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Does Unobserved Heterogeneity Matter? A Panel Data Analysis of
the Gender Pay Gap
Amynah Gangji, Kristian Orsini and Salimata Sissoko
Dulbea (Université Libre Bruxelles)
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Outlines
This paper provides evidences on the effect of controlling for unobserved individual heterogeneity in estimating the (un)adjusted gender pay differentials.
Using the European Community Household Panel (ECHP), we present a cross-country comparison of the gender pay gap over time (1994-2001) based on cross-section and panel data estimation techniques.
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The European Community Household Panel (ECHP)
Annual interview of a representative set of European households. Length: 1994-2001
Covers many topics, subdivided into 2 groups: Data related to households (financial situation, housing
conditions, durable consumption, children,…) Data related to individuals (economic activities, income,
education and training, health, social relations, migrations, satisfaction with various aspects of life, etc.)
=> valuable source of information: allow countries comparison thanks to a standardised methodology as well as to study changes over time at the micro level.
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Sample*Countries: Belgium, Denmark, Ireland, Italy, United Kingdom, Germany, Spain, Ireland, the Netherlands
*Selected individuals: Wage-earners aged between 20 to 60 years, working in the private sector and not self-employed
BE: 7.226 observations and 2001 individuals
GE: 24.896 observations, 5759 individuals
*Years: 1994-2001
*Unbalanced panel data (BE: 36%; GE: 33%; UK, IT, DK: 30%)
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Countries
The select countries differ according to their welfare state model:The conservative-corporatist model (Belgium, France, Germany, Italy, The Netherlands and Spain)The Scandinavian model (Denmark) The liberal welfare model (Ireland and UK).
Furthermore, we can identify Italy and Spain as representative of the Mediterranean mode
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Countries
According to Gornick they also differ regarding the level of public support to child care arrangements, maternity and parental leave provision. High support (Denmark, France and Belgium)Medium support (West-Germany, Italy and the
Netherlands)Low support (Ireland, Spain and United-
Kingdom)
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MethodologyWage equations
Estimated model:
ln Wit = β0 + β1 Xit + β2 Zi + αi + εit
Xit: time-varying explanatory variables,
Zi : time-invariant explanatory variables,
αi : unobserved heterogeneity term constant over time. E(αi)= 0, σ²α
εit: error term E(εit)= 0, σ²ε, uncorrelated with X, Z and α
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MethodologyHow to estimate the wage equation?
• Ordinary Least Square (OLS) bias since do not take into account the unobserved
heterogeneity term • Fixed effects model (FE)
unbiased estimators but inefficient since do not take into account time-invariant variables
• Random Generalised Least Square (GLS)
only if E(αi | Xit, Zi) = 0 (Hausman test)• Random Generalised Least Square with
instrumentation (IV/GLS)
unbiased and efficient estimators
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MethodologyWage equations
1. Fixed effects model:ln Wit - ln Wi . = β (Xit - Xi .)+ (εit - εi . )
where Wi . = (1/Ti) , Xi . = (1/Ti)
2. Computation of the mean individual residuals
3. Between effect model
If E(αi | Xit, Zi) 0 =>Instrumentation of Zi
Proper instruments: Xi. strongly correlated with the Zi but uncorrelated with αi
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
lnˆ... iii XWd
)(ˆ.. iiii Zd
iT
t itW1
iT
t itX1
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MethodologyWage equations
4. Computation of variances estimations to compute weights.
where σ²ε is the residual variance from the fixed effects model and σ²be the residual variance from the between regressions.
5. Estimation of the GLS equation
Yit – θi Yi . = (Xit – θi Xi .)β + (1- θi ) Zi γ + (εit - θi ε i .)
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
²²
1i
iT
²ˆ)/1()/1(²ˆ²ˆ1
N
iibe TN
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MethodologyHausman test
Distributed as a chi-squared with a degree of freedom equal to the number of instruments used minus the number of time-invariant instrumented variables.
If the test reject the null hypothesis, need to use new combination of instruments until the test accept the null hypothesis.
