The Performance of British Columbia's Metropolitan Areas on the 3Ts Of

The performance of British Columbia’s Metropolitan Areas on the 3Ts of Economic Development

Benchmarking Project: Creativity Index for British Columbia

Dr. Kevin Stolarick Research Director

February 2014

Creative BC Benchmarking, February 2014

Contents Introduction ...... 4 3Ts Background Information ...... 7 The 3Ts and Economic Development ...... 9 Technology: Innovation and High-tech Production ...... 9 Measuring Technology ...... 10 Talent: Human Capital and the Creative Class ...... 12 Measuring Talent ...... 12 Tolerance: Openness, Inclusion, and Diversity ...... 15 Measuring Tolerance ...... 17 The “4th T” – Quality of Place ...... 18 Conclusions for BC’s Four CMAs ...... 19 Overall Creativity Index ...... 19 Vancouver ...... 19 Victoria ...... 19 Kelowna ...... 20 Abbotsford ...... 20 Overall – Technology ...... 20 Overall – Talent ...... 20 Overall – Tolerance ...... 21 Overall – Territory Assets/Quality of Place ...... 21 Vancouver ...... 21 Overall ...... 21 Technology ...... 22 Talent ...... 22 Tolerance ...... 22 Victoria ...... 22 Overall ...... 22 Technology ...... 23 Talent ...... 23 Tolerance ...... 23 Kelowna ...... 23 Overall ...... 23 Technology ...... 23 Talent ...... 23

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Tolerance ...... 24 Abbotsford ...... 24 Overall ...... 24 Technology ...... 24 Talent ...... 24 Tolerance ...... 25 Appendix A: Metric Definitions for Benchmarking ...... 1 Appendix B: High-Tech Industries - NAICS ...... 3 Appendix C: Map of Benchmarked Regions ...... 4 Appendix D: Research Methods ...... 5 Statistics ...... 6 American Statistical Sourcing ...... 7 Works Cited ...... 8

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Introduction

The Martin Prosperity Institute (MPI) has benchmarked the census metropolitan areas (CMAs) of British Columbia against each’s peer regions to understand their competitiveness within North America, with the aim of providing input to the development of a long-term creative economy blueprint for the province. The larger goal is to chart the transition to an economy based on creativity. At a moment when every region is looking for ways to become more competitive, the question is: how does BC stack up? This work is based on work originally completed as part of the “Ontario in the Creative Age" project. The data is based on data from 2006. While available newer data will be provided as part of this larger project, this report is (not by choice) restricted to data captured by the 2006 Canadian Census1. With the transition from the mandatory Census Long Form to the voluntary Household Survey, sufficient, reliable and more recent data is not available to complete this benchmarking. More recent data is available for US metros, but data from 2006 has been used here to keep the comparison consistent. Economic development is driven by what we call the three "T"s – technology, talent, and tolerance. All three are critical to generating sustained economic growth and prosperity. It is great to excel at one or two; however, sustained economic strength comes from performing well on all three. To see how the CMAs fare against competition, we compared them to metropolitan areas with roughly the same population from seventeen US states with a population of six million or more and the three of the most competitive provinces ⎯ Ontario, Quebec, and Alberta. (See Appendix C for the map of peer regions.) The map and table below show all of the metropolitan regions of BC. CMAs are in a darker shade than CAs (Census Agglomerations). In 2011, 87.6% of the population of British Columbia lived inside a CMA or CA. Of those 3,854,139 persons, 2,767,965 or 71.8% of all urban dwellers (62.9% of BC’s total population) live in the provinces four CMAs: Vancouver, Victoria, Kelowna, and Abbotsford – Mission. The number of

1 See Appendix D for more information on our research methods.

Martin Prosperity Institute -- Stolarick (Draft) 4 Creative BC Benchmarking, February 2014 persons living outside an urbanized area accounts for 12.4% of the provincial population.

Source: MPI. Statistics Canada, 2014. Map by Zara Matheson.

Population CMA or CA name Type 2011 2006 % change Vancouver CMA 2,313,328 2,116,581 9.3 Victoria CMA 344,615 330,088 4.4 Kelowna CMA 179,839 162,276 10.8 Abbotsford - Mission CMA 170,191 159,020 7.0 Kamloops CA 98,754 92,797 6.4 Nanaimo CA 98,021 92,361 6.1 Chilliwack CA 92,308 82,465 11.9 Prince George CA 84,232 83,225 1.2 Vernon CA 58,584 55,418 5.7 Courtenay CA 55,213 51,383 7.5 Duncan CA 43,252 41,387 4.5 Penticton CA 42,361 41,303 2.6

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Campbell River CA 36,096 34,707 4.0 Parksville CA 27,822 26,518 4.9 Fort St. John CA 26,380 25,136 4.9 Port Alberni CA 25,465 25,343 0.5 Cranbrook CA 25,037 24,138 3.7 Quesnel CA 22,096 21,049 5.0 Williams Lake CA 18,490 18,760 -1.4 Salmon Arm CA 17,683 16,205 9.1 Squamish CA 17,479 15,256 14.6 Powell River CA 16,689 16,537 0.9 Terrace CA 15,569 15,420 1.0 Prince Rupert CA 13,052 13,392 -2.5 Dawson Creek CA 11,583 10,994 5.4 Source: MPI. Statistics Canada, 2014.

When benchmarking on the 3Ts, which will be briefly explained below, normative claims are made based on current economic and social trends as to what assets regions should be attempting to maximize if they are to achieve economic growth. The 3Ts of economic development: Technology, Talent, or Tolerance provides a means to judge performance relative to other jurisdictions and their future socio-economic prosperity. The Creativity Index, which combines a region’s scores on the 3Ts, was originally conceived and developed to be a leading as opposed to a lagging indicator of regional prosperity. By looking at a region’s current position relative to a set of reasonable benchmark regions, anticipated performance can be approximated. Each CMA’s peers for benchmarking were selected based upon their population size, geographic location, and presence in one of the peer states or provinces for British Columbia. The selected regions are important components of the North American economic system, which is broadly defined by national borders, provincial/state divisions, municipal and county boundaries, but more importantly by actual integrated regions of economic activity. These peers are what Allen Scott would call “global city-regions” (Scott, 2001). Global city-regions are an extension of the global city theories of Sassen (1991), Knox (1995) and Friedmann and Wolff (1982). They are the centres of multinational corporations, knowledge transfer and a particularly unequal distribution of wealth. (Scott, 2001). Entities that resemble city states are emerging, demanding

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political power and autonomy over economic and social activities. These regions are not defined by pre-existing jurisdictional divisions. They are real in that the borders between those jurisdictions are porous allowing the free flow of people and commerce. This free flow between municipalities is based primarily on geographic proximity and the use of highway and rail infrastructure to move people efficiently and cost effectively across space. As the density of people and the velocity of activity increases, direct economic benefits are accrued in the form of higher wages and improved access to public goods such as health care, education, arts and culture. The organization of people in and around urban centres reduces the systematic and structural costs associated with the flow of knowledge. The global city-region becomes more international and more linked to the global network of commerce as it intensifies its use of space.

3Ts Background Information It is not a coincidence that certain global centres tend to be hotbeds of innovation and activity. Places like Paris, London, New York and more recently San Jose, home to Silicon Valley, are all prosperous. These regions inevitably produce a continuous infusion of new ideas, exporting of new products, services and or cultural fads in fashion, literature, computers or finance industries around the world. The global-city regions defy the old division between manufacturing centres and cultural/service centres. These large multifunctional regions are not absorbing manufacturing processes; rather manufacturing is declining as a share of the North American economy. The individuation and specialization that characterized cities in a manufacturing based economy have become obsolete. Just as the industrial revolution brought to an end the rural community, the rise of the creative economy is bringing about an end to the industry town and the large cities built upon single industries. Places like Pittsburgh and Detroit are struggling to survive in a world that has passed them by. Once pillars of American capitalism, these regions have been downgraded to second or third tier regions. The Ontario regions of Windsor, Oshawa and Hamilton are experiencing the same shock as they struggle to maintain employment and their old standards of living that were tied to specific industrial sectors.

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The centrality of knowledge in global cities allows individuals to redefine and create new markets. Scattered knowledge is of little use; when focused in specific nodes it becomes accessible for those who can reconfigure it into creative output. The creative activities of today’s economy require a workforce that is educated but their agglomeration in a region does not come about by chance. All regions must organize their resources to align incentives and pull capital from all around the globe. Capital can be defined as factors of production that are not significantly altered by productive activities and remain available for future finite uses. Examples of capital are financial (monetary), physical, social and human capital. These forms of capital are used to both reproduce and expand the current stock of capital in a society. Physical capital like factories, large equipment, and various forms of real-estate remains rooted in place while human and financial capital have been largely freed to move without friction in the economy. The relocation of human and financial capital requires an alteration of its social function as it must adapt and become part of the new regional system. While the qualities inherent to any form of capital remain constant across geographies, the organization and structure that embodies it alters its social function. The relation of various forms of new capital inter-jurisdictionally provides opportunities for economic growth in both relative and absolute terms. In absolute terms the movement of capital requires resources that are committed to its reproduction and therefore necessitates an expansion of the economic “pie”. The movement also causes relative economic growth, resulting from capital being put to more productive uses, decreasing costs or creating competitive advantages that result in larger returns – either wages or profits. All of which raise GDP per capita. The 3Ts of economic development are part of a theory that gives primacy to the attraction and retention of a specific type of capital – creative capital. Creative capital differs from human capital by identifying the Creative Class as key to economic growth and its focus on the underlying factors that determine their location decisions (Florida, 2002). In the creative economy, brawn and the ability to mass produce goods is subordinate to the innate human capability to generate new ideas, concepts, products and processes. The Creative Class is defined as people in occupations paid to think. Regions that attract and retain this group of workers are best positioned to succeed in the future. The global city hierarchy of the creative age will be determined not

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by access to natural resources, but by how and which is able to attract this class of worker. With the concentration of Talent and the multitude of perspectives that comes with people being able to carve out their own space in a new community (Tolerance), come new technologies and innovations that support continued growth (Technology). Each of the 3Ts plays an important role in the ability of regions to attract the Creative Class. As a result regions should not choose to focus on any one ‘T’; each is necessary but not sufficient for economic growth. In the creative age, regions will continued to be judged by their GDP per capita and other traditional measures, but it will be their overall creative output that determines their sustained success. For more information on our terminology refer to the Understanding our Terminology section at www.MartinProsperity.org. Detailed information about the data

items, methodology, and statistical sources are provided in the Appendices.2

The 3Ts and Economic Development

Technology: Innovation and High-tech Production Robert Solow, Paul Romer, Robert Lucas among others, have shown in different ways that technology is the driving force behind economic growth (e.g. Solow, 1956; Romer, 1990). Regions cannot access the global economy (let alone compete in it) without technologies that connect and provide high speed information processing. Global city-regions like Vancouver, Toronto, Seattle, and Los Angeles (to varying degrees) have highly sophisticated technology sectors and consumers. Success in the creative age is determined by regions able to gain first mover advantages. Regions that are able to introduce innovations and that have well developed high-tech industrial complexes are able to reap significant benefits in the form of sustainable growth and the production of new wealth. The Overall Technology Ranking is based on three separate measures that reflect a region’s innovativeness and the size of their high-tech producing industries. The three measures are: the North American Tech-Pole Index based on the share of employment

2 “Ontario Competes” is the first document released as part of the Martin Prosperity Institute’s benchmarking analysis for the Ontario in the Creative Age project. This document acts as a primer for all subsequent benchmarking releases; therefore, we highly recommend that one read this first. Follow this path to do so: http://martinprosperity.org/media/pdfs/Ontario_Competes.pdf

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in high-tech industries relative to the North American average, and two innovation measures: 1) total patents and 2) the year over year growth in patents for a five year period. The former is based on information from US County Business Pattern and Statistics Canada. All patent data is based on utility patent data from the United States Patent and Trade Office (USPTO). Utility patents are granted for the discovery of a process, machine, article of manufacture, or composition of matter that is new, useful and non-obvious.

Measuring Technology An economy is not technologically advanced because it is prosperous. Rather, it is prosperous because it is technologically advanced. Technology, and in particular, technological innovation, improves competitiveness by either providing new goods or services or by inducing cost advantages, often through productivity gains. Second, competitive advantages generate profits, which can be redistributed back into production in the form of investment or to increasing the average wage of employees. New ideas are what fuel economic growth. The competition amongst the most technologically advanced regions resembles what is a called a "race to the top" in game theory. And the way to win a race to the top is to take the most direct route. Look for the environment where structural conditions direct individuals and firms to produce more efficient outcomes, and you will find the frontrunners in the race to prosperity. Unlike some kinds of competition, which drain the rivals' resources, a race to the top affords efficiency gains for all of society, while the risk-taking innovators bear the costs of the rewards they expect to reap. The more companies and individuals you have trying to improve things, the better off the entire society will be. The nature of competition between firms has changed over the past decades. The marketplace for goods and services has developed from inter-firm rivalry in relatively small geographic regions to a global battle between large multinational corporations. At the apex of this economic ladder, regions are separated only by marginal differences in productivity. As a result, firms within regions are competing aggressively for the smallest technological advantages over their rivals. What this means is that if you're not

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innovating, you are not only failing to grow, you are giving your rivals room to do so. There is no stasis in this game. To determine how a region stacks up technologically against its competitors, we looked at two indicators: how much innovation is simmering in the province, and how important technology-related industries are to the economy. A great way to measure technological innovation is to track applications for patents. Patents are used to guarantee inventors a period of time to recoup the cost associated with bringing new ideas to the market. In the process of patenting products, inventors disclose information related to the product so that others may learn and benefit from their work. Patents promote the accumulation and growth of knowledge in the public rather than in the private sphere. You need patent protection to foster innovation, just as you need innovation to spur patent applications. To adjust for the size difference between the regions, we calculated the number of patents per 10,000 people. But patent activity measures only catalogued innovation, not the importance of that technology to the economy. The North American Tech-Pole Index is an indicator designed to capture the size and importance of tech industries in a region. A high ranking indicates a region with a significant level of activity in high-tech industries. The level of activity is not tied to the total economic output but rather to the number of people employed. The differential is significant, underscoring the value of technology as a driver of economic growth. It is clear that these are the kinds of jobs to cultivate, but “this isn’t your father’s technology”. Appendix B lists the specific industries used in constructing the Tech Pole Index, and they were specifically selected to most closely match the industries used in the original Tech Pole Index established by the Milken Institute. Technology. Today’s “high tech” includes many new occupations or new parts in existing occupations. However, just having a significant proportion of the workforce in technology related jobs is not enough to measure up in this first of the three "T"s. While it is critically important to have large numbers of people employed in technology industries, it is equally crucial to fuel these industries with patentable new ideas.

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Talent: Human Capital and the Creative Class The Creative Class is composed of people who are paid to think for a living, including people working in Technology, Arts and Culture, Professional, including legal, financial, and medical, and Education (TAPE) occupations. The indicators used for Talent combine an examination of the Creative Class with other, more traditional measures of human capital. Using both an occupational measure and educational measures better captures the creative capital of a region. Human capital became a major theme in economics with the work of Jacob Mincer (1958), Gary Becker (1964), and most recently Ed Glaeser (2001). Their work has demonstrated the importance of investing in personal productivity as a way to generate growth for firms and regions. Due the high correlation between the Talent Index, population greater than 25 years of age with a Bachelor’s Degree or above and the Creative Class, only the latter is used to rank the peer regions on Talent. The Creative Class reflects the ability of individuals to transfer their abilities as measured by the Talent Index into high value economic activities manifested in occupations. One key to improving a region’s ranking against its technological peers is the performance of the region’s talent, the second of the three "T"s. Any region requires its creative people to provide the innovation necessary to compete globally. How the region stacks up against the competition will go a long way towards determining the kind of prosperity that will develop.

