The IPL newsletter: Volume 18, Issue 369

News from the IPL


Alphabet’s Sidewalk Labs Announces Partnership with Waterfront Toronto to Create the Neighbourhood of the Future

Sidewalk Toronto
Sidewalk Labs and Waterfront Toronto announced “Sidewalk Toronto,” their joint effort to design a new kind of mixed-use, complete community on Toronto’s Eastern Waterfront. Sidewalk Toronto will combine forward-thinking urban design and new digital technology to create people-centred neighbourhoods that achieve precedent-setting levels of sustainability, affordability, mobility, and economic opportunity. Knowing that great neighbourhoods aren’t planned from the top down, Sidewalk Toronto will create the conditions for a community to be built—and innovations launched—by people, companies, startups, academic centres, and local organizations over many years. Sidewalk Toronto aims to make the Eastern Waterfront the global hub of a new industry focused on urban innovation to improve the quality of city life, tapping into Toronto’s already-thriving tech sector and developing innovations that could benefit communities and neighbourhoods elsewhere in the city. To help get started, Alphabet plans to move Google’s Canadian headquarters to the Eastern Waterfront. The district will become a place for tens of thousands of people to live, work, learn, and play—and to create and advance new ideas that improve city life, from climate-positive energy systems that can deliver a new standard in sustainability, to self-driving transit that makes streets safer, to new construction techniques that can lower housing costs. It will also reflect the cultural diversity and openness of Toronto, and help connect all Torontonians to waterfront beaches, parks, and communities.

Editor's Pick

Impact and Effectiveness of Public Support for Business Innovation

David A. Wolfe, Innovation Policy Lab, University of Toronto
As the 21st century unfolds, there is a growing recognition that the competitive global landscape is altering the context within which government support for innovation programs should be assessed. The primary justification for this area of public policy is the widespread recognition of the link between innovation and productivity growth and its impact on future income levels. Technological advance, broadly construed, is the most important source of productivity growth; but recent evidence suggests that those advances are concentrated among the leading firms in more technologically innovative sectors, while both lagging firms and sectors that experience a lower rate of productivity growth tend to reduce average productivity levels across the entire economy. The changing dynamics of innovation in the 21st century accentuates the need for a clearer understanding of what the current state of research tells us about the design, implementation and effectiveness of business innovation policies. This report explores a number of conceptual and policy design issues that are relevant for an understanding of these issues within the federal government. It provides an overview of some of the relevant conceptual frameworks used in leading industrial economies, as well as some that have experienced more rapid innovation-based (RIB) economic development. It provides an introduction to recent thinking in the academic and policy relevant literature on the nature of these design issues and summarizes some of the insights and findings of recent reviews that have been undertaken on program impacts. It is intended to be a high level review of the current state of thinking on these issues.

Innovation Policy

The State of Data Innovation in the EU

Nick Wallace and Daniel Castro, ITIF
Data innovation is happening today because the rapid growth in the ability to collect, store, analyze, and share large quantities of information at low cost drives new forms of economic activity, scientific discovery, and social innovation. For example, in health care, greater use of medical data can help doctors to diagnose problems much earlier, and manage long-term conditions better. In schools, teachers and administrators can use data to personalize educational software to meet the needs of individual pupils. And in business, an array of data-driven tools can help companies streamline their business processes and become more responsive to their customers. In the financial sector, for example, companies use sophisticated analytics and large datasets to prevent fraud as well as to improve and expand their lending services. Member states that more effectively embraced data innovation will find it easier to respond to social and economic challenges in the years ahead. This means member states that may lag behind other European countries today could lead the EU’s competitive edge in the future if they support and invest in the underpinnings of the data economy. To identify the areas where member states are doing well or need to improve, this report examines a range of indicators across three categories: data; technology; and people and firms.

Innovator’s Dilemma: IPO or No?

