Editor's Note: This article was the first published in the June 2008 World Cities Summit edition of ETHOS.

At the dawn of a new century, broad demographic, economic and environmental forces are giving American cities their best chance in decades to thrive and prosper. The renewed relevance of cities derives in part from the very physical characteristics that distinguish cities from other forms of human settlement: density, diversity of uses and functions, and distinctive design.

Across the United States (U.S.), a broad cross section of urban practitioners—private investors and developers, government officials, community and civic leaders—are taking ambitious steps to leverage the distinctive physical assets of cities and maximise their economic, fiscal, environmental and social potential.

A special class of urban interventions—what we call “transformative investments”—is emerging from the millions of transactions that occur in cities every year. The hallmark of transformative investments is their catalytic nature and seismic impact on markets, on people, on the city landscape and urban possibilities—far beyond the geographic confines of the project itself.

Recognising and replicating the magic of transformative investments, and making the exception become the norm is important if U.S. cities are to realise their full potential.

THE URBAN MOMENT
The U.S. is undergoing a period of dynamic change, comparable in scale and complexity to the latter part of the nineteenth century. Against this backdrop, there is a resurgence in the importance of cities due to their fundamental and distinctive physical attributes.

Cities offer a broad range of physical choices—in neighbourhoods, housing stock, shopping venues, green spaces and transportation. These choices suit the disparate preferences of a growing population that is diverse by race, ethnicity and age.

Cities are also rich with physical amenities—mixed-use downtowns, historic buildings, campuses of higher learning, entertainment districts, pedestrian-friendly neighbourhoods, adjoining rivers and lakes—that are uniquely aligned with preferences in a knowledge-oriented, post-industrial economy. A knowledge economy places the highest premium on attracting and retaining educated workers, and an increasing proportion of these workers, particularly young workers, value urban quality of life when making their residential and employment decisions.

Finally, cities, particularly those built in the nineteenth and early twentieth centuries, are compactly constructed and laid out along dense lines and grids, enhancing the potential for the dynamic, random, face-to-face human exchange prized by an economy fuelled by ideas and innovation. Such density also makes cities perfect agents for the efficient delivery of public services as well as the stewardship of the natural environment.

Each of these elements—diversity, amenities and density—distinguishes cities from other forms of human settlement. In prior generations, these attributes were devalued in a nation characterised by the single family house, the factory plant, cheap gas, and environmental profligacy. In recent history, many U.S. cities responded by making the wrong physical bets or by replicating low-density, suburban development—further eroding the very strengths that make cities distinctly urban and competitive.

Yet, the U.S., a nation in demographic and economic transition, is revaluing the quality of life uniquely offered by cities and urban places, potentially altering the calculus by which millions of American families and businesses make location decisions every year.

DELIVERING "CITYNESS": THE RISE OF TRANSFORMATIVE INVESTMENTS
Across the U.S., a practice of city building is emerging that builds on the re-found value and purpose of the urban physical landscape, and recognises that cities thrive when they fully embrace what Saskia Sassen calls “cityness”.¹

The move to recapture the American city can be found in all kinds of American cities: global cities like New York, Los Angeles and Chicago that lie at the heart of international trade and finance; innovative cities like Seattle, Austin and San Francisco that are leading the global economic revolution in technology; older industrial cities like Cleveland, Pittsburgh and Rochester that are transitioning to new economies; fast-growing cities like Charlotte, Phoenix and Dallas that are regional hubs and magnets for domestic and international migration.

The new urban practice can also be found in all aspects or “building blocks” of cities: in the remaking of downtowns as living, mixed-use communities; in the creation of neighbourhoods of choice that are attractive to households with a range of incomes; in the conversion of transportation corridors into destinations in their own right; in the reclaiming of parks and green spaces as valued places; and in the revitalisation of waterfronts as regional destinations, new residential quarters and recreational hubs.

Yet, as the new city building practice evolves, it is clear that a subset of urban investments are emerging as truly “transformative” in that they have a catalytic, place-defining impact, creating an entirely new logic for portions of the city and a new set of possibilities for economic and social activity.

We define these transformative investments as “discrete public or private development projects that trigger a profound, ripple effect of positive, multi-dimensional change in ways that fundamentally remake the value and/or function of one or more of a city’s physical building blocks”.

This subset of urban investments share important characteristics:

• On the economic front, transformative investments uncover the hidden value in a part of the city, creating markets in places where markets either did not exist or were only partially realised.
• On the fiscal front, transformative investments dramatically enhance the fiscal capacity of local governments, generating revenues through the rise in property values, the growth in city populations, and the expansion of economic activity.
• On the cognitive front, transformative investments redefine the identity and image of the city. They effectively “re-map” previously forgotten or ignored places by residents, visitors and workers. They create nodes of new activities and new places for people to congregate.
• On the environmental front, transformative investments enable cities to achieve their “green” potential by cleaning up the environmental residue from prior industrial uses or urban renewal efforts, by enabling repopulation at greater densities to occur and by providing residents, workers and visitors with transportation alternatives.
• On the social front, transformative investments have the potential, while not always realised, to alter the opportunity structure for low-income residents. When carefully designed, staged and leveraged, they can expand the housing, employment and educational opportunities available to low-income residents and overcome the racial, ethnic and economic disparities that have inhibited city performance for decades.

DISSECTING SUCCESS: HOW AND WHERE TRANSFORMATIVE INVESTMENTS TAKE PLACE
The best way to identify and assess transformative investments is by examining exemplary interventions in the discrete physical building blocks of cities: downtowns, neighbourhoods, corridors, parks and green spaces, and waterfronts.

Downtowns
If cities are going to realise their true potential, downtowns are compelling places to start. Physically, downtowns are equipped to take on an emerging set of uses, activities and functions and have the capacity to absorb real increases in population. Yet, as a consequence to America’s sprawling appetite, urban downtowns have lost their appeal. Economic interests, once the stronghold in downtowns, have moved to suburban town centres and office parks, depressing urban markets and urban value.

Across the US, downtowns are remaking themselves as residential, cultural, business and retail centres. Cities such as Chattanooga, Washington, DC and Denver have demonstrated how even one smart investment can inject new energy and jumpstart new markets. The strategic location of a new sports arena in a distressed area of downtown Washington, DC fits our definition of a transformative investment. Leveraging the proximity of a transit stop, the MCI Arena was nestled within the existing urban fabric on a city-owned urban renewal site. The arena’s pedestrian-oriented design strengthened, rather than interrupted, the continuity of the 7th Street retail corridor.² Today, the area has been profoundly transformed as scores of new restaurants, retail and bars dot the arena’s surroundings. Residents and visitors rely heavily on the nearby transit to come to this destination.

Neighbourhoods
Ever since the physical, economic and social agglomeration of “city” was established, the function of neighbourhoods has remained relatively untouched. While real estate values of neighbourhoods have shifted over time in response to micro- and macro-economic trends, a subset of inner city communities have remained enclaves of poverty. Victims of earlier urban renewal and public housing efforts, millions of people are consigned to living in neighbourhoods isolated from the economic and social mainstream.

Cities such as St. Louis, Louisville and Atlanta have been at the forefront of public housing (and hence neighbourhood) transformation, supported by smart federal investments in the 1990s. For example, the demolition of the infamous high-rise Vaughn public housing project in St. Louis enabled the construction of a new human scale, mixed-income housing development in one of the poorest, most crime-ridden sections of the city. This redevelopment cured the mistakes made by failed public housing projects, by restoring street grids, providing quality design, and injecting a sense of social and physical connection. Constructing a mix of townhouses, garden apartments and single family homes helped catalyse other public and private sector investments.

What made this investment transformative was that it included the reconstitution of Jefferson Elementary, a nearby public school. Working closely with residents, and with the financial support of corporate and philanthropic interests, the developer helped modernise the school, making it one of the most technologically advanced educational facilities in the region. A new principal, new curriculum, and new school programmes helped it become one of the highest performing inner city schools in the state of Missouri.

Corridors
City corridors are the physical tissue that knit disparate parts of a city together. In the best of conditions, corridors are multi-dimensional in purpose, where they are destinations as much as facilitators of movement. In many cities, however, corridors are simply shuttling traffic past blocks of desolated retail and residential areas or they have become yet another cookie cutter image of suburbia—parking lots abutting the main street, standardised buildings and design, and oversized and cluttered signage.

Cities like Portland, Oregon and urban counties like Arlington, Virginia have used mass transit investments and land use reforms to create physically, economically and socially healthy corridors that give new residents reasons to choose to live nearby and existing residents reasons to stay.

Portland conceived a streetcar to spur high density housing in close-in neighbourhoods that were slowly shedding old industrial uses. The streetcars traverse a three-mile route through residential areas, the water front, to the university. Since its construction, the streetcar has not only expanded transportation choices, it has helped galvanise new destinations along its route—including new neighbourhoods, retail clusters, and economic districts.

Parks and Open Space
City green spaces (such as parks, nature trails, bike paths) were initially designed to provide the lungs of the city and an outlet for recreation, entertainment and social cohesion. As general conditions declined in many cities, the quality of urban parks also declined, to the great consternation of local residents. Green spaces were turned into under-used, if not forgotten, areas of the city; or worse still, hot spots of crime and illegal activity. Such blight discouraged cities to transform outmoded uses (such as manufacturing areas) into more green space. In cities with booming development markets, parks failed to be designed and incorporated into the new urban fabric.