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
)ˆˆ())ˆ(ˆ)ˆ(ˆ()'ˆˆ(²~ 1
GLSwGLSwGLSwW
Null hypothesis: E(αi | Xit, Zi) = 0
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Average gender pay gap (1994 & 2001)Table 1: Average gender wage gap in European countries, 1994 and 2001 (euros)
1994 2001
Male Female Gap Male Female Gap
Belgium 12.00 10.05 16.2% 14.20 11.99 15.6%
Denmark 17.37 14.85 14.5% 20.57 17.25 16.1%
France 11.75 9.61 18.2% 11.71 9.86 15.8%
Germany 12.44 9.44 24.1% 13.59 10.53 22.5%
Ireland 9.59 6.87 28.4% 11.75 9.42 19.9%
Italy 7.49 6.35 15.3% 7.83 6.53 16.6%
The Netherlands 15.87 11.75 25.9% 15.54 12.51 19.5%
Spain 6.31 4.84 23.2% 7.02 5.39 23.2%
United-Kingdom 12.21 8.31 32.0% 14.62 10.83 25.9%
Source: European Community Household Panel (ECHP)
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EstimationVariables used
• Actual tenure <1 year of tenure, 1-5 years, 6-10 years (reference), 11-15 years, 16 years and more.
• potential experience & potential experience squared: =age-age when started first job - tenure
• Type of contract:- permanent employment (reference)- fixed-term, short-term contract, casual work with no contract
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
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EstimationVariables used
• Occupations - ISCO 1-DIGIT:1. Legislators senior officials & managers2. Professionals3. Technicians & associate professionals4. Clerks (reference)5. Service workers&shops & market sales workers6. Skilled agricultural&fishery workers7. Craft and related trades workers8. Plant & machine operators & assemblers9. Elementary occupation
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
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EstimationVariables used
• Industries - ISCO 1-DIGIT:1. Mining and quarrying (C)2. Manufacturing (D) (reference)3. Electricity, gas and water supply (E) (reference)4. Construction (F)5. Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods (G) 6. Hotels and restaurants (H)7. Transport, storage and communication (I)8. Financial intermediation (J)9. Real estate, renting and business activities (K)
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EstimationVariables used
• Enterprise’s size:Small size (1-99 employees) (reference)Medium size (100-500 employees)Large size (>500 employees)
• Level of education:Education low (ISCED 0-2)(reference)Education medium (ISCED 3)Education high (ISCED 5-7)
• Job status Supervisory Intermediate, Non-supervisory (reference)
A. Gangji, K. Orsini and S.Sissoko Why Are Inequalities so Unequal?
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OLS - PoolOLS - Wave1
OLS -Wave8Random
EffectFixed Effect GLS, IV
0,016 0.020 0.010 0.024 0.021 0.027(0,001)*** (0.003)*** (0.003)*** (0.001)*** (0.033) (0.002)***
-0,024 -0.032 -0.014 -0.035 -0.046 -0.039(0,002)*** (0.006)*** (0.006)** (0.003)*** (0.005)*** (0.003)***
-0,095 -0.102 -0.041 -0.080 -0.042 -0.062(0,010)*** (0.028)*** (0.034) (0.009)*** (0.010)*** (0.009)***
-0,051 -0.034 -0.026 -0.033 -0.001 -0.018(0,009)*** (0.025) (0.027) (0.008)*** (0.009) (0.008)**