Shai Bernstein, Stanford University
This article identifies the advantages and disadvantages of the IPO market, and then examines the consequences that IPOs have on corporate innovation and innovation strategy. In an analysis of more than 2,000 technology firms that submitted IPO filings (and produced roughly 45,000 patents during the eight-year study period), the author finds that firms experience substantial declines in innovation quality after their IPO. A comparison of firms that went public and those that ultimately decided to withdraw their IPO registration suggests that the average quality of innovation declined by about 40 percent five years after the IPO event for the first group, while the latter group remained on their same innovation trajectory. One potential reason for the decline in innovation quality and originality is that IPOs tend to lead to an increased likelihood that innovative employees depart the firm. Inventors were roughly 18 percent more likely to leave the firm after an IPO, and were more likely to go on to start new ventures. Some potential reasons for this are that early employees may receive substantial financial windfalls after going public, which may incentivize risk-taking, or that those workers could be more inclined to work in entrepreneurial environments.

Clusters & Regions

Big Cities, Small Cities – and the Gaps

Mark Muro and Jacob Whiton, Brookings
All year, the Metro Program has been documenting the nation’s prosperity divides, ranging from the tech divide to the productivity divide to the output divide. Over and over, the stark unevenness of the nation’s city and regional economic map reads like a Rosetta stone of the nation’s frustration. But now let’s talk about another gap: the city size gap. City size matters because it’s a major influence on city prosperity and adaptability as well as local worker fortunes. Bigger cities are more productive. They are more innovative. They draw better-educated workers by offering higher wages. And yet here’s what may matter most in an era of disruptions: whether they rely on local retail activity or coal mines, or a hospital or auto parts plant, small metropolitan areas are having a hard time adapting to recent technology transitions that seem to favor large urban concentrations that vastly increase the returns to proximity. What’s driving the rise of the big and the decline of the small are the powerful, ubiquitous forces of agglomeration amplified by technology, which are powering growth and more growth in large metropolises at the expense of the drift of smaller, less educated, and techy places.

Great Lakes Economy: Examining Cross-Border Supply Chains

Jeff Desjardins, Visual Capitalist
If the region surrounding the Great Lakes was its own country, it would be the 3rd largest economy in the world with a GDP of $6 trillion. That’s bigger than Japan or Germany, and certainly a force on the global stage. However, this highly-integrated Great Lakes economic engine is different than many others – that’s because it has an international border right down the middle of it. The area’s five massive freshwater lakes are actually nestled right between eight U.S. states and two Canadian provinces, making frictionless trade a necessity to stay competitive in global markets. In today’s extremely competitive and borderless global economy, many goods that get produced are ultimately the result of a group effort. Both large and small companies rely heavily on highly specialized suppliers from all parts of the globe to get what they need to build the best product. Luckily, in the Great Lakes economy, one does not have to go far to find goods or services to fill these gaps.

Statistics & Indicators

2017 Kauffman Index of Growth Entrepreneurship
U.S. entrepreneurial growth in 2016 continued to rebound from the Great Recession slump, across different industries and geographies, for the third year in a row, according to this edition of the Index of Growth Entrepreneurship. The report also found that startups are growing more rapidly and reaching scale at higher rates than in the years following the Great Recession. However, despite the rebound in recent years, fewer companies are growing to become medium-sized or larger in terms of employment when compared to the levels in the 1980s and 90s. High-growth companies today create fewer jobs than they did in the past. Thanks to the leveraging potential of technology, revenue and value creation can take off dramatically while job growth lags behind. Startups that turned five years old in 2016 grew an estimated 75.6 percent in their first five years of operation – from almost six employees when they were founded to more than 10 employees for surviving businesses in their fifth year. This in an increase of more than 5 percentage points compared to 2015. The Share of Scaleups – the number of firms starting small and growing to scale in their first 10 years – stayed at 1.1 percent in the most recent year, but remains below the 1.6 percent seen in the late 1980s. Entrepreneurial growth is geographically diverse, spreading to places other than the stereotypical entrepreneurial hubs and largest U.S. cities. The five metropolitan areas with the highest levels of entrepreneurship were, in order: Washington, D.C.; Austin, Texas; Columbus, Ohio; Nashville, Tennessee; and Atlanta.

