The Task Force on Competitiveness, Productivity, and ... · Western Ontario Smart Growth Panel by...

1 November 14, 2002 © 2002 Institute for Competitiveness and Prosperity

The Task Force on Competitiveness, Productivity, and Economic Progress

Presentation to Western Ontario Smart Growth Panel

byJames Milway, Executive Director

Owen SoundNovember 14, 2002


This is a copy of the presentation given by Jim Milway in Owen Sound on November 14th 2002. It was part of a consultation organized by the Instituteand the Western Ontario Smart Growth Panel.

This document provides an outline of the presentation and is incomplete without the accompanying oral commentary and discussion. It represents work in progress based on research conducted by the Institute for Competitiveness and Prosperity.

Much of the material is from the Institute’s two Working Papers and the 1st

Annual Report which can be viewed at our Web site, www.competeprosper.ca

The Web site also provides more information on the Institute and the Task Force on Competitiveness, Productivity, & Economic Progress.

We ask that you acknowledge the Institute as the source if you use the material from this presentation.


Task Force MandateTo measure and monitor Ontario’s competitiveness, productivity and

economic progress compared to other provinces and the US statesprovinces and the US states and to report to the public on a regular basis.

Long Term AspirationWe aspire to have a significant influence in increasing Ontario’s

competitiveness, productivity and capacity for innovation. This will help ensure continued success in the creation of good jobs, increased prosperity

and a high quality of life for all Ontarians.

We will accomplish this by undertaking research, publishing breakthrough reports and proposing significant innovations in public policy which stimulate

businesses, governments and educational institutions to take action.

The Task Force


Task Force Members

Roger L. Martin, ChairmanJames L. Balsillie, Research in MotionTimothy D. Dattels, Goldman SachsLisa de WildeDavid Folk, Jefferson PartnersSuzanne Fortier, Queen’s UniversityGordon Homer, Scotia CapitalDavid Johnston, University of WaterlooDavid Keddie, National Compressed Air and National Drilling SystemsMark Mullins, MSG Hedge CorporationWilliam Orovan, McMaster Medical SchoolTimothy H. Penner, Procter & GambleBelinda Stronach, Magna InternationalDaniel Trefler, University of Toronto


•The Institute’s First Working Paper, A View of Ontario: Ontario’s Clusters of Innovation released April 29

•Stakeholder consultations with several jurisdictions and industry groups

•Second Working Paper, Measuring Ontario’s Prosperity: Developing an Economic Indicator System released August 21

•The Task Force’s First Annual Report, Closing the Prosperity Gap released November 5

Our progress to date


Summary of Working Papers

GDP per capita is a key indicator of economic prosperityOntario is a leader in Canada but just one of the pack in North America

Productivity drives GDP per capita

Clusters of traded industries increase competitiveness

Ontario’s Clusters of Innovation


Canada Among Leading Nations

GDP per Capita at Purchasing Power Parity (PPP) in CDN$ (2000)

Note: Only countries with population of significant size. If all countries were included, Canada would rank 8th.Source: OECD Main Accounts, National Data; CANSIM

Rank Country GDP per capita at PPP

1 United States $43,099

2 Norway $36,501

3 Switzerland $36,467

4 Ireland $35,301

5 Denmark $35,164

6 Canada $33,878

7 Netherlands $33,682

8 Austria $32,671


$29,557

$21,388$21,787

$25,505

$28,958

$0

$10,000

$20,000

$30,000

$40,000

Ontario Lombardia Baden-Wurttemberg

Rhone-Alpes Cataluna

Ontario versus “The Four Motors”

(Italy)(Germany)

(France) (Spain)

GDP Per Capita, 1999 (PPP)

Source: Statistics Canada; Eurostat

GDP/ Capita


Ontario Fares Well Among Leading Nations

GDP per Capita at Purchasing Power Parity (PPP) in CDN$ (2000)

Source: OECD Main Accounts, National Data; CANSIM; Institute for Competitiveness & Prosperity analysis

