LISBON COUNCIL Human Capital in Regions and Cities

8/7/2019 LISBON COUNCIL Human Capital in Regions and Cities

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H u m a n C

a p i t a l

InnG r o w t h a n d J o b s

bility

Policy Brie

Human Capital Leading Indicators:How Europes Regions and Cities CanDrive Growth and Foster Social InclusionBy Peer Ederer, Philipp Schuller and Stephan Willms


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Table o Contents

Human Capital Leading Indicators or European Regions ........................................TK

Case Studies .................................................................................................................TKHuman Capital Leading Indicators or European Regions and Cities ...................... 2

Case Studies .................................................................................................................16Bratislava (Slovakia) ........................................................................................................17Emilia Romagna (Italy) ....................................................................................................22Helsinki (Finland) ............................................................................................................28Navarra (Spain) ...............................................................................................................34So a (Bulgaria) ...............................................................................................................42Stockholm (Sweden) ....................................................................................................... 48West Midlands (United Kingdom) ...................................................................................53

League Tables: Regions Ranked by Human Capital Leading Indicators ................... 60

Share o Complex Jobs in Work orce ..............................................................................60Youth Unemployment Rate ............................................................................................62Long-Term Unemployment as Percentage o Overall Unemployment ............................... 64Innovation (Measured as Public and Private R&D as a Percentage o Overall GDPand Patent Applications per One Million Inhabitants) ......................................................66

Annex: Additional Indicator-Based Rankings ............................................................ 68GDP per Capita ..............................................................................................................68Overall Educational Attainment o Work orce ................................................................. 70

Note on Methodology and Data ................................................................................72Interviews ....................................................................................................................76Bibliography and Additional Reading .......................................................................80Acknowledgments ......................................................................................................85


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2 Lisbon Council Policy Brie : Human Capital in Regions and Cities

Te world is entering a new era a timewhen economic value will be created notby land, labour and capital, but by theknowledge, skill and ingenuity with whichthose traditional economic inputs can berecombined into new products and serviceso ever greater value. It is a world where thedepth o a citys, regions or nations humancapital will determine the winners rom thelosers, where the quality o our work orcewill decide the degree o our prosperity,where our institutions will be judged notby the length o their tenure but by theirability to create, attract, retain, and deploy as much human talent as possible.1

And yet our institutions are pro oundly humbled. Faced with global challengesthat will require revolutionarily di erentresponses, they are sent into battleequipped with an outmoded statistical

ramework clearly designed or a di erentera a time when the earths resourceswere not yet understood to be ultimately

nite; a moment when innovation took place mostly in laboratories, when atypical household was led by a single malebreadwinner, when the average Europeanlived about 15 years less than today and theaverage Chinese person might have thoughtexport meant selling a bit o surplusproduce in a neighbouring village.

Tat is the imbalance this study sets out toaddress. How can we arm policy makers particularly at the level o regions and cities with the analytical ramework they willneed to thrive in a truly global, knowledge-

based economy? What are the tools andlevers at policy makers disposal? Whatpolicies deliver the best results? What arethe most e ective levers? And how canthose levers be pulled in the most e ectiveway? In other words, how can we helppolicy makers at the local level to ensuretheir region has the human capital it willneed to deliver prosperity to citizens in anage o trans ormation?

Te study you hold in your hands is theproduct o one year o intensive research,conducted by a team o 11 social scientists,working at the Lisbon Council.2 Buildingon the original paradigms laid down inour ground-breaking studiesTe EuropeanHuman Capital Index (2006)andTe European Human Capital Index: Te Challenge o Central and Eastern Europe (2007), which sought to look at human-capital policies at the national level,this policy brie takes a more granularapproach.3 It seeks to look at human capitalper ormance at the local and regional level,analysing the statistical database and theexperience o seven broadly diverse regionsin search o new insights into the human-capital policies that work best.

Among the key ndings:

I. O all the levers a policy maker hasavailable at his or her disposal, thereare our key indicators where goodper ormance can be closely correlatedto local prosperity. I a region can scorewell in all our, it means that region

Human Capital Leading Indicators or European Regionsand Cities

1. Paul Ho heinz ,Europe 2020: Why Skills are Key or Europes Future (Brussels: The Lisbon Council, 2009).2. The project was made possible by a research grant rom the European Community Programme or Employment and Social Solidarity PROGRESS (2007-

2013), managed by DG employment, social a airs and equal opportunities o the European Commission.3. Peer Ederer,The European Human Capital Index: Innovation at Work (Brussels: The Lisbon Council, 2006); Peer Ederer, Philipp Schuller and Stephan

Willms,The European Human Capital Index: The Challenge o Central and Eastern Europe (Brussels: The Lisbon Council, 2007).


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3Lisbon Council Policy Brie : Human Capital in Regions and Cities

is likely to be a wealthy, prosperousand socially cohesive one. Te ourindicators are 1) the number o complexjobs in a region or city; 2) the numbero jobs available or young people andthe ease with which young peoplecan nd employment, 3) the ability to get the unemployed back to work (thereby avoiding high levels o long-term unemployment), and 4) theintensity o investment in researchand development and the volume o local patent applications, a proxy orthe innovativeness o the region.Statistical analysis shows that, takentogether, these our indicators serveas an excellent orecaster o overallper ormance in the human-capitalsphere, explaining ully 71% o regional

di erences in gross domestic productper capita in a multivariate linearregression (see Chart 1 above or more).4 In other words, policy makers who cansuccess ully deliver in these our areasare destined to do well in attracting,retaining and deploying human capitalin ways that will give tangible economicand social results to their regions andcities. Other human capital indicators such as the share o the localpopulation with tertiary education,the employment o 25- to 35-year-old women or the employment rateo the elderly are much less precisepredictors o prosperity or a region. Forthis reason, we have chosen to call the

our statistical checkpoints mentionedabove theHuman Capital Leading

4. A multivariate linear regression looks at the way in which a variety o input data are connected to or can explain one outcome variable, in this caseGDP per capita, purchasing power parity (PPP) adjusted. The linear regression describes the line through the multidimensional space ormed by the inputdata and the outcome variable that is closest to all data points. I the t o the line is good, the knowledge o the input variables allows us to implythe associated per-capita income even in cases where income cannot be measured. The t o the line is called the coe cient o determination, orR2. An R2 o 100% indicates that all observations li e on the line, while an R2 o 0% indicates that there is no optimal line and no apparent statistic alrelationship between the data and the outcome.

* Based on a multivariate linear regression

Source: Eurostat European Regional and Urban Statistics Database

Correlation* of Regional GDP per Capitawith Human Capital Indicators

Regional GDP per Capita and Performancein Human Capital Leading Indicators

TertiaryEducation

29%

Human CapitalLeading Indicators

plus AdditionalHuman Capital

Indicators

71%

Human CapitalLeading

Indicators

71%

Bottom 10%in Human Capital

LeadingIndicators

11,820

Top 90%in Human Capital

LeadingIndicators

41,323

Medium 50%in Human Capital

LeadingIndicators

21,798

Chart 1: Top Per ormance in Human Capital Leading Indicators Closely Predicts Regional Income Di erencesThe three columns show statistical comparisons o human capital indicators with regional levels o prosperity. Inthe chart at le t, the rst column uses the share o people with tertiary education (2007) as the only input variable,and shows a very low correlation between this common proxy or human-capital development and regional wealth.By contrast, the second column uses the our Human Capital Leading Indicators described in this paper: youthunemployment (2007), share o long-term unemployed among all unemployed (2007), share o complex jobs (2008)and number o patents and level o R&D spending (Innovation Index 2003), and shows a very high correlationwith regional prosperity. The third column adds additional human-capital indicators to the measurement, includingthe share o people with tertiary education (2007), the employment rate o women aged 25-35 (2007) and theemployment rate o the elderly aged 55-64 (2007), and shows little improvement in correlation or variation withthe our Human Capital Leading Indicators. The output variable in each case is regional GDP in euro (PPP per capita2007, measured in logarithms).


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Indicators , and we recommend thatregional administrators build anddevelop their human-capital strategy around improving them.

II. Regions vary in human-capitalper ormance more among themselvesthan countries do, based on closecomparison o Human CapitalLeading Indicators at the national andregional level (see Chart 2 on page 6

or more). Whats more, the HumanCapital Leading Indicators haveless predictive value at the nationallevel than they do at the local leveldue to the homogenizing e ect o national statistics.5 Tis has importantimplications. Nations, because they are made o collections o regions,o ten contain vastly di erent levels o human-capital development withinthem di erences whose specialcharacteristics are somehow lost when

statistics are aggregated at the nationallevel. Tere ore, it is particularly hard

or national administrators to improveor target widely varying human capitalsituations with a single, one-size- ts-all human capital policy. Because o this, we recommend that many humancapital development decisions andstrategies be delegated to the regionallevel, where they can be most e ective.Nations should also make sure thatregions have the authority and resourcesthey need to develop success ul human-capital strategies.

