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Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok...

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Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow
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Page 1: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Students as catalysts of city and regional growth

Mark Livingston, Moira Munro and Ivan Turok

University of Glasgow

Page 2: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

“Britain’s great teenage transhumance”

Students - rapidly growing section of city populations:– 0.8m (1991) - 2.3m (2005)– Transient – but distinct (& relatively fixed) characteristics– Increasingly varied (though social disparities remain)– A growing target of policy attention – talent attraction

Potential impacts:

1. Source of (skilled) labour supply

2. Stimulus to neighbourhood revitalisation

3. A catalyst for new consumer services & amenities

4. Intangible effects: atmosphere, image, reputation

Page 3: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Especially important in former industrial cities?

• Economic diversification• Human capital in-migration• Low demand housing• Richer amenities• Image enhancement

• AND student location decisions less influenced by state of the local labour market so can help to initiate growth

Page 4: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Objectives

• Analytical framework to examine effects on cities, neighbourhoods and disadvantaged communities

• Net effects at regional scale (origins & destinations)• How effects differ between types of HEI and regional

contexts• Tensions and policy lessons

Methods• Quantitative national picture of student places• 5 case studies across the UK for causal relationships

and detailed impacts

Page 5: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Example of simple typology

HEI Type Student

origin

Graduate destination

Examples

Local ladder Local Local ?

Springboard Local Elsewhere ?

Magnet Elsewhere Local ?

Training ground Elsewhere Elsewhere ?

Page 6: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

1. Students as workers

• Do students occupy distinct niches or displace locals for jobs?– Great majority work in ‘low value’ service industries

• Students may offer:– Flexibility– Greater social capital & soft skills– Lower wage expectations?– Specialised skills?

• Could block entry points, depress wages, increase casual work

• But could attract/retain businesses, foster learning, increase competitiveness

Page 7: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Student workers (2001 census)

% of students economically active

England 36.3

Scotland 44.0

Wales 33.0

Page 8: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Student workers

% of students economically active

% of economically active students living at home

Gloucester 53.7 44.3Aldershot 52.9 49.5Swindon 52.4 40.6Ipswich 51.7 33.2Worthing 51.2 50.2Milton Keynes 50.7 42.8Wigan 50.4 65.3Southend 49.3 52.1Crawley 49.2 54.4Peterborough 49.0 41.8Blackburn 48.9 49.7Warrington 48.5 54.0Hastings 48.5 40.7Blackpool 48.4 51.9

% of students economically active

% of economically active students living at home

Leicester 34.16 28.39Newcastle 33.37 36.26Manchester 33.15 31.45Leeds 33.05 19.49Liverpool 32.56 34.74Bristol 32.25 21.49York 31.35 14.14Norwich 31.08 19.49Southampton 30.34 16.88Hull 29.89 23.42Sheffield 29.58 23.44Coventry 28.55 23.88Nottingham 25.86 20.32Oxford 19.24 5.73Cambridge 14.26 7.39

Page 9: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Students and economic activity

Economically active students as a % of economically active population

Oxford 7.08Cambridge 5.28Southampton 3.99Coventry 3.63Brighton 3.60Leeds 3.51York 3.46Luton 3.34Leicester 3.34Plymouth 3.17Liverpool 3.10Nottingham 2.79Sheffield 2.71Derby 2.70London 2.68Bristol 2.68

Page 10: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Hours worked

% of students

1-2 hours 0.7

3-5 hours 4.0

6-15 hours 36.9

16-30 hours 30.2

31-37 hours 9.2

38-48 hours 14.9

49 + hours 4.1

Page 11: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

More students tend to work where there is more work

0

10

20

30

40

50

60

40.0 45.0 50.0 55.0 60.0 65.0 70.0 75.0

overall employment rate (%)

% o

f s

tud

en

ts e

mp

loy

ed

Page 12: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Students work more where more students work

% Economic active vs % of full time working students

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

% of full time students

% E

cono

mic

ly a

ctiv

e

PUA

Page 13: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

2. Student as residents

• Negative media portrayals are common:– Anti-social, attract crime, create grime, undermine

neighbourhood cohesion– ‘Studentification’ and displacement

• BUT also – vibrant, ‘buzzy’ quarters; novel and interesting businesses; social diversity

• Can students help neighbourhood regeneration?

Page 14: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

How students live

0%

20%

40%

60%

80%

100%

England Scotland Wales

Other

Alone

Student hhlds

Communal

With Parents

Page 15: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

% of population that are students

Aldershot 1.2Warrington 1.2Wakefield 1.2Ipswich 1.2Burnley 1.2Milton Keynes 1.2Barnsley 1.1Wigan 1.1Worthing 1.1Crawley 1.1Gloucester 1.1Hastings 1.0Swindon 1.0Doncaster 1.0Peterborough 0.9Mansfield 0.9Grimsby 0.9Southend 0.9

Cambridge 17.0Oxford 16.7Southampton 6.5Coventry 5.7York 5.5Leeds 5.1Nottingham 5.0Brighton 4.9Leicester 4.5Sheffield 4.2Bristol 4.2Plymouth 4.1Liverpool 3.9London 3.6Luton 3.5Norwich 3.5Newcastle 3.5

Page 16: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Leeds: Census 2001

Page 17: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Bradford: Census 2001

Page 18: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Students & area deprivation

0

2

4

6

8

10

12

14

16

18

20

Least 2 3 4 5 6 7 8 9 Most

England

Scotland

Wales

(Students living independently)

Page 19: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Bristol

Page 20: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Newcastle

Page 21: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

3. Students as consumers

• Supporting the night-time economy• Demand for (& supply of) culture, arts, music,

entertainment – lively attractive urban areas• Can these amenities help to attract other forms of

investment?

Page 22: Students as catalysts of city and regional growth Mark Livingston, Moira Munro and Ivan Turok University of Glasgow.

Conclusions

• Initial support for significance of students as workers and residents

• Suggests different kinds of ‘student cities’ with different kinds of impact, positive and negative

• Next steps:– More data analysis– And then case studies…


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