Rank Country GDP per Capita at PPP

1 United States $43,009

Ontario $36,808

2 Norway $36,501

3 Switzerland $36,467

4 Ireland $35,301

5 Denmark $35,164

6 Canada $33,878

7 Netherlands $33,682

8 Austria $32,671


Select States and Provinces for Comparison

States and Provinces with Population over 6 Million

Note: US Statistics – 2000; Canadian Statistics - 2001Source:Statistics Canada (Census 2001); US Census Bureau (Census 2000)

6.1

6.3

7.1

7.4

8.0

8.2

8.4

9.9

11.4

11.9

12.3

12.4

16.0

19.0

20.9

33.9

0 5 10 15 20 25 30 35

Indiana

Massachusetts

Virginia

Quebec

North Carolina

Georgia

New Jersey

Michigan

Ohio

Ontario

Pennsylvania

Illinois

Florida

New York

Texas

California

Population in Millions


Ontario Ranks 14th Among its Peer GroupGDP per Capita for Select States and Province (2000)

(CDN$)

$30,313

$35,742

$36,808

$38,246

$39,615

$39,715

$39,803

$42,352

$42,713

$43,073

$43,771

$44,676

$45,527

$48,034

$50,960

$52,213

$54,302

$- $10,000 $20,000 $30,000 $40,000 $50,000 $60,000

Quebec

Florida

Ontario

Indiana

Michigan

Ohio

Pennsylvania

North Carolina

median

Texas

Georgia

Virginia

Illinois

California

New York

New Jersey

Massachusetts

GDP per Capita in CDN$

$5,905 below median

Note: OECD Main Accounts, National Data; CSNSIM II; US Department of Commerce, BEA (June 2002); Institute for Competitiveness and Prosperity Analysis


The Prosperity Gap is Widening

Source: OECD; Statistics Canada; US Department of Commerce, BEA; Institute for Competitiveness & Prosperity analysis Note: 1980 data used for Ontario and Quebec based on 1981 results

Real GDP per Capita

0

10

20

30

40

50

60

1980 1985 1990 1995 2000 Year

$000

Ontario (+36%)

Median (+54%)

Leader (+50%)

Ontario Rank 11th 11th 14th 14th 14th Performance Gap $841 $1,792 $2,782 $2,793 $5,905

20 year change



GDP per capita is a key indicator of economic prosperity





Component Parts of GDP per Capita

GDP Per Capita:

XX

Productivity

GDPPopulation JobsX

Profile Utilization Intensity

Potential labour force Jobs Hrs Worked

Source: Adapted from Baldwin, J., Maynard, J.P., and Wells, S.(2000). “Productivity Growth in Canada and the United States.” Isuma.Vol. 1, No. 1 (Spring 2000). Ottawa: Policy Research Initiative

Participation

Employment

Cluster mix

Cluster content

Urbanization

Effectiveness

Potential labour force Hrs Worked


Productivity Key to Prosperity Gap

Ontario’sCurrent GDPper capita

(86.2% of median)

Profile Urban-ization

Mix ofclusters

Participation Employment Effective-ness

$36,808

$974

$3,210

$998$125

$863

$42,713

$3,524

Median GDP per capita

Prosperity Gap: $5,905 or 13.8% of median GDP/capita

$Per Capita, 2000

UtilizationProfile Productivity

Source: Statistics Canada, Bureau of Economic Analysis, Institute for Competitiveness and Prosperity Note: Median comprises 16 North American jurisdictions with populations that exceed 6 million

Intensity

$405

Intensity


R2 = 0.4448

60

70

80

90

100

110

120

130

140

150

60 65 70 75 80 85 90 95 100

Quebec

Florida

New York

New Jersey

Ontario

California

Massachusetts

Indiana

North Carolina

Georgia

Ohio

Virginia

PennsylvaniaMichigan

Texas

Illinois

Urbanization and ProductivityPer cent of Population in Urban Areas vs. Labour Productivity

(1997, Ontario labour productivity = 100)Relative Labour Productivity

Per cent of Population Living in Urban Areas

Source: Le Letourneau, R. (2000). "A Regional Perspective on the Canada-US Standard of Living Comparison." Occasional Paper No. 22. Ottawa: Industry Canada; Statistics Canada, Census 2001; U.S. Census Bureau; Census 2000; Institute for Competitiveness and Prosperity