Across the US, cities are pursuing a variety of strategies to reclaim or augment urban green spaces. Cities like Atlanta, for example, have created transformative parks from outmoded economic uses, such as manufacturing land along urban waterfronts or by converting old railway lines into urban trail-ways.

Cities like Scranton have reclaimed existing urban parks consumed by crime and vandalism. This has required creative physical and programmatic investments, including: redesigning parks (removing physical and visibility barriers such as walls, thinning vegetation, and eliminating “dark corners”); increasing the presence of uniformed personnel; increasing the park amenities (such as evening movies and other events to increase patronage);³ and providing regular maintenance of the park and recreational facilities.⁴

Waterfronts
Many American cities owe their location and initial function to the proximity to water: rivers, lakes and oceans. Waterfronts enabled cities to manufacture, warehouse and ship goods and products. Infrastructure was built and zoning was aligned to carry out these purposes. In a knowledge-intensive economy, however, the function of waterfronts has dramatically changed, reflecting the pent-up demand for new places of enjoyment, activities and uses.

As with the other building blocks, cities are pursing a range of strategies to reclaim their waterfronts, often by addressing head-on the vestiges of an earlier era.

New York has overhauled the outdated zoning guidelines for development along the Brooklyn side of the East River, enabling the construction of mixed-income housing rather than prescribing manufacturing and light industry uses.

Pittsburgh and many of its surrounding municipalities have embarked on major efforts to re-mediate the environmental contamination found in former industrial sites, paving the way for new research centres, office parks and retail facilities.

Milwaukee, Providence and Portland have demolished the freeways that separated (or hid) the waterfront from the rest of the downtown and city, and unleashed a new wave of private investment and public activities.

WHAT IS THE RECIPE FOR SUCCESS?
The following are underlying principles that set these diverse investments apart from other transactions:

Transformative Investments advance “cityness”: Investments embrace the characteristics, attributes, and dynamics that embody “city”—its complexity, its intersection of activities, its diversity of populations and cultures, its distinctively varied designs, and its convergence of the physical environment at multiple scales. Project by project, transformative investments are reclaiming the true urban identity by strengthening aspects of the ‘physical’ that are intrinsically urban—be it density, rehabilitation of a unique building or historic row, or the incorporation of compelling, if not iconic, design.

Transformative Investments require a fundamental rethinking of land use and zoning conventions: In the midst of massive economic global change, 21st century American cities still bear the indelible markings of the 20th century. In the early 20th century, for example, government bodies enacted zoning to establish new rules for urban development. While originally intended to protect “light and air” from immense overbuilding, later versions of zoning added the segregation of uses—isolating housing, office, commercial and manufacturing activities from each other. Thus, transformative investments require, at a minimum, variances from the rigid, antiquated rules that still define the urban landscape. In many cases, examples of successful transformative investments have become the tool to overhaul outdated and outmoded frameworks and transform exceptions into new guidelines.

Transformative Investments require innovative, often customised financing approaches: Cities have distinctive physical forms (e.g., historic buildings) and distinctive physical visions (e.g., distinct districts). Yet private and even public financing of the American physical landscape, for the most part, is standardised and routinised, enabling the production of similar products (e.g., single family homes, commercial strips) at high volume, low cost and low quality. Transformative investments, however, require the marrying of multiple sources of financing (e.g., conventional debt, traditional equity, tax-driven equity investments, innovative financing arrangements, public subsidy, patient philanthropic capital), placing stress on project design and implementation. In addition, achieving social objectives often require building innovative tax and shared equity approaches into particular transactions, so that appreciations in property value can serve higher community purposes (e.g., creating affordable housing trust funds). As with regulatory frames, the evolution from exceptional transactions to routinised forms of investments is required to ensure that transformative investments become more the rule rather than the exception.

Transformative Investments often involve an empirically-grounded vision at the building block level: While a vision is not a necessary pre-requisite for realising transformative investments, cities that proceed without one have a higher probability of making the wrong physical bets, siting them in the wrong places, or ultimately creating a physical landscape that fails to cumulatively add up to “ cityness”. It is easy to find such examples around the country, such as isolated mega-projects (a new stadium or convention centre) or waterfront revitalisation efforts that constructed the wrong projects, having misunderstood the market and the diversifying demographic.

Telescoping the possibilities and developing a bold vision must be done through an empirically-grounded process. A visioning exercise should therefore include: an economic and market diagnostic of the building block; a physical diagnostic; an evaluation of existing projects; and the development of a vision to transform the landscape. From here, disparate actors (public, private, civic, not-for-profit) will have the best instruments to assess whether a physical project could meet specific market, demographic and physical needs—increasing its chances of becoming truly transformative.

Transformative Investments require integrative thinking and action: Transformative investments are often an act in “connecting the dots” between the urban experiences (e.g., transportation, housing, economic activity, education and recreation), which are inextricably linked in reality but separated in action. This requires a significant change in how cities are both planned and managed.

On the public side, it means that transportation agencies must re-channel scarce infrastructure investments to leverage other city building goals beyond facilitating traffic. It means that agencies driving a social agenda, such as schools and libraries, have to re-imagine their existing and new facilities to integrate strong design and move away from isolated projects.

In the private sector, it means understanding the broader vision of the city and carefully siting and designing investments to increase successful city-building and not just project-building. It means increasing their own standards by using exemplary design and construction materials. It means finding financially beneficial approaches to mixed income housing projects and mixed use projects instead of just single uses. In all cases, it requires holistic thinking that cuts across the silos and stovepipes of specialised professions and fragmented bureaucracies.

BUILDING GREAT CITIES
For the first time in decades, American cities have a chance to experience a measurable revival. While broader macro forces have handed cities this chance, city builders are also learning from past mistakes. After investing billions of dollars into city revitalisation efforts, the principles underpinning particularly successful and catalytic projects—transformative investments—are beginning to be clarified. The most important lesson for cities, however, is to embrace “cityness”, to maximise what makes them physically and socially unique and distinctive. Only in this way will American cities reach their true greatness.

---

• ¹Saskia Sassen defined the term “cityness” to be the concept of embracing the characteristics, attributes, and dynamics that embody “city”: complexity, the convergence of the physical environment at multiple scales, the intersection of differences, the diversity of populations and culture, the distinctively varied designs and the layering of the old and the new. Sassen, S., “Cityness in the Urban Age”, Urban Age Bulletin 2 (Autumn 2005).
• ²Strauss, Valerie, “Pollin Says He’ll Pay for Sports Complex District, Awaits Economic Boost, Upgraded Image”, Washington Post, Thursday, 29 December 1994.
• ³Personal communication from Peter Harnik, Director, Center for City Park Excellence, Trust for Public Land, 6 June 2005.
• ⁴Harnik, Peter, “The Excellent City Park System: What Makes it Great and How to Get There”. San Francisco, CA: The Trust for Public Land, 2003. Available online at http://www.tpl.org/tier3_cd.cfm?content_item_id=11428&folder_id=175

      

Event Information

On February 2 and 3, 2010, the Brookings Institution Metropolitan Policy Program and Lazard convened leaders from the public sector, energy, infrastructure, finance and venture capital communities for an in-depth conversation focused on innovative policy and business practices that will help build the next American economy.

California Governor Arnold Schwarzenegger and Pennsylvania Governor Edward G. Rendell provided the keynote remarks. Both stressed the need for strategic investments in innovative infrastructure and energy practices going forward.

Framing the conference was the notion that the next American economy must be export-oriented, low carbon, innovation-fueled and opportunity rich—an idea which has been proposed by leading economists such as Director of the National Economic Council Larry Summers. It is with this mindset that Brookings and Lazard put together high-level, dynamic panels that centered around the private sector needs for building out the next American economy—and the policy implications. Specifically, they focused on how the traditional industry leaders (e.g., utility companies), the new industry leaders (e.g., venture capital investors), and public sector leaders can work together to move our country forward, especially within the metro areas where the resources and networks that drive innovation are rooted.

For media coverage of the event, please visit the following:

Time Is Running Out: The New York Times – Bob Herbert

Watching China Run: The New York Times – Bob Herbert

High Hopes for Clean-Energy Jobs: The Wall Street Journal - Rebecca Smith

Campaign for 'Next American Economy' Begins: San Francisco Chronicle - Andrew Ross

Bruce Katz, Vice President and Director, Metropolitan Policy Program, Brookings Institution		Vernon Jordan, Senior Managing Director, Lazard and California Governor Arnold Schwarzenegger
Wall Street Journal reporter Rebecca Smith leads a conversation with business leaders		Pennsylvania Governor Edward Rendell
Conference participants Jim Robinson of RRE Ventures and Michael Ahearn of First Solar		From left: Bob Herbert (New York Times), Mallory Walker (Walker and Dunlop) and George Bilicic (Lazard)

Video

• The Keys to American Competitiveness

Audio

• The Next American Economy: Transforming Energy and Infrastructure Investment

Transcript

• Transcript (.pdf)
• Bruce Katz's delivered remarks (.pdf)

Event Materials

• 0203_transcript
• 0203_nextecon_katz
• 0203_overview
• 0203_agenda
• 0203_nextecon_pres

      

If you live in a city or suburb, chances are your regional government has tried to get your attention. Did you notice? Many of the issues your regional government is grappling with are actually important to you: the quality of the air you breathe, the quality of public transportation, the availability of green open space, and more.

As important as these issues are, I can almost guarantee that planners from your region have had to work extra hard to convince the press -- not to mention the citizens that live and work there -- to pay attention. The problem is, regional planning is about as exciting to the public as televised bowling and the press don’t seem to find the topic as newsworthy as it should be.

