Ian Gordon Geography Department and Spatial Economics Research Centre London School of Economics

1. Who makes it up the London Escalator?ambition, migration and advancement in a big city labour market Ian Gordon Geography Department and Spatial Economics Research Centre London School of Economics LSE London Monday seminar, 17th January 2011

2. Escalators paved with gold? ‘Start spreading the news ...... these vagabond shoes are longing to stray ..... right through the very heart of it’

3. But Who Makes it Up ? • Maybe not the poor orphan of legend • ‘Contrary to popular belief, Dick Whittington was not a poor, ill-treated orphan who managed against all the odds to work his way up to Lord Mayor. Coming from a wealthy family, Richard Whittington had a successful business and civic career before he became Lord Mayor. [and] carved out a successful business career in a very practical way as a mercer (dealer in costly fabrics such as silk), wool merchant and royal financier’.Corporation of London web site

4. But perhaps the most professionally ambitious • ‘I want to wake up in a city, that never sleeps .. and find I’m a number one .. top of the list, king of the hill … • ‘If I can make it there, I’m gonna make it anywhere …. It’s up to you ……’ • New York, New York • ‘when we started, the limits of our ambition was just to be the best f ...ing band in London. We disdained the provinces; it was a real London mind-set. But once the world beckoned ……… ’ • K. Richards, Life, 2010

5. Or the Foxiest ?

6. Outline • Context and motivation • Sketch of theory • Methods • Results from LFS and BHPS analyses • Some conclusions

7. Context & Motivation

8. Context • Part of SERC project on skills, migration and labour markets • with Champion/Coombes (working on Census LS data cf LFS / BHPS) • Inspired by Fielding’s classic papers on South East England (=extended London region) as ‘escalator region’ in 1970s/80s • Seeking to update/extend to wider range of British city-regions • Given even greater concentration of graduate jobs in London • 50% above average • 75% filled by migrants from RUK / overseas • All net RUK migrants now graduates • And shift focus from inter-class mobility to human capital acquisition + selectivity of mobility / effects & people vs place • via Glaeser et al on agglomeration / labour market effects • Potential policy interests in relation to: • LT equity / efficiency impacts of agglomerating advanced jobs in core + Question of how far life chances (for natives) really vary between core / periphery - If migration can get you on the escalator

9. What Needs to be Explained • Stylised Facts from Fielding studies: • Existing workers (as well as entrants from education) move further/faster up occupational ladder if based in London/SE • Effect is particularly strong for migrants to the region • But significant proportion of the beneficiaries subsequently move on • More generally: • Why it is that young/qualified migrants are drawn to dynamic city economies - if real incomes for given jobs/quals are no higher ? = Aspect of a more general issue for neo-classical models of labour migration • if migration is equilibriating but costly, why does any individual choose to make a move - rather than wait for others to do so ?

10. 2. Sketch of Theory • Acquiring Competences • Locational Implications and Selectivity • Signalling • Life / career Cycles • Summary of Expectations

11. Acquiring competences • Two elements of human capital: • Static: current competences of value for some activities • Dynamic: capacity/disposition (‘ambition’) to use opportunities on/around job (or study) to add, develop/extend competences • Variability of jobs in opportunities for competence dev.: • Inherently – in relation to job requirements (specialisation, programmability, novelty/proximity to cutting-edge) • By design – employers’ choice to inhibit / encourage workers efforts to develop competences of value inside/outside org.

12. Locational Implications & Selectivity • Workers with strong disposition / capacity to develop HC on the job should choose: • Jobs with more positive opportunities • Locations with more such jobs • Dense / dynamic flexible labour markets • with maximum chances to secure financial rewards for acquired HC • without need to incur high movement costs • To organise lives to minimise costs of any necessary movement → particular attraction to agglomerations with: • High order/non-routine functions • Many employers + Flexible / high turnover labour markets • Employers needing such workers (learners / explorers) should also be drawn there

13. Signalling • Information is problematic / asymmetric both for: • Dynamic aspect of Human Capital • Not certified – and may lapse • Opportunities for development offered by jobs • Both workers and firms with real interest in development may signal this by: • locating in dense agglomerations with many similar employers, despite: • Higher money wages • Not particularly high real wages (for competence levels)

