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The route out of the routine: mobility and the changing structure of

occupations

Craig Holmes and Ken Mayhew

International Labour Process Conference, University of Leeds, April 16th 2011

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Introduction

• Occupational structures change over time• This structure is important for a number of labour market

outcomes.– Much focus on wage distributions and wage inequality– Changes may also impact on occupational mobility

• In this paper, we ask what happens to workers displaced by these changes– Are they able to move to higher skill, higher wage jobs?– Are they forced into lower skill, lower wage jobs?– Do the qualifications, specific and general skills they have affect their

prospects

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Introduction

• What might cause a change in the occupational structure?• Skill-biased technical change

– Computer capital take-up increases firm demand for skilled workers and replaces unskilled workers

• Routinisation hypothesis (Autor, Levy and Murnane, 2003):– Computer capital replaces tasks, not skills– Labour employed in routine tasks can be swapped for technology– Occupations performing non-routine tasks grow

• Polarisation hypothesis (Goos and Manning, 2007)– Routine occupations found in middle of income distribution– Non-routine occupations found at top and bottom of distribution

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Theory

• Model of occupations with task-biased technological progress and task

• Following routinisation:– More qualified move to higher skill non routine, less qualified move to

lower skill service jobs– Older workers moves to higher skill jobs, younger workers move to

lower skill jobs, everything else being equal– Workers with more routine occupation specific skills are less likely to

move

• Routine jobs are “getting old” (Autor and Dorn, 2009)– Model predicts a more complex relationship between age and

mobility

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Data

• National Child Development Study (NCDS)– Members of NCDS were all born in a single week in March 1958– Data has been collected on these members in a series of waves. – Use waves 1981, 1991, 1999-2000, 2004-5– Data covers age 23 to age 46-7– N = 10-12,000 in each wave– Data on work histories, qualifications, wages (current occupation)

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Data

• Occupations coded in KOS (1981) SOC90 (1991, 1999) and SOC2000 (2004).– Manually converted to SOC2000 based on occupation descriptions– Reduced to 3 digit coding to reduce dropped observations

• Occupations placed into one of six groups:– Professional, managerial, intermediate, routine, service, manual non-

routine– Allocation based on description, wages and wider economy

employment changes– Managerial and intermediate are both higher skill, non-routine

occupations without qualification entry requirements– Manual non-routine and service are both low skill non-routine

occupations.

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Methodology

• Would like to ask how routinisation has affected transitions from routine occupations

• Counterfactual dataset does not exist• Alternative:

– Look at 5 periods of transitions: 1981-1986, 1986-1991, 1991-1995, 1995-1999 and 1999-2004

– Include a measure of routinisation using changes in employment share of routine workers across entire economy (LFS data)Year 1981-6 1986-91 1991-5 1995-9 1999-2004

Period of transition 1 2 3 4 5

Change in employment share -4.30% -15.29% -3.27% -1.90% -6.27%

Rate of decline -6.55% -24.91% -7.09% -4.44% -15.32%

ROUTINISATION 0.0655 0.2491 0.0709 0.0444 0.1532

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Methodology

• Logit model:– Dependent variable (end of period occupation) is dichotomous (Y = 0

or 1)– Estimates the conditional probability that the explanatory variable

takes the value of one.– One equation estimated for each destination occupation.– Conditional on starting in a routine occupation N=11,963

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Methodology

• Baseline model:

• ACADEMIC and VOCATIONAL are vectors of dummies• Reference group: white, male, level 3 qualifications• Also see which factors mitigate the effects of routinisation• Interaction model (1) - role of labour market experience:

– Interact PERIOD and SPECIFIC with ROUTINISATION

• Interaction model (2) – role of qualifications:– Interact qualification dummies with ROUTINISATION

iiRiSiP

iViAiNiFii

RSPECIFICPERIOD

VOCATIONALACADEMICNONWHITEFEMALEPLOGITZ

0

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Results

• Baseline estimation:– Higher academic qualifications increase probability of “upwards”

moves– Level 2 and 3 academic qualifications not significantly different

(except professional)– Vocational qualifications between level 4 not significant. Role of level

3 qualifications for mobility?– Higher qualifications do not reduce probability of moving to low skill

service occupations– Routinisation increases probability of upward and downward moves

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Results

• Interaction models show that qualifications, specific and general skill/experience mitigate effect of routinisation– Displaced workers with intermediate academic qualifications and

higher vocational qualifications more likely to move to intermediate occupations following routinisation

– Those with higher academic qualifications more likely to move to professional occupations following routinisation

– Qualifications did not help the displaced move to managerial occupations, however general labour market experience did.

