Transcript Introducing The *Class* Ceiling

The Class Ceiling
Social Origin Pay Gaps
in the Higher Professional and
Managerial Occupations
Daniel Laurison
Based in part on “The Class Pay Gap in Higher Managerial and Professional
Occupations” by Daniel Laurison and Sam Friedman, accepted for publication in
American Sociological Review
1
Social Class Mobility
2
What is Class position?
No two social scientists agree!
• Relation to the means of production
(Marx)
• Education (various Social Sciences)
• Income (Economists)
• “Big-Class” (dominant Sociologists)
• “Micro-Class” (challenger Sociologists)
• Social Space (Bourdieu)
3
The Big Classes (EGP/NS-SEC )
1: Higher managerial, administrative and professional occupations:
CEO, Professor, Stock Broker, Doctor, Military Officer
2: Lower managerial, administrative, and professional occupations:
Teacher, Nurse, Store Manager, IT consultant
3: Intermediate Occupations: Bookkeeper, Secretary, Teaching Assistant
4: Self-Employed: frequently Plumbers, Carpenters, Hairdressers, Taxi Drivers
5: Lower Supervisory and Technical: Chef, Electrician, Communication Operator
6: Semi-Routine Occupations: Sales & Retail Assistant, Care Worker, Landscaper
7: Routine Occupations: Carpenter, Cleaner, Truck or Bus Driver
8: Never worked or long-term unemployed
4
Reproduction of Privilege
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
In whole UK
In Higher Management or
Professions
Higher Managerial or Professional Parent
Lower Managerial or Professional Parent
Intermediate, Self-Employed, or Technical/Supervisory Parent
Semi-Routine or Routine Occupation, or No Earner Parent
5
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Over-Representation of the Privileged
in Top Jobs
Semi-Routine or
Intermediate, Self- Lower Managerial or Higher Managerial or
Routine Occupation,
Employed, or
Professional Parent Professional Parent
or No Earner Parent Technical/Supervisory
Parent
6
Problems with Mobility
Studies
• Ignores resources beyond single-variable measure
of class position
• Dominant focus on mobility rates between big
“classes,” on access to top jobs.
• Might miss potentially important differences
between or within specific high-status
occupational groups
7
Data and Approach
2014 UK Labour Force Survey: Nationally representative, Government data
Class Origin Question: What was the occupation of the main
income earner in your household when you were 14 years old?
Destination: Only those in elite occupations (NS-SEC 1/EGP 1)
Higher managerial, administrative and professional occupations
Excluded respondents: in full-time education, not aged 23-69, no parental
occupation data
 43,444 respondents
6,104 in NS-SEC 1-categorized elite occupations
3,510 with income, origin, AND occupation data
8
Social Mobility into Elite Occupations
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Long-Range Mobile
Mid-Range Mobile
Short-Range Mobile
Intergenerationally Stable
9
[email protected]; [email protected]
“Micro-Class” Over-Representation
25
20
15
10
5
0
Micro-Stable
NS-SEC 1 Origins
Gender &
Race/Ethnicity
in the
Workplace
Exclusion
Tokenism
Glass Ceilings
Pay/Earnings gaps
11
Main Research Question:
A Class Ceiling?
Do the upwardly mobile face a “class
ceiling” in terms of earnings within higher
professional and managerial occupations?
12
The Class Pay Gap
(Mean Logged Weekly Earnings in NS-SEC 1 by Social Origin)
6.8
6.7
6.6
6.5
6.4
6.3
6.2
6.1
NS-SEC 1
NS-SEC 2
NS-SEC 3
Parents (Higher Parents (Lower
Parents
Mgrs & Profs) Mgrs & Profs) (Intermediate
Occs)
NS-SEC 4
NS-SEC 5
NS-SEC 6
NS-SEC 7
Parents (Self- Parents (Lower Parents (SemiParents
employed)
Supervisory & Routine Occs) (Routine Occs)
Tech)
[email protected]
NS-SEC 8
Parents (No
Earner in
Household)
Models for Earnings Differences
Dependent Variable: Logged Weekly earnings (in £) (also untransformed weekly earnings & also
untransformed hourly earnings)
I. Demographic & Hours Worked: Age (in years); Age squared; Female; Not White; Country of
Birth: reference=England, vs outside the UK, Northern Ireland, Scotland, Wales.