And then there is Paris. In one year, approximately a hundred articles and editorials on Grand Paris, a new regional effort, were printed in the city’s main paper, Le Monde. Grand Paris has also been covered by UK newspapers, such as the Telegraph and The Guardian, and by US newspapers, such as The New York Times and The Christian Science Monitor. In my interviews with Parisian architects, economists, and sociologists, they tell me that it’s not only the press that is paying attention. Ordinary citizens on the streets and cafes are talking about Grand Paris and Paris as a region.

So what happened?

Turns out, President Sarkozy created a political and media frenzy this past year when he announced his intention to design a new Paris that incorporates the suburbs. Looking at his effort from a socio-economic perspective, Sarkozy should be lauded for his effort to reconnect the isolated suburbs to the economic heart of Paris. The 2005 riots by African immigrants in some of these suburbs gave the world a real peek into some of the inequities found here.

His push has been to look past local political boundaries and acknowledge the new Paris that is emerging -- one that is both larger in geography and socio-economically more diverse. In 2007, the metropolitan area produced more than a quarter of France’s GDP, with a Gross Metropolitan Product of $731.3 billion.

Yet, his national government cites that Paris is underdeveloped in important sectors, and that the region’s economic growth has been slowing over the past two decades. Sarkozy also saw this as an opportunity to redefine the region in a post-Kyoto era, where sustainable development is no longer an afterthought.

Sarkozy retained 10 architectural teams with heavy hitters, such as Richard Rodgers, and asked them to “think big” on how to physically redefine the Paris region. In response, they offered lofty ideas for new economic centers, new high density housing hubs, and even a Paris covered with green roofs. For a moment, one could even argue that these teams breathed a new life of possibility for Paris. 

But politics is local—even when the French President is involved. 

As it turns out, Paris already has a plan for their region; one that was formally approved by the local jurisdictions and leaders and is now simply waiting for sign off by Sarkozy’s government. This plan addresses many of the issues Sarkozy argues that the region lacks, such as the need to address the 20 years of underinvestment in public infrastructure.

It also turns out that Grand Paris flies directly in the face of the regional coalition building effort under way. An important number of leaders that comprise the region’s 1,231 jurisdictions are already forging a common agenda on cross cutting issues such as transportation and economic development. These are just two of the several missteps that have made the idea turn sour.

So what seems to have started as a visionary act to physically remake the region has turned into a story on jurisdictional entanglements and hurt egos -- and the press ate it up. Interestingly, this controversy and all the press it generated has actually been an important win for regionalism in the end.

      

When President Obama unveiled his budget allocation for high-speed rail, he said, “In France, high-speed rail has pulled regions from isolation, ignited growth [and], remade quiet towns into thriving tourist destinations.” His remarks emphasize how high-speed rail is increasing the accessibility of isolated places as an argument for similarly investments. So, what’s the source of this argument in the European context?

In November 2009, the European Union’s ESPON (the European Observation Network for Territorial Development and Cohesion) released a report called “Trends in Accessibility.” ESPON examined the extent to which accessibility has changed between 2001 and 2006. ESPON defines accessibility as how “easily people in one region can reach people in another region.” This measurement of accessibility helps determine the “potential for activities and enterprises in the region to reach markets and activities in other regions.”

ESPON’s research concluded that in this five-year period, rail accessibility grew an average of 13.1 percent. The report further concludes that high-speed rail lines have “influenced positively the potential accessibility of many European regions and cities.”

In particular, the research found that the core of Europe--Germany, France, Belgium, the Netherlands, and Switzerland--has the highest potential accessibility. Europe’s core produces the highest levels of economic output and has the highest population densities. ESPON argues that with such densities, the core has found reason to link their economic hubs (cities) with high-speed rail. These are the places in Europe where they have the greatest returns on investment.

But ESPON also found that high speed rail is starting to increase the accessibility of isolated places such as France’s Tours, Lyon, and Marseille. This is a very important finding for Europe. They have a long-standing policy of social cohesion and balance, striving to create economic sustainability and population stability across Europe. The objective is for areas well beyond core to thrive economically and to dissuade people from migrating in search of jobs. Fiscally, social cohesion translates into investing disproportionately more money into areas not producing sufficient levels of economic output. High-speed rail is but one of the many strategies intending to produce “economic and social cohesion,” states a European Commission report on high-speed rail.

But we are not Europe. While their thesis underpinning high-speed rail is social cohesion, what is our underlying thesis for high-speed rail? And what does this look like spatially? What was the logic behind the selection of Florida over other possible corridors? Is this line going to strengthen our national economy and GDP? Clarity on this score will help ensure the project is a success and offers a high return on investment. Lessons from this accessibility study say that places with high population levels and GDP output offer the greatest accessibility and therefore success.

It would be a pity if the U.S. finally jumped on the high-speed bandwagon but still missed the train.

      

Even the most well-intentioned public policy can have unintended consequences. President Obama’s promise of doubling exports offers one thread of a broader strategy for getting our economy back on track.

Increasing our output of goods to ship and sell abroad implies that if all goes well, a growing number of goods will be transported to one of our 400 ports. Yet, as Rob Puentes has determined, our top 15 ports already move over 73 percent of the value of international freight. Increasing our exported goods means one of two possibilities: additional goods will be funneled to just a handful of ports or other ports will need to move international cargo.

And here is where the pain starts. Increasing port activities has real and often severe consequences for the cities, towns, and neighborhoods located nearby. The most immediate ramification is the increased volume in truck traffic on local roads and arterials. Back in 2005, the U.S. Department of Transportation surveyed 23 ports and found that 58 percent found local access to be below average conditions or, in other words, choked with congestion.

With more trucks carrying additional loads, some ports will likely find they have little choice but to push for port expansion to handle the supply. The process of local authorities approving port expansions is wrenching and emotional for the entire community--a controversy perhaps only superseded by the siting of jails.

If these costs seem reasonable to get our country back on track, try to argue this point to neighborhoods already burdened with these impacts. Accomplishing this national goal at the local level will not be so easy.

Yet, an easy answer for the feds is that they don’t have authority over local land use. This is also the case in Germany, where local land use decisions are determined by state and local governments. Yet on the issue of ports, Germany’s federal government has taken a keen interest in how local municipalities are supporting port activity. Their interest grew out of a desire to increase the volume of exports. In German cities and regions that contain “ports of national importance”, local municipalities will now be encouraged by the feds to change the hierarchy of land uses and activities within their zoning processes.

Specifically, local governments will be asked to consider how new uses, such as housing, will not hurt the competitiveness of the port. So instead of port noise needing to be mitigated by the port, homebuilders, and ultimately homeowners, could be responsible for mitigating the noise. One noise mitigation strategy is that homebuilders install heavy, noise-proof glass.

If the Germans should be lauded for at least trying to reconcile national economic objectives with local priorities, I wonder if more can be done than create neighborhoods of glass.

      

In partnership with the ESADE Business School and the City of Barcelona, the Metropolitan Policy Program planned and participated in three intensive days of learning in Barcelona in June 2011.  The focus of the session was to look at examples of strategies Barcelona, Spain and its greater metropolitan region is embracing to rebuild and re-invent their economies.  The goal is to share innovative ideas with U.S. metros engaged in similar initiatives as they face the challenge of moving to a new economic growth model.

This paper features brief synopses of the tours and meetings held with the City of Barcelona and the Catalonia Region on their economic development strategies.

Specific strategies include:

Barcelona Activa »

Barcelona Economic Triangle » (PDF)

22@Barcelona » (PDF)

Parc de l’Alba »

Click on any image below for a larger version

Barcelona Activa
The 22@Barcelona revitalization area	The Parc de l'Alba revitalization area

Downloads

• Download the Full Paper

      

Once upon a time, innovation was an isolationist sport. In America’s innovative economy 20 years ago, a worker drove to a nondescript office campus along a suburban corridor, worked in isolation, and kept ideas secret.

Today, by contrast and partly a result of the Great Recession, proximity is everything. Talented people want to work and live in urban places that are walkable, bike-able, connected by transit, and hyper-caffeinated. Major companies across multiple sectors are practicing “open innovation” and want to be close to other firms, research labs, and universities. Entrepreneurs want to start their companies in collaborative spaces, where they can share ideas and have efficient access to everything from legal advice to sophisticated lab equipment.

These disruptive forces are coming to ground in small, primarily urban enclaves—what we and others are calling “innovation districts.” By our definition, innovation districts cluster and connect leading-edge institutions with startups and spin-off companies, business incubators, and accelerators in the relentless pursuit of cutting-edge discoveries for the market. Compact, transit-accessible, and highly networked, they grow talent, foster open collaboration, and offer mixed-used housing, office, retail, and 21st century urban amenities. In many respects, the rise of innovation districts embodies the very essence of cities: an aggregation of talented, driven people assembled in close quarters, who exchange ideas and knowledge. It’s in the vein of what urban historian Sir Peter Hall calls “a dynamic process of innovation, imitation and improvement.”

Globally, Montreal, Seoul, Singapore, Medellin, Barcelona, Cambridge, and Berlin offer just a few examples of evolving innovation districts. In the US, the most iconic innovation districts can be found in the downtowns and midtowns of cities like Atlanta, Cambridge, Philadelphia, Pittsburgh, San Diego, and St. Louis, where advanced research universities, medical complexes, research institutions, and clusters of tech and creative firms are sparking business expansion, as well as residential and commercial growth. Even a cursory visit to Kendall Square in Cambridge, University City in Philadelphia, or midtown Atlanta shows the explosion of growth and mixed development occurring around institutions like MIT, the University of Pennsylvania, and Georgia Tech.