Measuring Talent There are a number of ways to measure something as intangible as talent, but they fall into two categories: education level and occupation. Education is a good proxy for talent⎯measure the population's education level and you begin to get a sense of what it is capable of achieving. And looking at what those people actually do day in and day out is a good way measuring how talented they are. Talent's role in regional development is not entirely straightforward. It is not a commodity in the traditional sense or a product that the individual can use. Talent enhances a region’s prosperity, and through this the individual benefits. This process occurs through a number of mechanisms, such as the attraction of business and the

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utilization of knowledge and skills to the creation of new ideas, which in turn lead to greater economic productivity. Talent is the driving force behind production. Talented people generate ideas and bring them to market. And it is a talented workforce that innovates and develops the technologies that stimulate economic development. Moreover, this dependence on talent only increases in a global economy marked by the flow of new ideas and the sharing of knowledge. Talent breeds talent. The processes that allow a region to perform well on talent are not accidental. There are distinct ways in which a region can concentrate its efforts to improve upon its talent base. By creating, attracting, and retaining talent, a region can achieve advantages over other places. Although regional advantage was once limited to transportation access, natural resources and the costs of labour, this is no longer the case. Talent is becoming increasingly uneven and divergent between regions. And, while talent creation is important, the regions that can successfully attract and retain talent will ultimately be the most competitive. More than ever before, talented workers have the ability to locate wherever they desire. An excellent example of this would be Silicon Valley, which acts as a talent magnet, drawing talented workers from all over North America and globally. These workers have in turn created some of the most successful companies in the world, thus it is no surprise that Northern California is an incredibly prosperous region. But while great migrations of talented people mean that some places swell with creative, innovative people, things do not look as promising if you live in one of the places where your talented neighbours are packing up to head to more prosperous locales. The sobering reality is that if you are not attracting talent, you are probably losing it. In the race to the top, those in front just get faster, while those tailing tend to fall further behind. As with the other two "T"s, the point is not just to perform decently. The goal must be to rank among the very best globally competitive jurisdictions. What is truly surprising is that researchers affiliated with the Martin Prosperity Institute have shown that college degrees have no significant impact on income, and are unlikely to affect regional development.3 Improving performance requires putting

2 MPI Working Paper - Richard Florida, Charlotta Mellander, Kevin Stolarick (2009). Talent, Technology and Tolerance in Canadian Regional Development

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investments where they are most effective. The Brain Drain/Gain Index measures the number of people graduating with BA degrees in the region, versus the number of people working with degrees in the same region. It tells us roughly what direction a region's talent is headed. A Brain Drain/Gain Index number of over 1.0 indicates that a region is attracting educated workers, and a number of less than 1.0 indicates that a region is losing them to other places. If a region could develop talent at the same pace it attracts it, it would climb these indices and, more importantly, show measurable gains in innovation. Although education shows a high correlation with regional development, it is not the only indicator of talent. Talent is measured by other factors, and creativity is an extremely important dimension. Unfortunately, capturing the creative component of talent is difficult when using education levels as a measure. The inability of education to properly describe all aspects of talent forces us to use other indicators as well if we want a complete picture. Instead of looking just at what people know, we need to look at what they actually do4. Occupational skill affects wages, and through this leads to increases in regional labour productivity. It is a dynamic measure which makes occupation an excellent measure of talent, and has been shown to have strong relationships with regional development. Looking at specific occupations, we can measure the creative component of a region’s workforce; if you can figure out how creative a region's workforce is, you can benchmark how talented it is. Creative workers are important because of their ability to invent and innovate. Companies locate in cities and regions with large numbers of creative workers in order to capture the benefits these people offer. Not only do good companies attract good people; good people attract good companies. Creativity is measured by examining jobs that pay a person to think; this is in contrast to most working class jobs, which require routine physical inputs. We refer to this group of creative workers as creativity-oriented, or the Creative Class. Although the exact definition of the Creative Class is not fixed and will change over time as the requirements of various occupations change, it is possible to identify the occupations

4 MPI Working Paper - Karen King, Charlotta Mellander, Kevin Stolarick (2009). What You Do, Not Who You Work For: A Comparison of the Occupational and Industry Structures of Canada, the United States, and Sweden

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which currently can be considered as ‘creative’ work. Broadly, the acronym TAPE is used to describe the Creative Class. It stands for Technology, Arts and Culture, Professionals, Educators⎯people who add economic value by using their creativity. Generally, the Creative Class includes senior and specialist managers, high-ranking business and finance positions, health care professionals, scientists and advanced technicians, educators, professional occupations in arts, culture and sport, and thinkers like judges, lawyers, social workers and psychologists. The important characteristic these occupations share is their intellectual autonomy. These people are not only paid to think, but to make decisions. A subsection of the Creative Class has been identified as the Super Creative Core. These people are considered to be extremely creative, developing new knowledge across many fields of study and work in occupations “that produce new forms and ideas that are readily transferable and widely useful” (Florida, 2002). They tend to be the professionals and teachers across the disciplines of science and culture who furnish a society with its ideas. Because of the uniqueness and potentially distinct advantage that this group of workers provides, we have also benchmarked the Super Creative Core.

Tolerance: Openness, Inclusion, and Diversity

So far, we have focused primarily on how talent and technology are important to continued success, but little has been said of how a region can improve in these areas. This is the role the third "T" plays in regional development: talent is attracted to a place by tolerance of other views, ethnicities, and sexual orientations, and that talent in turn generates technology and economic development. While tolerance is not normally considered vital to economic growth, openness and inclusiveness are not just ethical goals⎯they imply whole new ways of thinking that lead to innovation. John Stuart Mill (1869) recognized long ago that tolerance is essential to objective thinking. The toleration of diverse opinions allows an intellectual freedom that is just not available when the individual rights of the person are not given their fullest expression.

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In other words, a society should strive for tolerance not for the sake of the people it is called upon to tolerate, but for everyone's benefit. We all benefit from tolerance and positive attitudes towards diverse points of view. It is only when everyone is free to express diverse opinions that we can fully explore the world. Just as technology breeds technology, and talent attracts talent, tolerance leads to more tolerance. It attracts the Creative Class. The Creative Class can be defined along two lines. First, they prize individuality and the opportunity for self-expression. Second, they very clearly value diversity and openness; in fact, the very idea of an occupationally defined creative class cuts across all classifications based on ethnicity, gender, or sexual orientation. A bellwether subgroup of this class is what we call Bohemians, or the artists and iconoclasts that keep a culture fresh and fizzing with new ideas. Bohemians do not seek to be at the core of accepted culture; they would rather remain on the edge where they can be individuals, and allowed freedom of self-expression. A vibrant economy relies on these people for innovation, and tolerance of the new and challenging is what attracts and keeps them around. The regions and cities with the highest concentrations of bohemians tend to be the world's most exciting and prosperous, just as tolerant regions provide talent the space necessary to conduct research and to engage in activities that may not be possible in less open and diverse places. The level of tolerance in a society or region can only be approximated. To understand the variation in tolerance between different North American jurisdictions we use five variables which measure diversity as a marker of tolerance: the Mosaic Index, Visible Minorities Index, the Bohemian Index, the Integration Index and the Gay and Lesbian Index indicate the openness and diversity of regions. The Bohemian, Gay and Lesbian, and Mosaic index are used as the main indicators of openness. The Integration Index measures whether racial groups live together in a community. The diversity of a region, which is measured by the Visible Minority Index, indicates low barriers to entry. A tolerant and inclusive culture does not guarantee success, but it does provide greater access for everyone. Tolerance acts to equalize differences; it facilitates talent by embracing difference and focusing on merit. Of course, tolerance does not magically erase all inequalities, but it works towards this goal. Canada, generally, has a culture of

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tolerance. People from all over the world come to live here. While BC does have a core cultural group, it does not exclude other groups on the periphery from accessing the public sphere. So it may not come as a surprise that the regions in the province perform well on tolerance measures. Finally, we created the Bohemian Index in an attempt to measure the freedom individuals have to express themselves in a given region. The index measures whether the number of bohemians in a region is greater or less than the average. A culture of tolerance creates a place for any region among North America's most competitive jurisdictions. Those regions become a magnet for exactly the kind of people needed to nourish economic growth and cross the threshold between an economy built on brawn to one fuelled by brains. The infusion of new ideas that comes with rubbing shoulders with different cultures and perspectives and tolerance ensures continuation of building on that strength.

Measuring Tolerance Tolerance is often overlooked. As the 3rd T of economic development, Tolerance is necessary to the ability of regions to act as magnets of creative capital. The collection of Tolerance indicators does not indicate that regions with high levels of gay and lesbians, bohemians, or immigrants cause economic growth. Rather, these indicators go deeper, reflecting cultural elements that are difficult to capture empirically. Regions that are receptive to different types of people have a more open-minded culture, which is conducive to creativity. The creative process that leads to innovation needs space in the social system for ideas to form. When regions are open to new ideas and tolerant they become attractive as places where people can easily network and connect. The ability to tap into the rich diversity of a region is a great competitive advantage that all regions should aspire to. The Overall Tolerance Ranking is based on four of the five measures that reflect the openness and diversity of the peer regions. The four measures are: 1) the Bohemian Index, which compares the share of regional employment in a select group of occupations against the North American share; 2) the Gay and Lesbian Index which measures the share of a region’s same sex marriages relative to the North American average; 3) The Mosaic Index, or the percent of the population that is foreign born; and

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4) the Integration Index, which uses neighbourhood and regional data to determine how racially mixed the peer regions are.

The “4th T” – Quality of Place While available and open jobs are still an important component of attracting workers to a region, for creative workers just the job is not enough. Regions also have to be diverse, inclusive places as previously discussed, but also need other regional amenities or characteristics to be successful in attracting and retaining creative workers. Territorial Assets or Quality of Place are also included as part of the benchmarking package. For this benchmarking, three broad areas, each with their own specific measures are provided. This is called the “4th T” in order to call attention to the fact that, unlike the 3Ts, strong performance for a region can’t always be measured or compared across multiple regions using the same measures. Each region needs to work to leverage and maximize the attractiveness of its own regional amenities rather than try to be just like every other region or work to provide the same bundle of amenities as everyone else. The measures provided here are among those typically used to measure quality of place and are meant to provide some indication of each CMA’s quality of place, but the reader is cautioned that true success with regional amenities comes from focusing on uniqueness and not ubiquity. The measures presented are social and cultural, civic, and housing and transportation assets. For social and cultural, arts and culture establishments (museums, libraries, etc.) and restaurants and bars are considered. Both are measured on an effective per capita basis so that both number and availability to the average resident are considered. For civic assets the measures are voter turnout at the last federal election and total crime per capita. The housing and transportation category includes three measures. They are: population density, the ratio of median housing value to household income (lower values are better), and the total number of solo drivers of cars to all other methods of commuting to work (again, lower is better). As with all benchmark measures, the full details are provided in Appendix A.

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Observations for BC’s Four CMAs Below in the report are specific comments and observations for each CMA and following that are the detailed benchmark scorecards for each CMA. First are some comments common to all the CMAs in British Columbia (for this point just CMAs). This will include overall comments followed by comments for technology, talent, and Tolerance.

• Generally, the CMAs have an older population than their peer benchmark regions. Abbotsford is the exception, but the other three are all either the oldest or second oldest among their peers. • Cost of living is generally higher. Again, away from the coast, and it is not as bad. But for the coastal CMAs, cost of living is much higher.

Overall Creativity Index

Creativity Rank City Index 1 Seattle, WA 0.87 2 Boston, MA 0.85 3 Vancouver, BC 0.81 4 Los Angeles, CA 0.81 5 Montréal, QC 0.78 6 New York, NY 0.76 7 Atlanta, GA 0.76 8 Toronto, ON 0.74 9 Dallas, TX 0.72 10 Chicago, IL 0.70 11 Detroit, MI 0.62 Vancouver (metro Vancouver)

Creativity Rank City Index 1 Ann Arbor, MI 0.84 2 Victoria, BC 0.82 3 Santa Barbara, CA 0.72 4 Tallahassee, FL 0.70 5 London, ON 0.68 6 Lansing, MI 0.67 7 Spokane, WA 0.56 8 Fort Wayne, IN 0.52 9 Canton, OH 0.45 10 Reading, PA 0.38 11 Peoria, IL 0.38 Victoria (metro Victoria)

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Creativity Rank City Index 1 Sherbrooke , QC 0.68 2 Kelowna, BC 0.58 3 Bloomington, IL 0.51 4 Trois-Rivières, QC 0.51 5 Greater Sudbury, ON 0.48 6 College Station, TX 0.44 7 State College, PA 0.44 8 Battle Creek, MI 0.42 9 Mount Vernon, WA 0.38 10 Dalton, GA 0.27 11 Rocky Mount, NC 0.24 Kelowna (regional Kelowna)

Creativity Rank City Index 1 Sherbrooke , QC 0.68 2 Kelowna, BC 0.58 3 Bloomington, IL 0.51 4 Trois-Rivières, QC 0.51 5 College Station, TX 0.44 6 State College, PA 0.44 7 Battle Creek, MI 0.42 8 Abbotsford, BC 0.39 9 Mount Vernon, WA 0.38 10 Dalton, GA 0.27 11 Rocky Mount, NC 0.24 Abbotsford (Abbotsford and Mission)

Overall – Technology • Technology scores, especially patents and patenting, are not particular strengths for the CMAs. • In general the scores for the larger CMAs are basically ‘OK’ and in the middle, but the scores for smaller CMAs is not as good. In general, smaller metros have lower absolute scores anyway, and that pattern is clearly seen here.

Overall – Talent • Canada generally does very well on share of the population with a post-secondary education but, especially when compared to metros in the US, Canada generally has much lower scores on university and graduate education.

Martin Prosperity Institute -- Stolarick (Draft) 20 Creative BC Benchmarking, February 2014

• That pattern is clearly seen in these CMAs and with the smaller CMAs even the share of the population with at least a high school diploma is much lower. • The share of the workforce in the Creative Class is generally pretty good for the CMAs. It is not quite as good for the smaller regions, but this is a very typical result. • The Super Creative Core makes up a much larger share of the workforce in the CMAs than for the peers. This could be either a factor of the different occupational definitions that are used in Canada (NOCS) and the US (SOC) or from the difference in CMA and MSA definitions and land areas or from Canadian firms employing more Super Creative Core workers.

Overall – Tolerance • This whole area is simply a tremendous strength for the CMAs as it is for the larger cities across Canada. • Even the smaller CMAs measure up quite well on this dimension.

Overall – Territory Assets/Quality of Place • Crime is almost always much higher for the CMAs. This is also true for Canada as a whole. Quite likely, and this is an explanation that has been offered often in the literature, this is a combination of a reporting bias from individuals and a result of the way crime is reported in Canada. The reporting bias results from individuals in Canada simply reporting many more small or even nuisance crimes than in cities in the US. It’s not that Canada has more crime – more crimes are reported. • Housing costs when compared to household income for the CMAs is just much higher than in the US peers. • The discussion and analysis of the individual territory assets results for each CMA are left to the reader. Other than these couple of important observations, the remainder of the scores and rankings are self-explanatory.

Vancouver (metro Vancouver) Overall • Vancouver is the smallest of the benchmark regions as it is in the group of regions with over 2 million population, but Vancouver just passed that mark. • The overall results reflect that Vancouver is being compared to larger regions. • Vancouver has a fairly high median age. • Vancouver has the highest cost of living, even higher than New York. But, part of this result is driven by the fact that Stats Canada defines CMAs to be more compact and smaller in total land area than the US Office of Management and Budget which sets the standards for US Metropolitan Statistical Areas (MSAs). New York is the entire metro, including significant parts of New Jersey and the suburban and even exurban areas. So, overall the cost of living is lower. • Vancouver has a low GDP per capita. Only Montreal is lower. Since this is on a per capita basis, the difference in population is taken into account.

Martin Prosperity Institute -- Stolarick (Draft) 21 Creative BC Benchmarking, February 2014

• The overall Creativity Index for Vancouver is fairly high, and Vancouver ranks third among the peer metros.

Technology • Vancouver ranks low in total number of patents, but given the smaller population compared to the other metros, it is not a real surprise. However, when measured on a per 10,000 people basis, Vancouver’s patent performance is the best among major Canadian cities, but not that great • Average patent growth has been good but lower total numbers make higher growth rate possible. • Vancouver if firmly in the middle on the High Tech and Tech Pole rankings.

Talent • Vancouver is roughly on par with 33% of its workforce in the Creative Class. Canadian cities all have a higher share of their workforce in the Super Creative Core – this could be either a factor of the different occupational definitions that are used in Canada (NOCS) and the US (SOC) or from the difference in CMA and MSA definitions and land areas or from Canadian firms employing more Super Creative Core workers. • Like cities across Canada, Vancouver has a large share of the population with some postsecondary education, but is low in comparison to US metros when compared on bachelor’s degrees and graduate degrees. • The Brain Drain/Gain Index score above 1.0 means that Vancouver has a greater share of its workforce with a BA than the share of university-aged students attending university. The region is attracting educated people from other locations. And, although Vancouver has a positive score on this measure, it does not score as well as most of the benchmark metros.

Tolerance • This whole area is simply a tremendous strength for Vancouver as it is for the larger cities across Canada.