II. Educational Qualifications. Degree: reference= University Degree vs PhD, MA, Post-Grad Ed
Cert, Other Post-Grad, Higher Ed, A-Levels, GCSEs, Other Qualifications, No Qualifications;
Degree Class: reference= 2:2/Lower 2nd Class, vs N/A (e.g. no degree, foreign degree), Pass, Third
Class, 2:1/Higher Second Class, 1st Class.
III. “Human Capital”: Job-Related Training last 3 months (binary); Job Tenure (in years); Past
Health Problems (scale 0-2); Current Health Problems (scale 0-4).
IV. Work Context: Public sector (vs private); Industry: reference=Public admin, vs Education &
Health, Agriculture, Forestry & Fishing, Energy & Water, Manufacturing, Construction,
Distribution, Hotels & Restaurant, Transport & Communication, Banking & Finance, Other
services; Firm Size, reference= less than 25 employees, vs 25 to 49, 50 to 499, 500 or more; Work
region Professionals (vs Managers).
V. Specific Occupation: Specific SOC 2010 code (I let Stata choose the reference category)
Origin Earnings Gaps Net of Controls
MODEL I
MODEL II
MODEL III MODEL IV MODEL V
ONLY
DEMO-
ADDING
GRAPHIC
ADDING
HUMAN
CONTROLS EDUCATION CAPITAL
Origins (vs NS-SEC 1 Parents)
NS-SEC 2 (Lower Mgrs & Profs) 0.929**
0.946*
NS-SEC 3 (Intermediate Occs) 0.880*** 0.916**
NS-SEC 4 (Self-employed) 0.833*** 0.872***
NS-SEC 5 (Lower Supervisory & Tech) 0.872*** 0.911**
NS-SEC 6 (Semi-Routine Occs) 0.818*** 0.878***
NS-SEC 7 (Routine Occs) 0.792*** 0.848***
NS-SEC 8 (No Earner in Household) 0.834*** 0.886*
0.947*
ADDING
WORK
CONTEXT
0.955*
0.913*** 0.932**
ADDING
SPECIFIC
OCCUPATIONS
0.974
0.947*
0.870*** 0.899*** 0.917**
0.907**
0.916**
0.937*
0.874*** 0.891*** 0.911**
0.845*** 0.867*** 0.883***
0.889*
0.881**
0.897*
More Earnings Coefficients for Class Origin
LOGGED WEEKLY EARNINGS
NS-SEC 1 (ALL) NS-SEC 1.1
Short-range Mobile -0.039
NS-SEC 1.2
-0.013
-0.047
Mid-range Mobile -0.080***
-0.077
-0.081***
Long-range Mobile -0.127***
-0.108*
-0.135***
Weekly Gross Earnings (untransformed GBP)
Short-range Mobile (NS-SEC 2 parents) -40.19
-11.81
-50.75*
Mid-range Mobile (NS-SEC 3, 4, 5) -87.33***
-81.65*
-86.81***
Long-range Mobile (NS-SEC 6 & 7) -115.38***
-110.99*
-117.45***
Hourly Gross Earnings £
Short-range Mobile -1.118
-1.368
-1.072
Mid-range Mobile -2.243***
-2.329
-2.112***
Long-range Mobile -3.495***
-2.98
-3.308***
798
2421
N 3219
Blinder-Oaxaca Decomposition
LOGGED EXPONENTIATED
VALUES
VALUES
P>T
NS-SEC 1 origins
6.729
£ 836.4
0.00
NS-SEC 3 to 8 origins
6.582
£ 721.8
0.00
Difference
0.147
115.9%
0.00
“Explained”
0.068
107.0%
44%
0.00
“Unexplained”
0.080
108.3%
56%
0.00
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Blinder-Oaxaca Decomposition continued
CONTRIBUTION
TO THE PAY GAP
Base Model Controls
Age & Age Squared
Female
Not White
Country of Birth
Quarter Responded to Survey
Paid Hours Worked
-0.0351
-0.0049
0.0002
-0.0012
0.0010
0.0032
0.0698
-0.0036
0.00
0.07
0.70
0.59
0.36
0.64
47.4%
-2.4%
0.00
0.32
-5.3%
0.0011
-0.0001
-0.0087
0.0019
Work Context
Region of Work
Industry
Public Sector
Firm Size
Specific Occupation
-23.8%
-3.4%
0.2%
-0.8%
0.7%
2.2%
45.0%
Human Capital
Current Health Problems Scale
Past Health Problems Scale
Job Tenure in Years
Job-Related training last 3 months
P>T
-25.0%
Education
Educational Qualifications
Degree Classification
% OF DIFFERENCE
EXPLAINED
0.7%
-0.1%
-5.9%
1.3%
0.26
0.81
0.00
0.16
31.2%
0.0222
-0.0039
-0.0065
0.0142
0.0182
15.1%
-2.7%
-4.4%
9.6%
12.3%
0.00
0.23
0.03
0.00
0.02
