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Cultural diversity and London’s economy

Cultural diversity and London’s economy. Max Nathan London School of Economics | SERC | LSE Cities LSE London seminar , 5 March 2012. What I’m going to talk about. The big picture Concepts and theory Evidence: labour markets, wider effects Cultural diversity and London firms

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Cultural diversity and London’s economy

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  1. Cultural diversity and London’s economy Max Nathan London School of Economics | SERC | LSE Cities LSE London seminar, 5 March 2012

  2. What I’m going to talk about The big picture Concepts and theory Evidence: labour markets, wider effects Cultural diversity and London firms Policy lessons I’m an economic geographer. I use a lot of economics There will be equations 2

  3. Headlines London exhibits ‘super-diversity’ Immigration and natural change twin drivers of this Policymakers need to think about both labour market effects (of immigrants) and wider effects (of diversity) London’s diversity has economic benefits for the capital’s businesses - for example, on innovation Economic effects of immigration on London and (some) Londoners seem more mixed The current policy mix needs to change 3

  4. Context 4

  5. Population change in the UK Source: ONS (2010) 5

  6. Stylised facts The UK has become more diverse over the past two decades - alongside other ‘Western’ countries(Putnam 2007) Two drivers: immigration and natural change 2007: net immigration = 52% of UK population growth 2009: non-’white British’ groups = 1/6 of the English population 2050: minority ethnic groups = 21% of the UK population? (ONS 2011, Wohland et al 2011) Diversity is urbanised: cities and urban areas have the largest migrant and minority populations (Champion 2006) 6

  7. Super-diversity? Vertovec: ‘diversification of diversity’ since the early 1990s has led to super-diversity(Vertovec 2006, 2007) 1994: Ireland, India, Pakistan, Germany, USA 2008: Poland, Zimbabwe, China, ex-USSR, Czech Republic Growth of ‘new migrant communities’ (Kyambi 2005) ESOL: from c.10-20% of children, 2003-2009 (DfE 2011) 2011 Census: likely rise in mix of religions practised Super-diversity is an urban phenomenon, and largely a London phenomenon … 7

  8. London Source: Hall (2011) 8

  9. London London exemplifies the cosmopolitan world city: Major centre of world financial system (still) Contributes c.20% of UK GVA London schoolchildren speak over 300 languages Contains 40% of net migration to the UK, has around 48% of England’s non-white populations (GLA 2008, Gordon et al 2007, Champion 2006, Baker and Eversley 2000) London’s cultural diversity is seen as a social, economic asset - by London government, Whitehall, Londoners (GLA 2008, Legrain 2004, Leadbeater 2008)

  10. London … is uncharted territory. Never have so many different kinds of people tried living together in the same place before. What some people see as the great experiment of multiculturalism will triumph or fail here. Benedictus (2005) By the tenth century [the city] was populated by Cymric Brythons and Belgae, by remnants of the Gaulish legions, by East Saxons and Mercians, by Danes, Norwegians and Swedes, by Franks and Jutes and Angles, all mingled and mingling together to form a distinct tribe of ‘Londoners’ … Peter Ackroyd, London (2000) 10

  11. Some more history 883AD: King Alfredbans the Danes from London. Sent to live east of the Lea (Keith 2005) Complaints across medieval Britain that ‘foreigners were practising their own customs’(Vertovec 2007) 1610: Elizabeth I orders the expulsion of ‘negars and Blackamoores’ from the capital (Sandu 2004) 1867: Times leader: ‘there is hardly such a thing as a pure Englishman on this island … our national denomination, to be strictly correct, would be a composite of a dozen national titles’ (Sandu 2004) 11

  12. Theory and evidence 12

  13. Definitions ‘Cultural diversity’ = mix of ethnic / cultural identity groups Requires a prior notion of cultural identity Cultural identity = multifaceted, subjective, evolves over time (Aspinall 2009, Michalopolous 2008, Ahlerup and Olsson 2007 etc.) This means that quantifying cultural identity and thus cultural diversity is very hard Workaround = use ‘identity proxies’ such as country of birth, ONS ethnic groups, anduse simple shares or indices for diversity (Ottaviano et al 2007) 13