Victoria (metro Victoria) Overall • Victoria has the highest median age among the benchmark regions. Really, much higher median age. Not that this is surprise to anyone. • Victoria has a very high cost of living. It is actually tied for first with Ann Arbor, Michigan, a major US college town. • Victoria had relatively strong population and job growth. • The GDP per capita is especially impressive considering Victoria has the lowest population among all the benchmark metros.

Martin Prosperity Institute -- Stolarick (Draft) 22 Creative BC Benchmarking, February 2014

• The Creativity Index for Victoria is high, and the CMA ranks second only behind Ann Arbor.

Technology • Victoria scores lowest on total patents and patents per 10,000 residents but highest on average annual patent growth. The high patent growth is mostly the result of having such low patent numbers. • The city shows better performance among its peers on High Tech and the Tech Pole.

Talent • Victoria is in the top half of workforce in the Creative Class at 33%. • The region is also very strong on Super Creative Core. • Victoria’s educational performance, especially BA and graduate scores are quite high by Canadian standards, but only roughly in the middle when compared with US metros. • The Brain Drain/Gain Index shows that Victoria is producing university educated at a higher level than the region is able to put them to work – a brain drain situation.

Tolerance • This whole area is simply a tremendous strength for Victoria as it is for the larger cities across Canada. • One exception for Victoria is the share of the population that is a visible minority. It is much lower in Victoria than for larger cities across Canada, but not that much lower than for other similarly sized Canadian cities.

Kelowna (regional Kelowna) Overall • Kelowna has a much lower cost of living than many of the other benchmark cities and ranks much lower than Vancouver and Victoria. • Kelowna has seen strong population and job growth. • Overall, Kelowna ranks second among its benchmark peers on the Creativity Index, but, not unexpectedly, as a smaller city, its overall score on the Creativity Index is much lower than Vancouver and Victoria.

Technology • Kelowna ranks in the middle on the various patent measures and still shows strong and significant patent growth. • The region also ranks highly against its peers on the High Tech and Tech Pole scores, but as a smaller city, the absolute scores are lower.

Talent

Martin Prosperity Institute -- Stolarick (Draft) 23 Creative BC Benchmarking, February 2014

• Kelowna ranks and scores like a typical Canadian city on BA and graduate education levels. • However, it scores much lower than other regions on the share of the population above 25 with a high school diploma but without a BA. Given the fairly low BA and graduate scores, this means that Kelowna scores poorly overall on talent in that a significant share of the population is without a high school diploma.

Tolerance • This whole area is simply a tremendous strength for Kelowna as it is for the larger cities across Canada.

Abbotsford (Abbotsford and Mission) Overall • It should be noted that because of the way the peer benchmark cities are selected, it turned out that Kelowna is considered a benchmark for Abbotsford, but Abbotsford is not a benchmark for Kelowna. So, Kelowna is also on this list but simply as one of the ten benchmark regions for Abbotsford. • Unlike the other CMAs in BC, Abbotsford does not have one of the highest median ages. In fact, Abbotsford is in the lower half by median age. • Abbotsford, like Kelowna, has a lower cost of living, and Abbotsford is tied for second lowest cost of living among the peers. • The region has seen strong population and job growth but with a decrease in the average wage paid. • Abbotsford is in the bottom third among its peers on the Creativity Index. It also has a fairly low score in absolute terms.

Technology • Abbotsford is just solidly in the middle on all of the technology scores. • Given the small size of the CMA, the absolute scores are quite low.

Talent • Abbotsford has a very low share of its workforce in the Creative Class. At 21% is ranks second from the bottom among the peers. • The region ranks more in the middle on the Super Creative Core, but given the typical very strong performance among Canadian cities on this measure, Abbotsford’s “middle” score should be interpreted as quite low. • Abbotsford ranks and scores like a typical Canadian city on BA and graduate education levels – perhaps even a little lower than typical even for a Canadian city. • However, it scores much lower than other regions on the share of the population above 25 with a high school diploma but without a BA – even lower than Kelowna. Given the fairly low BA and graduate scores, this means that Abbotsford scores poorly on overall

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talent levels across the region and that a significant share of the population is without a high school diploma.

Tolerance • This whole area is simply a strength for Abbotsford as it is for the larger cities across Canada. • Abbotsford, as it typical for smaller cities, does not score as highly on the gay and lesbian index. • The region also has a lower integration index score, but part of the reason for that lower score is because of the fairly large share of the population that is a visible minority.

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Following are the detailed benchmark reports for:

1. Vancouver (metro Vancouver)

2. Victoria (metro Victoria)

3. Kelowna (regional Kelowna)

4. Abbotsford (Abbotsford and Mission)

Martin Prosperity Institute -- Stolarick (Draft) 26 Benchmark Summary: Vancouver, BC vs. 10 Peer Regions

Peer Peer Peer Provincial/State Summary Statistics Vancouver, BC Minimum Average Maximum Average Total Population, 2006 2,117,000 2,116,581 6,876,000 18,819,000 546,000 GDP (CAD millions) 2006 $96,000 $96,000 $414,000 $1,273,000 $29,000 Median Age, 2006 39.1 33.1 36.7 39.3 37.5

Vancouver, Peer Peer Peer Peer Provincial/State Overall Performance BC Ranking Minimum Average Maximum Average Population Growth (00-05) 6.5% 5 0% 7.2% 20.9% 5.7% Job Growth (00-05) 5.6% 7 -2.6% 8.1% 18.7% 9.3% GDP per capita, 2006 Change $45,000 10 $43,100 $59,000 $73,700 $45,000 in Average Wage (00-05) -1.4% 7 -6.3% -1.2% 2.8% 0.1% Creativity Index 0.81 3 0.62 0.76 0.87 N/A

Vancouver, Peer Peer Peer Peer Provincial/State Technology BC Ranking Minimum Average Maximum Average Total Patents, 2005 418 10 378 2,012 5,298 517 Patents per 10,000, 2005 Patent 1.97 8 1.04 3.03 6.09 2.46 Growth, Short Term (00-05) North 0.8% 2 -8.3% -2.0% 5.5% -0.5% American High Tech LQ, 2006 1.27 6 0.65 1.23 2.01 0.63 North American Tech Pole Index 1.471 8 1.198 3.289 8.527 0.189

Vancouver, Peer Peer Peer Peer Provincial/State Talent BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 33.1% 5 28.9% 33.2% 39.5% 26.1% Super Creative Core as % of Workforce, 2006 17.9% 3 9.6% 14.5% 18.4% 11.0% Pop > 25, Above High School below BA, 2006 Talent 51.2% N/A 47.2% 51.5% 60.4% 59.0% Index (Pop > 25, BA and above), 2006 Pop > 25, 24.9% 10 21.2% 30.4% 40.6% 21.7% Graduate and/or Professional Degree, 2006 7.6% 10 6.6% 10.8% 17.5% 7.5% Brain Drain/Gain Index, 2006 1.30 8 0.87 1.38 1.73 N/A

Vancouver, Peer Peer Peer Peer Provincial/State Tolerance BC Ranking Minimum Average Maximum Average Visible Minorities (% Pop), 2006 41.4% 4 16.2% 33.8% 49.0% 11.1% Mosaic Index (% Pop), 2006 39.3% 2 8.5% 23.3% 45.4% 7.9% Gay and Lesbian Index, 2006 1.56 2 0.71 1.29 1.69 0.81 Bohemian Index, 2006 1.82 1 0.79 1.34 1.82 0.69 Integration Index, 2006 0.49 4 0.23 0.44 0.72 N/A

Vancouver, Peer Peer Peer Peer Territorial Assets BC Ranking Minimum Average Maximum Social and Cultural Assets Arts and Cultural Establishments per 10,000, 2006 11.74 1 0.79 4.70 11.74 Resturants and Bars per 1,000, 2006 3.24 2 1.60 2.26 3.30 Civic Assets Federal Voter Turnout (%), 2004/2006 62% 4 45% 57% 68% Violent and Property Crime per Capita, 2006 0.09 11 0.03 0.05 0.09 Housing and Transportation Assets Population Density (KM2), 2006 736 5 206.43 595.39 1020.34 Median Housing Value to Income Ratio, 2005 8.02 10 2.71 5.63 10.89 Drivers per Other Modes, 2006 3.26 4 1.62 10.64 32.65

11 Regions in Peer Group: Atlanta, GA; Boston, MA; Chicago, IL; Dallas, TX; Detroit, MI; Los Angeles, CA; Montréal, QC; New York, NY; Seattle, WA; Toronto, ON; Vancouver, BC

Summary Statistics

Summary Statistics Peer Peer Peer Provincial/State Vancouver, BC Minimum Average Maximum Average Total Population, 2006 2,117,000 2,116,581 6,876,000 18,819,000 546,000 GDP (CAD millions) 2006 $96,000 $96,000 $414,000 $1,273,000 $29,000 Median Age, 2006 39.1 33.1 36.7 39.3 37.5

Total Population Vancouver, BC and Peer Regions, 2006

New York, NY 18,819,000 Los Angeles, CA 12,950,000 Chicago, IL 9,507,000 Dallas, TX 6,006,000 Atlanta, GA 5,135,000 Toronto, ON 5,113,000 Boston, MA 4,619,000 Detroit, MI 4,469,000 Montréal, QC 3,636,000 Seattle, WA 3,263,000 Vancouver, BC 2,117,000

Source: Statistics Canada Catalogue no. 94-581-XCB2006004. US Census Bureau, American Community Survey. (2006).

GDP (CAD Millions) Vancouver, BC and Peer Regions, 2006

New York, NY $1,272,700

Los Angeles, CA $761,900 Chicago, IL $555,900

Dallas, TX $380,200 Boston, MA $314,600 Atlanta, GA $292,000 Toronto, ON $262,100 Detroit, MI $239,300 Seattle, WA $219,500 Montréal, QC $156,600 Vancouver, BC #N/A $96,300

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Median Age Vancouver, BC and Peer Regions, 2006

Montréal, QC 39.3 Vancouver, BC 39.1 Boston, MA 38.2 Detroit, MI 37.7 Toronto, ON 37.5 New York, NY 37.4 Seattle, WA 37.1 Chicago, IL 35.3 Atlanta, GA 34.6 Los Angeles, CA 34.3 Dallas, TX 33.1

Source: Statistics Canada Catalogue no. 97-551-xcb2006012. U.S. Census Bureau, 2006 American Community Survey.

Vancouver, BC 0.00 109.86 Toronto, ON 104.14 Boston, MA 103.77 Atlanta, GA 101.43 Dallas, TX 101.43 Chicago, IL 101.43 Seattle, WA 100.45 Detroit, MI 96.23 Montréal, QC 95.36 New York, NY 94.42 Los Angeles, CA 85.08

Overall Performance

Vancouver, Peer Peer Peer Peer Provincial/State Overall Performance BC Ranking Minimum Average Maximum Average Population Growth (00-05) 6.5% 5 0% 7.2% 20.9% 5.7% Job Growth (00-05) 5.6% 7 -2.6% 8.1% 18.7% 9.3% GDP per capita, 2006 Change in $45,000 10 $43,100 $59,000 $73,700 $45,000 Average Wage (00-05) -1.4% 7 -6.3% -1.2% 2.8% 0.1% Creativity Index 0.81 3 0.62 0.76 0.87 N/A

Population Growth Vancouver, BC and Peer Regions, (00-05)

Atlanta, GA 20.9% Dallas, TX 16.4% Toronto, ON 9.2% Seattle, WA 7.2% Vancouver, BC 6.5% Montréal, QC 5.3% Los Angeles, CA 4.7% Chicago, IL 4.5% New York, NY 2.7% Boston, MA 1.5% Detroit, MI 0.4%

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and Statistics Canada Catalogue no. 95-f0495-xcb-01004 US Census Bureau, American Community Survey. (2006) and US Census, 2000

Job Growth Vancouver, BC and Peer Regions, (00-05)

Atlanta, GA 18.7%

Dallas, TX 16.9% Los Angeles, CA 14.1% Seattle, WA 9.3% New York, NY 9.0% Chicago, IL 7.3% Vancouver, BC 5.6%

Toronto, ON 4.5%

Montréal, QC 3.4%

Boston, MA 3.0%

Detroit, MI -2.6%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

GDP per Capita Vancouver, BC and Peer Regions, 2006

Boston, MA $73,700 Seattle, WA $70,000 New York, NY $69,400 Dallas, TX $66,400 Atlanta, GA $60,500 Los Angeles, CA $60,000 Chicago, IL $60,000 Detroit, MI $54,000 Toronto, ON $51,300 Vancouver, BC $45,500 Montréal, QC $43,100

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Boston, MA 2.8%

Los Angeles, CA 2.0%

New York, NY 1.0%

Seattle, WA 0.5%

Toronto, ON 0.3%

Montréal, QC -1.2%

Vancouver, BC -1.4%

Atlanta, GA -2.7%

Chicago, IL -2.8% Dallas, TX -5.1%

Detroit, MI -6.3%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

Creativity Index Vancouver, BC and Peer Regions, 2006

Seattle, WA 0.87

Boston, MA 0.85 Vancouver, BC 0.81

Los Angeles, CA 0.81 Montréal, QC 0.78

New York, NY 0.76 Atlanta, GA 0.76

Toronto, ON 0.74 Dallas, TX 0.72

Chicago, IL 0.70

Detroit, MI 0.62

Source: MPI Analysis. Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Technology

Total Patents Vancouver, BC and Peer Regions, 2005

Los Angeles, CA 5,298 New York, NY 4,062 Boston, MA 2,711 Chicago, IL 2,267 Detroit, MI 2,022 Seattle, WA 1,713 Dallas, TX 1,710 Atlanta, GA 993 Toronto, ON 555 Vancouver, BC 0 418 Montréal, QC 378

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07). Patents have allocated by population for all Canadian CMAs excluding those in Ontario. Due to unassigned patents we have assumed that 1 patent is equal to 2.5 and have allocated accordingly

Patents per 10,000 Vancouver, BC and Peer Regions, 2005

Boston, MA 6.09 Seattle, WA 5.25 Detroit, MI 4.52 Los Angeles, CA 4.09 Dallas, TX 2.85 Chicago, IL 2.38 New York, NY 2.16 Vancouver, BC 1.97 Atlanta, GA 1.93 Toronto, ON 1.09 Montréal, QC 1.04

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

Patent Growth, Short Term Vancouver, BC and Peer Regions, (00-05)

Seattle, WA 5.5%

Vancouver, BC 0.8% Los Angeles, CA 0.4%

Atlanta, GA -0.4%

Detroit, MI -0.9%

Boston, MA -1.1%

Montréal, QC -1.5%

Dallas, TX -4.1%

Chicago, IL -6.1% New York, NY -6.9%

Toronto, ON 0.0%

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

North American High Tech LQ Vancouver, BC and Peer Regions, 2006

Seattle, WA 2.01

Los Angeles, CA 1.47

Montréal, QC 1.45

Boston, MA 1.42

Toronto, ON 1.29 Vancouver, BC 1.27

Dallas, TX 1.17

Detroit, MI 0.95

New York, NY 0.94

Atlanta, GA 0.87 Chicago, IL 0.65

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

North American Tech Pole Index Vancouver, BC and Peer Regions, 2006

Los Angeles, CA 8.527 New York, NY 4.995 Seattle, WA 4.440 Toronto, ON 3.702 Boston, MA 3.448 Montréal, QC 3.279 Dallas, TX 2.608 Vancouver, BC 1.471 Chicago, IL 1.282 Atlanta, GA 1.229 Detroit, MI 1.198

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

Talent

Creative Class as % of Workforce Vancouver, BC and Peer Regions, 2006

Boston, MA 39.5%

New York, NY 34.5% Toronto, ON 34.3% Seattle, WA 33.3% Vancouver, BC 33.1% Atlanta, GA 33.0% Montréal, QC 32.8% Los Angeles, CA 32.8% Chicago, IL 31.7% Dallas, TX 31.6% Detroit, MI 28.9%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Toronto, ON 18.4%

Montréal, QC 18.3% Vancouver, BC 17.9%

Boston, MA 16.4% Seattle, WA 15.4%

New York, NY 14.0%

Los Angeles, CA 12.9%

Dallas, TX 12.8%

Chicago, IL 12.1%

Atlanta, GA 11.9% Detroit, MI 9.6%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Above High School below BA Vancouver, BC and Peer Regions, 2006

Detroit, MI 60.4%

Seattle, WA 54.8% Chicago, IL 53.0% Atlanta, GA 52.5% Dallas, TX 51.8% Vancouver, BC 51.2% Montréal, QC 50.5% New York, NY 49.2% Boston, MA Los 48.6% Angeles, CA 47.5% Toronto, ON 47.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Boston, MA 40.6% Seattle, WA 36.1% New York, NY 34.5% Atlanta, GA 33.3% Chicago, IL 31.6% Dallas, TX 29.4% Los Angeles, CA 29.3% Toronto, ON 26.7% Detroit, MI 26.3% Vancouver, BC 24.9% Montréal, QC 21.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Graduate and/or Professional Degree Vancouver, BC and Peer Regions, 2006

Boston, MA 17.5% New York, NY 14.1% Seattle, WA 12.6% Chicago, IL 12.0% Atlanta, GA 11.1% Los Angeles, CA 10.0% Detroit, MI 9.9% Dallas, TX 9.3% Toronto, ON 8.3% Vancouver, BC 7.6% Montréal, QC 6.6%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Brain Drain/Gain Index Vancouver, BC and Peer Regions, 2006

Atlanta, GA 1.73

Seattle, WA 1.69 Dallas, TX 1.59

Toronto, ON 1.59

New York, NY 1.40

Chicago, IL 1.36

Boston, MA 1.35

Vancouver, BC 1.30

Los Angeles, CA 1.15 Detroit, MI 1.10

Montréal, QC 0.87

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007 and AUCC Enrollment numbers 2007. US Census Bureau, American Community Survey. (2006).