III. Te Europe 2020 strategy, adoptedby European heads o state andgovernment in March 2010, is hal right: it is right to ocus on humancapital as a key component o Europeandevelopment; it is wrong to address themember states rather than the regions.6 O Europe 2020s ve explicit targets,

5. We tested the Human Capital Leading Indicators at the national level or the 27 European Union member states, and, a ter nding an intense correlation(71%) at the local level, we ound a much weaker correlation o 63,5% at the national level.

6. For more on Europe 2020, visit the European Commission website at http://ec.europa.eu/europe2020/index_en.htm.

Europe 2020: Europes Human-Capital Development Strategy O the ve speci c targets in the EUs agship Europe 2020 agenda, our have a clearhuman-capital dimension.

1. Employment: Employ 75% o 20 to 64 year olds2. R&D / innovation: Invest 3% o the EUs GDP (public and private) in R&D and

innovation3. Education: Reduce school drop-out rates to below 10%; at least 40% o 30 to 34 year

olds should complete tertiary-level education (or equivalent)4. Poverty / social exclusion: Reduce number o people in or at risk o poverty by 20

million5. Climate change / energy: Cut greenhouse gas emissions by 20% o 1990 level (or 30%

i a satis actory international agreement can be achieved to ollow Kyoto); produce20% o all energy rom renewables and increase energy efciency by 20%


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our highlight explicitly human-capitalrelated goals (see the Europe 2020 box onpage 4). Tis makes Europe truly unique:it is the only major global actor whichhas come out so clearly and orce ully with a strategy or uture prosperity basedon human-capital development. Butthe programme misses the larger pointelaborated above i you want successin human capital development, you willhave more chances by going directly tothe local level, where policy making ismost direct and e ective. Tere ore, webelieve the Europe 2020 programmeshould ensure that each EuropeanRegion tailors the Europe 2020 strategy to its particular situation and translatesthe EU goals into regional targets andtrajectories.7

IV. Given the vast importance o localdecisions to success ul human-capitalpolicy making and the need to ensurethat agship national and Europeaninitiatives like Europe 2020 aree ectively implemented we believecities and regions should appointregional human capital managers tocoordinate, evangelise and implementbetter human-capital-raising policiesat the local level. Success ul regionsare already doing this, such as theseven regions studied in this paper(the case studies begin on page 16). Ineach o those regions and cities, thisvital task was taken up by in ormalnetworks or ormally responsibleagencies, coordination groups, task

orces, locally committed NGOs or

just enthusiastic individuals who, by their actions and agenda, have becomelargely sel -appointed human capitalmanagers or their region. Should thepolicy o appointing regional humancapital managers ever be systematizedand more broadly adopted, the humancapital manager would design, developand seek to implement a human capitalstrategy or the region. Such a strategy would steer and ocus resources tothose levers that achieve the most, anddisregard levers that are not relevant.Te kaleidoscope o coordination andprioritisation by the regional humancapital manager could include: theshaping o educational institutions romkindergarten to adult learning towardsthe needs o the regional economy, theattraction o particular types o industriesand businesses, the ostering o particulartypes o innovation and entrepreneurship,the provision o childcare acilities orworking parents, the integration o peripheral social groups into the labourmarket, and more. By ormulating andarticulating a regional or local humancapital strategy, the human capitalmanager will identi y a ew critical targetsagainst which the public can hold himor her or all other decision makers in theregion to account.

Te Human Capital Matrix inEuropean Regions and CitiesHuman capital is a vital input to economicgrowth, standing alongside nancial capitalas one o two key determinants o GDPin classical growth models (see Chart 2 on

7. Ibid.. The Europe 2020 programme sets out to ensure that each Member State t ailors the Europe 2020 strategy to its par ticular situation, and translatesthe EU goals into national targets and traj ectories (emphasis added).

There are our key human capital indicatorswhere good per ormance can be closelycorrelated to local prosperity.


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page 6 or more). Te question, then, ishow do we measure human capital? How do we determine the economic value o aregions, citys or countrys know-how andskills including the amount o humancapital which a region naturally possesses orcan attract and the e ectiveness with whichit is all deployed in the local economy?

A back o the envelope calculation already tells us a lot about the role skills play in modern economic li e. In industrialsocieties, the amount o money invested inpeoples salaries is roughly twice as muchas the return on nancial capital (measuredas interest payments and corporate pro ts).8 In other words, judging rom the pricesignals the market is sending, nearly two-thirds o all economic value in modernindustrial economies is created throughdirect investment in the skills and humancapital o our active work orce.

Te difculty modern societies ace, andEurope in particular, is not a shortageo human capital though even hereemployers tell us they cannot nd skilledworkers to do the jobs or which they have openings while overall demographictrends paint an ever more alarming picture

or Europes uture. Te difculties are,in many ways, how do we better use thehuman capital that we have? How dowe create and attract the human capitalwe will need to deliver the social andeconomic outcomes we seek? And how dowe activate and deploy human capital inways that will bring the most social goodto society at large?

o help policy makers grapple with theseseparate but related policy objectives,the Lisbon Council created theHumanCapital Matrix , a two-dimensionalgraphical representation o the key components that help us measure how much human capital a society has, andhow well that human capital is beingdeployed ( or more, see Chart 2 above).Te chart is based on a simple ormula.Stated plainly, it says the GDP o a country is the amount o human capital a regionpossesses (human capital endowment)times the amount o human capital that isactive in the labour market (human capitalutilisation) times the efciency with whichthat human capital is deployed (humancapital productivity) plus nancial capital.

Te model has already been deployed

+ Financial Capital = GDP

Human Capital Utilisation

Human CapitalProductivity

Human Capital Endowment

Chart 2: The Human Capital MatrixHuman capital endowment (the amount o human capital a region possesses) x human capital utilisation(the amount o human capital that is active) x human capital productivity (the e ciency with which humancapital is deployed) + nancial capital = gross domestic product.

8. Peer Ederer, Philipp Schuller and Stephan Willms,Gesch tsplan Deutschland (Stuttgart: Sch er-Poeschel, 2008).


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9. Ederer,European Human Capital Index ; Ederer, Schuller and Willms,European Human Capital Index: The Challeng e o Central and Eastern Europe .10. NUTS is the EU standard or re erencing the subdivision o countries into regions and cities or statist ical purposes. The acronym comes rom the French

nomenclature dunits territoriales statistiques . NUTS2 is the broadest o the three NUTS classi c ations. It includes but is not limited to Europeanregions with a population o 800,000 to 3 million inhabitants. There are 271 NUTS2 regions. For purposes o this study, we excluded London and Brusselsbecause they are statistical outliers.

success ully in earlier studies, whichmeasured the endowment, utilisationand productivity o human capital at thenational level.9 For this study, we set outto adapt the model to the regional level,looking at what the matrix could tell usabout the best, most e ective way thatlocal authorities could raise and improvehuman-capital strategies. We chose as our

ocus group 269 o the 271 regions o theNU S2 category, the regions that takentogether make up the modern 27-memberEU.10 Inner London and Brussels werele t out o the study due to per ormanceanomalies (the depth and wealth o humancapital in these two regions made themstatistical outliers, sitting in a category o their own). Te statistical analysis wastested in eld research in seven diverseEuropean regions, which will be presentedand discussed in the second hal o thispaper.

Te conclusions were in some wayssurprising. First and oremost, we oundthat many regions have more in commonwith similar areas in other countries thanthey do with other regions in their own

home country (See Chart 3 above ormore). Tis has important implications

or Human Capital Mangers. First andoremost, it means the speci c problem

a region might ace is best analysed andunderstood through comparison withother European regions that have a similarpro le and history. For example, thehuman capital challenges o a nationalcapital can have ew lessons or a humancapital manager in a thinly populated,rural region. Tis, in turn, means that,i a region is to benchmark per ormance,it should look to other similar regions

or ideas that have worked and the bestcomparisons on relative per ormance.

Whats more, we ound that, or all o theirdiversity, Europes regions could be airly easily clustered into our categories orpurposes o benchmarking their human-capital per ormance (see the map on page 9

or a geographic rendering o the clusteringand Chart 4 on page 8 or an economicsnapshot o the our main groupings).Te our groups are:

Youth Unemployent Rates Share of Complex Occupations Innovation

51%

20%

35%

88%95%

Variance between countriesVariance between regions

17%

Chart 3: Regions Vary More Among Themselves on Key Human Capital Indicators than EuropeanCountries DoVariance o three indicators between 269 regions and between 27 countries.