Other innovation districts can be found in Boston, Brooklyn, San Francisco, and Seattle, where former industrial and warehouse areas are charting a new innovative path, powered by their enviable location along transit lines, their proximity to downtowns and waterfronts, and their recent addition of advanced research institutions (reflected by Carnegie Mellon University’s decision to place its Integrative Media Program at the Brooklyn Navy Yard).

Perhaps the greatest validation of this shift is found in the efforts of traditional exurban science parks (like Research Triangle Park in Raleigh-Durham) to urbanize, in order to keep pace with the preferences of their workers for walkable communities and the preference of their firms to be near other firms and collaborative opportunities.

Innovation districts are already attracting an eclectic mix of firms in a diverse group of sectors, including life sciences, clean energy, design, and tech. We even see a return of small-scale and customized manufacturing, made possible by 3D printing, robotics, and other advanced techniques.

Unlike efforts to grow the “consumer city” via sports stadia, luxury housing, and high-end retail, innovation districts are intent on growing the firms, networks, and sectors that drive real, broad-based prosperity.

At a time of increasing concerns over inequality and resilience, innovation districts can spur productive, inclusive, and sustainable growth. If properly structured and scaled, they can provide a strong foundation for the commercialization of ideas, the expansion of firms, and the creation of jobs. They also offer the tantalizing prospect of expanding employment and educational opportunities for disadvantaged populations—many innovation districts are close to low- and moderate-income neighborhoods—as well as sparking more sustainable development patterns, given their embrace of transit, historic buildings, traditional street grids, and existing infrastructure.

Innovation districts represent one of the most positive trends that have emerged in the aftermath of the Great Recession. Smart cities, innovative companies, advanced universities, and financial institutions would be wise to embrace them.

This piece originally appeared on Quartz.

      

For years, corporate campuses like Silicon Valley were known for innovation. Located in suburban corridors that were only accessible by car, these places put little emphasis on creating communities where people work, live and go out.

But now, as the economy emerges from the recession, a shift is occurring where innovation is taking place. Districts of innovation can be found in urban centres as disparate as Montreal, Seoul, Singapore, Medellin, Barcelona, and London. They are popping up in the downtowns and midtowns of cities like Atlanta, Cambridge, Philadelphia, and St. Louis.

These are places where advanced research universities, medical complexes, and clusters of tech and creative firms are attracting businesses and residents.

Other innovation districts can be found in Boston, Brooklyn, San Francisco, and Seattle, where older industrial areas are being re-imagined and remade, leveraging their enviable location near waterfronts and city centres and along transit lines. Innovative companies and talented workers are flocking to these areas in abundance.

Even traditional science parks like Research Triangle Park in Raleigh-Durham are scrambling to urbanise to keep pace with their workers' preference for walkable communities and their companies' desire to be near other firms.

In these districts, leading anchor institutions and start-ups are clustering and connecting with one another. They are coming together with spin-off companies, incubators, and accelerators in the relentless pursuit of new discoveries for the market.

These areas are small and accessible, growing talent, fostering open collaboration, and offering housing and office space as well as modern urban amenities. They are both competitive places and "cool" spaces.

The growth of innovation districts is being driven by private and civic actors like universities, philanthropies, business associations and business improvement districts. Yet local governments play an important role in accelerating the growth of districts and maximising their potential . Three roles stand out:

1) Mayors are leading efforts to designate districts

Barcelona's former mayor Joan Clos set his eyes on transforming his city into a "city of knowledge". Through extensive, focused public planning and investment, Clos designed an innovation district from the debris of a 494-acre industrial area, which was scarred and separated from the rest of the city by railroad tracks. His vision included burying these tracks, increasing access via a new public tram, designing walkable streets, and creating new public spaces and housing.

Today, the area is a 21st-century urban community with 4,500 firms, thousands of new housing units, and clusters of universities, technology centres, and incubators.

Across the Atlantic in Boston, former mayor Tom Menino declared the South Boston waterfront an innovation district in 2010. Menino persuaded innovators like MassChallenge to move to the district and exacted important concessions from developers (including land for innovation-oriented retail, shared labs and other spaces, and micro-housing) to help realise the district's vision.

2) Changing land-use laws to build spaces with a mix of facilities

Barcelona and Research Triangle Park, for example, developed bold master plans encouraging the "mixing" of large and small firms, research facilities, housing, restaurants, and retail and outlining where to create open spaces for networking. Cambridge, Massachusetts, by contrast, has allowed incremental moves from rigid, antiquated rules to encourage similar outcomes in Kendall Square .

3) Supporting scarce public resources with large private and civic investments

In New York , former mayor Michael Bloomberg deployed $100m in municipal capital to prepare the infrastructure necessary to lure Cornell and Technion universities to Roosevelt Island. In other cities, including St Louis and Seattle, local resources are financing infrastructure improvements to buttress and accelerate private growth.

Given that many innovation districts are adjacent to low-income neighbourhoods, cities like Philadelphia are considering smart use of school investments to prepare disadvantaged youth for good jobs in the Stem (science, technology, engineering, and math) economy.

As this decade unfolds, we should expect more cities to use their powers in the service of this new model of innovative, inclusive, and resilient growth.

This opinion originally appeared in The Guardian

       

       

Event Information

View the report

The geography of innovation is shifting and a new model for innovative growth is emerging. In contrast to suburban corridors of isolated corporate campuses, innovation districts combine research institutions, innovative firms and business incubators with the benefits of urban living. These districts have the unique potential to spur productive, sustainable, and inclusive economic development.  

On June 9, the Metropolitan Policy Program at Brookings released “The Rise of Innovation Districts,” a new report analyzing this trend. The authors of the paper, Brookings Vice President Bruce Katz and Nonresident Senior Fellow Julie Wagner, were joined by leaders from emerging innovation districts across the country to discuss this shift and provide guidance to U.S. metro areas on ways to harness its potential.

Join the conversation on Twitter using #InnovationDistricts

Presentation by Bruce Katz

---

Event Photos

---

Bruce Katz, Vice President and Director, Metropolitan Policy Program

Lydia DePillis, John A. Fry, Nicole Fichera, Kofi Bonner, Julie Wagner

The Honorable Andy Berke, Mayor, City of Chattanooga, TN and Bruce Katz

Video

• What Are Innovation Districts?
• Innovation Districts Aligned With Disruptive Dynamics of Our Era
• Cities are For People
• Boston's District Hall a Living Room for Innovation Economy
• Innovation Happens Anywhere and Everywhere
• Are Innovation Districts Another Form of Gentrification?
• Philadelphia Behind but Competing in Innovation Districts
• Chattanooga Has Fastest, Cheapest Internet in Western Hemisphere
• We Live In an Innovation Century
• The Rise of Innovation Districts - Opening Remarks
• The Rise of Innovation Districts - Presentation by Bruce Katz
• The Rise of Innovation Districts - Panel Discussion
• The Rise of Innovation Districts - Moderated Dialogue

Audio

• The Rise of Innovation Districts: A New Geography of Innovation in America

Transcript

• Uncorrected Transcript (.pdf)

Event Materials

• 20140609_innovation_districts_transcript

       

The geography of innovation is shifting. For proof, start with Google, which over the past 10 years has taken the core R&D and innovation-oriented activities it once housed only in Silicon Valley and extended them into cities. The company’s presence in London’s Tech City, New York City’s Chelsea district, and Pittsburgh’s Bakery Square reflects management’s calculation that being in cities increases the company’s access to growing tech-oriented ecosystems, advanced research institutions, deep pools of talent, and distinct regional specializations.

In its decision to go urban, Google has been joined by not only other tech firms such as Twitter, Microsoft, and Spotify, but also companies like Comcast, Amazon, Pfizer, Quicken Loans, and countless numbers of small start-ups and entrepreneurs. (Our recent research for the Brookings Institution, “The Rise of Innovation Districts: A New Geography of Innovation in America,” provides the larger context for these corporate choices.)

For the past 50 years, the landscape of innovation has been dominated by regions like Silicon Valley—suburban corridors of spatially isolated corporate campuses, accessible only by car, with little emphasis on the quality of life or on integrating work, housing, and recreation. After visiting dozens of U.S. and European cities, interviewing hundreds of practitioners and experts on the ground, and scouring scholarly analyses of investor and firm behavior, we are convinced that a complementary new urban model is now emerging, in the form of what we and others are calling “innovation districts.”

These districts, by our definition, are “geographic areas where leading-edge anchor institutions and companies cluster and connect with start-ups, business incubators, and accelerators. Compact, transit-accessible, and technically-wired, innovation districts foster open collaboration, grow talent, and offer mixed-used housing, office, and retail.”

Globally, Barcelona, Berlin, Copenhagen, London, Medellin, Montreal, Seoul, Stockholm, and Toronto all contain emerging innovation districts. In the United States, the most iconic districts can be found in the downtowns and midtowns of Atlanta, Cambridge, Detroit, Philadelphia, Pittsburgh, and St. Louis. In each, advanced research universities, medical complexes, and clusters of tech and creative firms are sparking business expansion as well as residential and commercial growth.

Other innovation districts are developing in Boston, Brooklyn, Chicago, Portland, San Francisco, and Seattle. Former industrial and warehouse areas are undergoing a renaissance, powered by their enviable location along transit lines, proximity to downtowns and waterfronts, and recent additions of advanced institutions. (Note, for example, Carnegie Mellon University’s decision to place its Integrative Media Program at the Brooklyn Navy Yard.)