0,048 0.044 0.084 0.037 -0.012 0.016(0,012)*** (0.037) (0.035)** (0.010)*** (0.011) (0.010)*
0,148 0.107 0.198 0.125 0.003 0.079(0,010)*** (0.025)*** (0.031)*** (0.012)*** (0.015) (0.012)***
0,235 0.173 0.252 0.114 0.048 0.079(0,011)*** (0.030)*** (0.028)*** (0.010)*** (0.010)*** (0.009)***
0,094 0.070 0.092 0.054 0.026 0.040(0,007)*** (0.020)*** (0.021)*** (0.006)*** (0.007)*** (0.006)***
-0,072 -0.088 -0.072 -0.037 -0.021 -0.029(0,008)*** (0.024)*** (0.023)*** (0.006)*** (0.007)*** (0.006)***
0,233 0.228 0.260 0.126 0.055 0.091(0,009)*** (0.025)*** (0.024)*** (0.009)*** (0.010)*** (0.009)***
0,172 0.190 0.176 0.100 0.047 0.073(0,006)*** (0.018)*** (0.018)*** (0.006)*** (0.007)*** (0.006)***
0,099 0.109 0.079 0.145 - 0.179(0,008)*** (0.024)*** (0.023)*** (0.013)*** - (0.019)***
0,199 0.200 0.210 0.314 - 0.361(0,010)*** (0.029)*** (0.028)*** (0.015)*** - (0.021)***
2,541 1,328 1,486 2,498 3,825 2,460(0,025)*** (0.048)*** (0.053)*** (0.032)*** (1.238)*** (0.064)***
Constant
Medium size enterprise
Large size enterprise
Education medium
Education high
Supervisory (status)
Intermediate (status)
Fixed contract(status)
Tenure 1-5 years
Tenure 11-15 years
Tenure >15 years
Males
Potential experience
Potential experience^2/100
Tenure <1 year
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men women men women men women men women men women0.023 0.018 0.032 0.025 0.028 0.019 0.041 0.023 0.054 0.029(0.003)*** (0.004)*** (0.003)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.004)*** (0.004)***
-0.034 -0.032 -0.060 -0.048 -0.040 -0.030 -0.081 -0.053 -0.109 -0.061(0.006)*** (0.008)*** (0.004)*** (0.005)*** (0.004)*** (0.005)*** (0.004)*** (0.004)*** (0.007)*** (0.008)***
-0.035 0.021 -0.039 -0.022 -0.074 -0.118 -0.027 -0.027 0.009 -0.043(0.016)** (0.018) (0.009)*** (0.012)* (0.010)*** (0.015)*** (0.009)*** (0.010)*** (0.014) (0.015)***
-0.018 -0.009 -0.035 -0.020 -0.028 -0.031 -0.002 -0.008 0.013 -0.033(0.011) (0.012) (0.007)*** (0.008)** (0.008)*** (0.011)*** (0.007) (0.009) (0.011) (0.012)***
0.027 0.036 -0.000 0.004 0.016 0.034 0.024 0.002 -0.025 0.011(0.013)** (0.016)** (0.009) (0.010) (0.008)* (0.013)*** (0.012)** (0.014) (0.015)* (0.016)
0.051 0.066 -0.011 -0.012 0.051 0.077 -0.015 0.022 0.032 -0.019(0.016)*** (0.024)*** (0.012) (0.015) (0.013)*** (0.018)*** (0.018) (0.024) (0.023) (0.026)
0.045 0.082 0.139 0.029 0.254 0.166 0.073 0.044 0.034 -0.017(0.018)** (0.029)*** (0.026)*** (0.030) (0.026)*** (0.033)*** (0.014)*** (0.013)*** (0.023) (0.023)
0.028 0.023 0.097 0.089 0.178 0.241 0.070 0.106 0.043 0.089(0.017)* (0.019) (0.024)*** (0.030)*** (0.028)*** (0.039)*** (0.014)*** (0.016)*** (0.027) (0.024)***
0.029 -0.001 0.093 0.053 0.087 0.070 0.057 0.032 0.028 0.044(0.015)** (0.015) (0.022)*** (0.019)*** (0.022)*** (0.020)*** (0.013)*** (0.012)*** (0.022) (0.016)***
-0.043 -0.028 -0.053 -0.025 -0.029 -0.140 -0.077 -0.124 -0.046 -0.099(0.022)** (0.018) (0.029)* (0.023) (0.027) (0.021)*** (0.018)*** (0.013)*** (0.025)* (0.020)***
-0.013 -0.072 0.020 -0.014 0.009 -0.137 0.022 -0.005 0.003 0.029(0.018) (0.035)** (0.023) (0.047) (0.022) (0.045)*** (0.014) (0.025) (0.023) (0.032)
