Thinking inside the box? Assessing mobility through typologies of employment organisation Craig Holmes and Ken Mayhew SASE Annual Conference, Universidad Autónoma de Madrid, June 24 th 2011

Introduction Much of emphasis by UK policymakers for improving mobility is placed on the supply side – more human capital  greater upward mobility Labour market segmentation theories place more emphasis on organisation of employment within firms and occupations Evidence of strongly segmented labour markets is limited However, the organisation of employment in terms of mechanisms for within-firm and across-firm transitions is still an important barrier to mobility

Introduction LMS theories lead to a simply typology of jobs: – Internal labour markets – Occupational labour markets – Secondary segment Aims of this paper – Is this simple typology a useful tool for analysing mobility? – Has this changed over time?

Methodology UK Labour Force Survey Two years: 1986 and work characteristics over job quality; skills, education and training; job transitions, and tenure Factor analysis: – Reduces the larger set of variables to a smaller set of underlying, unobserved factors – Observed variables map onto different factors with different weights – Statistical software calculates weightings to explain as much variances as possible – Use only factors that explain more than 1/22 of the total variance

Methodology Grouping analysis: – Mean factor scores by occupation – Groupings suggested by data (not formal cluster analysis) – Focus on most common occupations (by narrowest occupational title) Changes over time – New occupations – Common occupations across both time periods

Results Factor analysis: PROMOTIONTURNOVERINDUSTRY NON-SPEC INTERNALSECURITYTRADEPROFESSIONAL (1986 only) SHIFT INTRA-FIRM OCC CHANGE INTRA-JOB FIRM CHANGE INTRA-JOB INDUSTRY CHANGE OTJ TRAININGFULL-TIMEAPPRENTICEPROF. QUALSSHIFT WORK INTRA-FIRM JOB CHANGE INTRA-OCC FIRM CHANGE INTRA-OCC INDUSTRY CHANGE DEGREEPERMANENTHOURS VARYPROF. QUALS (2008 only) INTRA-INDUSTRY OCC CHANGE INTRA- INDUSTRY FIRM CHANGE UNPAID OTSELF EMPLOYED INTRA-INDUSTRY JOB CHANGE FULL-TIME MORE RESPONS.

Results – grouping occupations 1986 – INTERNAL vs. TRADE:

Results – grouping occupations 2008 – INTERNAL vs. TRADE:

Results – mobility Mean scores for PROMOTION (inter-firm job transitions), 1986 vs. 2008

Results – mobility Mean scores for TURNOVER (across-firm job transitions), 1986 vs. 2008

Results – mobility Mean scores for INDUSTRY NON-SPECIFIC (across-industry job transitions), 1986 vs. 2008

Results – common occupations over time For occupations with large employment shares in both samples, TRADE and INTERNAL scores are highly correlated Development of occupational labour market No development of occupational labour market More internalisedNo occupationsNurses, manager-proprietors, cleaners, domestic and school helpers Less internalisedElectricians, motor mechanics, carpenters, production managers, software professionals Sales representatives, office managers, clerks

Results – common occupations over time Some of these changes are coupled with expected changes to security and mobility factor scores: – e.g. office managers and supervisors of clerks have seen falls in PROMOTION and rise in TURNOVER However, not always coupled with expected changes to mobility or security scores: – Production managers and systems analysts do not have higher TURNOVER – Marketing managers and cashiers have higher PROMOTION scores – Some skilled trades do not all have higher TURNOVER (e.g. carpenters) or INDUSTRY NON-SPECIFIC (e.g. electricians) – Teachers, typists and chefs have large changes in these outcomes, despite little change in TRADE or INTERNAL

Conclusion UK occupations across last thirty years can be grouped by methods of skill acquisition and relationship with employers – However, mobility and job security within these groups can vary greatly and may contradict theory – Groupings have become less distinct over time  hybrid groups, weaker ILMs and OLMs. – Changes to employment organisation of occupations does not always lead to predicted changes in security and mobility prospects Two directions suggested by this analysis: – Occupation factor scores may themselves be useful explanatory variables – Can a better typology of employment be found? Could it be routed as well in theory as the ILM-OLM-secondary segment model?

Contact Details Craig Holmes ESRC Centre on Skills, Knowledge and Organisational Performance (SKOPE), Department of Education, Norham Gardens, Oxford