  14. Economics of diversity In theory, a ‘diversity shock’ to an area might have: Effects in local labour markets (as e.g. immigrants arrive) Wider effects on consumer markets, business performance, entrepreneurship, trade etc. (as new communities form) Labour market analysis tends to be neo-classical, predicts average effect on UK ‘native’ wages, employment is zero Labour market institutional change – occupational clustering of migrants; low-quality employers become ‘migrant-dependent’; lock out of low-skill ‘natives’? 14

  15. Economics of diversity (2) Wider effects are under-explored Multiple channels, operating both at firm and city level Production complementarities may include: More diverse workforces = better mix of ideas; good for innovation? Co-ethnic networks = facilitate international market access? ‘Ethnic entrepreneurs’ = more likely to found start-ups? Versus lower social capital in diverse firms; discrimination? Urban consumer markets – cosmopolitan urban populations demand new products; or urban crowding, competition? 15

  16. Evidence: labour markets UK-wide studies suggest Small and/or insignificant average effects of immigrants Small negative effects on wages, jobs of low-skilled Britons Links to casualisation of entry-level work (MAC 2012, Green 2011, Cook et al 2011, Nathan 2011, Nickell and Salaheen 2008) London studies suggest Suggestive evidence of wage pressure for low-skilled UK-born Clear ‘migrant division of labour’: catering, cleaning, care 56-76% foreign-born workforce vs. 34% London ave. Importance of employment agencies, ‘hierarchies of hiring’ (Wills et al 2010, Gordon and Kaplanis 2012) 16

  17. Evidence: wider effects Evidence on production complementarities suggests Mixed evidence of workforce diversity on innovation Stronger evidence that co-ethnic networks and entrepreneurs help knowledge transfer, market access, trade (Ozgen et al 2011, Mare et al 2001, Kerr 2009, Wadhwa et al 2007, Saxenian 2006) Evidence on urban markets suggests Some links between population and service sector mix, mainly from qualitative studies in single cities Mixed evidence on immigration and housing costs (Sa 2011, Nathan 2011, Mazzolari and Neumark 2009, Gordon et al 2007, Saiz 2003) 17

  18. What we did 18

  19. Data and sample Source – London Annual Business Survey (LABS) Annual survey of firms across Greater London region Provides very rich information on workforce and ownership characteristics, business performance and constraints Years – 2005-2007, repeated cross-section Units – individual sites, with bias towards HQs Observations – 7,425 firms Context – 2004 EU expansion => very large increases in net migration (and thus diversity) in UK, especially London Focus – business owners / partners = key decision-makers

  20. Model Model is a simplified (knowledge) production function For firm i in sector j and year t, we estimate: Yijt = aDIVijt+ CONTROLSijtb + SECTj+ YEARt + ei (1) Y = innovation, commercialisation, sales orientation, reasons for firm foundation / entrepreneurship DIV = proxies: ‘migrant-diverse’ and ‘ethnic-diverse’ firms ‘migrant diverse’ = mix of UK/non-UK born partners / owners ‘migrant firm’ = all non-UK born partners / owners ‘ethnic diverse’ = at least half minority ethnic partners/owners

  21. Model (2) Our vector of controls includes: firm age firm size, sq root R&D spend Collaborative activity Exports PLC status Management ability (qualifications, experience, training etc.) Knowledge intensive business services (KIBS) dummy SECT = one of 150 3-digit SIC sectoral dummies YEAR = 2005, 2006 or 2007

  22. Innovation Source: LABS. Notes: Results are odds ratios. HAC standard errors in parentheses. All specifications include controls, year and SIC3 dummies: some observations dropped because of perfect prediction groups. * = significant at 10%, ** 5%, *** 1%. 22

  23. Commercialisation Source: LABS. Notes: Results are odds ratios. HAC standard errors in parentheses. All specifications include controls, year and SIC3 dummies: some observations dropped because of perfect prediction groups. * = significant at 10%, ** 5%, *** 1%. 23

  24. What type of firms? Source: LABS. Notes: Results are odds ratios. HAC standard errors in parentheses. All specifications include controls, year and SIC3 dummies: some observations dropped because of perfect prediction groups. * = significant at 10%, ** 5%, *** 1%. 24