Tolerance

Visible Minorities (% Pop) Vancouver, BC and Peer Regions, 2006

Los Angeles, CA 49.0%

Toronto, ON 42.5% Atlanta, GA 41.9% Vancouver, BC 41.4% New York, NY 40.4% Chicago, IL 36.4%

Dallas, TX 31.7% Detroit, MI 29.6% Seattle, WA 24.1%

Boston, MA 18.6% Montréal, QC 16.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Toronto, ON 45.4% Vancouver, BC 39.3% Los Angeles, CA 34.2% New York, NY 28.2% Montréal, QC 20.4% Dallas, TX 18.0% Chicago, IL 17.8% Seattle, WA 15.8% Boston, MA 15.8% Atlanta, GA 13.0% Detroit, MI 8.5%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Gay and Lesbian Index

Vancouver, BC and Peer Regions, 2006

Montréal, QC 1.69 Vancouver, BC 1.56 Seattle, WA 1.53 Atlanta, GA 1.37 Toronto, ON 1.35 Los Angeles, CA 1.33 Boston, MA 1.25 New York, NY 1.23 Dallas, TX 1.17 Chicago, IL 0.99 Detroit, MI 0.71

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-553-XWE2006002 and 97-552-XCB2006007. US Census (2006).

Vancouver, BC 1.82

Los Angeles, CA 1.81 Toronto, ON 1.75

New York, NY 1.75

Montréal, QC 1.54

Seattle, WA 1.35

Boston, MA 1.28

Atlanta, GA 0.94

Chicago, IL 0.93

Detroit, MI 0.80 Dallas, TX 0.79

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Integration Index Vancouver, BC and Peer Regions, 2006

Seattle, WA 0.72

Montréal, QC 0.68 Boston, MA 0.63

Vancouver, BC 0.49 Dallas, TX 0.43

Toronto, ON 0.43

Atlanta, GA 0.38

Detroit, MI 0.34 Los Angeles, CA 0.29 Chicago, IL 0.25 New York, NY 0.23

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and 94-580-XCB2006005. US Census Bureau, American Community Survey. (2006).

Arts and Cultural Establishments per 10,000 Vancouver, BC and Peer Regions, 2006

Vancouver, BC 11.74

Toronto, ON 10.99 Montréal, QC 10.45

Los Angeles, CA 7.58 New York, NY 3.15

Seattle, WA 1.70 Boston, MA 1.56 Atlanta, GA 1.45 Chicago, IL 1.39 Dallas, TX 0.92 Detroit, MI 0.79

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Toronto, ON 3.30

Vancouver, BC 3.24 Montréal, QC 2.94

Seattle, WA 2.36

Boston, MA 2.23

New York, NY 2.02 Chicago, IL Los 1.84 Angeles, CA 1.83 Atlanta, GA 1.80 Detroit, MI 1.70 Dallas, TX 1.60

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Student/Teacher Ratio Vancouver, BC and Peer Regions, 2006

Detroit, MI 12.67 Seattle, WA 13.94 Atlanta, GA 14.83 Dallas, TX 15.30 New York, NY 15.79 Los Angeles, CA 16.45 Toronto, ON 17.04 Montréal, QC 17.13 Vancouver, BC 18.20 Chicago, IL 18.69 Boston, MA 19.84

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

New York, NY 2.04 Detroit, MI 2.02 Boston, MA 1.78 Montréal, QC 1.49 Toronto, ON 1.26 Vancouver, BC 1.24 Dallas, TX 0.95 Seattle, WA 0.91 Chicago, IL 0.81

Atlanta, GA 0.65 Los Angeles, CA 0.61

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Federal Voter Turnout (%) Vancouver, BC and Peer Regions, 2004/2006

Toronto, ON 67.7%

Detroit, MI 66.0% Montréal, QC 63.6%

Vancouver, BC 62.4%

Seattle, WA 62.0%

Boston, MA 61.6% Chicago, IL 54.9% Atlanta, GA 50.7% New York, NY 50.0% Dallas, TX 46.2% Los Angeles, CA 45.1%

Source: MPI Analysis. Elections Canada Official Voting Results of the 39th General Election – Poll-by-Poll Results. US, POLIDATA (www.polidata.us )

Violent and Property Crime per Capita Vancouver, BC and Peer Regions, 2006

New York, NY 0.026

Atlanta, GA 0.039 Los Angeles, CA 0.043

Dallas, TX 0.044 Toronto, ON 0.045

Boston, MA 0.050

Detroit, MI 0.059 Montréal, QC 0.060

Chicago, IL 0.062 Seattle, WA 0.063 Vancouver, BC 0.091

Source: Statistics Canada CANSIM TABLE 3260021 (2006). US, ACCRA Cost of Living Index (2007).

Population Density (KM^2) Vancouver, BC and Peer Regions, 2005

Los Angeles, CA 1,020 New York, NY 984 Toronto, ON 866 Montréal, QC 854 Vancouver, BC 736 Chicago, IL 503 Boston, MA 468 Detroit, MI 429 Dallas, TX 250 Atlanta, GA 234 Seattle, WA 206

Source: MPI Analysis (2008). Statistics Canada, Catalogue No. 94-581-X2006005

Dallas, TX 2.71

Detroit, MI 3.33 Atlanta, GA 3.36

Montréal, QC 4.24 Chicago, IL 4.42

Toronto, ON

Seattle, WA 5.73

Boston, MA 6.30

New York, NY 7.74

Vancouver, BC 8.02

Los Angeles, CA 10.89

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, American Community Survey 2006

Drivers per Other Modes Vancouver, BC and Peer Regions, 2006

New York, NY 1.62 Montréal, QC 2.59 Toronto, ON 2.64 Vancouver, BC 3.26 Boston, MA 4.99 Chicago, IL 5.88 Seattle, WA 7.79 Los Angeles, CA 9.74 Atlanta, GA 17.41 Dallas, TX 28.50 Detroit, MI 32.65

Source: Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Peer Peer Peer Provincial/State Summary Statistics Victoria, BC Minimum Average Maximum Average Total Population, 2006 330,000 330,088 396,000 458,000 546,000 GDP (CAD millions) 2006 $15,000 $14,000 $18,000 $21,000 $29,000 Median Age, 2006 43.1 33.4 36.8 43.1 37.5

Peer Peer Peer Peer Provincial/State Overall Performance Victoria, BC Ranking Minimum Average Maximum Average Population Growth (00-05) 5.8% 4 0% 4.1% 7.4% 5.7% Job Growth (00-05) 7.1% 3 -3.3% 4.0% 11.6% 9.3% GDP per capita, 2006 Change $47,000 5 $37,500 $47,000 $65,200 $45,000 in Average Wage (00-05) 1.9% 3 -8.8% -0.1% 9.0% 0.1% Creativity Index 0.82 2 0.38 0.61 0.84 N/A

Peer Peer Peer Peer Provincial/State Technology Victoria, BC Ranking Minimum Average Maximum Average Total Patents, 2005 31 11 31 110 394 517 Patents per 10,000, 2005 Patent 0.94 11 0.94 2.87 11.45 2.46 Growth, Short Term (00-05) North 17.5% 1 -12.7% 1.3% 17.5% -0.5% American High Tech LQ, 2006 0.90 3 0.26 0.79 1.87 0.63 North American Tech Pole Index 0.115 3 0.008 0.105 0.385 0.189

Peer Peer Peer Peer Provincial/State Talent Victoria, BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 33.2% 4 24.7% 30.0% 38.2% 26.1% Super Creative Core as % of Workforce, 2006 18.6% 1 9.4% 13.1% 18.6% 11.0% Pop > 25, Above High School below BA, 2006 Talent 55.9% N/A 41.2% 57.9% 67.5% 59.0% Index (Pop > 25, BA and above), 2006 Pop > 25, 24.4% 7 17.8% 27.7% 51.7% 21.7% Graduate and/or Professional Degree, 2006 8.8% 6 6.0% 10.6% 26.2% 7.5% Brain Drain/Gain Index, 2006 0.70 10 0.68 0.88 1.27 N/A

Peer Peer Peer Peer Provincial/State Tolerance Victoria, BC Ranking Minimum Average Maximum Average Visible Minorities (% Pop), 2006 10.3% 8 0.0% 14.7% 37.7% 11.1% Mosaic Index (% Pop), 2006 18.8% 3 2.2% 9.5% 23.6% 7.9% Gay and Lesbian Index, 2006 1.53 1 0.59 0.95 1.53 0.81 Bohemian Index, 2006 1.60 1 0.35 0.72 1.60 0.69 Integration Index, 2006 0.80 3 0.54 0.71 0.90 N/A

Peer Peer Peer Peer Territorial Assets Victoria, BC Ranking Minimum Average Social and Cultural Assets Maximum Arts and Cultural Establishments per 10,000, 2006 6.85 1 0.77 2.01 6.85 Resturants and Bars per 1,000, 2006 2.75 1 1.67 2.02 2.75 Civic Assets Federal Voter Turnout (%), 2004/2006 70% 2 54% 64% 71% Violent and Property Crime per Capita, 2006 0.09 11 0.03 0.05 0.09 Housing and Transportation Assets Population Density (KM2), 2006 475 1 52.78 150.10 474.71 Median Housing Value to Income Ratio, 2005 8.17 10 2.44 4.59 12.82 Drivers per Other Modes, 2006 3.47 1 3.47 18.53 37.98

11 Regions in Peer Group: Ann Arbor, MI; Canton, OH; Fort Wayne, IN; Lansing, MI; Peoria, IL; Reading, PA; Santa Barbara, CA; Spokane, WA; Tallahassee, FL; London, ON; Victoria, BC

Summary Statistics

Total Population Victoria, BC and Peer Regions, 2006

London, ON 458,000 Lansing, MI 454,000 Spokane, WA 447,000 Canton, OH 410,000 Fort Wayne, IN 409,000 Reading, PA 401,000 Santa Barbara, CA 400,000 Peoria, IL 370,000 Ann Arbor, MI 344,000 Tallahassee, FL 338,000 Victoria, BC 330,000

Source: Statistics Canada Catalogue no. 94-581-XCB2006004. US Census Bureau, American Community Survey. (2006).

GDP (CAD Millions) Victoria, BC and Peer Regions, 2006

London, ON $21,200

Santa Barbara, CA $20,900

Ann Arbor, MI

Lansing, MI $20,200 Fort Wayne, IN $18,700

Spokane, WA $18,000 Peoria, IL $17,400

Reading, PA $15,600 Victoria, BC #N/A $15,400 Canton, OH $15,000 Tallahassee, FL $13,900

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Median Age Victoria, BC and Peer Regions, 2006

Victoria, BC 43.1

Canton, OH 40.2 London, ON 38.6 Reading, PA 38.1 Peoria, IL 37.4 Spokane, WA Fort 36.1 Wayne, IN 35.6 Lansing, MI Santa 34.6 Barbara, CA 33.8 Tallahassee, FL 33.5 Ann Arbor, MI 33.4

Source: Statistics Canada Catalogue no. 97-551-xcb2006012. U.S. Census Bureau, 2006 American Community Survey.

Ann Arbor, MI 107.38 Victoria, BC 107.38 Fort Wayne, IN 103.77 Reading, PA 101.43 Spokane, WA 100.45 Tallahassee, FL 100.45 Lansing, MI Santa 97.81 Barbara, CA 96.23 Peoria, IL 93.30 Canton, OH 92.89 London, ON 91.06

Overall Performance

Peer Peer Peer Peer Provincial/State Overall Performance Victoria, BC Ranking Minimum Average Maximum Average Population Growth (00-05) 5.8% 4 0% 4.1% 7.4% 5.7% Job Growth (00-05) 7.1% 3 -3.3% 4.0% 11.6% 9.3% GDP per capita, 2006 Change in $47,000 5 $37,500 $47,000 $65,200 $45,000 Average Wage (00-05) 1.9% 3 -8.8% -0.1% 9.0% 0.1% Creativity Index 0.82 2 0.38 0.61 0.84 N/A

Population Growth Victoria, BC and Peer Regions, (00-05)

Reading, PA 7.4%

Spokane, WA Ann 6.9% Arbor, MI 6.6%

Victoria, BC 5.8% Tallahassee, FL 5.5%

London, ON Fort 5.1%

Wayne, IN 4.8%

Lansing, MI 1.4%

Peoria, IL 0.9% Canton, OH 0.8%

Santa Barbara, CA 0.2%

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and Statistics Canada Catalogue no. 95-f0495-xcb-01004 US Census Bureau, American Community Survey. (2006) and US Census, 2000

Job Growth Victoria, BC and Peer Regions, (00-05)

Spokane, WA 11.6%

Reading, PA 10.4% Victoria, BC 7.1%

Tallahassee, FL 6.1% Santa Barbara, CA 3.4%

London, ON 3.2%

Peoria, IL 2.4%

Canton, OH 2.2%

Fort Wayne, IN 1.0% Ann Arbor, MI 0.1%

Lansing, MI -3.3%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

GDP per Capita Victoria, BC and Peer Regions, 2006

Ann Arbor, MI $65,200 Santa Barbara, CA $54,500 Peoria, IL $48,600 Fort Wayne, IN $47,300 Victoria, BC $46,700 Lansing, MI $46,500 London, ON $46,300 Tallahassee, FL $43,700 Spokane, WA $42,300 Reading, PA $40,700 Canton, OH $37,500

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Santa Barbara, CA 9.0% Tallahassee, FL 3.7% Victoria, BC 0.0% 1.9% Ann Arbor, MI 1.6% London, ON 0.1% Peoria, IL -0.1% Spokane, WA -0.3% Lansing, MI -0.9% Reading, PA -3.7% Fort Wayne, IN -4.0% Canton, OH -8.8%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

Creativity Index Victoria, BC and Peer Regions, 2006

Ann Arbor, MI 0.84 Victoria, BC Santa Barbara, CA 0.72 Tallahassee, FL 0.70 London, ON 0.68 Lansing, MI 0.67 Spokane, WA Fort 0.56 Wayne, IN 0.52 Canton, OH 0.45 Reading, PA 0.38 Peoria, IL 0.38

Source: MPI Analysis. Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Technology

Technology Peer Peer Peer Peer Provincial/State Victoria, BC Ranking Minimum Average Maximum Average Total Patents, 2005 31 11 31 110 394 517 Patents per 10,000, 2005 Patent 0.94 11 0.94 2.87 11.45 2.46 Growth, Short Term (00-05) North 17.5% 1 -12.7% 1.3% 17.5% -0.5% American High Tech LQ, 2006 0.90 3 0.26 0.79 1.87 0.63 North American Tech Pole Index 0.115 3 0.008 0.105 0.385 0.189

Total Patents Victoria, BC and Peer Regions, 2005

Ann Arbor, MI 394 Santa Barbara, CA 206 Canton, OH 134 Fort Wayne, IN 96 Lansing, MI 70 Peoria, IL 68 Reading, PA 55 Spokane, WA 55 London, ON 51 Tallahassee, FL 46 Victoria, BC 0 31.00

Patents per 10,000 Victoria, BC and Peer Regions, 2005

Ann Arbor, MI 11.45 Santa Barbara, CA 5.15 Canton, OH 3.27 Fort Wayne, IN 2.35 Peoria, IL 1.84 Lansing, MI 1.54 Reading, PA 1.37 Tallahassee, FL 1.36 Spokane, WA 1.23 London, ON 1.11 Victoria, BC 0.94