R2 = 0.4448

60

70

80

90

100

110

120

130

140

150

60 65 70 75 80 85 90 95 100

Quebec

Florida

New York

New Jersey

Ontario

California

Massachusetts

Indiana

North Carolina

Georgia

Ohio

Virginia

PennsylvaniaMichigan

Texas

Illinois

Impact of Ontario’s Low UrbanizationPer cent of Population in Urban Areas vs. Labour Productivity

(1997, Ontario labour productivity = 100)Relative Labour

Productivity

Per cent of Population Living in Urban AreasSource: Le Letourneau, R. (2000). "A Regional Perspective on the Canada-US Standard of Living Comparison." Occasional Paper No. 22. Ottawa: Industry Canada; Statistics Canada, Census 2001; U.S. Census Bureau; Census 2000; Institute for Competitiveness and Prosperity

A shift to median urbanization improves productivity by 8.7% - this translates directly to GDP per capita


Mix of Clusters: US Clusters

Source: Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School

Upstream Materials and Products

Industrial and Supporting Functions

Final Consumption Goods and Services

Metals and Materials Multiple Business Food/Beverages

Construction Materials Education and Knowledge Creation Agricultural Products

Metal Manufacturing Business Services Processed Foods

Forest Products Heavy Machinery Fishing and Fishing Products

Forest Products Financial Services Housing/Household

Petroleum/Chemicals Motor Driven Products Building Fixtures, Equipment & Services

Oil and Gas Prefabricated Enclosures Lighting and Electrical Equipment

Chemical Products Production Technology Furniture

Plastics Analytical Instruments Textiles/Apparel

Semiconductors/Computer Heavy Construction Services Textiles

Information Technology Transportation and Logistics Apparel

Automotive Footwear

Distribution Services Health Care

Transportation and Logistics Medical Devices

Power Pharmaceuticals and Biotechnology

Power Generation Personal

Power Transmission and Distribution Leather and Sporting Goods

Office Jewelry and Precious Metals

Publishing and Printing Tobacco

Telecommunications Entertainment/Leisure

Communications Equipment Entertainment

Defense Hospitality and Tourism

Aerospace Engines

Aerospace Vehicles and Defense

Identifying 41 Clusters of Traded Industries


Results from the US Cluster Mapping Project

$42

$26

$31

Average Wage ($US thousands)


Traded Clusters Local Industries

The Economics of Traded Clusters and Local Industries

Natural Resources

Share of Employment

32%

67%

1%

Share of Income

43%56%

1%

20.48

1.38

6.40

Patents per 10,000 employees


Distribution of Traded Cluster Employment

London

1%

63%

36%

Share of Employment in Traded Clusters

Note: US Statistics are for 1999; Canadian Statistics are for 2000Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School

US

1%

67%

32%

Ontario

1%

59%40%

Traded Clusters Local Industries Natural Resources

Windsor

1%

52%47%


Dynamics of a Cluster: Pressure and Support


Context for Firm

Strategy and Rivalry

Context for Context for Firm Firm

Strategy and Rivalryan Rivalry

Related and Supporting Industries


Factor(Input)

Conditions

FactorFactor(Input) (Input)

ConditionsConditions

The availability and quality of local suppliers and related

industries

Demand ConditionsDemand Demand


The underlying inputs firms draw on in competing

– natural (physical) resources– human resources– capital resources– physical infrastructure– administrative infrastructure– information infrastructure– scientific and technological

infrastructure

The context shaping the types of strategies employed and the nature of local rivalry

The nature of home demand for products and services


Competitive vs. Uncompetitive Clusters

Context for Firm


Context for Firm




Factor(Input)

Conditions

FactorFactor(Input) (Input)

ConditionsConditionsDemand

ConditionsDemand Demand



Demand Demand

ConditionsFactor(Input)

Factor(Input)

Conditions

Competitive Clusters:May rely on any part of the full

diamond

Other (Chance Gov’t)

Other (Chance Gov’t)