  25. Sales / markets Source: LABS. Notes: HAC standard errors in parentheses. All specifications include controls, year and SIC3 dummies: some observations dropped because of perfect prediction groups. * = significant at 10%, ** 5%, *** 1%. 25

  26. Entrepreneurship

  27. Implications 27

  28. Toplines Topline = London’s cultural diversityhelps London firms Diversity is linked to ideas generation, but not to successful commercialisation of those ideas Diversity seems to have a stronger effect for less ‘knowledge-intensive’ firms (e.g. retail, consumer services) All-migrant teams also help ideas generation, with a stronger effect in knowledge-intensive firms Migrant-headed and migrant-diverse firms sell largely to international markets; ethnic diverse firms more localised Migrant status has a small but robust link to entrepreneurial behaviour 28

  29. Issues (1) Why do diversity and co-ethnicity not feed through to commercialisation? Bad ideas / different skill sets? Management experience, skills are key barriers to growth for minority ethnic firms (Lee 2012) Have we measured commercialisation correctly? Discrimination? Other constraints on business growth: finance, space etc. … ? Potential for stronger business support policies? 29

  30. Issues (2) Is the immigration cap a good idea? Doesn’t look like it: Restricts London’s talent pool; migrant status is linked to entrepreneurial behaviour Entrepreneurship Visa = £50k bond! Restrictions on post-study visas may have similar effect Labour market institutions in London If firms hire more diverse teams, workers who would have been hired are ‘losers’ (Borjas and Doran 2012) … but probably get other jobs Case for re-regulating some employment agency activity? Better enforcement of minimum wage, working conditions More effective employment and training for low-skilled Londoners 30

  31. Knowledge gaps Who are the entrepreneurs? Is there a hierarchy of entrepreneurship? Is there really a ‘commercialisation gap’? Need to explore sectoral differences in more detail Would the same population have the same effects in other cities? Comparative studies of same groups in London, NYC London is unique. Similar effects in other UK cities? 31

  32. Thanks. m.a.nathan@lse.ac.uk personal.lse.ac.uk/nathanm squareglasses.wordpress.com @iammaxnathan

  33. Identification challenges Cities / positive selection, simultaneity – raise levels of both innovation and DIV => exploit quasi-experiment conditions post-2004 Individuals / ethnic entrepreneurs – ambitious / talented people would be innovative anywhere => separate tests on company founders Firms / both-ways causation – more innovative firms may a) hire b) attract a more diverse workforce => instrumental variables approach

  34. Descriptives Source: LABS 34

  35. Market shares For firm i in sector j and year t, we estimate: Yijt = a+ bDIVijt+ CONTROLSijtb + SECTj+ YEARt + ei (2) Y = % local / national / international sales DIV = No. of migrant / minority ethnic partners / owners (migown_1ormore, ethown, migfirm) CONTROLS = firm age, size, R&D spend, collaboration, mgt ability SECT = one of 150 3-digit SIC sectoral dummies YEAR = 2005, 2006 or 2007 Estimate as seemingly unrelated regressions => provides some efficiency gains over OLS

  36. Company founders We isolate the subset of LABS respondents who are involved in company formation LABS gives reasons for company formation. We classify these as ‘entrepreneurial’, ‘locked out’ or ‘other’ We look at whether migrant status affects reasons for company formation For founder i, sector j, yeart: Pr(Yijt = 1) = aDIVijt+ MGTijtb + DIV*MGTijtc + Sj+ Tt + ei (3) Y = Reason for firm formation (entrepreneuial / locked out / other) DIV = Dummy for migrant founder MGT = management ability controls (qualifications, courses, training, experience)

  37. IV • Issue = both-ways causation in firms. Upwards bias on DIV • Problem = not a true panel, hard to find suitable instrument • Approach = exploit historic settlement patterns at LAD level (cf Altonji and Card 1991). For firm i, borough j, year t: • pDIVijt = DIVjtbase(4) • t = 2007, tbase = 2001 (using 2001 Census data) • Estimate on 2007 data only, 2SLS with robust SE’s • Caveats = single cross-section, instrument dummies with continuous variables

  38. IV (2)

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