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

Patent Growth, Short Term Victoria, BC and Peer Regions, (00-05)

Victoria, BC 0.0% 17.5%) Tallahassee, FL 13.2% Santa Barbara, CA 4.9% Canton, OH 4.7% Spokane, WA 3.0% Ann Arbor, MI 1.3% Lansing, MI -0.6% London, ON -1.1% Fort Wayne, IN -6.5% Peoria, IL -9.3% Reading, PA-12.7%

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

North American High Tech LQ Victoria, BC and Peer Regions, 2006

Ann Arbor, MI 1.87

Santa Barbara, CA 1.73

Victoria, BC 0.90

London, ON 0.72

Fort Wayne, IN 0.68 Spokane, WA 0.66

Reading, PA 0.65

Tallahassee, FL 0.53

Lansing, MI 0.43

Peoria, IL 0.27 Canton, OH 0.26

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

North American Tech Pole Index Victoria, BC and Peer Regions, 2006

Ann Arbor, MI 0.385 Santa Barbara, CA 0.319 Victoria, BC 0.115 London, ON 0.101 Fort Wayne, IN 0.066 Spokane, WA 0.059 Reading, PA 0.046 Tallahassee, FL 0.023 Lansing, MI 0.022 Peoria, IL 0.009 Canton, OH 0.008

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

Talent

Peer Peer Peer Peer Provincial/State Talent Victoria, BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 33.2% 4 24.7% 30.0% 38.2% 26.1% Super Creative Core as % of Workforce, 2006 18.6% 1 9.4% 13.1% 18.6% 11.0% Pop > 25, Above High School below BA, 2006 55.9% N/A 41.2% 57.9% 67.5% 59.0% Talent Index (Pop > 25, BA and above), 2006 Pop 24.4% 7 17.8% 27.7% 51.7% 21.7% > 25, Graduate and/or Professional Degree, 2006 8.8% 6 6.0% 10.6% 26.2% 7.5% Brain Drain/Gain Index, 2006 0.70 10 0.68 0.88 1.27 N/A

Creative Class as % of Workforce Victoria, BC and Peer Regions, 2006

Tallahassee, FL 38.2%

Ann Arbor, MI 35.6%

Lansing, MI 34.3%

Victoria, BC 33.2% London, ON Santa 29.0% Barbara, CA 28.8% Fort Wayne, IN 27.3% Spokane, WA 26.8% Peoria, IL 26.7% Canton, OH 25.4% Reading, PA 24.7%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Victoria, BC 18.6% Ann Arbor, MI 16.5% Tallahassee, FL 15.5% London, ON 15.3% Lansing, MI Santa 15.2% Barbara, CA 12.8% Spokane, WA Fort 10.6% Wayne, IN 10.0% Peoria, IL 9.8% Reading, PA 9.8% Canton, OH 9.4%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Above High School below BA Victoria, BC and Peer Regions, 2006

Canton, OH 67.5%

Fort Wayne, IN 64.8% Peoria, IL 63.7%

Spokane, WA 63.3%

Lansing, MI 59.6%

Reading, PA 59.5%

London, ON 58.5% Victoria, BC 55.9%

Tallahassee, FL 53.3% Santa Barbara, CA 49.4%

Ann Arbor, MI 41.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Ann Arbor, MI 51.7%

Tallahassee, FL 32.2% Lansing, MI Santa 31.7% Barbara, CA 30.4% Spokane, WA 27.9% Peoria, IL 25.3% Victoria, BC 24.4% Fort Wayne, IN 23.8% Reading, PA 21.4% Canton, OH 18.1% London, ON 17.8%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Graduate and/or Professional Degree Victoria, BC and Peer Regions, 2006

Ann Arbor, MI 26.2% Tallahassee, FL 13.2% Lansing, MI 12.4% Santa Barbara, CA 11.2% Spokane, WA 9.2% Victoria, BC 8.8% Peoria, IL 8.6% Fort Wayne, IN 8.1% Reading, PA 7.2% London, ON 6.2% Canton, OH 6.0%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Brain Drain/Gain Index Victoria, BC and Peer Regions, 2006

Fort Wayne, IN 1.27 Peoria, IL 1.08 Spokane, WA Ann 1.01 Arbor, MI 0.96 Reading, PA Santa 0.93

Barbara, CA 0.82 Canton, OH 0.80 Tallahassee, FL 0.74 Lansing, MI 0.71 Victoria, BC 0.70 London, ON 0.68

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007 and AUCC Enrollment numbers 2007. US Census Bureau, American Community Survey. (2006).

Tolerance

Visible Minorities (% Pop) Victoria, BC and Peer Regions, 2006

Tallahassee, FL 37.7%

Ann Arbor, MI 24.2% Santa Barbara, CA 22.2%

Lansing, MI 15.9% Fort Wayne, IN 15.8% Reading, PA 15.1%

London, ON 11.0% Victoria, BC 10.3% Spokane, WA 9.2%

Canton, OH N/A Peoria, IL N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Santa Barbara, CA 23.6% London, ON 19.1% Victoria, BC 18.8% Ann Arbor, MI 11.4% Reading, PA 6.9% Lansing, MI 6.0% Tallahassee, FL 4.9% Spokane, WA 4.8% Fort Wayne, IN 4.5% Peoria, IL 2.4% Canton, OH 2.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Gay and Lesbian Index

Victoria, BC and Peer Regions, 2006

Victoria, BC 1.53 Ann Arbor, MI 1.29 Santa Barbara, CA 1.15 London, ON 1.04 Tallahassee, FL 0.97 Lansing, MI 0.95 Spokane, WA 0.85 Fort Wayne, IN 0.75 Reading, PA 0.70 Peoria, IL 0.61 Canton, OH 0.59

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-553-XWE2006002 and 97-552-XCB2006007. US Census (2006).

Victoria, BC 1.60 Ann Arbor, MI 1.02 London, ON Fort 0.92 Wayne, IN Santa 0.85 Barbara, CA 0.63 Tallahassee, FL 0.58 Canton, OH 0.54 Spokane, WA 0.52 Peoria, IL 0.43 Lansing, MI 0.43 Reading, PA 0.35

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Integration Index Victoria, BC and Peer Regions, 2006

Spokane, WA 0.90 Canton, OH 0.82 Victoria, BC 0.80 London, ON 0.78 Peoria, IL 0.73 Lansing, MI 0.71 Fort Wayne, IN 0.68 Reading, PA 0.67 Ann Arbor, MI 0.65 Tallahassee, FL 0.57 Santa Barbara, CA 0.54

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and 94-580-XCB2006005. US Census Bureau, American Community Survey. (2006).

Peer Peer Peer Peer Territorial Assets Victoria, BC Ranking Minimum Average Maximum Social and Cultural Assets Arts and Cultural Establishments per 10,000, 2006 6.85 1 0.77 2.01 6.85 Resturants and Bars per 1,000, 2006 2.75 1 1.67 2.02 2.75 Civic Assets Federal Voter Turnout (%), 2004/2006 70% 2 54% 64% 71% Violent and Property Crime per Capita, 2006 0.09 11 0.03 0.05 0.09 Housing and Transportation Assets Population Density (KM2), 2006 475 1 52.78 150.10 474.71 Median Housing Value to Income Ratio, 2005 8.17 10 2.44 4.59 12.82 Drivers per Other Modes, 2006 3.47 1 3.47 18.53 37.98

Arts and Cultural Establishments per 10,000 Victoria, BC and Peer Regions, 2006

Victoria, BC 6.85 London, ON 3.74 Santa Barbara, CA 2.97 Ann Arbor, MI 1.48 Spokane, WA 1.30 Peoria, IL 1.30 Tallahassee, FL 1.07 Reading, PA 0.95 Canton, OH 0.90 Fort Wayne, IN 0.81 Lansing, MI 0.77

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Victoria, BC 2.75 London, ON Santa 2.47 Barbara, CA 2.20 Peoria, IL 2.14 Spokane, WA 2.02 Canton, OH 1.91 Fort Wayne, IN 1.82 Ann Arbor, MI 1.79 Lansing, MI 1.74 Tallahassee, FL 1.72 Reading, PA 1.67

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Student/Teacher Ratio Victoria, BC and Peer Regions, 2006

Peoria, IL 11.37

Tallahassee, FL 14.78 London, ON 15.10

Lansing, MI Santa 15.73 Barbara, CA 15.77

Canton, OH 16.50 Fort Wayne, IN 16.90

Spokane, WA 16.93

Ann Arbor, MI 17.05

Victoria, BC 18.08

Reading, PA 21.63

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

London, ON 2.24 Ann Arbor, MI 1.86 Victoria, BC 1.26 Canton, OH 1.15 Peoria, IL Lansing, 1.13 MI 1.10 Tallahassee, FL 1.04 Spokane, WA Fort 0.92 Wayne, IN 0.76 Reading, PA Santa 0.47 Barbara, CA 0.20

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Federal Voter Turnout (%) Victoria, BC and Peer Regions, 2004/2006

Tallahassee, FL 71.1% Victoria, BC 69.7% Ann Arbor, MI 68.8% Lansing, MI 68.7% London, ON 66.7% Canton, OH 66.4% Peoria, IL 63.7% Spokane, WA 61.7% Santa Barbara, CA 59.5% Reading, PA 55.8% Fort Wayne, IN 53.8%

Source: MPI Analysis. Elections Canada Official Voting Results of the 39th General Election – Poll-by-Poll Results. US, POLIDATA (www.polidata.us )

Violent and Property Crime per Capita Victoria, BC and Peer Regions, 2006

Canton, OH 0.031

Santa Barbara, CA 0.035 Tallahassee, FL 0.038

Spokane, WA 0.045 Lansing, MI 0.045

Peoria, IL 0.049

Reading, PA Fort 0.051 Wayne, IN Ann 0.052

Arbor, MI 0.059 London, ON 0.073 Victoria, BC 0.093

Source: Statistics Canada CANSIM TABLE 3260021 (2006). US, ACCRA Cost of Living Index (2007).

Population Density (KM^2) Victoria, BC and Peer Regions, 2005

Victoria, BC 475 Ann Arbor, MI 184 Reading, PA 179 London, ON 172 Canton, OH 162 Fort Wayne, IN 115 Lansing, MI 102 Spokane, WA 97 Peoria, IL 57 Santa Barbara, CA 56 Tallahassee, FL 53

Source: MPI Analysis (2008). Statistics Canada, Catalogue No. 94-581-X2006005

Peoria, IL 2.44 Fort Wayne, IN 2.44 Reading, PA 2.99 Canton, OH 3.01 Lansing, MI 3.20 London, ON Spokane, WA 3.84 Tallahassee, FL 3.93 Ann Arbor, MI 4.15

Victoria, BC 8.17 Santa Barbara, CA 12.82

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, American Community Survey 2006

Drivers per Other Modes Victoria, BC and Peer Regions, 2006

Victoria, BC 3.47

London, ON Ann 6.62 Arbor, MI Santa 8.32

Barbara, CA 10.52 Lansing, MI 14.17

Spokane, WA 15.25 Reading, PA 16.16

Canton, OH 26.49 Tallahassee, FL 27.67

Fort Wayne, IN 37.18 Peoria, IL 37.98

Source: Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Peer Peer Peer Provincial/State Summary Statistics Kelowna, BC Minimum Average Maximum Average Total Population, 2006 162,000 115,700 153,000 197,000 546,000 GDP (CAD millions) 2006 $7,000 $5,000 $7,000 $9,000 $29,000 Median Age, 2006 43.4 25.7 36.5 43.8 37.5

Peer Peer Peer Peer Provincial/State Overall Performance Kelowna, BC Ranking Minimum Average Maximum Average Population Growth (00-05) 9.8% 3 0% 5.9% 12.4% 5.7% Job Growth (00-05) 12.9% 2 -3.6% 5.0% 19.9% 9.3% GDP per capita, 2006 Change $42,000 7 $35,500 $45,000 $58,200 $45,000 in Average Wage (00-05) -0.6% 5 -11.2% -1.6% 3.9% 0.1% Creativity Index 0.58 2 0.24 0.45 0.68 N/A

Peer Peer Peer Peer Provincial/State Technology Kelowna, BC Ranking Minimum Average Maximum Average Total Patents, 2005 17 6 2 18 42 517 Patents per 10,000, 2005 Patent 1.05 6 0.14 1.20 2.98 2.46 Growth, Short Term (00-05) North 27.8% 2 -4.5% 13.2% 56.7% -0.5% American High Tech LQ, 2006 0.70 2 0.22 0.57 1.54 0.63 North American Tech Pole Index 0.030 3 0.002 0.020 0.079 0.189

Peer Peer Peer Peer Provincial/State Talent Kelowna, BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 25.7% 6 18.5% 24.8% 29.4% 26.1% Super Creative Core as % of Workforce, 2006 12.0% 6 5.6% 11.9% 16.3% 11.0% Pop > 25, Above High School below BA, 2006 Talent 21.3% N/A 21.3% 54.5% 65.5% 59.0% Index (Pop > 25, BA and above), 2006 Pop > 25, 12.4% 9 12.0% 21.3% 40.2% 21.7% Graduate and/or Professional Degree, 2006 3.4% 10 3.4% 7.8% 20.5% 7.5% Brain Drain/Gain Index, 2006 0.00 11 0.00 0.69 1.28 N/A

Peer Peer Peer Peer Provincial/State Tolerance Kelowna, BC Ranking Minimum Average Maximum Average Visible Minorities (% Pop), 2006 5.1% 3 0.0% 5.1% 28.1% 11.1% Mosaic Index (% Pop), 2006 14.6% 2 2.2% 7.6% 15.0% 7.9% Gay and Lesbian Index, 2006 0.70 9 0.64 0.78 1.03 0.81 Bohemian Index, 2006 1.05 1 0.16 0.45 1.05 0.69 Integration Index, 2006 0.86 4 0.52 0.77 0.92 N/A

Peer Peer Peer Peer Territorial Assets Kelowna, BC Ranking Minimum Average Maximum ` Social and Cultural Assets Arts and Cultural Establishments per 10,000, 2006 6.66 1 0.22 2.31 6.66 Resturants and Bars per 1,000, 2006 2.96 2 1.46 2.16 3.02 Civic Assets Federal Voter Turnout (%), 2004/2006 63% 1 40% 629% 6333% Violent and Property Crime per Capita, 2006 0.07 11 0.02 0.05 0.07 Housing and Transportation Assets Population Density (KM2), 2006 56 5 25.34 71.54 160.76 Median Housing Value to Income Ratio, 2005 7.14 11 2.48 3.54 7.14 Drivers per Other Modes, 2006 12.28 5 4.84 28.50 169.98

11 Regions in Peer Group: Battle Creek, MI; Bloomington, IL; College Station, TX; Dalton, GA; Greater Sudbury, ON; Mount Vernon, WA; Rocky Mount, NC; Sherbrooke , QC; State College, PA;

Summary Statistics

Total Population Kelowna, BC and Peer Regions, 2006

College Station, TX 197,000 Sherbrooke , QC 187,000 Kelowna, BC 162,000 Bloomington, IL 161,000 Greater Sudbury, ON 158,000 Rocky Mount, NC 146,000 Trois-Rivières, QC 142,000 State College, PA 141,000 Battle Creek, MI 138,000 Dalton, GA 134,000 Mount Vernon, WA 116,000

Source: Statistics Canada Catalogue no. 94-581-XCB2006004. US Census Bureau, American Community Survey. (2006).

GDP (CAD Millions) Kelowna, BC and Peer Regions, 2006

Bloomington, IL $8,600 Sherbrooke , QC $7,200 Greater Sudbury, ON $7,200 Kelowna, BC #N/A $6,800 Dalton, GA $6,700 Rocky Mount, NC $6,700 College Station, TX $6,500 State College, PA $5,800 Mount Vernon, WA $5,500 Battle Creek, MI $5,500 Trois-Rivières, QC $5,300

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Median Age Kelowna, BC and Peer Regions, 2006

Trois-Rivières, QC 43.8

Kelowna, BC 43.4 Greater Sudbury, ON 41.0

Sherbrooke , QC 40.2 Rocky Mount, NC 38.2

Battle Creek, MI 37.8 Mount Vernon, WA 37.3

Dalton, GA 33.8 Bloomington, IL 31.0

State College, PA 29.3 College Station, TX 25.7

Source: Statistics Canada Catalogue no. 97-551-xcb2006012. U.S. Census Bureau, 2006 American Community Survey.