Perhaps the greatest validation of this shift is the fact that traditional exurban science parks like Research Triangle Park in Raleigh-Durham are now responding with efforts to meet the new demand for more vibrant and collaborative work and living environments.

Innovation districts are already attracting an eclectic mix of firms in the app economy and high tech sector as well as in high-value, research-oriented sectors such as life and material sciences, clean energy, and data computing. They are also home to companies in highly creative fields like architecture, design, theater production, advertising, and marketing. We even see a return to cities of small-scale and customized manufacturing, made possible by 3D printing, robotics, and other advanced techniques.

Much of this activity reflects a fundamental rethinking by corporate management about how and where innovation happens. In turn, it is making the case that discrete urban geographies can be instrumental in strengthening the competitive advantages of specific firms and clusters.

Rather than being the outgrowth of heavy-handed government programs, innovation districts are instead emerging from broader trends and market forces. For example, an economy increasingly oriented toward innovation (particularly through open collaborations) naturally rewards urban density. Companies, researchers, and entrepreneurs working in close proximity are able to share ideas rather than invent in isolation. No one company can master all the knowledge it needs, so they rely on a network of industry collaborators. A recent New York Times article on the growth of Pfizer, Novartis, and other major pharmaceutical companies in Cambridge, makes the point explicitly:

Pharmaceutical companies traditionally preferred suburban enclaves where they could protect their intellectual property in more secluded settings and meet their employees’ needs. But in recent years, as the costs of drug development have soared and R&D pipelines slowed, pharmaceutical companies have looked elsewhere for innovation. Much of that novelty is now coming from biotechnology firms and major research universities like MIT and Harvard, just two subway stops away.

If the benefits of urban density were already being experienced, they take on heightened importance in what Michael Mandel has called the “age of convergence” —when companies must simultaneously push forward with technology and content. Other analysis by the Center for an Urban Future in New York City finds many tech players focusing less on building new technologies and more on “applying technology to traditional industries like advertising, media, fashion, finance, and health care.” These shifts reinforce the importance of proximate location as companies strive to be physically close to the individuals and companies they partner with.

The rise of a convergence and collaborative economy also raises questions of how commercial buildings—offices, research labs, business incubators, and innovation institutes—should be designed. Thus, the creative solutions being tried in vanguard innovation districts will yield broad lessons. With their many variations on incubator space, collaborative venues, social networking, product competitions, technical support, and mentoring, they are beginning to sort out the best physical and social platforms for entrepreneurial growth.

Finally, large-scale demographic migrations are putting new value on cities and demanding more and better choices in where workers live, work and play. The City Observatory recently found, for example, that the number of young college graduates living within three miles of city centers (i.e., where innovation districts tend to be located) has surged, up 37 percent since 2000. This is happening not just in talent magnets like Denver, Portland, OR, and San Diego, but also in older industrial cities like Buffalo, Cleveland, and Pittsburgh.

The confluence of these disruptive economic, social, and demographic dynamics has changed corporate calculus. As companies design forward-looking strategies, they should be asking whether and how a greater commitment to urban locales could help them squeeze out even more success.

This commentary was originally published by Harvard Business Review.

       

In the year since we released “The Rise of Innovation Districts: A New Geography of Innovation in America,” Brookings has visited or interacted with dozens of leaders in burgeoning innovation districts in the United States and Europe. In so doing, we’ve sharpened our knowledge of what’s happening on the ground and gained some important insights into how cities and metros are embracing this new paradigm of economy-shaping, place-making, and network-building.

Innovation districts capture the remarkable spatial pattern underway in the innovation economy—the heightened clustering of anchor institutions, companies, and start-ups in small geographic areas of central cities across the United States, Europe, and other global-trading regions.

The rise of innovation districts has been situated against the familiar backdrop of suburban corporate campuses and science parks. Accessible only by car, these spatially isolated corridors place little emphasis on the quality of life or on integrating work, housing, and recreation.

By contrast, in our report we found the rise of urban innovation hubs to be the organic result of profound economic and demographic forces that are altering how we live and work. The growing application of “open innovation”—where companies work with other firms, inventors, and researchers to generate new ideas and bring them to market—has revalued proximity, density, and other attributes of cities. At the same time, the growing preference of young talented workers to congregate in vibrant neighborhoods that offer choices in housing, transportation, and amenities has made urban and urbanizing areas increasingly attractive.

We also found that innovation districts uniformly contain a mix of economic, physical, and networking assets. Economic assets are the firms, institutions, and organizations that drive, cultivate, or support an innovation-rich environment. Physical assets are the public and privately owned spaces—buildings, open spaces, streets, and other infrastructure—designed and organized to stimulate new and higher levels of connectivity, collaboration, and innovation. Lastly, networking assets are the relationships between actors—such as between individuals, firms, and institutions—that have the potential to generate, sharpen, and/or accelerate the advancement of ideas. These assets, taken together, create an innovation ecosystem—the synergistic relationship between people, firms, and place that facilitates idea generation and advances commercialization.

One year later, innovation districts continue to rise. What have we learned about how they are evolving?

First, the model of innovation districts has been embraced, co-opted, and (in some cases) misappropriated, further reinforcing the need for grounding this work in empirically based evidence.

A simple Google search will reveal the extent to which the language of “innovation districts” (or “innovation quarters,“ “innovation neighborhoods,” or “innovation corridors”) has rapidly permeated the field of urban and metropolitan economic development and place-making.

In some places, this labeling is being accurately used by globally recognized research institutions (e.g., Carnegie Mellon in Pittsburgh, Drexel University in Philadelphia) that are both experiencing extraordinary growth near their campuses as well as designing intentional efforts to build on their distinctive assets. In communities as diverse as Philadelphia, Pittsburgh, and St. Louis in the United States and Manchester and Sheffield in England, local leaders are conducting deep empirical analysis to understand their competitive advantages and existing weaknesses within their innovation ecosystem. They are exploring what it means to encourage greater collaboration and cooperation across their institutions, firms, and entrepreneurs. And they are exploring ways to better create “place” so as to increase overall vitality, facilitate innovation, and spur the growth of new businesses and jobs.

In other places, the nomenclature reflects an aspiration—and is spurring more deliberate efforts by local stakeholders to grow distinctive innovation ecosystems. In cities like Albuquerque, N.M., Chattanooga, Tenn., Chicago, Ill., Durham, N.C., and San Diego, Calif., local leaders are using the innovation district paradigm as a platform to measure their current conditions, develop strategies for addressing gaps and challenges, and build coalitions of stakeholders that can together help realize a unified vision for innovative growth. Some of these budding districts represent typologies not outlined in our report but that are ripe for future research, including “start-up” enclaves in or near downtowns of cities that lack a major anchor as well as “public markets” that blend locally produced food products and crafts with maker spaces, digital design, and other innovations in the creative arts.

There is one unfortunate trend in the rising use of the "innovation district" lexicon. In a number of cities, local stakeholders have applied the label to a project or area that lacks the minimum threshold of innovation-oriented firms, start-ups, institutions, or clusters needed to create an innovation ecosystem. This appears to result either from the chase to jump on the latest economic development bandwagon, the desire to drive up demand and real estate prices, or sometimes a true lack of understanding of what an innovation district actually is. The motivation for real estate developers to adopt the moniker seems clear: to achieve a price premium for their commercial, residential, and retail rents. Yet these sites are typically a collection of service-sector activities with little focus on the innovation economy. The lesson: labeling something innovative does not make it so.

From all these observations, it is clear that the field needs a routinized way to measure the starting assets of innovation districts—both to separate true districts from “in name only” ones as well as to give individual communities a platform for developing targeted strategies going forward. This means both running the numbers—conducting a quantitative audit—and undertaking a more qualitative assessment of strengths and weaknesses. Irrespective of their phase of development, innovation districts must evaluate the extent to which they have a critical mass of economic, physical, and networking assets to collectively generate the vitality that these districts demand. They need to evaluate the competitive advantages they have in certain economic sectors and learn how to cultivate them. And they need to ensure that they have the connectivity, diversity, and quality of place necessary to create a unique and vibrant environment in which innovation can thrive.

To facilitate this process, we are working in close collaboration with Mass Economics and the Project for Public Spaces to develop an audit template and tool. Over the next year, we intend to sharpen this tool in a subset of innovation districts across the country and then encourage others to employ it in their own established or burgeoning districts.

Second, the core economic assets of innovation districts are not fixed; in fact, many innovation districts are being created or enhanced by the relocation of major anchor facilities as institutions strive to achieve the highest return on investment.

The conventional notion of an “anchor” institution is that it is solidly weighted in a particular place. Yet over the past decade a substantial number of innovative companies and advanced educational and research institutions have moved key facilities and units as a means of generating greater innovation output. Examples of new locations include the University of California-San Francisco’s biotechnology campus in Mission Bay (2003); the University of Washington’s medical research hub in Seattle’s South Lake Union (2005); Brown University’s medical school in downtown Providence, R.I. (2011); Duke’s Clinical Research Institute in downtown Durham (2013); Carnegie Mellon University’s Integrative Media Program in the Brooklyn Navy Yard (2013); and, most famously, the new Cornell Tech campus on Roosevelt Island in New York City (2015).