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40,000

30,000

20,000

10,000

GDP per capita (PPP adjusted) in 2007

50,000

0

1 Excluding ex-communist regions2 Excluding thinly-populated regions

Ex-CommunistThinly populated 1Northern 1,2Continental 1,2

Chart 4: The Richest Regions Are in Western Europe and Densely PopulatedBoxes show the medium 50% o the regions, whiskers show the medium 80% within each group.


1. Densely-populated ContinentalEuropean regions, such as Madrid(Spain) and Dsseldor region(Germany). Tere are 30 Europeanregions in this category, encompassing97 million inhabitants.

2. Densely-populated Northern Europeanregions, such as North Holland andHovedstaden (Copenhagen), Denmark.Tis grouping is made up o similarregions rom Ireland, the UnitedKingdom, Flanders, Netherlands andScandinavia. It includes South Finlandand South Ireland because o the strongdominance o Helsinki and Dublinin those areas. Tere are 37 regions inthis category, encompassing 68 millionpeople.

3. Tinly-populated West Europeanregions such as South Sweden andBretagne, France. Here, the averagepopulation density is around 76 peopleper square kilometre, compared witha densely-populated regions average o 417 people per square kilometre andan EU-27 average o 114 people persquare kilometre. Malta and the French,Portuguese and Spanish island regionsare included in this group as well, alongwith Slovenia because o its proximity toAustria and the relative openness o the

ormer Yugoslavia. Tere are 141 regions

in this category, encompassing 210million inhabitants.

4. All regions in ormerly Communistcountries, such as Prague (Czech Republic)and Estonia. Due to their history, theseregions ace truly unique human-capitalchallenges. Berlin and other ormer GDR-based regions are included in this group,as we ound their statistical pro le inhuman capital terms was closer to theirex-Communist neighbours than theirWest European counterparts. Tere are16 regions in this category, encompassing117 million citizens. What then does theHuman Capital Matrix tell us about thehuman capital situation in these ourcategories?

Human Capital Endowment raditionally, many analysts and policy

makers use educational attainment ratesas a proxy or human capital endowmentand a way o measuring human capitalitsel . Tis approach has several advantages;

or example, the educational attainmento the local work orce is relatively easy tomeasure and the size o national university cohorts is well known. Tis, in turn, givessocial scientists enough hard data to builda reasonably accurate data-based analysis.But is it the right one? Te problem is,simply counting university graduates in


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11. Uniquely, this is not t he case or thinly-populated Western European regions, which show litt le t between educational at tainment and the prevalence ocomplex jobs.

12. Ederer,European Human Capital Index.

a country or region doesnt tell us nearly enough about how human capital is beingdeployed. And it tells us even less aboutthe relationship o human capital toeconomic wealth generation. As part o thisstudy, we conducted a bivariate regressionlooking at the statistical correlation o tertiary education attainment with regionalprosperity (as measured by PPP-adjustedGDP per capita), and ound the correlationwas only 29% considerably less than the

t we ound with the our Human CapitalLeading Indicators described in the rstsection o this paper (see Chart 1 on page3 or more).

But there is another way o measuringhuman capital endowment a way thatbrings together the key strands o bothcreating and attracting human capital:the share o complex jobs among overallemployment. Complex jobs are managerialpositions, entrepreneurial activitiesor pro essions that typically require auniversity education such as engineering,law or medical services. Across Europeanregions, complex and managerial work account or around 22% o all jobs; inwealthier regions, the percentage soars to33%; among the poorer regions, it allsto 13%. For a ull ranking o European

regions based on the share o complex jobsas a percentage o all jobs, see able 1 onpage 60.

Whats more, we ound that in densely-populated regions, the tertiary educationindicator and the share o complex jobsindicator are almost interchangeable (seeCharts 5 and 6 on page 10 or more). Tetwo indicators rise and all alongside o each other.11 But which comes rst? Is it theuniversity degrees that attract the complexjobs? Or the complex jobs that attract theuniversity graduates?

We believe complex jobs is a better leveror local policy makers to target because

it is a better magnet or talent, and o ersconcrete, instantly identi able, andmutually rein orcing advantages to any human capital manager who can deliver.Speci cally, complex, non-routine jobsgenerate high economic value to the regionwhere they are ound, and are accordingly well paid. But good jobs also create morehuman capital via more intensive on thejob learning than less demanding jobs,ensuring employment and high salariesand wages in the uture.12 As has beenshown elsewhere, two to three times asmuch human capital is created at the

Ex-Communist

West European Thinly-Populated

Northern Densely-Populated

Continental Densely-Populated

Economic Models at the Regional Level: Four GroupsHistorical and geographical grouping o NUTS2 Regions across Europe.


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workplace as in ormal learning institutionssuch as schools and universities. Tese areskills such as team behaviour, problemsolving, communications and leadershipas well as the unctional work skills thatEuropean workers continually learn attheir work place. Te more complex anddemanding the jobs o engineers, lawyersand managers, the more opportunity thereis or learning. And the more a personlearns, the more he will earn and improve

uture employability. What is more, thesejobs tend to have what economists callpositive externalities. Every lawyer orengineer requires or provides work ora number o other jobs, such as book keepers, production personnel, travelagents, hairdressers, and so will expandemployment also in areas with less humancapital endowment.

As the share o complex and non-routinejobs in the overall mix o jobs per ormed ina regional economy is the most importantindicator or human capital endowment,how can a regional human capital managerattract such highly quali ed jobs?

Te best, most obvious way o doing thisis by attracting inward and direct oreigninvestment. Companies bring jobs with

them, and a human capital managerwho can attract a major investmentto his or her region will see his or herhuman capital base rise proportionately.In this particular case, the chicken mostcertainly does ollow the egg. But someregions such as Bratislava and Helsinki,whose experience will be pro led in thecase studies that begin on page 16 havedone extremely well by ocusing on theegg namely, the number o locally available graduates ready or work incomplex jobs. In 1995, the governmento Finland launched 67 graduate schools,employing 722 postgraduate trainees. Tenumber o degrees con erred was used asan indicator or allocating unds amonguniversities, giving universities a strongincentive to graduate more students. By 2006, the number o graduate schoolsin Finland had risen to 124, with 1458student posts, a signi cant increase whichhad a tangible impact on human capitalendowment in Helsinki, where about hal o the degrees were based ( or more, seeChart 7 on page 11 and the Helsinki CaseStudy, which begins on page 28). Similarly,Slovakia enacted a highly success ul MBA programme, seeking to train local businessexecutives as a way o attracting oreigninvestment and raising the game o local

40%

30%

20%

10%Share of highly educated in 2007

Share of complex occupations in 2008

50%

0%

0% 10% 20% 30% 40% 50%

Charts 5 and 6: Education Leads to Better Jobs in Densely Populated Regions and in Ex-Communist RegionsComplex jobs and higher education in denselypopulated regions (excluding ex-communist).


40%

30%

20%

10%Share of highly educated in 2007

50%

0%

0% 10% 20% 30% 40% 50%

Share of complex occupations in 2008

Complex jobs and higher education in ex-communistregions.


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1600

1200

800

400

PhD students and target number (1989-2009) 1800

1400

1000

600

200

01994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

PhD Rest of FinlandPhD HelsinkiNational Target

Chart 7: Helsinki Doubled the Number o PhD Students in Response to Nationally-Mandated TargetsPhD students and target number (1989-2009).

Source: Ministry o education, Finland. The data or Helsinki region have been obtained by aggregating the data o eight universities in the region: Universityo Helsinki, Helsinki University o Technology, Helsinki School o Economics, Swedish school o Economics and Business Administration, University o Artand Design, Sibelius Academy, Theatre Academy and Academy o Fine Arts.

businesses as well (see the Bratislava CaseStudy, which begins on page 17).

In this game, densely populated regionshave inherent advantages. Lowertransaction costs and the possibility o higher specialisation make urban regionsa natural magnet or highly skilled labour.But densely populated areas must work to retain and activate human capital,as well. One policy lever or raising theshare o complex jobs could be to ocuson the provision o childcare acilities, sowomen, who statistically make up a largeproportion o the highly-educated in mostmodern societies, are not orced to leavetheir careers when they have a child, orcan quickly re-enter the work orce i they do. Seemingly small levers like these canhave a large e ect; they make it possible

or regions to retain and activate humancapital that would otherwise be lost tothem.