College Station, TX 107.38 Battle Creek, MI 104.14 Trois-Rivières, QC 103.77 Sherbrooke , QC 100.45 State College, PA 100.45 Mount Vernon, WA 100.28 Bloomington, IL 98.95 Dalton, GA 97.52 Kelowna, BC 97.52 Greater Sudbury, ON 97.14 Rocky Mount, NC 96.23

Overall Performance

Peer Peer Peer Peer Provincial/State Overall Performance Kelowna, BC Ranking Minimum Average Maximum Average Population Growth (00-05) 9.8% 3 0% 5.9% 12.4% 5.7% Job Growth (00-05) 12.9% 2 -3.6% 5.0% 19.9% 9.3% GDP per capita, 2006 $42,000 7 $35,500 $45,000 $58,200 $45,000 Change in Average Wage (00-05) -0.6% 5 -11.2% -1.6% 3.9% 0.1% Creativity Index 0.58 2 0.24 0.45 0.68 N/A

Population Growth Kelowna, BC and Peer Regions, (00-05)

Mount Vernon, WA 12.4%

Dalton, GA 12.0% Kelowna, BC 9.8%

Bloomington, IL 7.2% College Station, TX 6.4%

Sherbrooke , QC 6.3%

State College, PA 3.8%

Trois-Rivières, QC 2.9%

Rocky Mount, NC 2.3% Greater Sudbury, ON 1.7%

Battle Creek, MI 0.0%

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and Statistics Canada Catalogue no. 95-f0495-xcb-01004 US Census Bureau, American Community Survey. (2006) and US Census, 2000

Job Growth Kelowna, BC and Peer Regions, (00-05)

Mount Vernon, WA 19.9% Kelowna, BC 12.9% Dalton, GA 8.7% Bloomington, IL 4.7% College Station, TX 3.6% Rocky Mount, NC 3.1% Sherbrooke , QC 2.6% State College, PA 2.4% Trois-Rivières, QC 1.6% Greater Sudbury, ON -0.5% Battle Creek, MI -3.6%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

GDP per Capita Kelowna, BC and Peer Regions, 2006

Bloomington, IL $58,200 Dalton, GA $51,500 Mount Vernon, WA $49,700 Rocky Mount, NC $46,900 State College, PA $46,800 Greater Sudbury, ON $45,300 Kelowna, BC $41,900 Battle Creek, MI $40,800 Sherbrooke , QC $38,400 Trois-Rivières, QC $37,300 College Station, TX $35,500

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Greater Sudbury, ON 3.9%

State College, PA 3.7%

College Station, TX 3.4%

Sherbrooke , QC 0.6%

Kelowna, BC -0.6

Mount Vernon, WA -1.6%

Trois-Rivières, QC -1.8% Bloomington, IL -2.1%

Battle Creek, MI -5.9% Rocky Mount, NC -6.5% Dalton, GA -11.2%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

Creativity Index Kelowna, BC and Peer Regions, 2006

Sherbrooke , QC 0.68 Kelowna, BC 0.58 Bloomington, IL 0.51 Trois-Rivières, QC 0.51 Greater Sudbury, ON 0.48 College Station, TX 0.44 State College, PA 0.44 Battle Creek, MI 0.42 Mount Vernon, WA 0.38 Dalton, GA 0.27 Rocky Mount, NC 0.24

Source: MPI Analysis. Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Technology

Total Patents Kelowna, BC and Peer Regions, 2005

State College, PA 42 College Station, TX 31 Battle Creek, MI 29 Bloomington, IL 28 Sherbrooke , QC 22 Kelowna, BC 0 17 Mount Vernon, WA 11 Dalton, GA 9 Greater Sudbury, ON 8 Trois-Rivières, QC 4 Rocky Mount, NC 2

Patents per 10,000 Kelowna, BC and Peer Regions, 2005

State College, PA 2.98 Battle Creek, MI 2.10 Bloomington, IL 1.74 College Station, TX 1.58 Sherbrooke , QC 1.18 Kelowna, BC 1.05 Mount Vernon, WA 0.95 Dalton, GA 0.67 Greater Sudbury, ON 0.51 Trois-Rivières, QC 0.28 Rocky Mount, NC 0.14

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

Patent Growth, Short Term Kelowna, BC and Peer Regions, (00-05)

Trois-Rivières, QC 56.7% Kelowna, BC 0.0% 27.8% Bloomington, IL 24.6% Greater Sudbury, ON 22.2% Sherbrooke , QC 15.1% Mount Vernon, WA 5.9% Rocky Mount, NC 0.0% Battle Creek, MI -0.3% College Station, TX -0.7% Dalton, GA -2.0% State College, PA -4.5%

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

North American High Tech LQ Kelowna, BC and Peer Regions, 2006

State College, PA 1.54

Kelowna, BC 0.70

Sherbrooke , QC 0.68

Rocky Mount, NC 0.67

College Station, TX 0.65 Trois-Rivières, QC 0.47

Greater Sudbury, ON 0.46

Bloomington, IL 0.36

Mount Vernon, WA 0.35

Dalton, GA 0.22 Battle Creek, MI 0.22

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

North American Tech Pole Index Kelowna, BC and Peer Regions, 2006

State College, PA 0.079

Sherbrooke , QC 0.035 Kelowna, BC 0.030 Rocky Mount, NC 0.018 College Station, TX 0.018 Greater Sudbury, ON 0.014 Trois-Rivières, QC 0.012 Bloomington, IL 0.008 Mount Vernon, WA 0.004 Dalton, GA 0.002 Battle Creek, MI 0.002

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

Talent

Creative Class as % of Workforce Kelowna, BC and Peer Regions, 2006

Sherbrooke , QC 29.4%

Battle Creek, MI 27.5%

Bloomington, IL 27.1%

Trois-Rivières, QC 26.8%

Greater Sudbury, ON 26.0%

Kelowna, BC 25.7%

College Station, TX 24.9% Mount Vernon, WA 23.6%

Rocky Mount, NC 22.3% State College, PA 21.2%

Dalton, GA 18.5%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Sherbrooke , QC 16.3%

College Station, TX 16.0% Bloomington, IL 15.3%

Trois-Rivières, QC 15.2% Greater Sudbury, ON 14.3%

Kelowna, BC 12.0%

Mount Vernon, WA 10.6%

Battle Creek, MI 9.9%

Rocky Mount, NC 8.3%

Dalton, GA 7.0% State College, PA 5.6%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Above High School below BA Kelowna, BC and Peer Regions, 2006

Battle Creek, MI 65.5%

Rocky Mount, NC 63.5% Mount Vernon, WA 63.5%

Greater Sudbury, ON 60.1%

Trois-Rivières, QC 59.1%

Sherbrooke , QC 54.4%

Dalton, GA 54.1% Bloomington, IL 53.6%

College Station, TX 52.5% State College, PA 51.7%

Kelowna, BC 21.3%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

State College, PA 40.2% Bloomington, IL 39.8% College Station, TX 31.2% Mount Vernon, WA 21.0% Battle Creek, MI 19.1% Sherbrooke , QC 18.1% Rocky Mount, NC 14.9% Trois-Rivières, QC 14.0% Kelowna, BC 12.4% Greater Sudbury, ON 12.0% Dalton, GA 12.0%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Graduate and/or Professional Degree Kelowna, BC and Peer Regions, 2006

State College, PA 20.5%

College Station, TX 12.9% Bloomington, IL 12.4% Mount Vernon, WA 8.1% Battle Creek, MI 6.5% Sherbrooke , QC 6.4% Dalton, GA 4.3% Rocky Mount, NC 4.0% Trois-Rivières, QC 3.4% Kelowna, BC 3.4% Greater Sudbury, ON 3.4%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Brain Drain/Gain Index Kelowna, BC and Peer Regions, 2006

Mount Vernon, WA 1.28

Dalton, GA 1.23 Battle Creek, MI 0.98 Bloomington, IL 0.81 Rocky Mount, NC 0.70 Greater Sudbury, ON 0.62 State College, PA 0.61 College Station, TX 0.54 Trois-Rivières, QC 0.43 Sherbrooke , QC 0.35 Kelowna, BC N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007 and AUCC Enrollment numbers 2007. US Census Bureau, American Community Survey. (2006).

Tolerance

Visible Minorities (% Pop) Kelowna, BC and Peer Regions, 2006

College Station, TX 28.1%

Battle Creek, MI 15.8%

Kelowna, BC 5.1%

Sherbrooke , QC 3.7%

Greater Sudbury, ON 2.1%

Trois-Rivières, QC 1.6%

Bloomington, IL N/A Dalton, GA N/A Mount Vernon, WA N/A Rocky Mount, NC N/A State College, PA N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Dalton, GA 15.0%

Kelowna, BC College 14.6% Station, TX 10.9%

Mount Vernon, WA 10.1%

State College, PA 6.9% Greater Sudbury, ON 6.6%

Sherbrooke , QC 5.5% Bloomington, IL 4.7% Rocky Mount, NC 3.4% Battle Creek, MI 3.1% Trois-Rivières, QC 2.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Gay and Lesbian Index Kelowna, BC and Peer Regions, 2006

Trois-Rivières, QC 1.03 Sherbrooke , QC 0.89 State College, PA 0.85 Dalton, GA 0.83 Mount Vernon, WA 0.76 Rocky Mount, NC 0.75 Bloomington, IL 0.73 College Station, TX 0.72 Kelowna, BC 0.70 Greater Sudbury,… 0.64 Battle Creek, MI 0.64

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-553-XWE2006002 and 97-552-XCB2006007. US Census (2006).

Kelowna, BC 1.05 Sherbrooke , QC 0.79 College Station, TX 0.58 Greater Sudbury, ON 0.55 Trois-Rivières, QC 0.51 State College, PA 0.39 Dalton, GA 0.29 Mount Vernon, WA 0.24 Bloomington, IL 0.22 Battle Creek, MI 0.17 Rocky Mount, NC 0.16

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Integration Index Kelowna, BC and Peer Regions, 2006

Trois-Rivières, QC 0.92

Sherbrooke , QC 0.88 Greater Sudbury, ON 0.87

Kelowna, BC 0.86 Bloomington, IL 0.85

State College, PA 0.84

Mount Vernon, WA 0.77

Battle Creek, MI 0.69

Dalton, GA 0.64

College Station, TX 0.58 Rocky Mount, NC 0.52

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and 94-580-XCB2006005. US Census Bureau, American Community Survey. (2006).

Territorial Assets Peer Peer Peer Peer Kelowna, BC Ranking Minimum Average Maximum ` Social and Cultural Assets

Arts and Cultural Establishments per 10,000, 2006 6.66 1 0.22 2.31 6.66

Resturants and Bars per 1,000, 2006 2.96 2 1.46 2.16 3.02

Civic Assets Federal Voter Turnout (%), 2004/2006 63% 1 40% 629% 6333% Violent and Property Crime per Capita, 2006 0.07 11 0.02 0.05 0.07 Housing and Transportation Assets

Population Density (KM2), 2006 56 5 25.34 71.54 160.76 Median Housing Value to Income Ratio, 2005 7.14 11 2.48 3.54 7.14 Drivers per Other Modes, 2006 12.28 5 4.84 28.50 169.98

Arts and Cultural Establishments per 10,000 Kelowna, BC and Peer Regions, 2006

Kelowna, BC 6.66 Sherbrooke , QC 4.92 Trois-Rivières, QC 4.80 Greater Sudbury, ON 2.27 State College, PA 1.84 Mount Vernon, WA 1.64 Battle Creek, MI 1.38 College Station, TX 0.76 Bloomington, IL 0.68 Rocky Mount, NC 0.27 Dalton, GA 0.22

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Sherbrooke , QC 3.02

Kelowna, BC 2.96 Trois-Rivières, QC 2.82

Mount Vernon, WA 2.40 Greater Sudbury, ON 2.14 Bloomington, IL 1.97 Battle Creek, MI 1.89 College Station, TX 1.77 State College, PA 1.73 Dalton, GA 1.60 Rocky Mount, NC 1.46

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Student/Teacher Ratio Kelowna, BC and Peer Regions, 2006

Kelowna, BC N/A

Trois-Rivières, QC 13.58 State College, PA 13.83

Rocky Mount, NC 13.94 Greater Sudbury, ON 14.06

College Station, TX 14.53 Sherbrooke , QC 14.84

Dalton, GA 15.47

Bloomington, IL 15.68

Battle Creek, MI 16.19

Mount Vernon, WA 19.38

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Sherbrooke , QC 3.42 Dalton, GA 2.68 Mount Vernon, WA 2.59 State College, PA 1.14 Trois-Rivières, QC 0.81 Greater Sudbury, ON 0.32 Battle Creek, MI 0.29 Bloomington, IL 0.25 College Station, TX N/A Rocky Mount, NC N/A Kelowna, BC N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Federal Voter Turnout (%) Kelowna, BC and Peer Regions, 2004/2006

Kelowna, BC 63.3%

Sherbrooke , QC 66.0% Greater Sudbury, ON 65.4%

Trois-Rivières, QC 64.2%

Battle Creek, MI 62.6%

Bloomington, IL 61.6%

Mount Vernon, WA 61.0%

State College, PA 59.8%

Rocky Mount, NC 55.7%

College Station, TX 50.3% Dalton, GA 40.2%

Source: MPI Analysis. Elections Canada Official Voting Results of the 39th General Election – Poll-by-Poll Results. US, POLIDATA (www.polidata.us )

Violent and Property Crime per Capita Kelowna, BC and Peer Regions, 2006

State College, PA 0.022

Bloomington, IL 0.038 Trois-Rivières, QC 0.045

Dalton, GA 0.045 Sherbrooke , QC 0.048

College Station, TX 0.050

Greater Sudbury, ON 0.056 Rocky Mount, NC 0.057

Battle Creek, MI 0.058 Mount Vernon, WA 0.067 Kelowna, BC 0.073

Source: Statistics Canada CANSIM TABLE 3260021 (2006). US, ACCRA Cost of Living Index (2007).

Population Density (KM^2) Kelowna, BC and Peer Regions, 2005

Trois-Rivières, QC 161 Sherbrooke , QC 152 Dalton, GA 81 Battle Creek, MI 74 Kelowna, BC 56 Rocky Mount, NC 54 Bloomington, IL 52 State College, PA 49 Greater Sudbury, ON 47 College Station, TX 36 Mount Vernon, WA 25

Source: MPI Analysis (2008). Statistics Canada, Catalogue No. 94-581-X2006005

Trois-Rivières, QC 2.48

Battle Creek, MI 2.63

Rocky Mount, NC 2.71 Dalton, GA 2.76

Greater Sudbury, ON 2.76 Bloomington, IL

College Station, TX 3.10 Sherbrooke , QC 3.63

State College, PA 3.95 Mount Vernon, WA 4.99 Kelowna, BC 7.14

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, American Community Survey 2006

Drivers per Other Modes Kelowna, BC and Peer Regions, 2006

State College, PA 4.84

Sherbrooke , QC 7.06 Greater Sudbury, ON 7.65

Trois-Rivières, QC 10.54 Kelowna, BC 12.28

Bloomington, IL 12.78 College Station, TX 17.40

Mount Vernon, WA 18.87 Battle Creek, MI 24.81

Rocky Mount, NC 27.24 Dalton, GA 169.98

Source: Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Peer Peer Peer Provincial/State Summary Statistics Abbotsford, BC Minimum Average Maximum Average Total Population, 2006 159,000 115,700 153,000 197,000 546,000 GDP (CAD millions) 2006 $6,000 $5,000 $6,000 $9,000 $29,000 Median Age, 2006 36.8 25.7 36.1 43.8 37.5

Abbotsford, Peer Peer Peer Peer Provincial/State Overall Performance BC Ranking Minimum Average Maximum Average Population Growth (00-05) 7.9% 4 0% 6.4% 12.4% 5.7% Job Growth (00-05) 8.7% 3 -3.6% 5.9% 19.9% 9.3% GDP per capita, 2006 Change $39,000 8 $35,500 $44,000 $58,200 $45,000 in Average Wage (00-05) -1.0% 5 -11.2% -2.1% 3.7% 0.1% Creativity Index 0.39 8 0.24 0.44 0.68 N/A

Abbotsford, Peer Peer Peer Peer Provincial/State Technology BC Ranking Minimum Average Maximum Average Total Patents, 2005 12 7 2 19 42 517 Patents per 10,000, 2005 Patent 0.75 8 0.14 1.22 2.98 2.46 Growth, Short Term (00-05) North 10.8% 5 -4.5% 12.1% 56.7% -0.5% American High Tech LQ, 2006 North 0.56 6 0.22 0.58 1.54 0.63 American Tech Pole Index 0.019 4 0.002 0.021 0.079 0.189

