r$ conference halifax 11/2007 niosi1 towards competitive clusters in the maritimes jorge niosi...

R$ Conference Halifax 11/2007

Niosi 1

Towards competitive clusters in the Maritimes

Jorge Niosi

Canada Research Chair on the management of technology

Université du Québec à Montréal

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This presentation The Atlantic and Canadian clusters How to build competitive clusters:

attracting and creating human capital Knowledge production: University research, public and non-profit laboratoriesAttracting or nurturing private users of knowledge: innovative firms and spin-offsKnowledge localization: technology parksRegional advisory bodies: City committee for STIPicking sectors and locations

How to do it?

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Canadian and provincial STI policy Canada has developed an array of STI

policies nurturing the development of many new industries (aerospace, ICT, biotechnology, and others): tax credits for R&D, R&D subsidies for SMEs, university research councils, Technology Partnerships...

But, in spite of these policies being national, those new industries agglomerate in a few large metropolitan areas.

These Canadian regions are privileged by immigration, population and provincial policy

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The present situation in Canada Canada is one of the most cost-effective countries to

conduct R&D, coast to coast Yet, most innovation is concentrated in the nine

largest metropolitan areas: the 9 largest CMAs represent 50% of the country’s population, but 77% of industrial R&D expenditures, and 72% of scientist and engineers working in industrial R&D

Two methods are used to measure innovation: industrial R&D and patents

Both indicators point towards the dominance of Toronto, Montreal, Ottawa and Vancouver.

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The present situation in Canada Also, regions are not converging: increasing

differences in income and productivity, as well as population and R&D efforts are evident.

Between 1988 and 1999, Ontario’s productivity increased by 1.2%, by 0.4% in Quebec, 0.3% in Western Canada, and 0.2% in Atlantic Canada (according to Statistics Canada, 2006)

The four provinces of Atlantic Canada had in 2001 several thousand dollars in income below the Canadian average.

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Population in Canadian CMAsTab l e 1.1 : Canada’s popu l a t ion i n l a r gest C MA , 2002

CM A P o pu l a t i o n %

T o r o n to 5,020,447 16

M o n t rea l 3,547,112 11

Va n c o u v er 2,111,305 7

O tt awa Ga t i n eau 1,118,819 4

Ca l gar y 1,002,030 3

Ed m o n to n 979,907 3

Qué b ec 701,564 2

Ha mil to n 697,891 2

W i nn i peg 693,685 2

9 L arges t CM A s 50

T ot a l 31,372,58 7 100

S o urce: S t a t i s t i cs Ca n ada

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Industrial R&D in 2002 R&D activity in Canada is geographically concentrated

CM A CIE o n R & D

(C$000)

(suppressed

v a l ues)

% CIE o n

R & D

(C$000)

(es t im a t i o n )

R & D

Es t a b li s h m e n t s

(N)

% Sc i e n t i s t s &

E n g i n eers

(N)

%

T o r o n to 3,139,685 26 3,139,685 2345 19 14458 23

M o n t rea l 3,087,891 25 3,087,891 3066 25 15814 26

Va n c o u v er 605,728 5 605,728 813 7 4269 7

O tt awa Hu ll 838,713 7 2038,713 610 5 5837 9

Ca l gar y 287,687 2 287,687 424 3 1374 2

Ed m o n to n 70,961 1 70,961 218 2 580 1

Qué b ec 109,912 1 109,912 465 3 1122 2

Ha mil to n 37,880 0,3 37,880 206 2 320 0,5

W i nn i peg 47629 0,4 47629 194 2 333 0,5

9 L arges t

CM A s

8,226 ,086 66 9,426,086 8341 67 4 4107 72

T ot a l 12,257,169 100 12440 100 61624 100

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BERD is concentrating outside the Maritimes

1994 2003 1994 2003$ M $M % of GDP % of GDP

ON 4,112 7,066 1.32 1.43

QC 2,056 4,115 1.21 1.62

BC 591 1,075 0.59 0.74

AB 509 779 0.58 0.46

MN-SK 172 209 0.34 0.28

Atlantic 125 147 0.27 0.20

Canada 7,564 13,350 0.99 1.10

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Industrial R&D in 2002R&D activity in Canada is also industrially

concentratedSec to r R & D

e x pe n d i t ures

(C$ 000)

% R & D

Es t a b li s h m e n t s

% Sc i e n t i s t s

&

E n g i n eers

%

C o mm u n i ca t i o n equ i p m e n t 3,092 ,922 2 5 132 1 12 891 20

P h ar m aceu t i ca l s & m ed i c i n e 1,032,931 8 108 1 1938 3

C o m pu t er s y s t e m s & des i g n 983,234 8 1781 14 8920 14

A er o space a n d pr o duc t s 876,623 7 75 1 2387 4

Sc i e n t ifi c R & D 778,284 6 570 5 4393 7

Se mi c o n d uc to r &

O t h er c o m p o n e n t s

692,405 6 141 1 3645 6

I n f o r m a t i o n & cu l tu ra l

i n dus t r i es

643,886 5 449 4 4261 7

Wh o l esa l e t rade 558,797 5 958 8 2666 4

A rc h i t ec t ura l , e n g i n eer i n g

An d re l a t ed ser v i ces

417,161 3 640 5 3604 6

Mac h i n er y 416,337 3 955 8 2223 4

Na v i ga t i o n a l , m easure m e n t ,

Med i ca l & c o n t r o l

i n s t ru m e n t .