0.005 0.009 -0.021 -0.072 0.006 -0.124 -0.006 -0.017 -0.023 0.028(0.018) (0.035) (0.023) (0.030)** (0.021) (0.027)*** (0.014) (0.020) (0.022) (0.022)
-0.022 -0.014 0.029 -0.137 -0.037 -0.204 -0.026 -0.064 -0.037 -0.029(0.018) (0.026) (0.024) (0.027)*** (0.025) (0.028)*** (0.017) (0.018)*** (0.023) (0.023)
0.057 0.035 -0.045 -0.036 0.064 0.181 0.083 0.092 0.010 -0.127(0.025)** (0.058) (0.037) (0.055) (0.052) (0.119) (0.023)*** (0.034)*** (0.035) (0.068)*
-0.044 0.012 0.034 -0.080 -0.075 -0.166 0.024 0.048 0.007 0.035(0.018)** (0.039) (0.018)* (0.037)** (0.019)*** (0.050)*** (0.018) (0.039) (0.017) (0.046)
-0.041 -0.061 -0.051 -0.069 -0.011 -0.046 -0.060 -0.044 -0.067 -0.012(0.016)** (0.017)*** (0.016)*** (0.019)*** (0.017) (0.019)** (0.011)*** (0.012)*** (0.016)*** (0.020)
-0.050 0.040 -0.066 -0.063 -0.096 -0.109 -0.165 -0.084 -0.152 -0.043(0.048) (0.033) (0.039)* (0.035)* (0.038)** (0.040)*** (0.024)*** (0.016)*** (0.042)*** (0.025)*
Sec G
Sec H
Occupation8
Occupation9
Sec CE
Sec F
Occupation2
Occupation3
Occupation5
Occupation7
Tenure 1-5 years
Tenure 11-15 years
Tenure >15 years
Occupation 1
Potential experience
Potential experience^2/100
Tenure <1 year
IrelandBelgium Denmark France UK
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men women men women men women men women men women-0.020 0.002 -0.008 -0.006 -0.010 0.033 -0.018 0.000 0.011 0.096(0.020) (0.034) (0.022) (0.034) (0.024) (0.047) (0.015) (0.019) (0.025) (0.034)***
0.057 0.020 -0.128 -0.025 0.132 0.120 0.144 0.077 0.080 0.094(0.026)** (0.028) (0.036)*** (0.030) (0.041)*** (0.035)*** (0.021)*** (0.018)*** (0.039)** (0.028)***
0.006 0.009 0.048 -0.009 -0.020 -0.004 0.025 0.049 0.015 0.045(0.017) (0.017) (0.017)*** (0.021) (0.017) (0.021) (0.012)** (0.013)*** (0.018) (0.019)**
0.068 0.083 0.018 0.061 0.034 0.011 0.057 0.054 0.049 0.078(0.013)*** (0.019)*** (0.008)** (0.012)*** (0.009)*** (0.016) (0.010)*** (0.012)*** (0.014)*** (0.016)***
0.023 0.021 0.010 0.014 0.021 0.013 0.034 0.036 0.026 0.026(0.010)** (0.012)* (0.008) (0.010) (0.007)*** (0.011) (0.007)*** (0.008)*** (0.011)** (0.012)**
-0.041 0.016 -0.068 -0.103 -0.016 -0.080 -0.012 -0.065 -0.064 0.006(0.017)** (0.017) (0.016)*** (0.018)*** (0.012) (0.017)*** (0.016) (0.019)*** (0.021)*** (0.021)
0.067 0.036 0.069 0.025 0.081 0.065 0.061 0.046 0.120 0.090(0.015)*** (0.017)** (0.013)*** (0.017) (0.014)*** (0.019)*** (0.010)*** (0.012)*** (0.014)*** (0.015)***
0.070 0.021 0.073 0.009 0.059 0.074 0.053 0.059 0.082 0.063(0.012)*** (0.014) (0.011)*** (0.014) (0.010)*** (0.014)*** (0.007)*** (0.008)*** (0.011)*** (0.012)***
0.149 0.133 0.071 0.090 0.132 0.062 0.139 0.134 0.160 0.217(0.025)*** (0.046)*** (0.046) (0.031)*** (0.025)*** (0.024)*** (0.036)*** (0.032)*** (0.085)* (0.073)***
0.384 0.348 0.277 0.246 0.366 0.258 0.322 0.249 0.403 0.436(0.029)*** (0.048)*** (0.060)*** (0.042)*** (0.027)*** (0.026)*** (0.029)*** (0.027)*** (0.111)*** (0.109)***
1,992 1,983 2,460 2,466 2,460 2,466 2,460 2,466 2,460 2,466(0.040)*** (0.061)*** (0.064)*** (0.048)*** (0.064)*** (0.036)*** (0.064)*** (0.034)*** (0.064)*** (0.094)***