Abbotsford, Peer Peer Peer Peer Provincial/State Talent BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 21.1% 10 18.5% 24.4% 29.4% 26.1% Super Creative Core as % of Workforce, 2006 10.6% 7 5.6% 11.5% 16.3% 11.0% Pop > 25, Above High School below BA, 2006 Talent 17.0% N/A 17.0% 50.6% 65.5% 59.0% Index (Pop > 25, BA and above), 2006 Pop 11.6% 11 11.6% 21.3% 40.2% 21.7% > 25, Graduate and/or Professional Degree, 2006 3.6% 9 3.4% 7.8% 20.5% 7.5% Brain Drain/Gain Index, 2006 0.00 10 0.00 0.63 1.28 N/A

Abbotsford, Peer Peer Peer Peer Provincial/State Tolerance BC Ranking Minimum Average Maximum Average Visible Minorities (% Pop), 2006 22.5% 2 0.0% 7.0% 28.1% 11.1% Mosaic Index (% Pop), 2006 23.3% 1 2.2% 9.1% 23.3% 7.9% Gay and Lesbian Index, 2006 0.65 10 0.64 0.78 1.03 0.81 Bohemian Index, 2006 0.61 3 0.16 0.45 1.05 0.69 Integration Index, 2006 0.60 9 0.52 0.74 0.92 N/A

Abbotsford, Peer Peer Peer Peer Territorial Assets BC Ranking Minimum Average Maximum Social and Cultural Assets Arts and Cultural Establishments per 10,000, 2006 6.79 1 0.22 2.73 6.79 Resturants and Bars per 1,000, 2006 3.02 1 1.46 2.24 3.02 Civic Assets Federal Voter Turnout (%), 2004/2006 69.7% 1 40% 1257% 6973% Violent and Property Crime per Capita, 2006 0.09 11 0.02 0.05 0.09 Housing and Transportation Assets Population Density (KM2), 2006 254 1 25.34 90.38 254.05 Median Housing Value to Income Ratio, 2005 5.95 10 2.48 3.83 7.14 Drivers per Other Modes, 2006 18.90 8 4.84 29.52 169.98

11 Regions in Peer Group: Battle Creek, MI; Bloomington, IL; College Station, TX; Dalton, GA; Kelowna, BC; Mount Vernon, WA; Rocky Mount, NC; Sherbrooke , QC; Sta Trois-Rivières, QC; Abbotsford, BC

Summary Statistics

Total Population Abbotsford, BC and Peer Regions, 2006

College Station, TX 197,000 Sherbrooke , QC 187,000 Kelowna, BC 162,000 Bloomington, IL 161,000 Abbotsford, BC 159,000 Rocky Mount, NC 146,000 Trois-Rivières, QC 142,000 State College, PA 141,000 Battle Creek, MI 138,000 Dalton, GA 134,000 Mount Vernon, WA 116,000

Source: Statistics Canada Catalogue no. 94-581-XCB2006004. US Census Bureau, American Community Survey. (2006).

GDP (CAD Millions) Abbotsford, BC and Peer Regions, 2006

Bloomington, IL $8,600 Sherbrooke , QC $7,200 Kelowna, BC $6,800 Dalton, GA $6,700 Rocky Mount, NC $6,700 College Station, TX $6,500 Abbotsford, BC #N/A $6,200 State College, PA $5,800 Mount Vernon, WA $5,500 Battle Creek, MI $5,500 Trois-Rivières, QC $5,300

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

Median Age Abbotsford, BC and Peer Regions, 2006

Trois-Rivières, QC 43.8 Kelowna, BC 43.4 Sherbrooke , QC 40.2 Rocky Mount, NC 38.2 Battle Creek, MI 37.8 Mount Vernon, WA 37.3 Abbotsford, BC 36.8 Dalton, GA 33.8 Bloomington, IL 31.0 State College, PA 29.3 College Station, TX 25.7

Source: Statistics Canada Catalogue no. 97-551-xcb2006012. U.S. Census Bureau, 2006 American Community Survey.

College Station, TX 107.38 Battle Creek, MI 104.14 Trois-Rivières, QC 103.77 Sherbrooke , QC 100.45 State College, PA 100.45 Mount Vernon, WA 100.28 Bloomington, IL 98.95 Dalton, GA 97.52 Abbotsford, BC 97.52 Kelowna, BC 97.52 Rocky Mount, NC 96.23

Overall Performance

Population Growth Abbotsford, BC and Peer Regions, (00-05)

Mount Vernon, WA 12.4%

Dalton, GA 12.0% Kelowna, BC 9.8%

Abbotsford, BC 7.9% Bloomington, IL 7.2%

College Station, TX 6.4%

Sherbrooke , QC 6.3%

State College, PA 3.8%

Trois-Rivières, QC 2.9% Rocky Mount, NC 2.3%

Battle Creek, MI 0.0%

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and Statistics Canada Catalogue no. 95-f0495-xcb-01004 US Census Bureau, American Community Survey. (2006) and US Census, 2000

Job Growth Abbotsford, BC and Peer Regions, (00-05)

Mount Vernon, WA 19.9% Kelowna, BC 12.9% Abbotsford, BC 8.7% Dalton, GA 8.7% Bloomington, IL 4.7% College Station, TX 3.6% Rocky Mount, NC 3.1% Sherbrooke , QC 2.6% State College, PA 2.4% Trois-Rivières, QC 1.6% Battle Creek, MI -3.6%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

GDP per Capita Abbotsford, BC and Peer Regions, 2006

Bloomington, IL $58,200 Dalton, GA $51,500 Mount Vernon, WA $49,700 Rocky Mount, NC $46,900 State College, PA $46,800 Kelowna, BC $41,900 Battle Creek, MI $40,800 Abbotsford, BC $39,200 Sherbrooke , QC $38,400 Trois-Rivières, QC $37,300 College Station, TX $35,500

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006004. Bureau of Economic Analysis, 2008 Survey. (2006).

State College, PA 3.7%

College Station, TX 3.4%

Sherbrooke , QC 0.6%

Kelowna, BC -0.6%

Abbotsford, BC -1.0%

Mount Vernon, WA -1.6%

Trois-Rivières, QC -1.8% Bloomington, IL -2.1%

Battle Creek, MI -5.9% Rocky Mount, NC -6.5% Dalton, GA -11.2%

Source: Statistics Canada Catalogue no. 94-581-XCB2006004 and .95-F0495-xcb-01004. US, Bureau of Labor Statistics 2000 and 2006.

Creativity Index Abbotsford, BC and Peer Regions, 2006

Sherbrooke , QC 0.68 Kelowna, BC 0.58 Bloomington, IL 0.51 Trois-Rivières, QC 0.51 College Station, TX 0.44 State College, PA 0.44 Battle Creek, MI 0.42 Abbotsford, BC 0.39 Mount Vernon, WA 0.38 Dalton, GA 0.27 Rocky Mount, NC 0.24

Source: MPI Analysis. Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Technology

Technology Abbotsford, Peer Peer Peer Peer Provincial/State BC Ranking Minimum Average Maximum Average Total Patents, 2005 12 7 2 19 42 517 Patents per 10,000, 2005 Patent 0.75 8 0.14 1.22 2.98 2.46 Growth, Short Term (00-05) North 10.8% 5 -4.5% 12.1% 56.7% -0.5% American High Tech LQ, 2006 0.56 6 0.22 0.58 1.54 0.63 North American Tech Pole Index 0.019 4 0.002 0.021 0.079 0.189

Total Patents Abbotsford, BC and Peer Regions, 2005

State College, PA 42 College Station, TX 31 Battle Creek, MI 29 Bloomington, IL 28 Sherbrooke , QC 22 Kelowna, BC 17 Abbotsford, BC 0 12.00 Mount Vernon, WA 11

Dalton, GA 9

Trois-Rivières, QC 4

Rocky Mount, NC 2

Patents per 10,000 Abbotsford, BC and Peer Regions, 2005

State College, PA 2.98 Battle Creek, MI 2.10 Bloomington, IL 1.74 College Station, TX 1.58 Sherbrooke , QC 1.18 Kelowna, BC 1.05 Mount Vernon, WA 0.95 Abbotsford, BC 0.75 Dalton, GA 0.67 Trois-Rivières, QC 0.28 Rocky Mount, NC 0.14

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

Patent Growth, Short Term Abbotsford, BC and Peer Regions, (00-05)

Trois-Rivières, QC 56.7%

Kelowna, BC 27.8% Bloomington, IL 24.6%

Sherbrooke , QC 15.1% Abbotsford, BC 0.0% 10.8%)

Mount Vernon, WA 5.9%

Rocky Mount, NC 0.0% Battle Creek, MI -0.3% College Station, TX -0.7% Dalton, GA -2.0% State College, PA -4.5%

Source: MPI and Dieter Franz Kogler Analysis. USPTO (1975-07).

North American High Tech LQ Abbotsford, BC and Peer Regions, 2006

State College, PA 1.54

Kelowna, BC 0.70

Sherbrooke , QC 0.68

Rocky Mount, NC 0.67

College Station, TX 0.65 Abbotsford, BC 0.56

Trois-Rivières, QC 0.47

Bloomington, IL 0.36

Mount Vernon, WA 0.35

Dalton, GA 0.22 Battle Creek, MI 0.22

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

North American Tech Pole Index Abbotsford, BC and Peer Regions, 2006

State College, PA 0.079

Sherbrooke , QC 0.035 Kelowna, BC 0.030 Abbotsford, BC 0.019 Rocky Mount, NC 0.018 College Station, TX 0.018 Trois-Rivières, QC 0.012 Bloomington, IL 0.008 Mount Vernon, WA 0.004 Dalton, GA 0.002 Battle Creek, MI 0.002

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006009. County Business Patterns, 2006

Talent

Abbotsford, Peer Peer Peer Peer Provincial/State Talent BC Ranking Minimum Average Maximum Average Creative Class as % of Workforce, 2006 21.1% 10 18.5% 24.4% 29.4% 26.1% Super Creative Core as % of Workforce, 2006 10.6% 7 5.6% 11.5% 16.3% 11.0% Pop > 25, Above High School below BA, 2006 17.0% N/A 17.0% 50.6% 65.5% 59.0% Talent Index (Pop > 25, BA and above), 2006 Pop > 11.6% 11 11.6% 21.3% 40.2% 21.7% 25, Graduate and/or Professional Degree, 2006 3.6% 9 3.4% 7.8% 20.5% 7.5% Brain Drain/Gain Index, 2006 0.00 10 0.00 0.63 1.28 N/A

Creative Class as % of Workforce Abbotsford, BC and Peer Regions, 2006

Sherbrooke , QC 29.4% Battle Creek, MI 27.5% Bloomington, IL 27.1% Trois-Rivières, QC 26.8% Kelowna, BC 25.7% College Station, TX 24.9% Mount Vernon, WA 23.6% Rocky Mount, NC 22.3% State College, PA 21.2% Abbotsford, BC 21.1% Dalton, GA 18.5%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Sherbrooke , QC 16.3%

College Station, TX 16.0% Bloomington, IL 15.3%

Trois-Rivières, QC 15.2% Kelowna, BC 12.0%

Mount Vernon, WA 10.6%

Abbotsford, BC 10.6%

Battle Creek, MI 9.9%

Rocky Mount, NC 8.3%

Dalton, GA 7.0% State College, PA 5.6%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Above High School below BA Abbotsford, BC and Peer Regions, 2006

Battle Creek, MI 65.5%

Rocky Mount, NC 63.5% Mount Vernon, WA 63.5%

Trois-Rivières, QC 59.1%

Sherbrooke , QC 54.4%

Dalton, GA 54.1%

Bloomington, IL 53.6% College Station, TX 52.5%

State College, PA 51.7% Kelowna, BC 21.3% Abbotsford, BC 17.0%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Pop > 25, Graduate and/or Professional Degree Abbotsford, BC and Peer Regions, 2006

State College, PA 20.5% College Station, TX 12.9% Bloomington, IL 12.4% Mount Vernon, WA 8.1% Battle Creek, MI 6.5% Sherbrooke , QC 6.4% Dalton, GA 4.3% Rocky Mount, NC 4.0% Abbotsford, BC 3.6% Trois-Rivières, QC 3.4% Kelowna, BC 3.4%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Brain Drain/Gain Index Abbotsford, BC and Peer Regions, 2006

Mount Vernon, WA 1.28

Dalton, GA 1.23 Battle Creek, MI 0.98

Bloomington, IL 0.81

Rocky Mount, NC 0.70

State College, PA 0.61

College Station, TX 0.54

Trois-Rivières, QC 0.43

Sherbrooke , QC 0.35

Kelowna, BC N/A Abbotsford, BC N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007 and AUCC Enrollment numbers 2007. US Census Bureau, American Community Survey. (2006).

Tolerance

Visible Minorities (% Pop) Abbotsford, BC and Peer Regions, 2006

College Station, TX 28.1%

Abbotsford, BC 22.5%

Battle Creek, MI 15.8%

Kelowna, BC 5.1%

Sherbrooke , QC 3.7%

Trois-Rivières, QC 1.6%

Bloomington, IL N/A Dalton, GA N/A Mount Vernon, WA N/A Rocky Mount, NC N/A State College, PA N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Abbotsford, BC 23.3% Dalton, GA 15.0% Kelowna, BC 14.6% College Station, TX 10.9% Mount Vernon, WA 10.1% State College, PA 6.9% Sherbrooke , QC 5.5% Bloomington, IL 4.7% Rocky Mount, NC 3.4% Battle Creek, MI 3.1% Trois-Rivières, QC 2.2%

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Gay and Lesbian Index Abbotsford, BC and Peer Regions, 2006

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-553-XWE2006002 and 97-552-XCB2006007. US Census (2006).

Kelowna, BC 1.05 Sherbrooke , QC 0.79 Abbotsford, BC 0.61 College Station, TX 0.58 Trois-Rivières, QC 0.51 State College, PA 0.39 Dalton, GA 0.29 Mount Vernon, WA 0.24 Bloomington, IL 0.22 Battle Creek, MI 0.17 Rocky Mount, NC 0.16

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Integration Index Abbotsford, BC and Peer Regions, 2006

Trois-Rivières, QC 0.92

Sherbrooke , QC 0.88 Kelowna, BC 0.86

Bloomington, IL 0.85 State College, PA 0.84

Mount Vernon, WA 0.77

Battle Creek, MI 0.69

Dalton, GA 0.64

Abbotsford, BC 0.60

College Station, TX 0.58 Rocky Mount, NC 0.52

Source: Statistics Canada Catalogue no. 94-581-XCB2006007 and 94-580-XCB2006005. US Census Bureau, American Community Survey. (2006).

Arts and Cultural Establishments per 10,000 Abbotsford, BC and Peer Regions, 2006

Abbotsford, BC 6.79 Kelowna, BC 6.66 Sherbrooke , QC 4.92 Trois-Rivières, QC 4.80 State College, PA 1.84 Mount Vernon, WA 1.64 Battle Creek, MI 1.38 College Station, TX 0.76 Bloomington, IL 0.68 Rocky Mount, NC 0.27 Dalton, GA 0.22

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Abbotsford, BC 3.02

Sherbrooke , QC 3.02 Kelowna, BC 2.96

Trois-Rivières, QC 2.82

Mount Vernon, WA 2.40

Bloomington, IL 1.97 Battle Creek, MI 1.89 College Station, TX 1.77 State College, PA 1.73 Dalton, GA 1.60 Rocky Mount, NC 1.46

Source: Canadian Business Patterns, June 2007 Establ. Counts by CA/CMA, Industry Groups & Emp. Size Ranges. US, County Business Patterns 2006

Student/Teacher Ratio Abbotsford, BC and Peer Regions, 2006

Kelowna, BC N/A

Abbotsford, BC N/A Trois-Rivières, QC 13.58

State College, PA 13.83 Rocky Mount, NC 13.94

College Station, TX 14.53 Sherbrooke , QC 14.84

Dalton, GA 15.47

Bloomington, IL 15.68

Battle Creek, MI 16.19

Mount Vernon, WA 19.38

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Sherbrooke , QC 3.42

Dalton, GA 2.68 Mount Vernon, WA 2.59

State College, PA 1.14

Trois-Rivières, QC 0.81 Battle Creek, MI 0.29

Bloomington, IL 0.25

College Station, TX N/A Rocky Mount, NC N/A

Kelowna, BC N/A

Abbotsford, BC N/A

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, County Business Patterns, 2006

Federal Voter Turnout (%) Abbotsford, BC and Peer Regions, 2004/2006

Abbotsford, BC 69.7%

Kelowna, BC 63.3% Sherbrooke , QC 66.0%

Trois-Rivières, QC 64.2%

Battle Creek, MI 62.6%

Bloomington, IL 61.6% Mount Vernon, WA 61.0%

State College, PA 59.8% Rocky Mount, NC 55.7%

College Station, TX 50.3% Dalton, GA 40.2%

Source: MPI Analysis. Elections Canada Official Voting Results of the 39th General Election – Poll-by-Poll Results. US, POLIDATA (www.polidata.us )

Violent and Property Crime per Capita Abbotsford, BC and Peer Regions, 2006

State College, PA 0.022

Bloomington, IL 0.038 Trois-Rivières, QC 0.045

Dalton, GA 0.045 Sherbrooke , QC 0.048

College Station, TX 0.050

Rocky Mount, NC 0.057 Battle Creek, MI 0.058

Mount Vernon, WA 0.067 Kelowna, BC 0.073 Abbotsford, BC 0.093

Source: Statistics Canada CANSIM TABLE 3260021 (2006). US, ACCRA Cost of Living Index (2007).