405,814 3 259 2 2712 4

M oto r v e h i c l e & pa rt s 388,262 3 172 1 1592 3

Paper 365,518 3 103 1 430 1

Hea l t h care & s o c i a l

A ss i s t a n ce

345,663 3 103 1 1096 2

F o ur t ee n m a i n sec to rs 8,071 ,984 66 6,446 53 52 215 8 5

A ll sec to rs 12,257,169 100 12,440 100 61,624

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Large CMAs host many sectors: Toronto

Figure 1.10: Toronto CIE on R&D 2002 -

Main sectors

15%

10%

9%

7%

7%7%4%

4%

4%

4%

3%

26%

Pharmaceuticals &

medicine

Semiconductor &

comp.

Computer system

design

Wholesale trade

Aerospace prods

Scientific R&D

Communication equip.

Machinery

Motor vehicle & parts

Finance, ins., real

estate

Navigational,

meas.med.

All other industries

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…and Montreal

Figure 1.12: Montreal CIE on R&D 2002 Main sectors

17%

13%

8%

7%7%7%6%

5%5%

4%4%

17%

Aerospace prods

Pharmaceuticals &medicineHealth care & SocialAssis.Arch., engin. & related

Communication equip.

Information & cult. Ind.

Computer system design

Wholesale trade

Scientific R&D

Navigational, meas.med.

Paper

All other

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Smaller CMAs host few sectors: Quebec

Figure 1.15: Québec CIE on R&D 2002- Main

sectors

Scientific R&D

29%

Navigational,

measurement,

medical &

control

18%

Architectural &

engineering

10%

All other

29%

Computer

systems design

14%

Scientific R&D

Navigational,

measurement, medical

& control

Computer systems

design

Architectural &

engineering

All other

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…and Calgary

Figure 1.14: Calgary CIE R&D

29%

15%

2%4%5%5%5%

27%

4% 4%

Oil & Gas extraction

Petroleum & coal prodsOther chemicals

Navigational, meas.

Wholesale trade

Information & cult

Architect., engin.

Computer system design

Scientific R&D

All other

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Patents are granted to the largest CMAs

Tab l e 2.2 U S in d ust r ia l P a tents 200 2 - 4 i n l a r gest Canadia n C M As

CM A US Pa t e n t s 2002 - 4 % o f Ca n ada

T o r o n to 1841 31

O tt awa Hu ll 1297 22

M o n t rea l 1102 18

Va n c o u v er 727 12

Ca l gar y 362 6

Ha mil to n 280 5

Ed m o n to n 270 5

Qué b ec 80 1

W i nn i peg 86 1

9 L arges t CM A , b us i n ess pa t e n t s 6045 100

T ot a l U S pa t e n t s g ra n t ed t o

Ca n ad i a n i nv e n to rs, 2002 - 4

10222

Sou r ce: US P TO

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Population in Atlantic CMAs

Census Metropolitan Area 2006 Population

Halifax, NS 372,679

St John’s, Newfoundland 181,113

Moncton, NB 126,424

Saint John, NB 122,389

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US patents invented in Halifax (2002-4)Patent holder Nb

Dalhousie University 4

Individual inventors 4

Foreign companies subcontracting local skills 7

Canadian companies based in ROC 2

Canadian companies based in Halifax 9

Canadian companies based in NS, not Halifax 1

Other (Defence Canada, U. of Pittsburgh) 2

Total 29

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Private patent holders of Halifax Immunovaccine Technologies, a

Dalhousie University spin-off (1) Neocon International: plastic prods. (1) Darmos Toys (4) Algoplus Consulting: aviation safety

software (1) Blue Sky Entertainment (1) Ocean Nutrition: neutraceuticals (1)

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What to do: Increase skills and knowledge production Investing in university research to create local

spin-off firms And attracting public, private and non profit

laboratories Also luring human capital from abroad and

ROC Putting mechanisms in place to incorporate

new human capital in the labour pool.