Uncompetitive Clusters:Usually only rely on factor

conditions

Source: van der Linde and Porter, Cluster Meta-Study October 2001, Institute for Strategy and Competitiveness, Harvard Business School


Plastics

Oil and Gas

Chemical Products

Pharma-ceuticals

Power Generation

Aerospace Vehicles &

Defense

Lightning & Electrical Equipment

Financial Services

Publishing and Printing

Entertainment

Hospitality and Tourism

Transportation and Logistics

Information Technology

Communi-cations

Equipment

Medical Devices

Analytical Instruments

Education and

Knowledge Creation

Apparel Leather and

Sporting Goods

Agricultural Products

Processed Food

FurnitureBuilding Fixtures,

Equipment and

Services

Note: Clusters with borders or identical colors/shading except gray have at least 20% overlap of industries by number in both directions

Power Transmission

and Distr.

Business Services

DistributionServices

Fishing & Fishing

Products

Footwear

Forest Products

Heavy Construction

Services

Jewelry & Precious Metals

ConstructionMaterials

Prefabricated Enclosures

Textiles

Tobacco

Heavy Machinery

Aerospace Engines

Automotive

Production Technology

Motor Driven Products

Metal Manufacturing

Cluster Overlap in the US Economy







Ontario’s Clusters of InnovationWe have strength and diversity


Ontario and Traded ClustersShare of Employment in Traded Clusters

Canada and the US, and Select States and Provinces

Note: US Statistics are for 1999; Canadian Statistics are for 2000Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity analysis

25.7%

30.8%

32.3%

33.0%

33.4%

33.7%

33.8%

33.8%

33.9%

33.9%

34.3%

35.0%

36.1%

36.8%

37.7%

39.6%

39.7%

41.4%

20% 22% 24% 26% 28% 30% 32% 34% 36% 38% 40% 42%

Florida

Texas

New York

US

Ohio

Illinois

Michigan

Pennsylvania

New Jersey

Georgia

Virginia

California

North Carolina

Indiana

Massachusetts

Canada

Quebec

Ontario



A First Look at Ontario’s ClustersOntario’s Leading Clusters by Share of Employment (2000)

Traded Cluster (Rank in Ontario)

Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity analysis

0% 2% 4% 6% 8% 10% 12% 14%

Jewelry and Precious Metals (15)

Production Technology (14)

Building Fixtures, Equipment and Services (13)

Entertainment (12)

Processed Food (11)

Publishing and Printing (10)

Heavy Construction Services (9)

Distribution Services (8)

Transportation and Logistics (7)

Metal Manufacturing (6)

Hospitality and Tourism (5)

Education and Knowledge Creation (4)

Automotive (3)

Financial Services (2)

Business Services (1)



Ontario’s Leading Clusters Relative to Michigan

Note: US Statistics are for 1999; Canadian Statistics are for 2000Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

Traded Cluster (Rank in Ontario, Rank in Michigan)

0% 5% 10% 15% 20% 25%

Plastics (19, 5)

Publishing and Printing (10, 13)

Heavy Construction Services (9, 7)

Distribution Services (8, 11)

Transportation and Logistics (7, 10)

Metal Manufacturing (6, 3)

Hospitality and Tourism (5, 6)

Education and Knowledge Creation (4, 9)

Automotive (3, 1)

Financial Services (2, 4)

Business Services (1, 2)


Ontario

Michigan


London’s Leading Clusters

Leading Clusters by Share of Traded Cluster Employment (2000)

Note: * indicates that the location quotient is a Canadian quotient. The other quotients are North American quotients.Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

0.682,574 Heavy Construction Services10 0.522,638 Hospitality and Tourism9 0.702,656 Distribution Services8 1.193,333 Metal Manufacturing7 1.383,972 Processed Foods6 0.615,434 Business Services5 2.287,616Transportation and Logistics4 1.697,680 Education and Knowledge Creation3 3.369,205 Automotive2 2.4015,130Financial Services1

Location QuotientEmploymentCluster


Windsor’s Leading Clusters

Leading Clusters by Share of Traded Cluster Employment (2000)

Note: * indicates that the location quotient is a Canadian quotient. The other quotients are North American quotients.Source: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