Human Capital UtilisationRegions can have excellent humancapital endowments, but they will ail tobene t i the human capital is le t idle orunderutilised. Tis insight has importantimplications or a regional human capitalmanager. Put simply, human capital

managers must ocus on utilising thehuman capital in their region, and notsimply because there are very good moralreasons or doing so (unemployment isa social scourge, which ought not to beso readily accepted in some Europeanregions). In act, there are very goodeconomic reasons why this must be done aswell. When people work, they contributeto the regions economic wellbeing bothat the aggregate level, where their work adds to regional prosperity, but also atthe individual level, where their personalincome will improve and their humancapital base expand thanks to on-the-jobtraining and the routine exercising o vitalsocial skills. But the ipside is also true.High unemployment is a major break onhuman-capital development. Not only do the unemployed ail to contribute tothe economic advancement o the region,but their skills can deteriorate quickly,including vital social skills and equally important on-the-job training.

We tested unemployment indicators togauge their e ect on local human-capitaldevelopment, and ound two somewhatsurprising results. First and oremost, toa much greater extent than we expected,levels o youth unemployment and long-


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term unemployment show a remarkably close correlation with prosperity atthe regional level much more than abroad basket o other employment-basedindicators, which we also tested.13 As Chart8 above shows, youth unemploymentalone shows a statistically signi cant20% correlation with regional prosperity in densely populated regions; a 27%correlation in ormerly communist regionsand ully 44% in thinly populated regions.Among the 269 regions we analysed, theaverage rate o youth unemployment is16%; in the richest regions, that rate allsto a much more acceptable 6.5%. But inthe poorest regions, it soars to 31% asocial scourge that Europe ought not tobe willing to tolerate. See able 2 on page62 or a ranking o 269 European regionsbased on their youth unemployment rate.

Even more curiously, as the wages o young people are among the lowest in thework orce, the correlation we ound hintsat a deeper connection between youthunemployment and prosperity. Put simply,youth wages are too low to have much o adirect e ect on regional prosperity. Instead,we must look deeper or what would haveto be an important, indirect consequenceo high youth unemployment namely,the knock-on consequences o having somany young people out o the work orceat a key moment in their lives. Studieshave shown and the statistical evidence

presented in this paper con rms thatyoung people unable to gain entry to thelabour market or prolonged periods o time are at a high risk o developing intopermanently peripheral members o society.Having missed out on crucial humancapital acquisition in their early careers,they become disen ranchised economically and socially, and are more likely tobecome dys unctional or even criminalwith all o the associated economic costs.Conversely, an early entry into the labourmarket orms the basis or a workingcareer and corresponding li e habits andis typically ollowed by amily ormation,homebuilding or home-making and thecreation o community bonds, all o whichhave positive income e ects. In this way,the rate o youth unemployment is astrong indicator o a regions likely level o prosperity, and an area o human-capitaldevelopment to which a regional humancapital manager would be well advised topay attention.

Te other surprisingly signi cant indicatoro human-capital employment is the shareo long-term unemployment, which onits own explains ully 18.7% o economicprosperity in European regions.14 O ten,the social protection bene ts available tothe long-term unemployed are higher thanthe economic value these people couldcreate i they were working; this is theprimary reason why many o them are

Ex-Communist

27%

Thinly-populated 1

44%

Densely-populated 1

20%

1 Excluding ex-communist regions

Chart 8: High Youth Unemployment Has a Telling E ect on Income Variation at the Regional LevelIncome variance explained by youth unemployment rates (2007).


13. Other employment-based indicators we tested, but which showed no strong statis tical relationship with regional prosperity, include male employmentrates, emale employment rates, emale employment rates o ages 25 to 35 (the mother group), elderly employment rates (both 55 to 64, and 65 andover), hours worked and labour market exit age.

14. The calculations are based on 2007 employment gures. GDP is measured in logarithmic terms.


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long-term unemployed in the rst place,and why this problem is so difcult toresolve. As a result, GDP per capita shouldbe almost una ected by the level o long-term unemployed; the economic bene to having these people in work would,a priori, be too small to matter. But thestatistics tell us otherwise, indicating aclose correlation between the rate o long-term unemployment in a region and thelevel o local prosperity.15 One possibleexplanation may be the ladder e ect; i thelowest productivity workers stay o theworking ladder, then more quali ed peoplewill occupy the lowest rung. I insteadthey get on the ladder, they orce everyoneelse to move up one rung, in e ect raisingthe productivity o the human capitalalready employed. See Chart 9 on page 14

or a comparison o the overall long-termunemployed situation in the our mainregional classi cations deployed throughoutthis study and see able 3 on page 64 ora ranking o European regions based onthe number o long-term unemployed as apercentage o overall unemployed.

For the regional human capital manager,

the implications o this nding are airly obvious. Regions that can attack theproblems o youth unemployment andlong-term unemployment stand to reapconsiderable gains, both in terms o overallprosperity as well as in terms o humancapital utilisation. Success ul regions havealready ocused on these areas, putting inplace local schemes that help to employ and train the young and re-integrate thelong-term unemployed into the work orce.Navarra is a case in point. Regionaladministrators there introduced a highly success ul vocational training programmewhich did much to lower regional levelso youth unemployment and signi cantly improve the local skill base rom whichemployers might draw. Te results wereimpressive. Youth unemployment ell by nearly 3% between 2000 and 2007, andthe proportion o skilled workers in thelabour orce rose by more than 33%, easily outpacing the Spanish national average o 26% in the same period. Likewise, So a with the help o the United NationsDevelopment Programme launched ascheme to hire the long-term unemployed

or regeneration o local building projects.

Northern v. Continental: Di erent Paths to a Similar DestinationTe di ering experience and per ormance o Europes two types o densely-populated regi the Northern European regions (namely Ireland, UK, Scandinavia and Dutch-speakingBenelux) and Continental European regions (namely Austria, France, Germany, Greece,Italy, Portugal and French-speaking Benelux) on the Human Capital Leading Indicatorssheds interesting light on an age-old question: which European social model gives the bestresults in human capital terms? Te answer would appear to be both systems seem to work quite well, though they employ radically di erent ways o getting there. Northern Europearegions boast considerably more complex jobs, and universities a ter three decades o re award considerably more degrees than their counterparts in Continental Europe. And yet,both areas get remarkably similar social outcomes: GDP per capita in the Northern EuropeaRegions is 29,300 and in Continental Regions it is 31,400 a statistical dead heat. How ithis possible? It seems likely that many jobs in Continental Europe have content comparablto similar jobs in Northern European regions, but the training or the Continental Europeanregion-based jobs occurs within companies rather than at universities. In other words, the twsystems are delivering similar results, even i the pathways to them are very di erent.

GDP per capita (PPP adjusted) Share o complex occupations Share o highly educatedNorthern Regions 29,292 30% 30%Continental Regions 31,357 23% 24%


15. The e ect is not uni orm. We ound no statistically signi cant correlation between long-term unemployment rates and GDP per capit a in densely-populated or ex-communist regions. The e ec t was only observable or the 269 regions taken together as a whole and in thinly-populated regions.


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40%

50%

60%

30%

20%

10%

Share of long-term unemployed (2007) 70%

0%

1 Exclusing ex-communist regions2 Exclusing thinly populated regions

Ex-CommunistThinly-populated 1Northern 1,2Continental 1,2

Chart 9: Long-Term Unemployment is Most Widespread in Ex-Communist RegionsBoxes show the medium 50% o the regions, whiskers show the medium 80% within each group.


Te programme particularly targeted localRoma, ethnic urkish minority and othersocially marginalised groups. In a nine-yearperiod, it created 45,609 jobs and provided12,475 people with vocational training.While many o the jobs were temporary,10,471 men and women were reported tohave ound long-term employment a terthe project. For more on best practice romNavarra and So a, see the case studies thatbegin on pages 34 and 42, respectively.

Human Capital Productivity Te third dimension o the Human CapitalMatrix is human capital productivity, orthe efciency and e ectiveness with whichactive human capital is able to work. Oneway o measuring this would be to look atthe rate o nancial investment in a regionand the returns that investment achieves the resulting di erence would serve asa simple proxy or the productivity o thehuman capital that was used to deliverthat return. But this approach is deeply problematic. For starters, it is difcult todistinguish between long-term nancialbusiness investment and short-term capital

ows (as Ireland and Iceland have recently shown). Second, the rate o nancialreturn is hard to assess as companies o tendelay taxable pro t, which is one o thevariables we would most want to measure

or purposes o this indicator. And third,nancial assets and nancial returns are

recorded poorly at the regional level.