Observations 4260 2966 5299 2953 11756 7475 10718 8672 5524 4028
R² 1133 - 1238 - 2517 - 2248 - 1493 -
R² - - - - - - - - - -
var a - - - - - - - - - -
var e - - - - - - - - - -
Hausman test 2,53 0,03 0,26 0,33 4,20 9,12 1,95 7,84 1,51 0,21
p-value 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00
IrelandBelgium Denmark France UK
Constant
Medium size enterprise
Large size enterprise
Education medium
Education high
Sec K
Supervisory (status)
Intermediate (status)
Fixed contract (status)
Sec I
Sec J
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men women men women men women men women0.027 0.031 0.044 0.031 0.027 0.022 0.047 0.022(0.002)*** (0.003)*** (0.004)*** (0.004)*** (0.002)*** (0.002)*** (0.003)*** (0.006)***
-0.039 -0.056 -0.072 -0.059 -0.042 -0.038 -0.088 -0.083(0.003)*** (0.006)*** (0.006)*** (0.007)*** (0.004)*** (0.005)*** (0.004)*** (0.005)***
-0.062 -0.060 -0.014 -0.050 -0.010 -0.002 -0.044 -0.045(0.009)*** (0.013)*** (0.014) (0.014)*** (0.008) (0.011) (0.010)*** (0.013)***
-0.018 -0.021 0.009 -0.028 0.002 -0.016 -0.006 -0.020(0.008)** (0.011)** (0.010) (0.010)*** (0.006) (0.008)* (0.005) (0.007)***
0.016 -0.003 -0.014 -0.012 0.006 0.016 -0.004 -0.005(0.010)* (0.014) (0.012) (0.013) (0.007) (0.010) (0.008) (0.010)
0.079 0.032 -0.038 -0.063 -0.006 0.031 -0.009 0.022(0.012)*** (0.023) (0.019)** (0.023)*** (0.010) (0.014)** (0.011) (0.016)
0.130 0.141 -0.031 0.039 0.069 -0.019 0.049 0.076(0.018)*** (0.035)*** (0.018)* (0.019)** (0.017)*** (0.046) (0.016)*** (0.022)***
0.117 0.148 -0.010 0.037 0.019 0.029 0.044 -0.018(0.017)*** (0.021)*** (0.018) (0.019)** (0.017) (0.024) (0.016)*** (0.023)
0.024 0.016 -0.037 0.022 0.024 -0.021 0.025 -0.012(0.012)** (0.012) (0.016)** (0.012)* (0.010)** (0.018) (0.013)* (0.011)
-0.033 -0.071 -0.052 -0.030 -0.004 -0.066 -0.064 -0.072(0.016)** (0.016)*** (0.023)** (0.016)* (0.013) (0.016)*** (0.020)*** (0.016)***
-0.026 -0.040 -0.040 -0.014 -0.021 -0.078 0.015 0.005(0.013)* (0.022)* (0.021)* (0.036) (0.011)* (0.017)*** (0.014) (0.021)
-0.025 -0.049 -0.087 -0.005 -0.009 -0.096 0.047 0.044(0.014)* (0.024)** (0.022)*** (0.029) (0.012) (0.019)*** (0.015)*** (0.021)**
-0.070 -0.035 -0.029 -0.029 -0.009 -0.065 0.004 -0.004(0.014)*** (0.018)* (0.024) (0.025) (0.012) (0.016)*** (0.016) (0.021)
0.043 0.150 0.671 0.031 -0.046 -0.087 0.021 0.007(0.019)** (0.073)** (0.150)*** (0.150) (0.017)*** (0.034)** (0.023) (0.063)
-0.007 -0.034 -0.033 -0.093 -0.005 0.091 0.028 0.027(0.010) (0.033) (0.023) (0.036)*** (0.011) (0.033)*** (0.010)*** (0.026)
-0.045 0.003 0.010 -0.022 -0.012 0.007 -0.017 0.001(0.010)*** (0.014) (0.017) (0.019) (0.010) (0.013) (0.010)* (0.013)
-0.066 0.032 0.021 -0.120 -0.098 -0.007 -0.183 -0.111(0.020)*** (0.021) (0.046) (0.036)*** (0.025)*** (0.020) (0.031)*** (0.027)***
Tenure >15 years
Tenure 11-15 years
Tenure 1-5 years
Tenure <1 year
Occupation3
Occupation2
Occupation 1
Sec CE
Sec F
Sec G
Sec H
Occupation5
Occupation7
Occupation8
Occupation9
Germany
Potential experience^2/100
Potential experience
Spain NLD Italy