0.741,993 Heavy Construction Services10 0.882,097 Transportation and Logistics9 3.622,266 Heavy Machinery8 0.593,720 Business Services7 1.233,985 Education and Knowledge Creation6 4.114,056 Production Technology5 1.346,026Financial Services4 1.354,985Hospitality and Tourism3 3.436,969 Metal Manufacturing2

11.2921,999Automotive1

Location QuotientEmploymentCluster


The Location Quotient (LQ) Defined

The location quotient is a ratio measure of the concentration for a cluster in a particular location relative to the North American averageAn LQ >1 indicates a higher than average concentration in the particular location

London’s cluster LQs are calculated as follows:

)(

)(

EmploymentAmericanNorthTotalAmericaNorthinClustertheinEmploymentTotal

EmploymentLondonTotalLondoninClustertheinEmployment

LQ =


The Automotive ClusterLeading CMA’s by Traded Cluster Employment (2000)

Note: Location quotients are CanadianSource: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

0.18277 Thunder Bay10 0.34329 Sudbury9 0.221,431 Ottawa8 0.964,525 Hamilton7 3.287,954 St. Catharines6 3.369,205 London5 3.5310,217 Kitchener4

11.2921,999 Windsor3 12.8222,873 Oshawa2 1.6653,979Toronto1

Location QuotientEmploymentOntario CMA


Components of the Automotive Cluster

Source: Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity analysis

Flat Glass

Motor Vehicles

Production Equipment

Other Engines

Related Parts

Related MachineryRelated Vehicles

Related Equipment

Metal Processing

Automotive PartsForgings &

Stampings

Transportation Equipment

14 Narrow Sub Cluster Industries18 Broad Sub Cluster Industries Narrow Sub Clusters

Broad Sub Clusters

Automotive Components


The Financial Services Cluster

Leading CMA’s by Traded Cluster Employment (2000)


0.571,026Thunder Bay10 0.691,509Sudbury9 0.722,952 Oshawa8 0.814,319 St. Catharines7 1.346,026 Windsor6 1.227,960 Kitchener5 1.1411,027 Hamilton4 2.4015,130 London3 1.0915,633 Ottawa2 2.27167,241Toronto1



Components of the Financial Services Cluster


Leasing

Real Estate Investment

BankingComputer &

Communication Services

Research Organizations

Printing ServicesRelated Services

Professional Services

Information Providers

Securities Services

Insurance Products

Narrow Sub Clusters Broad Sub Clusters

Risk Capital Providers

Health Plans

Investment Funds


The Education and Knowledge Creation ClusterLeading CMA’s by Traded Cluster Employment (2000)

Note: Location quotients are North AmericanSource: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

0.511,502 Oshawa10 1.692,181 Thunder Bay9 1.572,482 Sudbury8 0.953,642 St. Catharines7 1.233,985 Windsor6 1.697,680 London5 2.119,904 Kitchener4 1.5610,914 Hamilton3 2.3123,943 Ottawa2 1.0354,523 Toronto1

Location QuotientEmployment Ontario CMA


Components of the Education and Knowledge Creation Cluster

Educational Institutions

Research Research Facilities

Related Professional Services

Supplies

Research Instruments

Pharmaceuticals

Publishing

Printing

Communication Services

Professional Services

Information Services

Computer Software and ServicesComputer and

Software Distribution

Computer Equipment



Broad Sub Clusters


The Transportation and Logistics ClusterLeading CMA’s by Traded Cluster Employment (2000)


0.56647Sudbury10 0.791,731Oshawa9 2.081,970Thunder Bay8 0.882,097Windsor7 0.953,266Kitchener6 1.173,301St. Catharines5 0.723,679Hamilton4 2.287,616London3 1.058,034 Ottawa2 1.4757,534Toronto1