However, we ound a di erent variablewhich is an excellent proxy or expectationsabout the uture success o regionalbusiness: the investment levels in researchand development by both the public andprivate sectors, and the number o patentsthat ow rom these investments. Tese arewell recorded on the regional level, clearly attributable to regional activities and areclosely tied to human capital investments.As proxies, R&D investment and patentsdo not create company or individualincome directly. Rather, they indicatecompanies and individuals aith in thehuman-capital productivity o the region.And the e ect high investment in R&Dand large numbers o patents existingside-by-side with high levels o regionalprosperity was observable across all ourregional groupings. See able 4 on page 66

or a ranking o European regions basedon local investment in R&D and patentapplications per one million members o the population.

What, then, are the lessons or a regionalhuman capital manager? First and

oremost, R&D and patents are only a


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proxy or real productivity, so it is notenough to simply boost them. Rather,the indicator should be used to measurerelative levels o success in other areas,namely, the regions ability to attract R&Dand to build con dence in the local areaas a business site. Put simply, the humancapital manager should ocus on improvingthe institutional, in rastructural and socialquality o the economic environment andthe integration o human capital creationwith the productive process and watch

or rising R&D per ormance as an outcomeo such institutional improvements. A casein point is Kista Science City outside o Stockholm, a locally developed sciencecommunity that today is home to 8,500companies and provides 67,172 jobs. OrEmilia Romagna, the Italian region, wherelocal administrators created new networkso universities and employers to speed theadoption o innovation. Or West Midlandsin the United Kingdom, which showed realingenuity in creating new jobs to tacklecontemporary social challenges. Teseinitiatives are discussed in greater detail inthe Emilia Romagna Case Study on page24, the Stockholm Case Study on page 48and the West Midlands Case Study onpage 53.

Te Road Ahead We began this essay by arguing that thetimes are evolving, tossing up new and ever-changing social and economic challengeswhich policy makers today are sometimesill equipped to address. But has the worldreally changed that much? In the MiddleAges, the main social institution was thevillage or manor. Te average person would

scarcely wander more than 20 kilometresbeyond the place where they were born,unless their eudal lord called upon themto wage war or amine drove them outdesperately in search o sa er climes.

And yet, even in an age o globalisation,the village remains our principal point o contact with the outside world. It is theplace where we raise our amilies, earnour livelihoods, build our homes, developour social connections and invest the vastmajority o our time. It is the rst point o contact most people have with government,policy, regulation and public administration.And, precisely because so many o us now enjoy unprecedented choice in our decisionso where to live, it is still the place wherepolicy makers should look rst i they want to conceive and deliver the kind o improvements that will sustain our way o living or generations to come.

Tat is the central message o this policy brie . Te challenge may indeed be global but the solution is local. Te evidencepresented in these pages shows that humancapital and human-capital development are areas where local policies can havethe astest and most direct e ect. A terall, nations are only collections o regions,many o them having less in common withtheir neighbour than with their peers in

ar-away lands. Nations may worry abouthuman capital, but it is the cities andregions within them that do the most todetermine how much o it there is, how e ectively it is deployed and how muchvalue it will be able to create.


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As part o this study, the Lisbon Councilvisited seven European regions Bratislava,Emilia Romagna, Helsinki, Navarra, So a,Stockholm and West Midlands to learnabout local initiatives and challenges inthe human capital eld. In each city andregion, we applied the three vectors o theHuman Capital Matrix, described on page6, to local conditions.

Te results served as an importantvalidation o the research presented in the

rst part o this paper, and o ered uniqueinsights into the human capital situationo the regions and cities themselves. Terecommendations and views expressed inthese case studies are those o the authorsalone.

Bratislava, Slovakia

Emilia Romagna, Italy

Soa, Bulgaria

Navarra, Spain

Helsinki, Finland

Stockholm, Sweden

West Midlands, UK

The Human Capital Challenge: Case Studies o Seven European RegionsAs part o this study researchers analysed the human capital situation in seven vastly di erent,geographically dispersed European regions.

Case Studies


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Overview Bratislavas impressively high gross

domestic product per capita (PPP-adjusted) places it in the No. 10 positionamong the European Union NU S2regions (See able 5 on page 68 or the

ull ranking). At 39,900, GDP per capitacomes in just below Vienna (40,600)and Stockholm (41,000). Interestingly,there are no other Slovak regions be orethe No. 219 position in this ranking.Indeed, Bratislavas GDP per capita is96% above the national average.

Bratislava attracts the majority shareo Slovakias oreign direct investment.Te region gathered 74% o the nations

oreign direct investment in 2009.16 Itsattractiveness can be attributed to threemain characteristics: 1) its convenientlocation allows it to serve both Westernand Eastern Europe, 2) the tax system,which is based on a at rate o 19%,simpli es business transactions, and 3)the level o educational attainment o itswork orce (29%) measured as the shareo individuals with a tertiary degree is noticeably higher than the nationalaverage (17%).

Women, youth and elderly (aged 55-64) are utilised well. Compared to the

gures or women and youth, whichplace Bratislava in the top 10% o all EUNU S2 regions, there may be some room

or improvement in elderly employmentas the regional per ormance is lower than24% o the EU NU S2 regions.

Bratislava posts gures in the upperechelon o the EU NU S2 regions in

nearly every category except innovation.Bratislavas level o innovation surpassesthe rest o the nation and other easternEuropean regions. However, it ares worsethan 54% o the EU NU S2 regions.Tis suggests the potential or signi cantreturns to investment in innovation.

Bratislava is one o the wealthiest regionsin Europe in terms o GDP per capita,PPP-adjusted. What policy areas can beaddressed to sustain its position amongthe other European NU S2 regions in thelong run?

Human Capital Endowment A large share o Bratislavas work orce is young,highly educated and has access to a relatively high percentage o demanding jobs. However,the quality o education and proximity to very attractive capital cities could pose problems or

uture regional growth.

Bratislavas share o workers with a graduatedegree (29%) sets it apart among the resto the nation and all o Eastern Europe.In act, this gure raises the nationalaverage o 17% as the next closest regionin Slovakia is Western Slovakia (ZpadnSlovensko) with 12.6%. While it is not the

oremost leader among the rest o Europe,it ares well compared to the Europeanaverage o 23%. Tis gure places it in the78th percentile o all EU NU S2 regions.In order to vie or a top spot, Bratislavawould need to improve by 19 percentagepoints to overtake the leader, WalloonBrabant (48%) (See able 6 on page 70

Bratislava

16. All gures re er to the NUTS2 region Bratislavsk K raj (SKOI). FDI data is our elaboration on data rom Slovak Investment and Trade Development Agency(SARIO),FDI In ow Out ow 2009 .

We still have a lot o memorisation and not enoughcreative thinking.Ivan Miklos, minister o fnance, Slovakia


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or a ranking o NU S2 regions by educational attainment).

It appears Bratislava will be able to takeadvantage o its educated population orsome time as the share o elderly aged65 and above is only 17% o the activepopulation (15-64).17

According to the ISCO distribution which measures the share o highly demanding positions in the region 27%o all jobs in Bratislava require a highlevel o skill. Tis percentage exceedsthe national average (17%), as well asthe European NU S2 average (22%)and retains a place in the 83rd percentileo the EU NU S2 regions.18 Te largegap between the quality o the jobsavailable in Bratislava and the rest o thecountry provides an explanation o theattractiveness o Bratislava or natives o other Slovak regions, which was mentionedby several people we interviewed in theregion. However, a majority o the jobsare classi ed under medium (47%)corresponding to the level o mediumeducational attainment in the majority o the working population (64%).19

According to local accounts, the quality o education is an area that could useimprovement. Slovakias Finance MinisterIvan Miklos described one issue: We stillhave a lot o memorization and not enoughcreative thinking.20

Te proximity to Vienna and Praguerepresents an additional potential threat tomaintaining Bratislavas stock o humancapital. Tere is a risk that individualswill migrate in order to seek higher wageselsewhere.

Human Capital UtilisationBratislava utilises women and youth well.Elderly employment surpasses the national average, but when compared to the Europeanaverage could use some improvement. Long-term unemployment gures are poor.

Bratislava utilises vulnerable groups, such aswomen and youth, well. Te regional youthunemployment rate is impressively low at8%. Tis is notably below the nationalaverage (19%) and the Eastern Europeanaverage (18%). Only 12% o the EUNU S2 regions can claim a better result.

Te emale employment rate is 11percentage points above the nationalaverage and surpasses the Lisbon Strategy goal o 60% with 73% o womenemployed. Tis is only 10 percentagepoints lower than the best per ormer o this category among EU NU S2 regions:the Aland Island in Finland employs 83%o its women. Tese gures are even moreencouraging considering the low share o women and men employed under part-time contracts. Only 4.35% o women and1.85% o men have part-time contracts.