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men women men women men women men women-0.018 0.038 -0.041 0.026 -0.002 0.010 -0.014 0.010(0.014) (0.027) (0.024)* (0.030) (0.013) (0.031) (0.016) (0.029)
0.228 0.009 -0.025 0.004 0.031 0.049 0.083 0.053(0.029)*** (0.036) (0.032) (0.028) (0.021) (0.024)** (0.030)*** (0.032)*
-0.007 0.017 0.004 -0.032 -0.033 0.024 -0.029 -0.047(0.014) (0.015) (0.018) (0.018)* (0.012)*** (0.013)* (0.014)** (0.016)***
0.079 0.070 0.038 0.017 - - - -(0.009)*** (0.016)*** (0.013)*** (0.019) - - - -
0.040 0.043 0.013 0.031 - - - -(0.006)*** (0.010)*** (0.010) (0.012)*** - - - -
-0.029 -0.013 -0.013 -0.046 -0.002 -0.013 -0.016 0.008(0.006)*** (0.009) (0.024) (0.019)** (0.009) (0.012) (0.009)* (0.013)
0.091 0.066 0.017 0.025 0.073 0.083 0.104 0.080(0.009)*** (0.013)*** (0.014) (0.014)* (0.008)*** (0.013)*** (0.010)*** (0.014)***
0.073 0.058 0.040 -0.000 0.031 0.066 0.079 0.042(0.006)*** (0.010)*** (0.012)*** (0.012) (0.006)*** (0.009)*** (0.007)*** (0.010)***
0.179 0.201 -0.006 0.018 0.165 0.138 0.100 0.098(0.019)*** (0.044)*** (0.121) (0.114) (0.025)*** (0.019)*** (0.064) (0.147)
0.361 0.376 0.335 0.246 0.468 0.335 0.403 0.258(0.021)*** (0.047)*** (0.243) (0.199) (0.049)*** (0.040)*** (0.085)*** (0.229)
2,460 2,466 2,460 2,466 2,460 2,466 2,460 2,466(0.064)*** (0.048)*** (0.064)*** (0.075)*** (0.064)*** (0.029)*** (0.064)*** (0.171)***
Observations 13885 6618 11443 6422 4260 6173 15755 9141
R² 3373 - 2691 - 1133 - 3453 -
R² - - - - - - - -
var a - - - - - - - -
var e - - - - - - - -
Hausman test 14,20 0,62 0,50 0,21 0,53 2,35 1,73 5,55
p-value 0,96 1,00 1,00 1,00 1,00 1,00 1,00 1,00
GermanySpain NLD Italy
Education medium
Education high
Constant
Intermediate (status)
Fixed contract (status)
Medium size enterprise
Large size enterprise
Sec I
Sec J
Sec K
Supervisory (status)
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Results Strong positive effect of education upon wage
BE, SP, UK: men better remuneratedFR, GE, IT: women better remunerated for an upper
secondary education, IRL: women better remunerated for tertiary
educationDK: women better remunerated
Positive influence of experience: concave relation
For all countries, except Spain, the return of experience is larger for men.
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Results An additional year of experience leads to from
about 1.5% higher wage in Belgium, Denmark, France and Spain to 2.1-2.6% in Germany, Ireland, the Netherlands and UK
Wage increases with level of tenure. The variables relative to job status (supervisory),
size of the company and type of contract show, when significant, a positive relation between wage and degree of supervision of an employee, the size of firm or the permanent nature of an employment contract. .
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Conclusion
Controlling for individual heterogeneity, we observe an increase of the male-female differential, the rates of the return of experience and education as well as a reduction of penalty due to low tenure, low skilled occupations, fixed employment contract and relatively small enterprise size.