Population Density (KM^2) Abbotsford, BC and Peer Regions, 2005

Abbotsford, BC 254 Trois-Rivières, QC 161 Sherbrooke , QC 152 Dalton, GA 81 Battle Creek, MI 74 Kelowna, BC 56 Rocky Mount, NC 54 Bloomington, IL 52 State College, PA 49 College Station, TX 36 Mount Vernon, WA 25

Source: MPI Analysis (2008). Statistics Canada, Catalogue No. 94-581-X2006005

Trois-Rivières, QC 2.48

Battle Creek, MI 2.63 Rocky Mount, NC 2.71

Dalton, GA 2.76 Bloomington, IL 2.81

College Station, TX

Sherbrooke , QC 3.63

State College, PA 3.95

Mount Vernon, WA 4.99

Abbotsford, BC 5.95

Kelowna, BC 7.14

Source: MPI Analysis (2008) . Statistics Canada Catalogue no. 97-559-XCB2006011 and 97-F0012-XCB-01049. US, American Community Survey 2006

Drivers per Other Modes Abbotsford, BC and Peer Regions, 2006

State College, PA 4.84

Sherbrooke , QC 7.06 Trois-Rivières, QC 10.54

Kelowna, BC 12.28 Bloomington, IL 12.78

College Station, TX 17.40 Mount Vernon, WA 18.87

Abbotsford, BC 18.90 Battle Creek, MI 24.81

Rocky Mount, NC 27.24 Dalton, GA 169.98

Source: Statistics Canada Catalogue no. 94-581-XCB2006007. US Census Bureau, American Community Survey. (2006).

Appendix A: Metric Definitions for Benchmarking

Summary Statistics Population Population Counts from ACS and Statistics Canada, 2006 Median Age Median Age from ACS and Statistics Canada, 2006 Overall Cost of Living Composite measure that use CPI data from both the US and Canada. Index Overall Statistics Population Growth (2000- (Population(2006) - Population(2001))/Population(2001) 2005) (Labor Force, Total Employment(2006) -Labor Force, Total Job Growth (2000-2005) Employment(2001))/Labor Force, Total Employment(2001) GDP per Capita, 2006 GDP/Population, PPP adjusted Change in Average Wage (Average Wage(2000) -Average Wage(2001))/Average Wage(2001) (2000-2005) State and Province: Technology (North American Tech Pole, Patent Growth (00- Creativity Index 05) and Total Patents, Tolerance ( Bohemian Index, Integration Index, Gay Index and Mosaic Index), Talent (Creative Class) each account for 1/3 of index Technology Measures Total number of patents issued to primary inventors in region 2005; US Patent & Total Patents, 2005 Trademark Office (USPTO) Patents per 10,000, 2005 Total patents issued per 10,000 residents 2005; USPTO & U.S. Census Patent Growth, Short Average annual growth in number of patents issued 2000-2005; USPTO Term (00-05) A location quotient captures the difference between a specific regions concentration of a specific characteristic and the average concentration across the North American High entire country or larger regions. The high tech LQ measures the concentration of Tech LQ, 2006 high technology among employment for a region against the concentration of high technology among employment for the US and Canada combined. Combination of two factors (1) the share of a region's employment that is high-tech North American Tech Pole and (2) the high tech location quotient (below) for U.S and Canada combined. Index High Tech includes software, electronics, biomedical products, and engineering Talent Measures Percentage of the employed population in the region in the Super Creative Creative Class, 2006 occupations (see below) or occupations in the following categories: Management, Business/Finance, Law, Healthcare(does not include Healthcare support) Percentage of the employed population in the region in occupations in the Super Creative Core, 2006 following categories: Computers, Architecture/Engineering, Science, Education, Arts and Design Percentage of the population aged 25 and above in the region that has a high school Pop> 25, Above High diploma or School Below BA, 2006 equivalent and Percentage of the population aged 25 and above in the region that has a college certificate (associate's degree for U.S.) Talent Index (Pop >25, BA Percentage of the population aged 25 and above with a bachelor's degree or higher and Above) Graduate and/or Percentage of population aged 25 and above with a graduate and or professional Professional Degree degree Percentage of the workforce, age 25 and above, with at least a college certificate Brain Gain/ Brain Drain divided by the percentage of the population age 20 to 24 currently attending Index college or university

Martin Prosperity Institute -- Stolarick Appendices 1 Creative BC Benchmarking, February 2014

Tolerance (Inclusiveness) Measures Visible Minorities (% Pop) Percentage of Non-white population Mosaic Index (% Pop) Percent of population that is foreign born Location quotient that is the ratio of same sex unmarried partners to total partners Gay and Lesbian Index in the region over same sex unmarried partners to total partners for the entire U.S. (from 2000); Census Bohemian Index; Location quotient that measures whether a region has more or Bohemian Index fewer professional artistically creative people than the average region 2006; estimated from Census, ACS

Integration Index Where VGroupDA,G is the population of group G in the dissemination area And where VGroupDA,H is the population of group H in the dissemination area Where VGroupG is the total population of group G in the CMA Where VGroupH is the total population in group H in the CMA

Territorial Assets Social and Cultural Assets Arts and Cultural Total number of arts and cultural establishments per 10,000 residents. Establishments per 10,000, 2006 Restaurants and Bars per Total number of restaurants and bars per 1,000 residents. 1,000, 2006 Civic Assets Federal Voter Turnout Voter turnout, percentage of eligible voters, who voted in the last federal election. (%), 2004/2006 Violent and Property Total number of violent and property crimes per resident. Crime per Capita, 2006 Housing and Transportation Assets Population Density (KM2), Total population divided by total metropolitan region area in square kilometers. 2006 Median Housing Value to Median housing value divided by mean household income for the metro. Income Ratio, 2005 Total number of people who drive solo commutes divided by the sum of people Drivers per Other Modes, who get to work by any other method -- this includes carpooling, public transit, 2006 bicycle, walking, or other modes.

Martin Prosperity Institute -- Stolarick Appendices 2 Creative BC Benchmarking, February 2014

Appendix B: High-Tech Industries - NAICS

Computer systems design and related services Architectural, engineering and related services Other professional, scientific and technical services Wired telecommunications carriers Scientific research and development services Motion picture and video industries Pharmaceutical and medicine manufacturing Aerospace product and parts manufacturing Semiconductor and other electronic component manufacturing Communications equipment manufacturing Navigational, measuring, medical and control instruments manufacturing Wireless telecommunications carriers (except satellite) Software publishers Medical equipment and supplies manufacturing Computer and peripheral equipment manufacturing Internet service providers, web search portals Telecommunications resellers

Martin Prosperity Institute -- Stolarick Appendices 3 Creative BC Benchmarking, February 2014

Appendix C: Map of Benchmarked Regions

Martin Prosperity Institute -- Stolarick Appendices 4 Creative BC Benchmarking, February 2014

Appendix D: Research Methods The process of benchmarking the Province of Ontario and its 15 Census Metropolitan Areas (CMAs) against peer regions in both the United States and Canada was conducted as part of the Ontario in the Creative Age project commissioned by the government of Ontario. In order to better understand the competitiveness regions we conducted a quantitative analysis of North America by collecting data from national statistical agencies on over 30 different indicators that have been shown to influence regional economic prosperity. These collections of indicators developed by Florida (2002) are representative of the 3Ts of economic development (Technology, Talent and Tolerance) and are part of his larger Creative Class theory.

In selecting the North American regions for the benchmarking, the main determinate of peers for BC’s CMAs was population. Population is a highly important variable to control for because each of the following factors is size and density dependent: the division of labour, economies of scope, agglomeration and scale. In total we compared the province to 20 peer states and provinces, selecting sub-national regions with a population of 6 million or more (17 states) and the 3 largest provinces (Ontario, Quebec, and Alberta). For the CMAs which range from Toronto with a population of 5.1 million to Peterborough with just under 120,000 people, we subdivided the 15 regions into five class categories (Population >2 million, 1-2 million, 0.5-1 million, 250,000-500,000 and 100,000-250,000) for which 10 peer regions having a similar population were selected. In total 50 peer regions were selected from the 20 peer states and provinces.

The indicators used to inform this report were based on previous research conducted by Richard Florida (2002) which showed that Technology, Talent, and Tolerance are key elements for the success and continued development of a region. A region needs substantial but balanced performance across ALL of the “Three Ts” to grow and be prosperous.

In order to maintain objectivity, the analysis involved in this benchmarking process was entirely quantitative. This may lead to results that seem odd when discussed out of context or by an individual with specific regional knowledge. For example, our analysis found that Ottawa-Gatineau is incredibly competitive on certain occupation measures which are a result of the large federal government presence in the CMA. When viewing the results it is important to remember that they have not been informed by specific knowledge that is local to the regions.

Martin Prosperity Institute -- Stolarick Appendices 5 Creative BC Benchmarking, February 2014

Statistics Visible Minorities and Mosaic Index: CMA Statistics Canada. Profile of Ethnic Origin and Visible Minorities for Census Metropolitan Areas, Tracted Census Agglomerations and Census Tracts, 2006 Census. Statistics Canada Catalogue no. 94-580- XCB2006005. Using University of Toronto Data Library Service. Version updated April 2, 2008. http://www.chass.uToronto.ca/datalib/cc06/profil06.htm. Beyond 20/20.

Visible Minorities and Mosaic Index: Provinces Statistics Canada. Profile of Ethnic Origin and Visible Minorities for Canada, Provinces, Territories, Census Divisions, Census Subdivisions and Dissemination Areas, 2006 Census. Statistics Canada Catalogue no. 94-580-XCB2006002. Using University of Toronto Data Library Service. Version updated April 16, 2008. http://www.chass.uToronto.ca/datalib/cc06/profil06.htm. Beyond 20/20.

Married and Common Law: Provinces and CMA Statistics Canada. Legal Marital Status (6), Common-law Status (3), Age Groups (17) and Sex (3) for the Population 15 Years and Over of Canada, Provinces, Territories, Census Metropolitan Areas and Census Agglomerations, 2001 and 2006 Censuses - 100% Data. Statistics Canada Catalogue no. 97-552- XCB2006007. Using University of Toronto Data Library Service. Version updated September 12, 2007. http://www.chass.uToronto.ca/datalib/cc06/tbt06. Beyond 20/20.

Classes, % high school, % BA, Talent, Population, Income and Wages (2005): Provinces Statistics Canada. Profile for Canada, Provinces, Territories and Federal Electoral Districts (2003 Representation Order), 2006 Census. Statistics Canada Catalogue no. 94-581-XCB2006007. Using University of Toronto Data Library Service. Version updated July 24, 2008. http://www.chass.uToronto.ca/datalib/cc06/profil06.htm. Beyond 20/20.

Classes, % high school, % BA, Talent, Population, Income and Wages (2005), Labor Force: CMAs and CAs Statistics Canada. Profile for Census Metropolitan Areas and Census Agglomerations, 2006 Census. Statistics Canada Catalogue no. 94-581-XCB2006004. Using University of Toronto Data Library Service. Version updated July 24, 2008. http://www.chass.uToronto.ca/datalib/cc06/profil06.htm. Beyond 20/20.

Income and Wages (2000), Labor Force, Population: CMAs and CAS Statistics Canada. Profile for Census Metropolitan Areas and Census Agglomeration, 2001 Census. Statistics Canada Catalogue no. 95-F0495-xcb-01004. Using University of Toronto Data Library Service. Version updated October 7, 2003. http://www.chass.uToronto.ca/datalib/cc01/profil01.htm. Beyond 20/20.

Income and Wages (2000), Labor Force, Population: Provinces Statistics Canada. Profile for Canada, Provinces, Territories and Forward Sortation Areas, 2001 Census. Statistics Canada Catalogue no. 95-F0495-xcb-01003. Using University of Toronto Data Library Service. Version updated October 23, 2003. http://www.chass.uToronto.ca/datalib/cc01/profil01.htm. Beyond 20/20.

HTLQ: All of Canada Statistics Canada. Industry-North American Industry Classification System 2002 (433), Class of Worker (6) and Sex (3) for the Labor Force 15 Years and Over of Canada, Provinces, Territories, Census Metropolitan Areas and Census Agglomerations, 2006 Census- 20% Sample D. Statistics Canada Catalogue no. 97-559-XCB2006009. Using University of Toronto Data Library Service. Version updated February 27, 2008. http://www.chass.uToronto.ca/datalib/cc06/tbt06. Beyond 20/20.

Boho: Canada Statistics Canada. Occupation- National Occupational Classification for Statistics 2006 (720), Class of Worker (6) and Sex (3) for the Labor Force 15 Years and Over of Canada, Provinces Territories, Census Metropolitan Areas and Census Agglomerations, 2006 Census-2. Statistics Canada Catalogue no. 97-

Martin Prosperity Institute -- Stolarick Appendices 6 Creative BC Benchmarking, February 2014

559-XCB2006011. Using University of Toronto Data Library Service. Version updated February 27, 2008. http://www.chass.uToronto.ca/datalib/cc06/tbt06. Beyond 20/20.

Boho: Canada Statistics Canada. Occupations-2001 National Occupational Classification for Statistics (718), Industry – 1997 North American Industry Classification System (120), Class of Worker (5), Sex(3) and 2000 Employment Income (2) for Population 15 Years and Over with Employment. Statistics Canada Catalogue no. 97-F0012-XCB-01049. Using University of Toronto Data Library Service. Version updated November 19, 2003. http://www.chass.uToronto.ca/datalib/cc01/sit01.htm#workp. Beyond 20/20. Gay Index: Province Statistics Canada. 2007. Status of Same-sex Couples (3), Sex (3) and Presence of Other Household Members (5) for the Same sex Couples in Private Households of Canada, Provinces and Territories, 2006 Census - 20% Sample Data. Topic Based Tabulations: Families and households. Statistics Canada Catalogue no. 97-553-XCB2006024. Ottawa. September 12, 2007

Gay Index: CMAs and CAs Statistics Canada. 2007; Persons in same-sex unions by broad age groups and sex for both sexes 2006 counts for Canada and census metropolitan areas and census agglomerations - 20% sample data (table). Families and Households Highlight Tables. 2006 Census. Statistics Canada Catalogue no. 97-553- XWE2006002. Ottawa. Released September 12 2007.

Statistics Canada. Gross Domestic Product (GDP) at basic prices, by North American Industry Classification System (NAICS) and Province, annually (Dollars). Cansim table no. 3790025 Using CHASS(University of Toronto. Version updated November 8, 2007. http://dc1.chass.uToronto.ca/cgi-bin/cansimdim/c2_getArrayDim.pl (accessed August 5, 2008). Statistics Canada. Postsecondary Student Information System (PSIS). February 7, 2008. Statistics Canada Catalogue

American Statistical Sourcing Bureau of Labor Statistics. (2006). Occupational Employment and Wage Estimates, Metropolitan Area Cross-Industry estimates. Version updated June 16, 2008. http://www.bls.gov/oes/oes_2006.htm US Census Bureau, American Community Survey. (2006). Selected Social Characteristics in the United States: 2006. Source: U.S. Census Bureau, 2006 American Community Survey Source: US Census, 2000 Source: County Business Patterns, 2006

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Works Cited Becker, G. S. (1964). "Human Capital: A theoretical and empirical analysis with special reference to education". New York, National Bureau of Economic Research.

E. L. Glaeser and D. C. Mare, “Cities and skills,” Journal of Labor Economics 19, no. 2 (2001): 316-342.

Florida, R. (2002). Rise of the Creative Class. New York: Basic Books.

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Martin Prosperity Institute. (2009). Ontario Competes: Performance overview using the 3Ts of economic development. Toronto: Martin Prosperity Institute.

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