Components of the Transportation and Logistics Cluster

Air Transportation Carriers

Bus Transportation

Marine Transportation Carriers

Transportation Arrangement

Handling and Storage

Airports

Bus Terminals

Ship Building

Passenger Transportation

Communication Equipment and Services

Computer Services and Equipment

Financial Services



Broad Sub Clusters


The Metal Manufacturing Cluster



0.25244Sudbury10 0.90728 Thunder Bay9 0.171,138 Ottawa8 1.041,939Oshawa7 1.173,333 London6 3.436,969 Windsor5 2.917,004 St. Catharines4 2.517,389 Kitchener3 5.4323,848Hamilton2 1.2842,578Toronto1



Components of the Metal Manufacturing Cluster

Metal Products

Fasteners

Wire and Springs

Metal ProcessingIron and Steel

Mills and Foundries

Nonferrous Mills and Foundries

Metal Furniture

Specialized Products

Metal Equipment

Metal Armaments

Specialized EquipmentProcessing Inputs

Related Machinery

Metal Machine Tools

Related Processing

Automotive Parts and Equipment

Nonferrous Metals

Related Metal Equipment

Related Metal ProductsVehicles



Broad Sub Clusters


The Hospitality and Tourism Cluster


Note: Location quotients are North AmericanSource: Statistics Canada, Canadian Business Patterns (June 2000); Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Institute for Competitiveness & Prosperity

0.481,611 Oshawa10 1.331,951 Thunder Bay9 1.292,321 Sudbury8 0.512,638 London7 0.573,025 Kitchener6 0.584,658 Hamilton5 1.354,985 Windsor4 2.5010,930 St. Catharines3 1.0712,714 Ottawa2 0.7947,965 Toronto1



Components of the Hospitality and Tourism Cluster

Tourism AttractionsTour Services

Passenger Transportation

Support Services

AccomodationsMarine Services

Specialized Inputs

Local Transportation

Related Transportation

Related Professional

Services

Other Attractions

Air Services

Vehicle DistributionOther Support Services



Broad Sub Clusters


What can Canadian businesses do?

StrategyFocus on the global peak Set aspirations and goals accordinglyCompete globally, serving the most sophisticated and demanding customersCompete on the basis of unique products and processes

Cluster BuildingBe a demanding and sophisticated customer...But, encourage local suppliers to meet global standards and follow you globallyCollaborate with competitors and governments to create specialized infrastructure and education...But, compete vigorously with the same competitors


What can Canadian Governments do?

Encourage an Environment of Pressure...Create an environment in which customer sophistication can flourish

Where possible, act as a sophisticated and demanding buyer Maintain an environment that features intense rivalry

While Balancing it with Critical Elements of SupportInvest heavily in the university research infrastructure

Scientific researchBusiness research

Invest in the key pieces of infrastructureEncourage and celebrate innovationEncourage and celebrate global competitivenessPromote clustering rather than dispersion


What can Canadian Universities do?

Aspirations

Focus on the global peak and set goals accordingly

Compete globally for faculty and students

Seek unique and differentiated positioning

Connectedness

Seek to collaborate with proximate businesses

Be guided in part by their needs

And seek to guide them with your research-based insights

47Friday, November 15, 2002

Based on your knowledge of the Cities of London and Windsor and the Region of Western Ontario, what industry clusters do you seeas most critical to its competitiveness and prosperity?

What are the three or four most important factors for the growth and competitiveness of the region and its clusters?

What are the greatest strengths of the business environment for enhancing the competitiveness of businesses or industries in theregion? What are the greatest challenges?

How should universities and colleges contribute to the economic development of London, Windsor, and Western Ontario?

Do individuals, firms and governments have global aspirations for the industry clusters in Western Ontario?

