)	0.106^*** (0.001)
From 10 to 12 years	0.336^*** (0.001)	0.272^*** (0.002)	0.332^*** (0.001)	0.27^*** (0.001)	0.258^*** (0.001)	0.272^*** (0.001)
From 13 to 15 years	0.619^*** (0.002)	0.317^*** (0.002)	0.543^*** (0.002)	0.487^*** (0.001)	0.307^*** (0.001)	0.435^*** (0.001)
16 and more years	1.070^*** (0.002)	0.321^*** (0.002)	0.678^*** (0.002)	0.88^*** (0.001)	0.334^*** (0.001)	0.573^*** (0.001)
Experience (15<Experience<20 omitted)
Experience<5	−0.578^*** (0.003)	−0.029^*** (0.004)	−0.086^*** (0.004)	−0.44^*** (0.002)	0.046^*** (0.001)	−0.0850^*** (0.002)
5<experience<10	−0.303^*** (0.001)	−0.000 (0.002)	−0.135^*** (0.002)	−0.218^*** (0.001)	−0.013^*** (0.001)	−0.131^*** (0.001)
10<experience<15	−0.133^*** (0.001)	−0.100^*** (0.002)	−0.146^*** (0.001)	−0.087^*** (0.001)	−0.039^*** (0.001)	−0.079^*** (0.001)
20<experience<25	0.089^*** (0.001)	0.037^*** (0.002)	0.107^*** (0.001)	0.056^*** (0.001)	0.052^*** (0.001)	0.054^*** (0.001)
25<experience<30	0.152^*** (0.001)	0.075^*** (0.002)	0.136^*** (0.001)	0.099^*** (0.001)	0.051^*** (0.001)	0.085^*** (0.001)
30<experience<35	0.156^*** (0.001)	0.075^*** (0.002)	0.155^*** (0.001)	0.133^*** (0.001)	0.064^*** (0.001)	0.116^*** (0.001)
35<experience<40	0.157^*** (0.001)	0.091^*** (0.002)	0.147^*** (0.001)	0.128^*** (0.001)	0.083^*** (0.001)	0.113^*** (0.001)
Experience>40	0.154^*** (0.001)	0.043^*** (0.002)	0.156^*** (0.001)	0.11^*** (0.001)	0.11^*** (0.001)	0.089^*** (0.001)
Nonmarried	−0.139^*** (0.001)	−0.087^*** (0.001)	−0.169^*** (0.001)	−0.100^*** (0.001)	−0.072^*** (0.001)	−0.114^*** (0.001)
Region	−0.119^*** (0.001)	−0.104^*** (0.001)	−0.102^*** (0.001)	−0.026^*** (0.0005)	−0.054^*** (0.001)	−0.016^*** (0.001)
Informal	−0.302^*** (0.001)	−0.506^*** (0.002)	−0.331^*** (0.001)	−0.276^*** (0.001)	−0.555^*** (0.002)	−0.243^*** (0.001)
Constant	3.566^*** (0.001)	2.866^*** (0.002)	3.483^*** (0.002)	4.092^*** (0.001)	3.528^*** (0.001)	4.045^*** (0.001)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 20,330; 2014/15: 21,075

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

Table A3

Unconditional Quantile Partial Effects on Female Log Wages (2005 – 2015) - RIF Regression (Without correction for selection bias)