Elderly utilisation stands at 54%. Althoughdecidedly higher than the national

17. For a comparison, in 2009 Emilia Romagna has a share o over 65 equal to 35% o the active population (15-64), Navarra is equal to 26%, Stockholm21%, So a 20%, Helsinki, West Midlands 24% (data rom 2008), Helsinki 23%.

18. Measured as the average o Bratislavas 4 EU NUTS2 regions.19. ISCO and ISCED Eurostat data rom 2008.20. Carter Dougherty, In Slovakia Education Becomes Growth Engine,The New York Times 25 March 2005.

There is the potential problem o brain drain,where many students and highly-skilled people goto Prague or elsewhere in the Czech Republic dueto language similarities. Prague poses

a higher threat o brain drain than Vienna. Anton Marcincin, economist or the World Bank in Slovakia and Slovenia


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average (38%), Bratislava remains in the76th percentile o all EU NU S2 regionsand arther still rom the leading Europeanregions. Bratislava would need to increasethis gure by 19 percentage points to catchup with top per orming Smaland and islandsin Sweden. Te regions exit age exacerbatesthese gures. Bratislava ollows the nationaltrend by exhibiting the shortest working li eamong all EU NU S2 regions with an exitage rom the job market o 58.7 years old.Over time, the early average retirement agewill inevitably reduce the total number o hours spent working. Currently total hoursworked are still considerable and lie above89% o EU NU S2 regions. Employees inBratislava work 69% o the available hours.Te room or improvement is more evident i we consider 20% o Eastern European regionspost higher gures or total hours worked.

At 54%, Bratislava records the lowest long-term unemployment rate among all Slovak regions and is about 30% lower than thenational average. However, this per ormancediminishes when compared to the other EUNU S2 regions. In act, it appears to be athreat to regional growth as only 21% o the other European NU S2 regions have ahigher long-term unemployment rate.

Human Capital Productivity Innovation should be a top priority or uture regional growth.

Our innovation indicator based onpublic R&D expenditures, business R&Dexpenditures, and EPO patents ranksBratislava above 82% o other Eastern Europeanregions. Tis impressive per ormance is severely reduced when compared to all EuropeanNU S2 regions as it alls behind 54% o the regions. Tis assessment is consistentwith the Regional Innovation Scoreboardwhich ranks Bratislavas innovativeness asaverage on a scale o low, average, mediumhigh and high. Te other Slovakian regionsscore as low innovators.

Government expenditure on R&D isparticularly detrimental to the ranking asonly 0.44% o GDP is allocated to R&Dthrough government mandate. Althoughexpenditures by universities have increasedover time, this contribution is stillinsigni cant at 0.26% o GDP. Possibly the most worrisome gure is that o privatebusinesses and enterprises. Expendituresin R&D as a share o GDP have decreased

rom 0.39% in 2002 to 0.14% in 2007.

Compared to traditional sectors, the automotiveindustry is characterized by aster changes andrequires more analytical work.

Jan Leinsk, academic director, STU

21. Slovak Universit y o Technology,Pro essional MBA Automotive Industry .

Best Practice rom Bratislava: MBAs and the University o the Tird Age

MBA automotive sectorBratislava and its surrounding regions produce more than our million cars every year.21 While Bratislava has a sufcient number o graduates, the carmakers and their suppliershave trouble lling managerial positions with candidates o appropriate experience andskills. A new MBA solves this challenge.


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22. The overriding objective o the ACVR acti vities is to concentrate automotive expertise in the Vienna Region and to initiate innovative projects, in order toincrease the competitive ability, the R&D quota, and the value creation and innovation level o the partner enterprises.

23. Slovak University o Technology,Pro essional MBA Automotive Industry .24. Jaap de Koning,Incentives to Take Up Work and Remain at Work Long er (Rotterdam: Erasmus University Rotterdam, 2005).25. See Centre o Continuing Education, University o the Third Age 2010/2011 (Bratislava: University o the Third Age, 2010).

It was the summer o 2006 when Jan Leinsk, academic director o the Slovak University o echnology in Bratislava, began to apply himsel to nding a solution. Healso intended to discover how university teaching time should be structured to meet thereal needs o the automotive industry. ogether with the Automotive Cluster ViennaRegion, which was looking or a cooperative partner, he decided to conduct a survey in17 automotive companies in Slovakia and Austria.22 Te aim was to better understand theskills and expertise required o the ideal automotive manager or technician. Te answersto the surveys represented the basis or setting up a pro essional MBA programme or theautomotive industry, which was open to recent graduates as well as candidates with work experience. Te MBA, tailored on the companies surveyed needs, is a part-time Masterrequiring our days a month and ten hours per day.23

Tis initiative is likely to create value or both participants and employers. Participantsare more likely to nd a job aligned with their skills and training and eel more preparedto enter the job market. Employers obtain personnel with the right skills to raise thecompanies productivity and acilitate growth.

University o the Tird AgeAs a persons productivity is likely to start decreasing a ter a certain age, the ageingprocess could lead to a decline in macroeconomic productivity. However, such a patternis not inevitable.24 Te establishment o the University o the Tird Age at ComeniusUniversity in Bratislava in 1990 is a good example o a uture-oriented strategy in thisregard. Te U A o ers a three-year programme or people over 50. During the rstyear the students are o ered basic lectures in each o the o ered disciplines. Te courseso study range rom pharmacy to economics, rom computers and in ormation to law.Second and third year students can enrol in specialised elds. Moreover, in additionto lectures and seminars, the University organises other activities to complement thepedagogical process such as: excursions, panel discussions, visits to other universities,in ormal meetings, visit to theatres and thematically conceptualised trips. Te interestin the programme has increased over time. Te number o senior students enrolledwent rom 235 in the academic year 1990/91 to more than 1800 in the academic year2009/2010.25 A ter completing their study the students are given certi cates.

Tis initiative helps the elderly maintain an agile mind and update their skills. Bothcharacteristics represent necessary pre-conditions to promote long-term utilisation o elderly in the job market without decreasing their productivity and competitiveness.

The MBA gave me a helicopter view inside theactory and made me able not only to produce

in ormation, but also to use that in ormation, toconnect the in ormation together and to give the

complete story.Participant in the automotive MBA master edition started in March 2009


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RecommendationsEvaluating the per ormance o theregion through the human capitaldimension allows us to ocus on themain challenges and provide concretepolicy recommendations that could helpBratislava develop and deploy its humancapital.

Bratislavas overall per ormance isexemplary compared to the other regionso Slovakia and all o the Eastern Europeanregions. However, public and private R&Dexpenditures should be increased or else theregion risks losing its competitive edge inthe near uture.

Fostering innovation, increasingcooperation between universities andbusinesses and youth entrepreneurship iscritical.

Given the attractiveness o the regionor oreign businesses the region could

create value by emulating Stockholmscreation o Kista (See the StockholmCase Study, which begins on page 48).Te creation o a business cluster canreduce obstacles to innovative e orts.Te lack o nancial resources is oneexample. Additionally, closeness betweenuniversities and businesses could

acilitate the alignment o educationalcurricula with the needs o employers.Tis would eventually smooth the hiringprocess or high skilled positions in theircompanies.

Te Automotive MBA is an interesting andvalid project. It can serve as a lighthouseproject to lead the way or tailoring othereducational paths to businesses needs.Increasing internship opportunities duringstudies could be an additional method toenhance students preparation or enteringthe job market.

Encouraging youth entrepreneurshipcould be a way to retain graduateswhile simultaneously maintaining andenhancing the competitive strengtho an economy. Te entrance o a new

rm into a particular market orces theincumbent rms to react by improvingefciency or introducing innovation.26 A best practice example or osteringyouth entrepreneurship is the creationo the Aalto society in Helsinki (see theHelsinki Case Study, which begins onpage 28).

Increase the working li e o the population.

Te University o the Tird Age is abene cial initiative because it assistselderly in maintaining a youth ulmentality that is a pre-condition

or productive utilisation o thisdemographic group. Tis also increasesthe incentive or employers to hire andemploy elderly longer. Additional policiesshould be adopted that aim to increaseretirement ages.

I eel I am appreciated and not a burden on society.Instead, I can be use ul and also teach somethingto my nephews or people in general. Student at the University o the Third Age, Comenius University

26. Isabelle de Voldere, Eva Janssens, Jonas Onkelinx, Leo Sleuwaegen,The Creative Economy Challenges and Opportunities or the DC Regions, (Ghent:Flanders District o Creativity, 2006).