Some Questions to Consider

49Friday, November 15, 2002

Overview of Annual Report

•Closing the Prosperity Gap

•Productivity for Prosperity

•AIMS for Opportunities

•Actions for Productivity and Prosperity


AIMS for Opportunities


AIMS - Attitudes

•Aspirations•Competitiveness•Entrepreneurship•Creativity


Aspirations, Competitiveness and Prosperity

• National competitiveness• Sustainable advantage

over local competition

• National competitiveness• Sustainable advantage

over local competition

• Primarily in home country• Broad participation• Serving most easily

satisfied customers

• Primarily in home country• Broad participation• Serving most easily

satisfied customers

• Replication with low cost labour /raw materials

• Minimal R&D• Weak branding

• Replication with low cost labour /raw materials

• Minimal R&D• Weak branding

• Global competitiveness• Sustainable advantage

over global competition

• Global competitiveness• Sustainable advantage

over global competition

• Globally in focused product niche

• Serving demanding customers at home and abroad

• Globally in focused product niche

• Serving demanding customers at home and abroad

• Unique product/process• High R&D• Global distribution• Branding

• Unique product/process• High R&D• Global distribution• Branding

Aspirations and Goals

Aspirations and Goals

Where to Play

Where to Play

How to Win

How to Win

Incompatible with Global Competitiveness

Compatible with Global Competitivneess


Key Florida/Gertler Results on Creativity

Ontario cities rank well on “melting pot/mosaic” and “bohemian” indices – compared to similar-sized US cities

Most Ontario cities rank near top in melting pot/mosaic index

Bohemian results vary more by city size:Toronto 4th ;Ottawa-Hull near top quartileKitchener, London in top quartile for their peer groupHamilton, St Catharines-Niagara, Oshawa closer to middle of packWindsor, Thunder Bay, Sudbury below average for cities of their size

Task Force conclusion: Ontario has the creative class necessary to compete; but aspirations, entrepreneurship, and attitudes towards competitiveness may be holding us back


AIMS - Investments

•Education, particularly post secondary•Machinery & equipment


Education Spending as % of GDP


Ontario Lagging in Master’s Degrees


Ontario Lagging in Business Degrees


Spending per Capita Lagging US Peer Group


Machinery & Equipment Investments Trail US


AIMS - Motivations

•Tax rates•Government policies and programs


Ontario’s Tax Rates Exceed Peer Group States

* Note: Tax as Percentage of After-Tax Labour Costs and Pre-Tax Capital Costs


AIMS - Structures

•Healthy market structures, as evidenced by vibrant clusters of traded industries

•Other supporting structures


Government Share of the Economy and Prosperity

GDP and Government Receipts, 1999

20,000

25,000

30,000

35,000

40,000

45,000

25% 30% 35% 40% 45%

Goverment Revenue as % of GDP

GDP per Capita

Quebec

OntarioFlorida

IndianaMichiganOhio

Pennsylvania

VirginiaNorth Carolina Texas

Georgia

IllinoisCalifornia

New York New Jersey

Massachusetts


Four Sets of Recommendations

1) Heighten aspirations across Ontario

2) Increase productivity-enhancing investments

for future prosperity

3) Adopt tax reforms that strengthen motivations

4) Strengthen market structures


Heighten Aspirations Across Ontario

Aspire to move from laggard to leader – achieving median prosperity by 2012 as first step:

Individuals – aspirations for personal upgrading

Firms – aspirations for global competitiveness

Governments – aspirations to invigorate environment to encourage individuals and firms

All – celebrate winners who set and meet high aspirations


Increase Productivity-Enhancing Investments

All stakeholders should increase productivity –enhancing investments, particularly post-secondary education:

Individuals – commit to life-long learning, contribute to alma mater, support unfreezing of tuition

Firms – continue partnerships with employees in formal training and education, support educational institutions financially

Provincial government – long-term strategy for sustainable funding taking into account roles of individuals, firms, and other private institutions

Further study into role of business education and prosperity


Adopt Tax Reforms that Strengthen Motivations

Provincial and federal governments to collaborate to explore breakthrough tax reform

Assess how government spending promotes economic prosperity


Strengthen Market Structures

Ontario government to continue work in exploring ways to strengthen Ontario cities

Local governments and stakeholders to collaborate on revitalizing urban cores and attracting and retaining knowledge workers


Proposed Research Plan

Attitudes:Measure aspiration on global competitiveness and strength of entrepreneurship (Ontario versus Peer Group)Follow-up on Florida/Gertler work

Investments:Consumption/investment trade-offsContinue post-secondary research; expand into primary and secondary

Motivations:Regulatory processes

Structures:Intra-cluster assessment – “Hollowing out”Peer group best practices on urban governanceOptimal size of government; spending structure choices of peer group

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