These “first mover” relocations show how corporate and university leaders are departing from the tradition of building new facilities within their existing footprint and are willing to seek out new areas (and even new cities) to retain, or achieve, competitive advantage in their respective clusters and fields. As Cornell Professor Ronald Ehrenberg said about his school’s isolated Ithaca, N.Y. campus, “It is very, very difficult for us to do the kind of development through tech transfer that a place like Stanford or Berkeley can do in San Francisco or Harvard or MIT can do in Boston.” Our strong sense in talking with leaders around the country is that we are still at the early stage of corporate and university relocations given the extent to which urban areas have been revalued. The physical relocation of key innovation assets has now become a critical competitiveness strategy for companies, universities, and even states.

In some cases, the “unanchoring of anchors” is also compelling local leaders to rethink the traditional borders and boundaries of the innovation economy. In Philadelphia, for example, University City has always been recognized as a settled innovation hub, given the co-location of such anchor institutions as Drexel University, the University of Pennsylvania, the University City Science Center, and others. The recent decision of Comcast to consolidate its corporate presence in the downtown area and build its major new Innovation and Technology Center less than 10 blocks from 30th Street Station and the Drexel Campus is convincing some leaders to “stretch” Philadelphia’s University City district to incorporate this new corporate giant.

Third, almost all innovation districts have significant work ahead to understand the rising value of “place” in the innovation ecosystem and leverage or reconfigure their physical assets to create dense and dynamic communities.

While our paper dissected various types of physical assets to help practitioners understand their individual roles and value, the more important message to convey now is the imperative to combine and activate physical assets in ways that create vibrant “places.” The Project for Public Spaces aptly describes place as “…environments in which people have invested meaning over time. A place has its own history—a unique cultural and social identity that is defined by the way it is used and the people who use it.”¹

Our review of innovation districts, including those cited in our paper, reveals that many have not yet maximized the potential for creating lively communities in which their residents and workers feel invested, reducing the potential innovation output of these communities. When designed and programmed well, a district’s public spaces—whether within buildings or outside of them—facilitate open innovation by offering numerous opportunities to meet, network, and brainstorm. Strong places entice residents and workers to remain in the area off hours, extending the opportunities for collaboration. Strong places create a culturally and educationally enriched environment that strengthens human interaction, knowledge, and motivation.

While some university-led districts have made some improvements over the years, districts anchored by medical campuses have significant work ahead. These spaces were designed as isolated fortresses that valued parking over walking (ironic given their health mission), with little or no attention paid to amenities, cultural activities, retail, or housing. Significantly, some medical campuses are often located in close proximity to downtowns, as part of universities, or near organic entrepreneurial communities (e.g., the proximity of Oklahoma City’s Health District to Automobile Alley). This raises the potential for smart (and related) place-making activities in a nearby area and reinforces the need to rethink traditional geographies and artificial boundaries when considering interventions.

Fourth, the rapid growth and impact of national intermediaries (what we call innovation cultivators) shows real promise in helping innovation districts grow and steward their networking assets and stimulating new innovation opportunities.

The past year has seen substantial growth in multicity intermediaries along with scores of locally grown accelerators and incubators. It appears more than ever that intermediaries are increasingly the catalyst to growing innovation and entrepreneurial energy within local districts and across start-ups, small and medium-sized enterprises, and, even to some extent, large companies and research institutions. They are designed to think and act horizontally, encouraging people and firms to interact and work together in ways and at a scale previously unseen.

A growing and increasingly important role for intermediaries is helping innovation districts evolve from the traditional “research and development” model to a “search and development” one, where crucial answers to their innovation questions and technological challenges are discovered by finding and collaborating with other firms. Some districts immediately recognized this potential and have gone to great lengths to grow, lure, and fund the development of multiple intermediaries across their districts.

The Cortex Innovation Community in St. Louis has, in a short period, clustered new buildings owned and/or supported by a number of well-respected intermediaries. These development and programmatic moves are effectively creating a new focal point for Cortex innovation activities. The new Cambridge Innovation Center, which offers space for start-ups combined with access to venture capital firms, professional services, and a plug-and-play physical environment, is already at 85 percent occupancy. A newly constructed Tech Shop—a do-it-yourself “maker space” equipped with industrial tools, machinery, and technology to support entrepreneurs—is under construction nearby. The near complete renovation of the Center for Emerging Technologies, which provides training, specialized facilities, and technical support, adds yet another layer of support for entrepreneurs and start-ups. Adding more to this mix is a soon-to-be-constructed space for tech-commercial activities combined with new housing, which will exponentially increase the number of people in a very small radius.²

As one can imagine, this clustering was deeply intentional and viewed as a way to stimulate new relationships, new networks, and the cross-fertilization of ideas; Cortex refers to this deliberate process as “innovation engineering.” We anticipate more innovation districts to follow suit, pursuing, if not cultivating, such intermediaries in their own innovation ecosystems.

Finally, the rise of innovation districts takes place in a national and urban political environment that demands inclusive growth and equitable outcomes.

The past year has seen the elevation of income inequality and social mobility as issues of national and urban significance. With the federal government mired in partisan gridlock, cities have become the vanguard of efforts to raise the minimum wage, expand affordable housing, and extend pre-K education, among other initiatives. These efforts come at a time when the civil unrest in Baltimore and Ferguson has refocused national attention on neighborhoods of high poverty.

Because of their location in the cores of central cities, many established and emerging innovation districts are located several blocks away from distressed communities. This proximity creates an enormous opportunity to show the positive impact that innovative growth can have on inclusive outcomes. Innovation districts create employment opportunities that can be filled by local residents and procurement and construction opportunities that can be fulfilled by local vendors and contractors. The districts generate tax revenues that can be used to fund neighborhood services and neighborhood regeneration. And they offer the potential to link the ample expertise and talent in anchor educational institutions with the needs of neighborhood schools and children.

Recognizing these benefits, local leaders are demonstrating a genuine commitment to growing more inclusive districts. In our work, we’ve seen several early models that could be built on and replicated. In the Barcelona 22@ district, for example, leaders are trying to quantify the growth in service jobs accessible to local and regional residents while, at the same time, connecting those residents to training that increases their skills in more innovation-oriented sectors. Last year, Drexel University opened a new “urban extension center” that offers career-building workshops, legal clinics, and other services to residents of the adjacent Mantua Promise Zone. The Evergreen Cooperative in Cleveland’s University Circle district has been working for several years to leverage local purchasing power to create business ownership and employment opportunities for low-income residents. And in Baltimore, the University of Maryland partnered with surrounding neighborhood organizations, residents, and institutions to develop a detailed new plan for building what the Baltimore Southwest Partnership envisions as a “diverse, cohesive community of choice built on mutual respect and shared responsibility.”

These examples represent concrete initiatives to ensure that nearby neighborhoods and their residents connect to and benefit from new growth opportunities in innovation districts and beyond. Scaling such efforts will be critical in the years to come, as the success of these districts will be defined in large part by their broader city and regional impacts.

As Brookings works this year to help unleash more innovation districts across the U.S. and Europe, we will continue to hone our observations and knowledge about trends, challenges, and strategies. We will compile and publish what we have learned for anchor leaders, policymakers, scholars, and practitioners, focusing on many of the issues—accelerating commercialization to improving inclusion—noted above. We will do this work in close collaboration with proven organizations like Mass Economics and Project for Public Spaces. We look forward to contributing to this rapidly changing space via empirical and on-the-ground research, strategy and policy development, convenings, and network building. Stay tuned.

Read The Rise of Innovation Districts: A New Geography of Innovation in America

---

       

Less than two years ago, the Brookings Institution unveiled the research paper, “The Rise of Innovation Districts,” which identified an emerging spatial pattern in today’s innovation economy. Marked by a heightened clustering of anchor institutions, companies, and start-ups, innovation districts are emerging in central cities throughout the world.

A Google search of the term “innovation district” reveals over 200,000 results, indicating the extent to which the phrase has permeated the fields of urban economic development, planning, and placemaking. The term is used to refer to areas, often in the downtowns of cities, where R&D-laden universities or firms are surrounded by a growing mix of start-ups and spin-offs. The term is also increasingly applied to densely populated urban neighborhoods where firms like Google are establishing campuses. But it also pops up to describe new office complexes whose amenities include a few stores or a fashionable coffee shop.

The variation in understanding of the term and its application suggests the need for a routinized way to measure the essential quantitative and qualitative assets of innovation districts. Given this, for the past nine months the Brookings Institution, Project for Public Spaces (PPS), and Mass Economics have collaborated to devise and test an audit tool for assessing innovation districts.

What to count? Considerations in designing an audit

Innovation ecosystems comprise complex, overlapping relationships between firms, individuals, unique spaces, private real estate, public infrastructure, capital, expertise, and conviviality, congregated in a roughly delineated area. To begin to determine how to identify and measure assets, we developed a process that was both rigorous and reflective, drawing together some of the brightest minds in the field, top practitioners on the ground, and a team strong in quantitative analysis.

First, we conducted research across numerous relevant topics including entrepreneurship, real estate development, commercialization, economic geography, city planning, institutional culture, finance, and inclusive development. This exercise generated hundreds of potentially applicable measures for the audit.  

       

Innovative activity and innovation districts are not evenly distributed across cities. Some metropolitan areas may have two or three districts scattered about, while other cities are lucky to have the critical mass to support even one strong district. London, however, a global city with nearly unparalleled assets, can best be understood as not just a collection of innovation districts but as a contiguous “city of innovation.” 