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27. For a comparison: Catalua and Antwerp have an ISCED share twice as high as Emilia Romagna.

Overview Emilia Romagna is among the wealthiest

regions in Europe. Its GDP per capita(PPP-adjusted) o 31,900 is 27% abovethe national average and has steadily increased over the past 10 years. Tisputs the region in the 88th percentile o all EU NU S2 regions. It is anked by Catalua (85th percentile) and Antwerp(91st percentile) and among our sample o regions it approaches Navarra (32,900 percapita) and Helsinki (33,800 per capita).

However, compared to these regions,educational attainment in EmiliaRomagna is relatively low. Only 15% o its working population has engaged inhigher education. Tis gure is not only signi cantly lower than regions withsimilar GDP per capita, but it is also low when compared to all o the EU NU S2regions. Only 20% o the cases present

gures lower than Emilia Romagna.27 Emilia Romagnas share of demanding jobs

(18%), measured by the ISCO distribution,is lower than the Italian average (19%) andthe EU NU S2 average (22%). Tis placesthe region in the 37th percentile o allEuropean NU S2 regions.

Youth unemployment and femaleemployment place the region in theupper-middle o all EU NU S2 regions,but the elderly employment gureremains in the lower echelon. Comparedto the EU NU S2 regions, EmiliaRomagna is in the 76th percentile oryouth unemployment, 58th percentile

or emale employment and the 31st

percentile with regard to elderly employment.

What regional dynamics enable EmiliaRomagna to post such high GDP guresin the ace o medium-level educationalattainment o its work orce?

Human Capital Endowment Matching the needs o local industries by requiring more specialised technicians thangraduates, means lowering the educational attainment level o the regions working age population. Although learning on the job holds great importance, the high quality o educationprovided suggests that the region has huge potential in terms o its work orce. I tapped, aneducated work orce could boost the productivity o the region.

While the per ormance in terms o ISCEDshare is weak, the quality o education inEmilia Romagna is high. According tothe 2006 PISA survey Emilia Romagnasper ormance is above the OECD average,with 510 vs. 500 points scored and well abovethe national score o 475.

Te regions ability to match the needs o its industrial sector with the supply romits educational institutions is remarkable.According to the ISCO distribution, amajority o the jobs are classi ed undermedium (52%) and thus correspond tothe educational attainment level o themajority o the population. Businessesin the region do not necessarily need

Emilia Romagna


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graduates. Graduates are too expensiveand o ten too ar rom the entrepreneurialtradition o the regions businesses. Te sizeo the regions SMEs does not enable themto ully exploit the potential o a graduate.Instead, businesses usually employ young,specialised technicians, coming rom themany pro essional schools o the region.

echnicians who will end up workingas middle-managers, thus testi ying thepro tability o their occupations.

Te key in Emilia Romagna is the role o learning on the job. Pro essionals enterbusinesses and basically complete andexpand their education there, tailoring itto the needs o the enterprise. Says ChiaraBentivoglio o the Banca dItalia: Oursmall companies produce niche goodsand require youth with work experience.Learning on the job has a great importancein these realities.

Human Capital UtilisationAlthough the region lacks highly quali ed human capital, it utilises women, youth and immigrants well. Tere is room or large improvements in elderly employment gures.

Emilia Romagna well utilises vulnerablegroups, such as women and youth. Te

emale employment rate is well above thenational average and with 67% o womenemployed surpasses the Lisbon Strategy goal o 60%.28 Te regions tradition o providing child care acilities compliments

this gure. Emilia Romagna boasts thehighest number o kindergarten placeso any region in Italy.29 Te utilisation o youth in the region is also notable. Withan 11% youth unemployment rate, only 24% o the EU NU S2 regions can claima lower number.

Figures or elderly per ormance are low.Emilia Romagna lays claim to one o thehighest proportion o elderly to workingage populations in Italy.30 As this trenddoes not show signs o changing in theimmediate uture, elderly work orceparticipation is key to maximizinghuman capital utilization in the region.Currently, only 38% o elderly participatein the regional work orce. Consideringabout 30% o the European NU S2regions per orm worse, this suggests thereis signi cant room or improvement.Despite these gures, the regions totalhours worked remain above the Europeanaverage, placing Emilia Romagna in the64th percentile.31 Tis result is partly dueto the regions proactive e orts to increasethe integration o migrants who make upa large share o the regional population.32 Not only do immigrants contribute to thelocal economy by per orming jobs whichmay be considered unappealing to nativeItalians, they o er an additional bene t.Te low average age o migrants (31 versus45 in the autochthonous population) may help alleviate the issues arising rom anageing population.

28. First region in Italy or emale employment; national average: 46.6% (2007).29. Emilia Romagna also shows best results among Italian regions both or the number o children attending kindergartens (24% o children between 0-2),

and or the percentage o municipalities o eri ng childcare services (81.8% o the municipalities, which account or 96.8% o t he children in the region).ISTAT, Lo erta comunale di asili nido e altri servizi socio -educativi per la prima in anzia, p.3, 2010 (http://www.istat.it/salastampa/comunicati/non_calendario/20100614_00/testointegrale20100614.pd )30. The elderly dependence ratio, which indicates the number o elderl y (65 and over) per 100 people in the ac tive population, is equal to 34.7 against anational average o 30.7. This indicates that in Emilia Romagna 34.7% o the active population are over 65 years old. This is 4 percentage points morethan in Italy as a whole.Indicatori demografci 2009, ISTAT, February 2010

31. The European average re ers to the average per ormance o the European NUTS2 regions.32. In 2008, 8.62% o the population were immigrants


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Human Capital Productivity A strong ocus on innovation and the ability o local businesses to compete on international markets through quality and niche products balance out rather weak educational attainments and allow the region to be among the wealthiest in Europe.

Te Regional Innovation Scoreboardclassi es Emilia Romagna as a medium-high innovating region. Tis is consistentwith our innovation indicator basedon public R&D expenditures, businessR&D expenditures and EPO patents which rates Emilia Romagna higher than79% o the European NU S2 regions.Te industrial sector is permeated by small businesses which represent theengine o economic expansion and wealthcreation. Small businesses amily-run or

organised in cooperatives are centres o employment, development and learning.Tey are the locus o working and socialli e.33 Te regional productive system ischaracterised by some important clusterscomposed mainly o SMEs, but alsolarger companies or co-operatives. Temain clusters are automotive, industrialmachinery, agricultural machinery, engines,biomedical and precision mechanics,shipbuilding, construction, agro- oodand ashion. World-leading brands in theautomotive sector, such as Ferrari, Ducati,Lamborghini and Maserati, are locatedin Emilia-Romagna Region and representthe best-known regional champions. Teregion maintains its competitive edge oninternational markets through high quality and niche products.

33. In June 2009, there were 5,545 cooperatives with 175,554 people working (8.98% o the working population o individuals aged 15 years and over in thewhole region). Data rom Eurostat and Il sole 24 ore,COOP pi orti della recessione , January 2010.

Best Practice rom Emilia Romagna: Research and Social Integration

Regional Programme or Industrial Research, Innovation and echnology rans er(PRRII )In 2002, Emilia-Romagna adopted a law aimed at acilitating and supportingthe collaboration between enterprises and the research system and promoting thequali cation o human capital in universities, research centres and enterprises in theresearch, innovation and technology trans er elds. In 2003, the Productive ActivitiesOfce o the Emilia-Romagna regional government started the Regional Programme orIndustrial Research Innovation and echnology rans er (PRRII ) to implement thelaw. Te High echnology Network was created, composed by a number o specialisedindustrial research laboratories and innovation centres dedicated to applied researchbased on interests, needs and technology trans er.

Te High echnology Network, organised into thematic technology plat orms, hasevolved towards the so called echnopoles, ten research acilities hosting the existing 34industrial research laboratories o the High echnology Network o Emilia-Romagna.


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It is organised in 43 di erent locations. Currently 1600 researchers are at work, o which 560 are new sta , committed to nding solutions or companies in the region, totrans ering technology and knowledge and to translating them into innovative productsand processes. Te echnopoles are oriented towards the most signi cant industries inthe region: high-tech mechanics, ood, buildings, energy and environment, navigation,biotechnologies, IC and multimedia. Te total commitment or this regional researchin rastructure amounts to 137 million (o which 94m come rom the ROP ERDF),which, together with the contribution o universities and research institutes (90 millioand rom the local authorities (14 million), brings the total investment to 241million

or the 2007-2013 programming period.

