www.skope.ox.ac.uk

‘Have earnings polarised in the UK?

Craig HolmesPembroke College, Oxford University and SKOPE

ISER, University of Essex, October 21st 2013

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Outline

• Background on the hourglass labour market• Polarisation and earnings distributions – some theory• Methodology – earnings distribution decomposition• Data• Decomposition results• Discussion and future work

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Background

• Routinisation hypothesis (Autor, Levy and Murnane, 2003):– Refinement of SBTC - technology related to tasks, not skills– Routine tasks substitutable for computer capital– Growth in non-routine jobs, decline in routine jobs

• Polarization hypothesis (Goos and Manning, 2007)– Routine occupations found in middle of income distribution– Non-routine occupations found at top and bottom of distribution– Ranking of jobs based on initial wages

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Background

• Goos and Manning (2007) – 1979-1999:

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Background

• Similar results observed in:– US (Autor, Katz and Kearney, 2006; Caranci and Jones, 2011) – Germany (Spitz-Oener, 2006; Oesch and Rodríguez Menés, 2011)– Spain and Switzerland (Oesch and Rodríguez Menés, 2011) – Across Europe (Goos, Manning and Salomons, 2009)

• Other explanations have been put forward:– Offshoring– Growing wage inequality and demand for services

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Background• Wage inequality in the UK has risen since the 1980s

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Background• Earnings growth by percentile, UK

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

1987-2001

1994-2007

Percentile

Real

ear

ning

s gro

wth

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Background

• More high-wage and low-wage jobs More inequality

Year Jobs earning below 2/3 * median hourly

wage

Jobs earning above 1.5* median hourly

wageInitial (1987) 20.2% 23.4%Final (2001) 23.0% 25.6%Initial (1994) 22.6% 25.2%Final (2007) 21.3% 25.9%

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Background

• Two main research questions:– To what extent has the shift towards non-routine employment

decreased the number of middle wage jobs / increased wage inequality

– Why, given that, has earnings distribution polarisation halted since mid 1990s?

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Polarisation and earnings distributions

• The shift away from routine work should increase the number of high-wage and low-wage jobs, everything else being equal

0 2 4 6 8 10 12 140.00

0.05

0.10

0.15

0.20

0.25

0.30

All

Routine

High skill non routine

Low skill non routine

Gross hourly wage, 1987

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Polarisation and earnings distributions

• However, wage structure of occupations unlikely to remain constant

• Autor, Katz and Kearney (2006) – relative wage of routine occupations falls– “Wage polarisation” – a US phenomenon?

• Wage differences between different non-routine occupations (Williams, 2012)– Other compositional changes – more educated workforce, lower union

membership, greater female participation– Non-uniform increase in demand for non-routine tasks?– Change in returns to other characteristics

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Methodology• Standard quantile regressions compute quantiles of a

distribution conditional on explanatory variables• However, we need to decompose unconditional distributions• Firpo, Fortin and Lemieux (2009) – two stage approach

1. Estimate a counterfactual distribution via reweighting initial distribution

2. Use re-centered influence functions to estimate distributional statistics (such as percentiles) as a linear expression of main explanatory variables

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Methodology• Data:

– N observations, N0 from initial distribution, N1 from final distribution– Ti = 1 if from final distribution, i = 1,...,N. Pr(Ti) = p

• Data can be reweighted• Reweighting:

– where p(X) = Pr (T=1|X)

)(1)(1

)1&Pr()1|Pr( 00

XpXp

pT

EF

pTyYTyYF

yYC

C

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Methodology• This counterfactual can be used to decompose wage and

composition effects of a distributional statistic:

• An recentered influence function of v(F) measures its sensitivity to each observation, where E(RIF) = v(F)– Assume a linear projection of RIF onto X:

– where j = {0, C, 1}

CW

CC

vvFvFvFvFvv

01

vjj

vj

vj XRIF

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A quantile regression approach• Hence:

• This is a more general case of the Blinder-Oaxaca decomposition, where v(F) is the mean.

CW TXEv 11|

00|1| TXETXEvC

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Data• Family Expenditure Survey, 1987-2001

– Around 10,000 observations each year– Usual gross pay and usual hours of work– Education – year left FT education four levels– Union membership – subscription fees>0

• Quarterly Labour Force Survey, 1994-2007– Around 150,000 observations each quarter (5 quarter membership)– Gross hourly pay directly reported– Educational qualifications– Union membership directly reported

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Data 1987 2001 1994 2007

Female 47.3% 50.3% 50.7% 52.1%Union membership 29.0% 15.3% 36.9% 31.5%Works part-time 23.6% 23.3% 26.3% 26.6%University graduates 9.4% 16.9% 13.4% 23.4%No qualifications 36.1% 18.6% 17.2% 8.3%Experience < 5 years 11.9% 9.4% 7.7% 8.2%Experience > 20 years 49.1% 53.5% 57.8% 53.8% Professional 11.2% 12.8% 11.9% 14.4%