Making it in America

McKinsey Global Institute
This data visualization looks at long-term trends in household income growth, employment and other economic indicators at the county level. The interactive US map indicates whether counties outpaced or lagged the national growth rate in household incomes and employment.

OECD Economic Surveys: United Kingdom

After a good performance until 2016, growth slowed in the first half of 2017. The unemployment rate has fallen to below 4.5%, but real wages are in a downward trend. Planned Brexit has raised uncertainty and dented business investment. Negotiating the closest possible EU-UK economic relationship would limit the cost of exit. The authorities should allow automatic stabilizers to work and identify in advance productivity-enhancing fiscal initiatives on investment, to be implemented rapidly were growth to weaken significantly in the run-up to Brexit, while safeguarding fiscal sustainability. Comprehensive policy packages should boost the productivity of lagging regions and cities, which requires local transport investments to foster connectivity, spending on research and development to raise innovation, housing investments to ease the matching of skills to jobs, and greater educational attainment and training tailored to business needs. Enhancing teachers’ training and other incentives, in particular in disadvantaged schools, would address teacher shortages and improve skills. Low-skilled workers participate less in lifelong learning and introducing targeted re-training programs would boost competencies more broadly. Tax and regulatory reforms of non-standard forms of employment would offset workers’ weaker bargaining power and ensure better job quality.

Policy Digest

Global Startup Ecosystem Report 2017

Startup Genome
The mission of the Global Entrepreneurship Network (GEN) is to help build one entrepreneurial ecosystem. People are mobile, ideas fly around the world, and capital moves rapidly across borders. Entrepreneurs no longer need to be constrained by geographic boundaries: startups in Africa working on global problems will seek connections with startups in Europe and the United States. Venture capitalists have followed this pattern, expanding their global investment portfolio over the past two decades.Yet we have lacked ways to fully capture the globalization of start-ups and the progress of the global entrepreneurial ecosystem. And, while we have evidence-based insights about the DNA of specific innovation hubs such as London, New York, and Silicon Valley, we have not understood what works in helping smaller ecosystems accelerate their growth and increase their performance. Until now. This report is a leap forward in our understanding of startup ecosystems and the global network of capital and connections that drive them. It also provides advanced analysis of the specific drivers of startup ecosystems, based on survey responses from thousands of technology startups from around the world.


By any measure, the global technology sector has been growing rapidly, outdistancing most other economic sectors over a sustained period of time. Projections indicate that this growth will continue at its current rate and perhaps even increase. Global gross domestic product today is around $100 trillion. The technology sector (information and communications technology) is roughly 4.5 percent of that, compared to only 2 percent in 1992. If the pace continues at current growth rates, then the tech sector will be 8 percent of global GDP within the next 15 to 20 years. Global growth, meanwhile, is projected to be about 2.6 percent, which means that the tech sector is growing twice as fast as the global economy.3 Long-term growth rates, however, give short shrift to the economic dominance of the technology sector:

  • Technology is one of the few sectors worldwide where the return on equity for public companies has increased.
  • Ten years ago, technology companies accounted for 17 percent of the foreign earnings of American multinationals. Today, this number is 46 percent.
  • Technology companies now lead the rankings of largest public companies.

On any given day, depending on the stock market’s gyrations, technology companies may occupy the five top spots in the world in terms of market capitalization. These numbers arguably understate the magnitude of the trends. When even old-line industrial corporations such as Boeing, Ford, General Electric, and John Deere are turning large parts of their businesses into software as a service (SaaS) offerings, it dramatically illustrates Marc Andreessen’s “software is eating the world” idea. Many technological advances, moreover, are excluded from official economic statistics. Since the advent of smartphones, for example, sales of cameras have plummeted. Yet this is calculated as a decline in GDP because the inclusion (and improvement) of cameras in smartphones is not captured in economic data. Similar effects are true for a wide variety of technological change.

