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					Decomposing Gender Wage Gaps
across the Distribution in Britain:
 Including Allowance for Sample
      Selection Adjustment
            Yekaterina Chzhen

 “Beyond Social Inclusion: Towards a More Equal
                    Society?”
       Loughborough, 23 January 2009
Outline

 Research aims
 Data

 Unadjusted gender wage gaps

 Variables

 Methods

 Descriptive statistics

 Decomposition analysis

 Conclusion
Research Aims

   Investigate differences between the log wage
    distributions of men and women working full-time in
    Britain, separately by sector
       „Glass ceiling effect‟
       „Sticky floors effect‟


   Decompose the wage gap into the part due to
    differences in characteristics and the part due
    differences in the returns to these characteristics

   Explore the contribution of women‟s self-selection
    into full-time employment to the gender wage gap
Data
   British Household Panel Survey (1991-2005) Wave 15
   Sample:
       Individuals aged 25-55
       Women and full-time men
       Excluding
            Self-employed men and women
            Those with missing observations on weekly hours
            Those working more than 75 hours a week
            Those earning less than £1/hour or £100/hour (gross)
            Those with missing observation on key variables
   Sample size:
       1,747 full-time men
            Public sector: 22%
            Private sector: 78%
       1,283 full-time women
            Public sector: 49%
            Private sector: 51%
       665 part-time women
       528 non-participating women
Mean wage gaps

Combined sample
                                 Full-time men      Full-time women       Part-time women
                                     13.50                 11.48                 8.88
 Hourly wage
                                     (8.02)                (7.40)               (5.79)
                                      2.47     0.16         2.31                 2.04
 Log hourly wage
                                     (0.50)                (0.49)               (0.51)
                                                         0.43


By sector
                             Public sector                         Private sector
                       Men                Women              Men               Women
 Wage              14.30 (7.16)         12.67 (8.10)     13.28 (8.23)        10.33 (6.47)
 Log wage           2.56 (0.45) 0.14    2.42 (0.47)      2.45 (0.51)    0.25 2.20 (0.49)
          Differences in wage distributions: full-time
          men and full-time women

           .8
           .6
density



           .4
           .2
            0




                0    1     2              3             4   5
                               log wage

                           males              females
          Differences in wage distributions: full-time
          men and all employed women

           .8
           .6
density



           .4
           .2
            0




                0   1      2              3             4   5
                               log wage

                           males              females
          Differences in wage distributions: full-time
          men and women by sector

            1               public                             private
density



           .5
            0




                0   1   2            3   4       5   0   1     2     3   4   5
                                             log wage
                                         males           females
               Unadjusted wage gap across distribution

                .6
                .4
log wage gap




                .2
                      0
                -.2




                          0   .2   .4              .6   .8   1
                                        quantile
               Unadjusted wage gap across distribution:
               public sector

                .6
                .4
log wage gap




                .2
                      0
                -.2




                          0   .2   .4              .6   .8   1
                                        quantile
               Unadjusted wage gap across distribution:
               private sector

                .6
                .4
log wage gap




                .2
                      0
                -.2




                          0   .2   .4              .6   .8   1
                                        quantile
Variables

   Human capital
         Years of actual work experience
         Highest level of education
         Age
                                   Public sector                   Private sector
                               Men             Women           Men               Women

Work experience (years)   13.33 (6.02)     11.73 (5.84)   12.87 (5.89)      11.50 (5.61)
Age                       40.98 (7.98)     40.83 (8.49)   39.69 (8.31)      39.07 (8.63)
Highest level of
education
--Degree                     0.36             0.42           0.19              0.16
--Other higher               0.41             0.35           0.42              0.37
--A-levels                   0.08             0.07           0.11              0.13
--O-levels                   0.09             0.12           0.16              0.19
--Other                      0.03             0.04           0.06              0.07
--None                       0.02             0.01           0.06              0.07
Variables