14. Life / Career cycles • People initially attracted to, and benefitting from agglomerations for HC developmental reasons may subsequently move on because: • Interest, capacity and benefits from further on job/local learning diminish with age / success / superior knowledge • for individual and/or employers • Incidental cultural characteristics of dynamic / developmental agglomerations fall off /invert with age / success / stability

15. Summary of Expectations • Escalating = combined effect of: • individuals’ dynamic HC / ambition • firms’ need for/tolerance of learners in partic job types • thick, competitive urban labour markets • Geography of escalators = consequence of; • spatial selectiveness of (a) and (b) • plus agglomeration effects on (c) • Very uneven outcomes individually and spatially • as consequence of positive feedback between these • maybe just one dominant escalator • Occupational advancement = key motive for migration • – in 2 distinct forms: • internal (non-localised) labour markets – career tracks • inter-firm, private markets with stronger spatialised character • Migrants should advance faster • but partly as effect of self-selection

16. METHODS

17. Scaling the Occupational Ladder Want a continuous measure of progress cf. Fielding focus on discrete inter-class shifts Job types involve unique combinations of human capital required for and / or generated by the work in competitive lm: pay rates reflect prices for each element and reflecting overall s & d: marginal prod + marginal cost Used 2-dimensional job classification: 4 digit occupations (371) 4 managerial / supervisory status categories JS scale value for each = average hourly earnings (LFS) - logged Combining direct and regression estimates, depending on n standardised for contextual influences year, region, firm size

18. A Measure of Ambition Conceived of as - a disposition to seek advancement by acquiring employment-relevant human and social capital Distinct from (immediate) material objectives / needs – and from social function of work Measure - based on two pairs of questions from 1991 /1999 BHPS waves about two most important aspects of ‘work’ and a desirable job: Scoring positively: promotion, career, initiative, job content Scoring negatively: to afford essentials, people’s company Ignoring: pay, security, hours, relations with manager U-shaped relation with (current) age - apparently lowered when first enter couplehood = part of reason for rather weak correlation across waves operational measure based on: (a) standardising for age & and scaling to 0-1 range; then (b) averaging 1991 and 1999 scores Related positively to qualifications + parental social class Also current region of residence, but not that of birthplace effect rather than cause ?

19. 3 Modelling Issues • Explaining levels or changes • trade-off = sample sizes versus process interest • both used here • The significance of lagged dependent variables • real effect of depreciation of human capital ? and/or • spurious reflection of measurement errors + other transient ‘noise’ • some efforts at modelling – but results here based on trial values • High proportion of JS ‘stayers’ – esp. in short run; • under-stated where measurement / coding not consistent • but exclude (at least for sig tests) because  non-normal  JS

20. 17 year JS Change (BHPS)

21. Two Data Sources • Labour Force Survey: • Regular, factual, very large sample • Longitudinal element only 12 months, by • 5 quarter panel structure – all vars but no movers and ?of coding consistency • Job / residence year ago ?s for all – memory but consistent • British Household Panel Study • 18 waves 1991-2008 with core of repeated questions + occasional extra attitudinal ones • Much smaller sample subject to attrition

22. RESULTS 1. Levels of Occupational Attainment

23. Levels • LFS shows: • For given age + qualifications: JS score • much higher for those working in Central London • high also for rest of Greater South East • only 2 of other 7 conurbations above UK average • Significant contributor to core’s higher earnings / productivity • BHPS shows: • Ambition as important as qualifications • Family background matters • Region of current residence (all of GSE) significant • not that of birth

26. 2. Occupational Progression over Time

27. Changes • LFS (1 year) shows: • All under 50s with degrees progress a bit more • But effect really concentrated among sub-set who: • migrated inter-regionally; and • work in Central London • BHPS (15 years) shows: • Apart from those gaining new qualifs (degrees) • Escalator benefit concentrated on: • Ambitious people spending time as GSE residents

30. Conclusions

31. Conclusions • Seems clear evidence of escalator effects for: • Central London workers and/or GSE residents • Maybe largely for migrants • But may just reflect selection effect for ‘ambition’ • The combination of Ambition + time in core region seems to be crucial to ‘moving on up’ • Not either on their own • At least consistent with sketched ‘theory’