Year	2005/06			2014/15
Covariates/Quantile	10	50	90	10	50	90
Task content indexes (1st. quartile omitted)
Information content Q2	0.169^*** (0.002)	0.078^*** (0.001)	−0.078^*** (0.001)	0.076^*** (0.001)	0.004^*** (0.001)	−0.076^*** (0.001)
Information content Q3	0.156^*** (0.003)	0.438^*** (0.002)	0.0030 (0.003)	0.002 (0.001)	0.140^*** (0.001)	0.009^*** (0.002)
Information content Q4	0.601^*** (0.002)	0.644^*** (0.002)	0.851^*** (0.003)	0.082^*** (0.001)	0.433^*** (0.001)	0.620^*** (0.002)
Automation content Q2	0.172^*** (0.002)	0.190^*** (0.001)	−0.078^*** (0.001)	0.092^*** (0.001)	0.065^*** (0.001)	−0.121^*** (0.002)
Automation content Q3	0.175^*** (0.002)	0.130^*** (0.001)	−0.481^*** (0.003)	0.141^*** (0.001)	0.162^*** (0.001)	−0.105^*** (0.001)
Automation content Q4	0.080^*** (0.002)	0.056^*** (0.001)	0.003 (0.003)	0.001 (0.001)	0.066^*** (0.001)	−0.446^*** (0.002)
Education (6 years or less omitted)
From 7 to 9 years	0.193^*** 3241(0.002)	0.108^*** (0.001)	0.051^*** (0.001)	0.134^*** (0.001)	0.075^*** (0.001)	0.021^*** (0.001)
From 10 to 12 years	0.290^*** (0.002)	0.257^*** (0.001)	0.192^*** (0.001)	0.308^*** (0.001)	0.301^*** (0.001)	0.095^*** (0.001)
From 13 to 15 years	0.346^*** (0.002)	0.508^*** (0.002)	0.664^*** (0.004)	0.392^*** (0.001)	0.563^*** (0.001)	0.524^*** (0.002)
16 and more years	0.366^*** (0.002)	0.687^*** (0.002)	1.8^*** (0.007)	0.437^*** (0.001)	0.705^*** (0.001)	1.608^*** (0.004)
Experience (15<Experience<20 omitted)
Experience<5	0.112^*** (0.003)	−0.045^*** (0.003)	−1.325^*** (0.011)	0.042^*** (0.001)	−0.093^*** (0.001)	−0.980^*** (0.007)
5<experience<10	0.056^*** (0.002)	−0.103^*** (0.002)	−0.467^*** (0.004)	0.027^*** (0.001)	−0.087^*** (0.001)	−0.374^*** (0.002)
10<experience<15	−0.004^** (0.002)	−0.075^*** (0.001)	−0.15^*** (0.002)	−0.004^*** (0.001)	−0.081^*** (0.001)	−0.120^*** (0.002)
20<experience<25	0.020^*** (0.002)	0.093^*** (0.001)	0.097^*** (0.003)	0.065^*** (0.001)	0.010^*** (0.001)	0.044^*** (0.002)
25<experience<30	0.087^*** (0.002)	0.13^*** (0.001)	0.126^*** (0.003)	0.050^*** (0.001)	0.054^*** (0.001)	0.088^*** (0.001)
30<experience<35	0.078^*** (0.002)	0.126^*** (0.001)	0.182^*** (0.003)	0.059^*** (0.001)	0.056^*** (0.001)	0.188^*** (0.002)
35<experience<40	0.132^*** (0.002)	0.156^*** (0.001)	0.144^*** (0.003)	0.068^*** (0.001)	0.051^*** (0.001)	0.153^*** (0.002)
Experience>40	0.051^*** (0.003)	0.215^*** (0.002)	0.171^*** (0.002)	0.042^*** (0.001)	0.042^*** (0.001)	0.108^*** (0.001)
Nonmarried	−0.093^*** (0.001)	−0.088^*** (0.001)	−0.11^*** (0.001)	−0.045^*** (0.001)	−0.076^*** (0.001)	−0.086^*** (0.001)
Region	−0.291^*** (0.001)	−0.242^*** (0.001)	−0.167^*** (0.001)	−0.110^*** (0.001)	−0.113^*** (0.001)	−0.093^*** (0.001)
Informal	−0.487^*** (0.002)	−0.158^*** (0.001)	−0.056^*** (0.001)	−0.541^*** (0.002)	−0.114^*** (0.001)	0.006^*** (0.001)
Constant	2.515^*** (0.003)	3.072^*** (0.002)	4.307^*** (0.003)	3.193^*** (0.002)	3.659^*** (0.001)	4.689^*** (0.002)

Notes: Bootstrapped standard errors are in parenthesis (200 replications of the entire procedure).

Number of observations 2005/2006: 18,192; 2014/15: 20,818

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data and O*NET.

Table A4

Aggregate Decomposition of wage change between 2005 and 2015 (without selection correction)

	90-10	90-50	50-10
A. All
Total Change	−0.457^*** (0.001)	−0.284^*** (0.001)	−0.173^*** (0.001)
Composition	−0.118^*** (0.001)	−0.119^*** (0.001)	0.001 (0.001)
Structure	−0.339^*** (0.001)	−0.165^*** (0.001)	−0.174^*** (0.001)
B. Males
Total Change	−0.555^*** (0.002)	−0.346^*** (0.001)	−0.208^*** (0.001)
Composition	−0.001 (0.001)	−0.001 (0.001)	0 (0.001)
Structure	−0.553^*** (0.002)	−0.345^*** (0.001)	−0.208^*** (0.001)
C. Females
Total Change	−0.415^*** (0.002)	−0.243^*** (0.001)	−0.172^*** (0.001)
Composition	−0.147^*** (0.001)	−0.150^*** (0.001)	0.003^*** (0.001)
Structure	−0.268^*** (0.002)	−0.093^*** (0.001)	−0.176^*** (0.001)

*** p<0.01,

** p<0.05,

* p<0.1

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data. 32

Table A5

Detailed Decomposition of the composition effect, based on Unconditional Quantile Partial Effects (without selection correction)