Managerial 7.3% 11.7% 12.5% 14.9%

Intermediate 10.1% 13.7% 14.0% 15.8%

Manual Routine 36.1% 26.4% 26.9% 19.9%12.2%Admin Routine 19.7% 15.2% 14.7%

Manual Non-routine 1.8% 0.8% 0.9% 1.1%

Service 13.8% 19.4% 17.9% 21.7%

N 7253 5908 32355 54098

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Composition and wage effects• FES, 1987-2001:

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

Composition

Wage structure

Percentile

Real

wag

e gr

owth

, 198

7-20

01

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Composition and wage effects• LFS 1994-2007:

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.000.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Composition

Wage structure

Percentile

Real

wag

e gr

owth

, 199

4-20

07

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Composition and wage effects• Both periods find compositional changes decreasing the

number of middle-wage jobs• Wage structure changes reverse this – partially in the 1987

and 2001, and completely between 1994 and 2007Year Jobs earning below

2/3 * median hourly wage

Jobs earning above 1.5* median hourly

wageInitial (1987) 20.2% 23.4%Composition effects only 24.0% 27.1%Final (2001) 23.0% 25.6%Initial (1994) 22.6% 25.2%Composition effects only 25.2% 27.3%Final (2007) 21.3% 25.9%

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Individual composition effects

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

Total estimated composition

Occupations

Education

Unions

Female

Percentile

Real

wag

e gr

owth

, 198

7-20

01

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Individual composition effects

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

Total estimated composition

Occupation

Education

Unions

Female

Percentile

Real

wag

e gr

owth

, 199

4-20

07

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The wage structure - aggregate

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

Wage structure Occupation Education

Unions Female Constant

Percentile

Real

wag

e gr

owth

, 199

4-20

07

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The wage structure - occupations

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%Professional

Managerial

Intermediate

Routine manual

Service

Percentile

Real

wag

e gr

owth

, 199

4-20

07

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The wage structure - education

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

Degree

Post compulsory

Percentile

Real

wag

e gr

owth

, 199

4-20

07

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Discussion• Wage structure reduces increase in inequality, despite change

in composition on the workforce• However, hard to interpret as educational or occupational

opportunities pulling the middle up – despite the “room at the top” mindset of policymakers

• An alternative interpretation – downward sloping wage structure is a ‘correction’ of compositional changes – not as many people in high wage jobs as we’d predict

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Discussion• Minimum wage has clearly having an effect at low-end• However, other wage structure effects also helping to reduce

lower-tail inequality e.g. male-female wage gaps, relative pay of service jobs

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Discussion• Increasingly heterogeneous occupational groups

Low pay Middle pay High pay

-5.00%

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%

Professionals Managerial

Intermediate Manual routine

Admin routine Service

Chan

ge in

em

ploy

men

t sha

re, 1

994-

2007

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Discussion• Unrelated to educational attainment? Graduates only:

Low pay Middle pay High pay

-5.00%

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

Professionals Managerial

Intermediate Manual routine

Admin routine Service

Chan

ge in

em

ploy

men

t sha

re, 1

994-

2007

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Discussion• This could reflect a supply problem if it reflects quality of

graduates• Could also reflect suitability of university route into labour

market vs. vocational education• Can not ignore changes on the demand side – in particular,

are technology and skilled labour always complements?• Brown, Lauder and Ashton (2011):

– “Knowledge work” “Working knowledge”– “Digital Taylorism” – deskilling of high skill work– “War for Talent” – high premium paid for small pool of graduates at

top universities

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Discussion• So far, defined high wage job as a fixed multiple of median pay• However, the size of the wage spectrum is relevant• Very high pay is increasing, even while high pay remains

constant• Some higher paid workers move closer in relative terms to the

middle as the top experience very rapid wage growth• What is an appropriate cut-off for these groups?

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Conclusion• Main points:

– Earnings distributions polarised during 1980s and 1990s– This polarisation was less than compositional shifts would have

predicted– Middle paying jobs stop declining in middle of 1990s, despite

continuation of compositional shifts• Areas for future investigation:

– Educational attainment and occupational demands do not seem to be offering opportunities to narrow earnings inequality

– What happens to occupational mobility, particularly at low end?– What has happened since 2007?

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Contact DetailsCraig Holmes

Pembroke College, Oxford, andESRC Centre on Skills, Knowledge and Organisational

Performance (SKOPE),

Email: craig.holmes@pmb.ox.ac.uk