   Family characteristics
        Marital status
        Children under 16 present
        Age of youngest child
   Attitude
        Disagrees that “family suffers if mother works full-time”
                                   Public sector                 Private sector
                             Men                   Women     Men               Women
Married                    0.62                    0.53    0.63                0.51
Disagree that family
suffers if mother works    0.42                    0.53    0.39              0.55
full-time
Child(ren) present         0.45                    0.35    0.45              0.30
Age of youngest child in
household
--5 years or younger       0.47                    0.29    0.52              0.34
--6-11 years               0.38                    0.42    0.29              0.31
--12-15 years              0.15                    0.29    0.19              0.34
Variables
   Workplace characteristics
       Supervisory duties
       Size of firm (under 25; 25-199; 200+)
       Occupational category (9 major ISCO categories)
                                  Public sector                 Private sector
                            Men                   Women     Men               Women
Managerial duties         0.49                    0.45    0.46                 0.45
Size of firm
--Under 25                0.18                    0.23    0.29              0.36
--25-199                  0.39                    0.46    0.37              0.36
--200 or over             0.43                    0.32    0.33              0.28
Occupational category
--Managers                0.12                    0.08    0.24              0.21
--Professionals           0.24                    0.29    0.11              0.07
--Technicians and
                          0.29                    0.24    0.12              0.13
Associate Professionals
--Admin/Secretarial       0.11                    0.23    0.03              0.23
--Skilled Trades          0.08                    0.01    0.20              0.04
--Personal Services       0.04                    0.13    0.01              0.08
--Sales and Customer
                          0.00                    0.00    0.03              0.12
Services
--Operatives              0.03                    0.00    0.17              0.06
--Elementary              0.08                    0.03    0.09              0.05
Methods

   Quantile regression (Koenker & Bassett, 1978)
       wi = xi΄βθ + uθi with Quantθ(wi|xi) = xi΄βθ   i=(1,…, n)

   Wage gap decomposition (Machado & Mata, 2005)
       Portion of the gap due to differences in characteristics and
        the portion due to differences in returns

   Simulating selection-corrected distribution of
    women‟s wages and correcting for sample selection
    into full-time work by women (Albrecht et al, 2007)
Descriptive statistics: full sample
Definitions                          Full-time men   Full-time women   Part-time women   Not working women
(1)                                         (2)               (3)              (4)               (5)
                                         13.50              11.48             8.88
Hourly wage                                                                                      -
                                         (8.02)             (7.40)           (5.79)
                                          2.47               2.31             2.04
Log hourly wage                                                                                  -
                                         (0.50)             (0.49)           (0.51)
                                        156.61             139.33           127.17             46.28
Work experience
                                        (71.05)           (68.69)           (63.90)           (75.51)
                                         13.05              11.61            10.60              3.86
Work experience (years)
                                         (5.92)             (5.72)           (5.33)            (6.29)
                                         39.97              39.94            40.83             40.48
Age
                                         (8.26)             (8.61)           (7.79)            (8.99)
Highest level of education
--Degree                                 0.23             0.29              0.16               0.15
--Other higher                           0.42             0.36              0.37               0.23
--A-levels                               0.10             0.10              0.11               0.13
--O-levels                               0.15             0.15              0.19               0.21
--Other                                  0.05             0.05              0.07               0.11
--None                                   0.05             0.04              0.08               0.18
Married                                  0.63             0.52              0.76               0.62
Disagree that family suffers if
                                         0.40             0.54              0.33               0.30
mother works full-time
Child(ren) present                       0.45             0.33              0.70               0.63
Age of youngest child in household
--5 years or younger                     0.51             0.31              0.45               0.58
--6-11 years                             0.31             0.37              0.35               0.29
--12-15 years                            0.18             0.32              0.20               0.12
Region
--South                                  0.29             0.27              0.30               0.30
--London                                 0.08             0.10              0.07               0.09
--East Midlands                          0.23             0.21              0.24               0.24
--North                                  0.25             0.26              0.27               0.26
--Wales                                  0.05             0.05              0.05               0.03
--Scotland                               0.09             0.11              0.08               0.08
               Log wage gap between full-time men and women paid like men




Public sector                                                                        Private sector




                                                                                        .4
 .4




                                                                                        .2
 .2




                                                                      log wage gap




                                                                                             0
       0




                                                                                       -.2
 -.2




                                                                                       -.4
 -.4




           0   .1   .2   .3   .4     .5       .6   .7   .8   .9   1                              0   .1   .2   .3   .4     .5       .6   .7   .8   .9   1
                                   quantile                                                                              quantile
Determinants of working full-time

   Women are more likely to work full-time if they:
     Have more years of work experience
     Have higher education qualifications

     Disagree with the statement “family suffers if
      mother works full-time”
     Live in Wales or Scotland

   Women are less likely to work full-time if they:
     Are married
     Have dependent children