Trillions of dollars in economic value is being created by the technology sector, with much of that growth driven by startups. This is good news. Areas of the economy with greater use of information technology enjoy faster employment growth than those that have slower adoption.4 Technology creates more jobs than it displaces overall, and advances such as artificial intelligence will improve living standards in many ways. Yet the technological payoff is not uniform. For this major engine of the world economy, with trillions of dollars in wealth—and much of it created by startups—only a handful of regions around the world are capturing these benefits.

  1. Divergence between regions. For many decades, the economic fortunes of different places— across and within countries—converged pretty steadily. In recent years that steady convergence turned into accelerated divergence instead: metropolitan areas have increasingly outperformed non-metro areas. However, new research suggests a divergence among seemingly successful American cities—places like San Francisco, New York City, and Boston have outpaced other cities. This divergence helps explain sluggish global growth. The Great Recession nominally ended in mid-2009, but the subsequent expansion has been comparatively weak by historical standards. More broadly, new business creation (across all types of firms, not just tech startups) has become increasingly concentrated. From 2010 to 2014, five American metro areas had the same level of business creation as the entire rest of the country. This divergence is driven by tech companies. Comparing the performance of the five largest public tech companies in four U.S. cities that are among our top 10 startup ecosystems, with that of the five largest public non-tech companies in other American cities, there is a marked difference. The speed at which large tech companies create wealth (as measured by their market capitalization growth rate) has been nearly three times higher than for non-tech companies since 2012. As a result, cities leading the global tech startup revolution, such as Silicon Valley, Seattle, New York City, and Boston have experienced much faster growth in this key resource than Philadelphia, Houston, Denver, and Atlanta. These four cities also have growing tech startup ecosystems, but ones that are not nearly as effective at creating unicorns and large tech winners.
  2. Concentration of startup ecosystem value. The effects of this concentration among startup ecosystems are evident in the global distribution of Ecosystem Value and Exit Values. Within the tech sector, companies reliant on network effects have outpaced their competitors—these “category kings” are growing faster and larger than all other public companies, thus capturing a bigger slice of market value. Based on data compiled by Battery Ventures, these roughly three dozen companies account for around one-fifth of the entire global market value of software companies. Among top ecosystems, there is a decided skew in where these “category kings” are located. Five ecosystems (Silicon Valley, New York City, Beijing, Seattle, and Shanghai) account for 49 percent of the market value of these dominant public companies. The skew will be exacerbated in coming years as most of the leading technology companies in the IPO pipeline (such as Uber and Airbnb) are based in California. The upshot is that, while the technology sector is growing twice as fast as the world economy and transforming all types of different industries, the vast majority of that wealth creation is concentrated in only a handful of places. Without attending to creating a strong startup ecosystem, the slice of global technology and economic returns that is captured by other regions will fall.
  3. Technical inequality between workers. The global technology sector is on its way to doubling its share of world GDP within the next two decades, with trillions of dollars in economic value being added by the expansion of software innovation. Much of that increase is driven by tech startups. Yet if current concentration levels persist, 80 percent or more of the value created by the tech sector will accrue to only a few cities in only a handful of countries. Concerns about what technological growth means for individual workers are high. It’s commonly thought that 47 percent of occupations in the United States are susceptible to automation. Already, technology-fueled job creation in the United States has been mostly concentrated among high-wage workers, worsening labor market polarization. Emerging markets look to be worse off: at current projections, 60 to 80 percent of jobs in China, Thailand, Argentina, and South Africa, among others, are threatened by automation. Some countries, in fact, are experiencing “premature de-industrialization,” wherein they shed manufacturing jobs before fully developing industrial economies. The twin forces of increasing automation and de-industrialization mean serious economic difficulty for many countries.