Regional programme or the social integration o immigrantsEmilia Romagna has the highest international net migration in Italy: in 2009, 10,5%o the population came rom other EU or non-EU countries compared to a nationalaverage o 7%.34 Migration implies positive human capital externalities or the receivingregion only i it is combined with social and cultural integration. In recognition o thisthe region took action in 2000 by partnering with local authorities. As a result o theircombined e orts, they launched a speci c regional programme or the social integratioo immigrants. Te aim o this programme was to curb discrimination o migrants,raise the trust level in the community and oster growth. Emilia Romagna adoptedregional law 5/2004 which was the rst system-wide re orm o the legal system withregard to immigration issues to be approved in Italy. In February 2006, the regionalgovernment complied with the law by adopting a three-year programme 2006-2008 toidenti y actions that would increase the social inclusion o oreigners. Tis was ollowin 2009 by the launch o a second three-year programme. Te priority action-itemsidenti ed by the programmes to oster immigrant integration ocus on language skillsantidiscrimination and cultural mediation measures. It introduced 40 indicators whichmeasure the integration level o oreigners in the region to monitor the program and itresults.

Te gures show evidence o improvements between 2004 and 2008 along most o theindicators. Te graduation rate o oreign students in high school increased 13%, the gabetween graduation rates o oreigners and Italians in high school reduced to one-eighand the number o oreign children in socio-educational services (0-3 years) increasedby 32%.35 Tese results highlight the ability o the region to improve equality, skills andaccess to services or migrants. Tese qualities are vital to promoting a diverse, sociallycohesive community where the bene ts o immigration ow more reely and quickly.

We have improved a lot in the last years.We have more workers, more amilies, more longterm residence permitsit means that we start tohave a history o success ul migration.Andrea Stuppini, head o social policy services or the acceptanceand integration o immigrants

34. Osservatorio regionale sul enomeno migratorio,Limmigrazione straniera in Emilia Romagna, 2010 and local interviews35. Data rom Osservatorio regionale sul enomeno migratorio


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RecommendationsEvaluating the per ormance o the regionthrough the human capital dimensions allows us to ocus on the main challenges and provide concrete policy recommendations that could help Emilia Romagna develop and deploy its human capital.

Despite having reached an advancedlevel o development, the region lagsbehind with respect to the expected levelo education. Tis should be seen asan opportunity to improve the regionscompetitiveness, rather than an obstacle.

Increase the human capital endowment.Te region has the potential to increaseits human capital stock by increasingthe educational attainment level o itswork orce. Tis would translate intohigher productivity or businesses.In this respect, the West Midlandsapproach o showing businesses thebene ts o graduates within the company should be a good example or EmiliaRomagna (see the West Midlands CaseStudy on page 53).

It will be difcult to increase the stock o human capital without adjustments in theskill requirements o employers.

Stress the approach promoted within theechnopoles project which aims at sharing

knowledge, skills and persons, with aninterdisciplinary logic that needs to bevalorised. Tis will lead to a better share o resources between businesses.

Increase the cooperation betweenuniversities and entrepreneurs in orderto better reach the regional developmentobjectives and to promote a strongerknowledge based economy. Universitiescommercialisation o products andcollaboration o businesses with researchinstitutions is still low. A good step

orward is represented by SPINNER 2013, the programme launched by EmiliaRomagna to support individuals interestedin developing innovative business ideas incollaboration with universities, researchcentres and enterprises36. Emilia Romagnacould also bene t rom re erencing theKista approach in this respect (see theStockholm Case Study on page 48).

Te large share o immigrants working inlow-skilled jobs or low wages represents anadditional constraint on the regions attemptto increase the quality o jobs because they increase the comparative advantages o medium-low technology sectors.

Attract more quali ed migrants. Despitethe lack o a ull coverage statisticalsystem or these gures, Emilia Romagnaappears to share some national trendsby attracting immigrants withoutsophisticated competencies or higheducational attainment. Te region shouldincrease its e orts to attract more quali edimmigrants so that beyond the increasein the ertility rate, migration could alsoproduce a growth e ect on wealth where,on average, a rise in the human capitallevel increases GDP per capita.37

36. Spinner 2013 is an action o the Regional Operational P rogramme (ROP) 2007-2013 o the European Social Fund (ESF), Axis I V Human Capital, Objective 2Regional Competitiveness and Employment supported by the Regional Department or Education, Pro essional Training, University and Research, Laboro Emilia-Romagna Region

37. Tito Boeri,Immigrazione e crescita (Milan: Fondazione Rodol o de Benedetti, 2010).


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According to a survey o 41 Italianuniversities (where 91% o oreign PhDstudents are enrolled) the main obstaclesdiscouraging students rom studying inthe country are red tape and low Englishpro ciency even among the publicadministration.38

Emilia Romagna should prepare orthe eventual aging o its population by improving the utilisation o its elderly work orce.

Deal with demographic change. In orderto counter the negative e ects o an ageingpopulation, the region should implementmeasures promoting longer work lives.Tese measures should provide incentivesto employers to hire older workers and

motivate the elderly to work longer.Promoting li e-long learning is

undamental to maintaining high elderly productivity. Highly educated workershave considerably higher chances to remainemployed at older ages than those withlower education. Furthermore, requenttraining and mobility during ones workingli e reduces the chances o unemploymentand inactivity later in li e.39 I a system o li e-long learning unctions well, elderly employees could serve as mentors oryouth entering their companies. Tiswould enable elderly employees to trans erknowledge and experience, speed up on-the-job training and simultaneously reducetheir incentive to retire early by lighteningtheir workload.

38. The survey was carried out by the Fondazione Rodol o de Benedetti bet ween April and May 2009.39. Jaap de Koning,Incentives to Take up Work and Remain at Work Longer (Rotterdam: Erasmus University, 2005).


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Overview Helsinki is a top performer in terms of

its highly educated work orce and shareo demanding, high-skilled jobs. With40% o its working population engagedin tertiary education, Helsinki exceedsthe national average (33%) as well as theEuropean NU S2 average (23%) andretains a place in the 98th percentile o allNU S2 regions.40 According to ISCO,33% o Helsinkis jobs are classi ed ashigh-skilled positions compared to 22%in the EU NU S2 regions.

Utilisation of human capital amongdi erent demographics revealsinconsistencies. While Helsinki remainsin the highest percentiles or its emaleemployment rate (97th) and elderly (aged55-64) employment rate (88th), its youthunemployment rate (14%) is higherthan 45% o the EU NU S2 regions.Compared with other densely populatedregions, this number ares worse as 56%have lower youth unemployment.

Innovation aids Helsinkis regionalcompetitiveness. Helsinki ranks No. 5and No. 6 out o 268 European NU S2regions in the Regional CompetitivenessIndex or innovation and overallcompetitiveness, respectively. Tis isconsistent with our indicator whichplaces Helsinki in the 95th percentileamong densely populated regions.

Helsinkis GDP per capita (PPPadjusted) is strong overall; however,comparing gures to other densely populated regions reveals some room

or improvement. GDP per capita rom

2007 shows a strong overall per ormanceat 33,800. Tis places the region inthe 91st percentile o all EU NU S2regions. However, the gure alls to the76th percentile when compared to similardensely populated regions.

Helsinki is well endowed with educatedhuman capital and highly demandingjobs and is considered one o the oremostregions in terms o innovation. Whatpolicy areas can be addressed to raiseGDP per capita to the level o other topper orming regions?

Human Capital Endowment Helsinki has a high rate o tertiary educationand large share o high-skilled jobs .

Helsinki boasts one o the most educatedworking populations in Europe and hasthe highest share in Finland as a whole.Forty per cent o its workers have takenpart in post-secondary education comparedwith a national average o just 32.7%.Tis puts Helsinki in the 98th percentileo all European NU S2 regions and not

ar behind the top per ormer, BrabantWallon (48%). According to the ISCOdistribution which measures the regionsshare o highly-demanding occupations 33% o the positions available to theseskilled workers are highly-demanding jobs.Compared with an EU NU S2 regionalaverage o 22%, this suggests economicconditions in Helsinki are quite avourable.

Helsinki

40. All gures re er to the NUTS2 region Etel-Suomi (F I18).


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41. The data or Helsinki region have been obtained by aggregating the data o eight Universities in the re gion: University o Helsinki, Helsinki Universit y oTechnology, Helsinki School o Economics, Swedish School o Economics and Business Administration, University o Art and Design, Sibelius Academy,Theatre Academy and Academy o Fine Arts. Ministr y o Education, Finland.

Not only does Helsinki have a highshare o educated workers, their overalleducational attainment level is high as well

LISBON COUNCIL Human Capital in Regions and Cities

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