     Are older
Determinants of working full-time:
public sector

                                                              Public sector
                                                   Probit (1)             Single Index (2)
                                           B           SE              B             SE
Constant                                   -0.47       0.30            -0.47         -
Work experience (years)                     0.20***    0.02            0.20          -
Work experience squared (x 100)            -5.30***    0.00            -2.65***      0.00
Age                                        -0.03***    0.01            -0.02***      0.00
Married                                    -0.24**     0.08            -0.12***      0.02
Positive working mother attitude.           0.36**     0.11            0.31***       0.03
Child(ren) present                         -1.06***    0.11            -0.53***      0.05
Interaction between positive working                   0.16
                                            0.25                       0.12*         0.05
mother attitude and presence of children
Highest level of education (ref: none)
   Degree                                  1.37***     0.19           0.69***       0.09
   Other higher                            1.00***     0.19           0.50***       0.09
   A-levels                                0.74***     0.21           0.26*         0.10
   O-levels                                0.59**      0.20           0.29**        0.10
   Other                                   0.47        0.25           0.26**        0.10

Number of observations                     1509        1509           1509          1509
Determinants of working full-time:
private sector

                                                              Private sector
                                                   Probit (1)             Single Index (2)
                                           B           SE              B             SE
Constant                                    0.11       0.27            0.11          -
Work experience (years)                     0.21***    0.02            0.21          -
Work experience squared (x 100)            -5.69***    0.00            -1.43***      0.00
Age                                        -0.03***    0.01            -0.01***      0.00
Married                                    -0.30***    0.08            -0.07**       0.03
Positive working mother attitude.           0.32**     0.11            0.09**        0.03
Child(ren) present                         -0.97***    0.11            -0.26***      0.04
Interaction between positive working
                                           0.12        0.15           0.02          0.05
mother attitude and presence of children
Highest level of education (ref: none)
   Degree                                  0.56***     0.16           0.14*         0.06
   Other higher                            0.36*       0.14           0.13*         0.05
   A-levels                                0.36*       0.16           0.12*         0.06
   O-levels                                0.23        0.15           0.04          0.05
   Other                                   0.09        0.18           0.02          0.06

Number of observations                     1495        1495           1495          1495
                    Sample selection based on observed characteristics




Public sector                                                                         Private sector
  .3




                                                                                       .3
  .2




                                                                                       .2
  .1




                                                                                       .1
                                                                       log wage gap
       0




                                                                                             0
                                                                                       -.1
 -.1




                                                                                       -.2
 -.2




                                                                                       -.3
 -.3




                                                                                       -.4
 -.4




           0   .1    .2   .3   .4     .5       .6   .7   .8   .9   1                             0   .1   .2   .3   .4     .5       .6   .7   .8   .9   1
                                    quantile                                                                             quantile
                    Sample selection based on unobserved characteristics




Public sector                                                                         Private sector
  .6




                                                                                      .6
  .4




                                                                                      .4
                                                                       log wage gap
  .2




                                                                                      .2
       0




                                                                                            0
                                                                                      -.2
 -.2




           0   .1    .2   .3   .4     .5       .6   .7   .8   .9   1                            0   .1   .2   .3   .4     .5       .6   .7   .8   .9   1
                                    quantile                                                                            quantile
                Log wage gap between full-time men’s wages and the wages that
                women would earn if they had men’s characteristics and women’s
                (selection adjusted) returns




Public sector                                                                    Private sector
 .35




                                                                                  .35
   .3




                                                                                    .3
 .25




                                                                                  .25
                                                                  log wage gap
   .2




                                                                                    .2
 .15




                                                                                  .15
   .1




                                                                                    .1
 .05




                                                                                  .05
       0




                                                                                        0


           0   .1   .2   .3   .4      .5      .6   .7   .8   .9                             0   .1   .2   .3   .4      .5      .6   .7   .8   .9
                                   quantile                                                                         quantile
Conclusion

   Larger unadjusted gaps at the top of the distribution:
    evidence of a glass ceiling effect in both sectors
   Most of the full-time wage gap is due to differences
    in returns to labour market characteristics between
    men and women
   Full-time women in both sectors have a higher
    earnings potential than part-time and non-
    participating women
       If all women worked full-time, the wage gap would be
        larger
       In the private sector, self-selection based on observed
        characteristics is most visible amongst higher earners
Literature cited

   Albrecht, J. van Vuuren, A. and Vroman, S. (2007).
    “Counterfactual Distributions with Sample Selection
    Adjustments: Econometric Theory and Application to the
    Netherlands.” Mimeo, Georgetown University

   Buchinsky, M. (1998). “The Dynamics of Change in the
    Female Wage Distribution in the USA: A Quantile
    Regression Approach.” Journal of Applied Econometrics
    13; 1-30

   Koenker, R. and Bassett, G. (1978). “Regression
    Quantiles.” Econometrica 46; 33-50

   Machado, J.A. and Mata, J. (2005).“Counterfactual
    Decomposition of Changes in Wage Distributions using
    Quantile Regression.” Journal of Applied Econometrics 20;
    445-465
Thank you!

   Contact details:
       yc535@york.ac.uk

				
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