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Increasing human capital supply and demand

Supply (public sector) Demand (private sector)

University fellowships Tax credits for R&D

Grant loans for students R&D subsidies

Selective immigration Public laboratories

Academic salaries Expatriate R&D labs

Tax exemptions for foreign researchers

University-Industry corporations

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Higher education R&D expenditures by province

Province Population HERD expenditures ($ Million)

HERD per capita (C$)

Provincial government HERD

funds Quebec 7,687,068 2,556 332 260 NS 932,966 298 319 6.0 Ontario 12,753,704 3,980 312 403 Alberta 3,455,062 962 278 183 Manitoba 1,182,921 295 249 15 Saskatchewan 990,112 217 219 20 BC 4,352,798 904 208 81 PEI 138,800 27 195 0.4 NB 748,878 130 174 3.7 Total 32,852,849 9,517 289 973.4 Massachusetts 6,398,743 2,079 325 New Hampshire 1,309,940 287 219 Vermont 623,050 117 188 Michigan 10,120,860 1,456 144 Indiana 6,271,973 759 121

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Attracting industrial R&D Four factors are key in the decision to locate

corporate R&D:- Output market potential- Intellectual property protection- Quality of R&D personnel (Route 128, Silicon

Valley, N. Carolina Research Triangle…)- University collaboration with industry (new

science, expertise of academic faculty, ease of collaboration)(Thursby and Thursby, 2006)

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The role of anchor tenants

In all high-tech industries, some organizations play the role of “anchor tenants” or attractors.

- In biotechnology and nanotechnology, universities play that role: they conduct key research and create the labour pool, and spin-off new companies

- In ICT and aerospace, large companies play that role I.e.: Canadair (now Bombardier) in Montreal aerospace, Nortel in Ottawa telecom cluster, and IBM Canada in Toronto’s software agglomeration. They contribute to the labour pool and spin-off companies.

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BERD by province

Population 2006, and R&D industrial expenditures 2003 Province Population BERD

expenditures ($ Million)

BERD per capita (C$)

Ontario 12,753,704 7,066 554 Quebec 7,687,068 4,115 535 BC 4,352,798 1,075 247 Alberta 3,455,062 779 226 Manitoba 118,2921 126 107 NS 932,966 78 84 Saskatchewan 990,112 83 84 NB 748,878 43 57 Newfoundland 512,500 19 37 PEI 138,800 7 50 Total 32,852,849 13,391 407

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Picking locations Larger cities are the places where the action

is, in Canada, the US and the European Union.

Also, the vast majority of landed immigrants go to the larger cities (Toronto, Montreal and Vancouver).

A new set of incentives is required to attract more skilled immigrants to the larger Atlantic metropolitan areas (I.e. faster recognition of academic degrees, faster entry in the labour market, acquisition of complementary skills).

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Picking locations

The best bets for the Atlantic Provinces are its CMAs (population as of 2006):Halifax (Nova Scotia) (372,000) (Canada’s 13th)St John (Newfoundland) (181,000)(Canada’s 20th)Moncton (New Brunswick )(126,000)(Canada’s 27th)

Rationale: larger cities create more externalities than small ones, thus usually attract more immigrants and knowledge circulate faster than in small cities

Rationale: universities are located in CMAs, spin-offs from universities, and attracted R&D labs, will locate in them because skilled people tend to settle in CMAs

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Virtuous circles of growth in larger CMAs

H i g h

d e m a n d f o r

s k i l l e d

p e r s o n n e l

H i g h s a l a r i e s

A t t r a c t i o n o f

R & D - i n t e n s i v e

f i r m s

S t r o n g l a b o u r p o o l o f s k i l l e d

w o r k e r s

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Vicious circles of stagnation in skilled labour

L o w d e m a n d

L o w s a l a r i e s

L o w c r i t i c a l

m a s s e s

L o w a t t r a c t i o n

o f R & D - a c t i v e

f i r m s

P o l i c y

o p p o r t u n i t y

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Policy opportunity

Increase the production of college and university graduates in the Atlantic provinces through grants, scholarships, increased academic personnel, more research.

Increase the attraction of skilled immigrants (faster recognition of degrees, faster admission by professional organizations, better upgrading programs in local universities).

Then attract anchor tenants

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Conclusion

Human capital is unanimously considered the main factor behind economic development

Thanks to the oil boom, Atlantic Canada has the means required to attract skilled labour and high technology industry and enter into a virtuous circle of sustained growth.

The main policy opportunity is in the area of the creation and attraction of human capital, a precondition to lure R&D-intensive firms.

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Conclusion For this purpose, two main and one minor set

of policy measures appear adequate:

- Increase the production of university research and graduates in science and technology intensive areas. Nurture spin-offs and lure venture capital

- Increase the attraction of skilled immigrants from rest of Canada and abroad by facilitating their insertion in the labour market

- Pick sectors: R&D in oil, gas and related activities; high-tech services (I.e. software). But be alert to other sectors growing spontaneously

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Bibliography

Niosi, J. (2000): Canada’s national system of innovation, Montreal & Kingston, McGill-Queen’s University Press.

Niosi, J. (2005): Canada’s regional systems of innovation, Montreal & Kingston, McGill-Queen’s University Press.

Niosi, J. and M. Bourassa (2007): Canada’s inventive cities, a presentation to the Annual Statistical Conference of Statistics Canada, Ottawa, May.

Thursby, J. and M. Thursby (2006): Here or there? A survey of factors in multinational R&D location. Report to the Government-Industry-University Research Roundtable, Washington, National Academies Press.