In his landmark book, Startup Communities, Brad Feld posited that it takes about 20 years for a vibrant entrepreneurial ecosystem to develop in a city or region. This is a good estimate. In New York City, where a vibrant startup ecosystem has coalesced in the last few years, the seeds were planted at least two decades ago. Building on prior efforts, Israel and Singapore implemented innovative and aggressive policies in the 1990s to spur the growth of their startup ecosystems. In Israel, Tel Aviv has been a top-performing startup ecosystem for several years, and in our 2017 rankings, Jerusalem was a close runner-up, scoring strong in Talent and Market Reach. Singapore appeared in the top 10 ranking for the first time in 2015 (though it fell slightly to 12th in the current ranking). Over the next 15 years, global economic value from technological change will double. But, because it takes roughly 20 years for a thriving startup ecosystems to develop, aggressive investments are needed urgently, or else more places will miss out on that wealth creation. The world needs more vibrant startup ecosystems to be part of the global circulation of innovation. This can be done by working together to build a more distributed global startup ecosystem. We know this is possible because a handful of places have successfully taken steps to foster thriving startup ecosystems. Applying the knowledge and lessons from those places, adapting them to different contexts and local strengths and weaknesses, and investing scarce resources in the right way can create more startup ecosystems in more places.


Canadian Science Policy Conference

Ottawa, 1-3 November, 2017
As the nation celebrates Canada’s 150th birthday, CSPC also invites you get engaged with CSPC 2017 and celebrate the science and innovation policy accomplishments together. We invite you to submit your suggestions and event proposals.

Understanding Smarter Cities: What Happens Next?

Toronto, 2 November, 2017
This panel discussion will showcase U of T expertise and perspectives on smart cities. Questions to be raised at the event include: What are smart or smarter cities or what should they be? How can cities get there? The intended audience includes local and regional stakeholders, government and industry partners that are developing smart cities strategies, researchers and community members. Panelists will highlight previous smart cities work and research including a recent workshop led by U of T on The Future of Smart Cities in India and also connect to the Canadian federal government’s upcoming $300M Smart Cities Challenge.

RBC Conference – The FinTech Revolution: What’s Happening, What to Expect, and Why Is It Important?

Toronto, 6 November, 2017
This conference includes talks on the Canadian FinTech Landscape (Andreas Park, University of Toronto); FinTech and Changes to How We Pay for Stuff (Angelo Melino, University of Toronto); The Evolving FinTech Ecosystem in the Context of the Greater Toronto Region (David Wolfe, University of Toronto); and FinTech – Risks an Opportunities from the Bank of Canada’s Perspective (Grahame Johnson, Bank of Canada).

WICK2017: 5th PhD Workshop Economics of Innovation, Complexity and Knowledge

Turin, Italy, 19-20 December, 2017
The aim of the workshop is to bring together young researchers from different disciplines and provide them a circumstance of discussion of both full and early works. The main topics the workshop will cover are Economics of Science, Firm and Regional Innovation Strategies, HR Analytics and Economic Philosophy. The event will feature keynote contributions from Dr. Frank Neffke and Dr. Torsten Heinrich.

GeoInno2018: 4th Geography of Innovation Conference

Barcelona, Spain, January 31st, 2017 – February 2, 2018
The aim of this event is to bring together some of the world’s leading thinkers from a variety of disciplines ranging from economic geography, innovation economics, and regional science, as well as economics and management science, sociology and network theory, and political and planning sciences.

The 12th Workshop on the Organization, Economics, and Policy of Scientific Research

Bath, UK, 27-28 April, 2018
As in previous years the aim of the workshop is to bring together a small group of scholars interested in the analysis of the production and diffusion of scientific research from an economics, historical, organizational, and policy perspective. We aim to attract contributions from both junior and senior scholars; a minimum number of slots are reserved for junior researchers (PhD students or postdoc scholars who obtained their PhD in 2015 or later).

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This newsletter is prepared by Jen Nelles.
Project manager is David A. Wolfe.