Our understanding of that innovative activity has taken a leap forward with the publication of a new report by the Centre for London called "Spaces to Think". Even for a paragon of innovation, a critique such as this is imperative if the city desires to maximize its assets while continuing to grow in a sustainable and inclusive manner. Much as we have recommended that urban leaders across the United States undertake an asset audit of their districts to identify key priorities, "Spaces to Think" focuses on 17 distinct districts, mapping their assets, classifying their typologies, and identifying governance structures.

The 17 study areas in "Spaces to Think"

The report provides lessons applicable to many cities.

Having identified, across all 17 districts, the three major drivers of innovative activity—talent, space, and financing—it becomes clear that the main hurdle for London, as a global magnet of talent and capital, is affordable physical space: “Increasing pressure for land…risks constraining London’s potential as a leading global city for innovation.” Similar to hot-market cities across the United States, many of the study areas of greatest promise are older industrial areas, such as Here East, Canary Wharf, and Kings Cross, where large plots of underutilized land have been reimagined as innovation districts. 

But who is prepared to undertake new regeneration projects? The report places significant responsibility on London’s many universities—whose expansions already account for much of the large-scale development opportunities in the city—for a “third mission” of local economic development. It is universities, the report notes, that are “devoting increasing amounts of money, resources, and planning to building new or redesigned facilities…pitched as part of a wider regeneration strategy, or the creation of an innovation district.” 

A second concern is the democratization of the innovation economy. Already a victim of rising inequality, London’s future growth must reach down the ladder. As we’ve argued, with intentionality and purpose, innovation districts can advance a more inclusive knowledge economy, especially given that they are often abut neighborhoods of above-average poverty and unemployment. Spaces to Think expands upon four key strategies: local hiring and sourcing practices for innovation institutions; upskilling of local residents through vocational and technical programs within local firms; increased tax yield, especially given recent reforms in which “local authorities retain 100 percent of business rates”; and shared assets and rejuvenation of place. This final lever requires inclusive governance that encourages neighborhood ownership of the public realm.

Finally, the report notes that, while there is much diversity of leadership in the study areas—some are university-led, some are entrepreneurial, some are industry-led—“good governance and good relations between institutions, are at the heart of what makes innovation districts tick.” This issue is at the heart of our work moving forward: identifying and spreading effective governance models that encourage collaboration and coordination between the public, private, and civic actors within innovation districts.

We are pleased that this future work will be strengthened by a new partnership between the Bass Initiative on Innovation and Placemaking and the Centre for London. The ambition of this Transatlantic Innovation Districts Partnership is to increase our mutual understanding of innovation districts found in Europe through additional qualitative and quantitative analysis and to integrate European leaders into a global network, all to accelerate the transfer of lessons and best practices from districts across the world.

       

A Q&A with Dennis Lower, president and CEO, Cortex Innovation Community

As leaders scan the landscape for strong examples of innovation districts, their tour is hardly complete without learning of the Cortex Innovation Community—an innovation district in the heart of St. Louis. We sat down with Dennis Lower, president and CEO of the Cortex Innovation Community to learn what kinds of interventions and instruments are driving their success.

What is the Cortex Innovation Community?

Cortex is the region’s largest innovation hub, generating 3,800 tech-related jobs and over $500 million in investment in the last 14 years. It’s located close to downtown and built on the intellectual assets and resources of St. Louis’ leading universities, a premier health care provider, and the Missouri Botanical Garden. The focal point is the 200 acres of old industrial land that one time separated these institutions but that now stitches them together. At full build-out, Cortex will likely generate $2 billion of development and create 13,000 jobs.

What sets Cortex apart from other innovation districts?

Of course, every district is distinctive and unique, building off its local character, culture, and assets. What sets Cortex apart, I would argue, is that we literally have billions of dollars of academic, cultural, and recreational assets in the neighborhoods that surround the district, which other places simply do not have.

We are bookended by two universities—Washington University and St. Louis University—each a magnet for international students and each with a reputation for research and academic excellence. Washington University, for example, was one of five consortium members funded by the National Institutes of Health to map the human genome. These universities, together with the University of Missouri-St. Louis, are the academic bedrock of our local innovation ecosystem.

Recent demographic analysis tells us we are now the most diverse employment environment in the region no matter how you slice it, including by age, ethnicity, and educational attainment.

Another Cortex advantage is the neighborhood that surrounds us. In addition to historic housing, the Grand Center arts district is to the east, to the west is Forest Park, which contains the St. Louis Zoo, fine arts and history museums, two golf courses, the St. Louis Science Center, abundant walking and biking trails, and the internationally renowned Botanical Garden. Restaurant corridors are to the north and south. I tell you all this to say that Cortex is where innovation, tech, culture, and community collide—and people are hungry for this mix.

Cortex Innovation Community is also a tax-exempt 501(c)3 that oversees the design and development of the innovation district. What makes your nonprofit unique in managing this district?

Cortex has been designated the master developer to transform an old industrial district into a center for innovation and commercialization. We are in a particularly advantageous position because the state and the city have granted the 501(c)3 powers of eminent domain, the power to abate taxes, and the power to approve or reject building plans. From a traditional economic development perspective, these powers have been critical in overcoming obstacles that land speculators sometimes put in our way. We have not had to use this power very often, fortunately. Only a handful of properties were acquired under the threat of eminent domain, and we reached an impasse only twice, sending us to court to purchase those properties. We take this responsibility seriously and only use eminent domain powers sparingly. We have a good reputation with the public as a result.

Can you describe one accomplishment you are particularly proud of?

We knew that to jump-start an innovation district it was essential to build entrepreneurial density. We developed an unorthodox strategy of sorts in that we built a concentration of innovation assets all within a block of each other. Today, we have six innovation centers, each with its own community and programming: the Center for Emerging Technologies, a traditional technical assistance incubator for information technology, bioscience, and consumer/manufacturing products; the BioGenerator, an accelerator with shared wet lab space and $3 million of shared core lab equipment; TechShop, a premier maker work space for prototyping and creating; the Cambridge Innovation Center–St. Louis, a co-working office and lab startup space); Venture Café–St. Louis, a shared public space for the startup community to meet weekly with 8 to 12 unconventional breakout educational sessions; and IdeaLabs/MedLaunch, a unique university graduate/undergraduate incubator that develops new technology to solve clinical problems. This strategy is working beyond our wildest expectations. It’s the “secret sauce” for supercharging our district’s innovation ecosystem. 

Venture Café: one of the six innovation centers that weekly draws together over 500 entrepreneurs from all technology sectors.

Can you highlight one particularly interesting innovation or invention coming out of Cortex? 

Let me highlight two. We have over 200 companies in Cortex—there’s too much innovation happening here to highlight only one!

First, we have a medical device company that is changing the way infectious diseases are diagnosed. Its products can rapidly detect bacterial infections, determine if the infection is resistant to a range of antibiotics, and provide clinicians with patient-specific guidance to treat infections quickly and accurately. Their first product can diagnose urinary tract infections in just three hours.

And then we have a company tackling the biggest challenge in agriculture today—preventing insects, diseases, and weeds from destroying food crops. This company is developing a cost-effective technology to produce and topically deliver RNAi for agricultural crops. Put simply, this technology helps plants develop desired genetic traits without the use of genetically modified organisms, or GMOs. This could be transformative.

Many people have asked us how innovation districts are supporting inclusive growth. There is a concern that innovation districts are focusing on innovation to the exclusion of employment of city residents, who may not possess the skills or education the district’s businesses are seeking.

We look at inclusion as an integral part of our work and mission at Cortex. We currently have six inclusion initiatives and will soon introduce two more. One of those is the development of a magnet high school in the St. Louis Public School District, the Collegiate School for Medicine and Biosciences. Working closely with the school district’s superintendent and an important group of institutional and civic leaders, we have been developing an urban high school centered on one of the major strengths of our Cortex sponsors—bioscience. We recruited our first class in 2013, providing instruction in a small, temporary school, and in 2015 moved to a permanent location that can support 400 students.

The students come from all across the region, representing the largest spread of zip codes of any regional public school. Currently, 53 percent of the students are African American, 23 percent are Asian, and 22 percent are white, representing a great mix. Last year’s proficiency testing in math and English revealed that we ranked first across the entire public school system. I find this particularly gratifying because a number of incoming freshmen were not performing at grade level. What this tells us is given the opportunity, creative teaching approaches, and a supportive structure, these kids will excel quickly. With our incoming 9th grade class this August, we will have a full complement of freshmen to seniors, graduating our first class in 2017.

Perhaps one of these students will find the next cure for cancer. To me, this illustrates an important part of our district’s DNA—to grow and cultivate innovation talent for the future.

       

The tide of uncertainty that has swept the United Kingdom after its vote to leave the European Union has spared few—including its emerging class of innovation districts.

These hubs of innovation—where anchor institutions, such as universities and R&D laden companies cluster and connect with startups, incubators, and a host of public spaces, coffee shops, retail and housing—are now asking themselves important questions that will affect their future. Will the U.K. broker a deal to continue free trade with Europe? Will access to talent across Europe be curtailed? Will the devalued pound keep U.K. advanced manufacturers competitive for the medium to long term? Will European Union legal frameworks be replaced with a regulatory platform that continues to support advanced sectors? What will happen to EU funding on science and innovation, such as Horizon 2020?

Of course, innovation districts are no stranger to uncertainty, if not chaos. These districts thrive on random mixing, on smashing different kinds of disciplines and people together to generate new ideas and new products for the market. In this close-knit, highly networked ecosystem, chaos breeds creativity. At the same time, the backbone of districts is a clear regulatory and legal framework with rules on intellectual property, investment, and funding streams. The twinning of chaos and certainty is what makes these places simply superb spaces to incubate new technology, aggregate talent, and experiment in linking placemaking with innovation.