Separate Models by Age Group
NS-SEC 2 Origins
NS-SEC 3-5 Origins
NS-SEC 6-8 Origins
.6
.8
1
23 to 29 year olds
30 to 39 year olds
40 to 49 year olds
50 to 59 year olds
60 to 69 year olds
[email protected]
1.2
1.4
Separate Models by Ethnic Group
Short-RangeNS-SEC
Mobile2 Origins
Mid-Range
Mobile
3-5 Origins
NS-SEC
Long-RangeNS-SEC
Mobile6-8 Origins
.6
.8
1
Ethnic Minorities
Whites
1.2
Separate Models by Gender
Short-RangeNS-SEC
Mobile2 Origins
Mid-Range
Mobile
NS-SEC
3-5 Origins
Long-RangeNS-SEC
Mobile6-8 Origins
.8
.9
1
Women
Men
1.1
Double Disadvantage
for Working Class-Origin Women
£50,000
£40,000
£30,000
£20,000
£10,000
£0
Women
Men
Long-Range Mobile
Mid-Range Mobile
Short-Range Mobile
Intergenerationally Stable
Class Earnings Gaps by Occupational Group
(NS-SEC 3-8 vs Stable)
Base model
All Controls
Lawyers
Lawyers
Finance
Finance
Lawyers
Public
Sector
Public
Sector
Doctors
Doctors
Public Sector
Mgrs & Dirs
Business
Mgrs &inDirs
in Business
Mgrs & Dirs in Business
IT Professionals
IT Professionals
IT Professionals
Protective
Civil Servants
Protective
Civil Servants
Accountants
Accountants
Protective Civil Servants
Business
Professionals
Business
Professionals
Other Life
Other Science
Life Science
Business Professionals
Engineers
Engineers
Other Professionals
Other Professionals
Engineers
Finance
Doctors
Accountants
Other Life Science
Other Professionals
Academics
Academics
Built Environment
Built Environment
Built Environment
Scientists
Scientists
Scientists
Academics
.6.6
.8
.8 1
1.21
1.4
[email protected]
1.2
.6
.8
1.4 1
1.2
1.4
[email protected]; [email protected]
Large Private Firms in Inner London
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
500+ Private firms in
Inner London
Other firms in Inner
London
long-range mobile
mid-range mobile
500+ Private Firms
Other UK
Other Firms Other UK
short-range mobile
all NS-SEC 1
intergenerationally stable
[email protected]; [email protected]
Large London Firms’ Pay Gaps (no controls)
£1,800
£1,600
£1,400
£1,200
£1,000
£800
£600
£400
£200
£0
500+ Private firms in Inner Other firms in Inner London 500+ Private Firms Other UK
London
Intergenerationally Stable
NS-SEC 3-8 Origins
Other Firms Other UK
[email protected]; [email protected]
Pay Gaps Net of Controls, Income
Percentile in NS-SEC 1 in Region
500+ Private Firms, Inner London, Base
500+ Private Firms, Inner London, Full
Other Firms, Inner London, Base
Other Firms, Inner London, Full
500+ Private Firms, Other UK, Base
500+ Private Firms, Other UK, Full
Other Firms, Other UK, Base
Other Firms, Other UK, Full
-20
-15
-10
-5
0
5
The Rest of the Gap?
• More sorting within occupations
• Cultural Capital
– Legitimate or “posh” hobbies, accent, style
– Private schooling & elite university attendance
• Social Capital
– Who you know
– “Microclass” effects
• Discrimination/Stigma/Homophily
• Aspirations & behavior
27
Summary of Key Findings
Beyond “access” upwardly
mobile face a powerful class
ceiling, earning 10 – 20% less.
Class-origin differences larger for men,
but women face double disadvantage.
Education & Sorting effects explain big part of pay gap.
60% of differences “unexplained.”
28
Implications for Class and Mobility Studies
– Importing feminist concept of
“glass ceiling” provides tools for
interrogating hidden class barriers
within occupations
– Focus on access fails to capture
stickiness of class origin
– Class position is best captured by
multiple measures, not any single
variable
29
Thank you!
30