Inequality measure	All			Males			Females
Inequality measure	90-10	90-50	50-10	90-10	90-50	50-10	90-10	90-50	50-10
Female	−0.002^*** (0.00003)	−0.002^*** (0.00003)	−0.00024^*** (0.00001)
Information	0.008^*** (0.0004)	−0.022^*** (0.0003)	0.03^*** (0.0003)	0.018^*** (0.0005)	0.01^*** (0.0004)	0.008^*** (0.0003)	0.039^*** (0.0008)	−0.039^*** (0.0007)	0.077^*** (0.0006)
Automation	−0.072^*** (0.00033)	−0.073^*** (0.00032)	0.001^*** (0.00023)	0.018^*** (0.0003)	0.00853^*** (0.0003)	0.009^*** (0.0002)	−0.117^*** (0.0013)	−0.09796^*** (0.0011)	−0.019^*** (0.0008)
Education	0.043^*** (0.0004)	0.03^*** (0.0003)	0.012^*** (0.0002)	0.057^*** (0.0006)	0.044^*** (0.0005)	0.013^*** (0.0002)	0.018^*** (0.0005)	0.013^*** (0.0003)	0.005^*** (0.0003)
Experience	−0.02^*** (0.0002)	−0.015^*** (0.00013)	−0.005^*** (0.0001)	−0.025^*** (0.00027)	−0.02^*** (0.00024)	−0.005^*** (0.0001)	−0.014^*** (0.00021)	−0.01^*** (0.00018)	−0.003^*** (0.0001)
Other	−0.075^*** (0.00034)	−0.038^*** (0.00021)	−0.037^*** (0.00029)	−0.07^*** (0.0004)	−0.043^*** (0.0003)	−0.026^*** (0.0003)	−0.073^*** (0.0006)	−0.016^*** (0.0003)	−0.057^*** (0.0005)
Total Composition Effect	−0.118^*** (0.001)	−0.119^*** (0.001)	0.001 (0.001)	−0.001 (0.001)	−0.001 (0.0008)	−0.000 (0.0006)	−0.147^*** (0.0015)	−0.150^*** (0.0012)	0.003^*** (0.0009)

*** p < 0.01,

** p < 0.05,

* p < 0.1.

Source: Compiled by authors based on ECH 2005, 2006 and 2014, 2015 data. 32.

Table A6

Detailed Decomposition of the structure effect, wage variation between 2005 and 2015, based on UQPE (without selection correction)

Inequality measure	All			Males			Females
Inequality measure	90-10	90-50	50-10	90-10	90-50	50-10	90-10	90-50	50-10
Female	0.066^*** (0.0012)	0.066^*** (0.0012)	0.00048 (0.0007)
Information	−0.048^*** (0.0016)	0.018^*** (0.0013)	−0.06594^*** (0.0013)	−0.108^*** (0.002)	−0.065^*** (0.002)	−0.043^*** (0.001)	0.051^*** (0.003)	0.082^*** (0.003)	−0.030^*** (0.002)
Automation	0.078^*** (0.002)	0.110^*** (0.0016)	−0.03173^*** (0.0012)	0.017^*** (0.003)	0.047^*** (0.002)	−0.030^*** (0.002)	0.082^*** (0.003)	0.077^*** (0.002)	0.005^*** (0.002)
Education	−0.151^*** (0.0021)	−0.103^*** (0.0018)	−0.04793^*** (0.0016)	−0.166^*** (0.003)	−0.119^*** (0.002)	−0.047^*** (0.002)	−0.076^*** (0.003)	−0.087^*** (0.002)	0.011^*** (0.002)
Experience	0.007^*** (0.002)	0.047^*** (0.0018)	−0.03913^*** (0.0014)	−0.003 (0.003)	0.028^*** (0.002)	−0.031^*** (0.002)	0.009^*** (0.003)	0.059^*** (0.003)	−0.051^*** (0.002)
Other	0.015^*** (0.0012)	−0.006^*** (0.0009)	0.02106^*** (0.001)	0.052^*** (0.002)	0.008^*** (0.001)	0.043^*** (0.001)	−0.038^*** (0.002)	−0.02^*** (0.001)	−0.018^*** (0.001)
Constant	−0.307^*** (0.0042)	−0.297^*** (0.0036)	−0.01043^*** (0.003)	−0.345^*** (0.006)	−0.244^*** (0.005)	−0.1^*** (0.004)	−0.296^*** (0.006)	−0.204^*** (0.005)	−0.092^*** (0.005)
Total Structure Efect	−0.339^*** (0.001)	−0.165^*** (0.0009)	−0.17362^*** (0.0006)	−0.553^*** (0.002)	−0.345^*** (0.001)	−0.208^*** (0.001)	−0.268^*** (0.002)	−0.093^*** (0.001)	−0.176^*** (0.001)