– Specific experience reduced mobility following routinisation– All qualifications did not reduce probability of moving to service

occupations following routinisation – implies non human capital barriers to mobility

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Results

• Logit is non-linear model, therefore size of effects vary across different types– e.g. Marginal effect of probability of transition to intermediate job

from level 2-3 academic qualifications may also depend on age, experience or vocational qualifications

• In logit models with interaction terms, significance and even direction of effects not the same as shown by coefficients (Ai and Norton, 2003).

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Results

• Illustrative examples used to show size of effects• Example 1: white male between the ages of 33 and 38, who

has worked in a routine occupation for one prior period

0 % routinisation 10% routinisation

Occupation No quals Level 2-3Marginal

effect No quals Level 2-3Marginal

effectInteraction

effect

Professional 0.6% 0.5% -0.1% 0.6% 0.9% 0.3% 0.4%

Managerial 1.3% 3.0% 1.7%* 1.5% 3.7% 2.2%* 0.5%

Intermediate 1.3% 2.3% 1.0%* 1.1% 2.8% 1.7%* 0.7%*

Routine 93.5% 91.5% -2.0%* 92.2% 89.0% -3.2%* -1.2%*

Service 1.1% 1.2% 0.1% 1.5% 1.5% 0.0% -0.1%

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Results

• Illustrative examples used to show size of effects• Example 2: white male between the ages of 33 and 38, who

has worked in a routine occupation for one prior period

0 % routinisation 10% routinisation

Occupation Level 2-3 Level 4-5Marginal

effect Level 2-3 Level 4-5Marginal

effectInteraction

effect

Professional 0.5% 3.5% 3.0%* 0.9% 7.6% 6.7%* 3.7%*

Managerial 3.0% 9.4% 6.4%* 3.7% 6.5% 2.8%* -3.6%

Intermediate 2.3% 5.6% 3.3%* 2.8% 6.1% 3.3%* 0.0%

Routine 91.5% 85.7% -5.8%* 89.0% 78.4% -11.6%* -5.8%*

Service 1.2% 0.5% -0.7% 1.5% 0.9% -0.6% 0.1%

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Results

• Illustrative examples used to show size of effects• Example 3: Level 3 academic and vocational qualifications and

no specific experience

0 % routinisation 10% routinisation

Occupation Aged 28-33 Aged 33-38Marginal

effect Aged 28-33 Aged 33-38Marginal

effectInteraction

effect

Managerial 4.7% 3.2% -1.5%* 5.4% 5.1% -0.3%* 1.2%*

Intermediate 4.1% 2.6% -1.5%* 4.8% 4.1% -0.7%* 0.8%*

Routine 89.4% 92.8% 3.4%* 84.0% 86.0% 2.0%* -1.4%*

Service 0.8% 0.6% -0.2% 1.3% 1.2% -0.1% 0.1%

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Conclusion

• This paper offers the first attempt to estimate some of the effects on occupational mobility resulting from the decline in routine jobs.

• Results:– Routinisation has been an important driver of occupational mobility– Some qualifications have proven to improve the prospects of the

displaced, however vocational qualifications have exhibited little effect

– Specific skill (or experience) decreases likelihood of displacement.– Controlling for that, older workers are more likely to move on

following routinisation - a more complex version of Autor and Dorn’s “this job’s getting old” conclusion

– May be some non-human capital barriers to mobility

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Conclusion

• Quantifying size of effects is difficult, and varies by “type”. • Using simple examples:

– Without routinisation, upward career mobility leads to between 7% and 15% of routine workers moving to new jobs each period.

– Up to 8% additional mobility was created for routine workers for a 10% decline in routine occupations, depending on the characteristics of the workers. In most cases, this additional mobility fell between 3% and 7%.

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Contact Details

Craig HolmesESRC Centre on Skills, Knowledge and Organisational

Performance (SKOPE), Department of Education,

Norham Gardens,Oxford

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