Yet from the distinctive innovation districts in London to those emerging in the middle of England, such as in Sheffield and Manchester, to those rising in Scotland, such as in Glasgow, this moment of uncertainty could be not only painful—it could be downright dangerous. 

In the face of such uncertain times, the temptation will be to sit back and wait for the cards to fall. But this tempered, conservative approach is ironically the more risky tactic.

We recommend another path.

Now is the time for the institutions and firms that are driving innovation districts to strengthen their competitive position and expand their reach.

Now is the time to try new forms of collaboration between universities, large companies, and local enterprises.

Now is the time to test more democratic modes of innovation with maker spaces, fab labs, and shared infrastructure and equipment.

Now is the time to forge new partnerships with other innovation districts in the United States and Europe to share promising strategies around commercialization, networking, and financing.

Now is the time to apply new energy to creative placemaking, including strengthening the innovation–place nexus around key nodes and applying quick interventions around traffic calming, bike lanes, and pop-up gathering spaces. 

U.S. cities and innovation districts have demonstrated that progress can persist even when higher levels of government are adrift. U.K. cities and districts can do the same.

       

How are two innovation districts in Stockholm successfully melding their tech and life science clusters to create new products?

What can the Wake Forest Innovation Quarter in North Carolina teach us about creating strong, vibrant, and innovative places?

How are innovation districts in Australia leveraging government policies and programs to accelerate their development?

Over the last year, members of the Anne T. and Robert M. Bass Initiative on Innovation and Placemaking team talked with hundreds of local leaders and practitioners advancing innovation districts in almost every global region. These conversations revealed the remarkable level of creativity and innovative, out-of-the-box thinking being employed to grow individual innovation districts.

In the course of our work, we have been intrigued by the question, is there value to be gained from a global network of innovation districts? To this end, we have reached out to successful global networks in Europe, the United States, and Asia to distill what it takes to make a strong and sustainable global network. Among our findings so far:

• Network members are solving on-the-ground challenges by talking with and learning from their peers. Several said that these horizontal exchanges are essential to leapfrogging ahead. 

• Online interaction is growing but network members say that face-to-face contact is critical. Comparing notes, asking questions, and engaging in conversations foster collaboration while maintaining a healthy dose of competition. 

• The right tools and supports can make all the difference. In networks where participants had full schedules, developing new ways to share intelligence, like early morning webinars or virtual conferences, regular e-newsletters, and simple methods to share data helped facilitate their learning. 

To what extent do you feel that a network of innovation districts might supercharge your own efforts and successes?

It would help our work tremendously if you could complete our on-line survey. It will take two minutes or less!

Editor's Note: If you're interested in receiving the latest news from the Bass Initiative, please sign up for our newsletter at this link, http://connect.brookings.edu/bass-initiative-newsletter-signup. Feel free to share it widely.

       

       

       

       

       

       

       

       

       

Event Information

A decade into the 21st century, the role of manufacturing in global and metropolitan economies continues to evolve. After 20 years of rapid globalization in which manufacturing production shifted to emerging markets, demand for consumption is growing there, too. Emerging market demand, in fact, has unprecedented momentum as 1.8 billion people enter the global consuming class. At the same time, a robust pipeline of product innovation and manufacturing processes has opened new ways for U.S. manufacturing companies to compete.

On November 19, the Metropolitan Policy Program at Brookings hosted a forum to release a report from the McKinsey Global Institute that examines the role of manufacturing in advanced and developing economies and the choices that manufacturers grapple with in this new era of global competition. Following presentations by the authors, an expert panel discussed the key trends shaping manufacturing competitiveness, global strategies, the next era of manufacturing innovation, and what these changes imply for growth and employment in manufacturing across the globe.

Video

• Bruce Katz: A Region Has to Know What It Can Do Well
• Martin Baily: Manufacturing Creates Jobs
• Katy George: Manufacturing Is an Entity That Is Constantly Shifting
• James Manyika: Manufacturing Matters a Great Deal
• Gardner Carrick: Education Is Key
• James W. Griffith: Closing Remarks

Audio

• Global Manufacturing: Entering a New Era

Transcript

• Uncorrected Transcript (.pdf)

Event Materials

• 20121119_global_manufacturing

       

Once upon a time, ambitious young people with a knack for math and science went to work in manufacturing. They designed planes, computers, and furniture, figured out how to lay out an assembly line, helped to make new cars faster and refrigerators more efficient, pushed the limits of computer chips, and invented new medicines. But, as the role of manufacturing diminished in advanced economies, the brightest talents tended to gravitate to finance and other service fields that were growing rapidly – and paying well.

But here’s some news: global manufacturing has the potential to stage a renaissance and once again become a career of choice for the most talented.

Of course, any manufacturing rebound in the advanced economies will not generate mass employment; but it will create many high-quality jobs. There will be more demand for software programmers, engineers, designers, robotics experts, data analytics specialists, and myriad other professional and service-type positions. In some manufacturing sectors, more such people may be hired than will be added on the factory floor.

Exploding demand in developing economies and a wave of innovation in materials, manufacturing processes, and information technology are driving today’s new possibilities for manufacturing. Even as the share of manufacturing in global GDP has fallen – from about 20% in 1990 to 16% in 2010 – manufacturing companies have made outsize contributions to innovation, funding as much as 70% of private-sector R&D in some countries. From nanotechnologies that make possible new types of microelectronics and medical treatments to additive manufacturing systems (better known as 3D printing), emerging new materials and methods are set to revolutionize how products are designed and made.

But, to become a genuine driver of growth, the new wave of manufacturing technology needs a broad skills base. For example, it will take many highly-trained and creative workers to move 3D printing from an astounding possibility to a practical production tool.

Consider, too, the challenges of the auto industry, which is shifting from conventional, steel-bodied cars with traditional drive trains to lighter, more fuel-efficient vehicles in which electronics are as important as mechanical parts. The Chevrolet Volt has more lines of software code than the Boeing 787. So the car industry needs people fluent in mechanical engineering, battery chemistry, and electronics.

Manufacturing is already an intensive user of “big data” – the use of massive data sets to discover new patterns, perform simulations, and manage complex systems in real-time. Manufacturing stores more data than any other sector – an estimated two exabytes (two quintillion bytes) in 2010. By enabling more sophisticated simulations that discover glitches at an early stage, big data has helped Toyota, Fiat and Nissan cut the time needed to develop new models by 30-50%.

Manufacturers in many other branches are using big data to monitor the performance of machinery and equipment, fine-tune maintenance routines, and ferret out consumer insights from social-media chatter. But there aren’t enough people with big-data skills. In the United States alone, there is a potential shortfall of 1.5 million data-savvy managers and analysts needed to drive the emerging data revolution in manufacturing.

The shift of manufacturing demand to developing economies also requires new skills. A recent McKinsey survey of multinationals based in the U.S. and Europe found that, on average, these companies derive only 18% of sales from developing economies. But these economies are projected to account for 70% of global sales of manufactured goods (both consumer and industrial products) by 2025. To develop these markets, companies will need talented people, from ethnographers (to understand consumers’ customs and preferences) to engineers (to design products that fit a new definition of value).

Perhaps most important, manufacturing is becoming more “democratic,” and thus more appealing to bright young people with an entrepreneurial bent. Not only has design technology become more accessible, but an extensive virtual infrastructure exists that enables small and medium-size companies to outsource design, manufacturing, and logistics. Large and small companies alike are crowd-sourcing ideas online for new products and actual designs. “Maker spaces” – shared production facilities built around a spirit of open innovation – are proliferating.

And yet, across the board, manufacturing is vulnerable to a potential shortage of high-skill workers. Research by the McKinsey Global Institute finds that the number of college graduates in 2020 will fall 40 million short of what employers around the world need, largely owing to rapidly aging workforces, particularly in Europe, Japan, and China. In some manufacturing sectors, the gaps could be dauntingly large. In the U.S., workers over the age of 55 make up 40% of the workforce in agricultural chemicals manufacturing and more than one-third of the workforce in ceramics. Some 8% of the members of the National Association of Manufacturers report having trouble filling positions vacated by retirees.

Indeed, when the NAM conducted a survey of high-school students in Indianapolis, Indiana (which is already experiencing a manufacturing revival), the results were alarming: only 3% of students said that they were interested in careers in manufacturing. In response, the NAM launched a program to change students’ attitudes. But not only young people need persuading: surveys of engineers who leave manufacturing for other fields indicate that a lack of career paths and slow advancement cause some to abandon the sector.

Manufacturing superstars such as Germany and South Korea have always attracted the brightest and the best to the sector. But now manufacturers in economies that do not have these countries’ superior track record must figure out how to be talent magnets. Manufacturing’s rising coolness quotient should prove useful, but turning it into a highly sought-after career requires that companies in the sector back up the shiny new image with the right opportunities – and the right rewards.

       

The weakness of the economic recovery in advanced economies raises questions about the ability of new technologies to drive growth. After all, in the years since the global financial crisis, consumers in advanced economies have adopted new technologies such as mobile Internet services, and companies have invested in big data and cloud computing. More than 1 billion smartphones have been sold around the world, making it one of the most rapidly adopted technologies ever. Yet nations such as the United States that lead the world in technology adoption are seeing only middling GDP growth and continue to struggle with high unemployment.

There are many reasons for the restrained expansion, not least of which is the severity of the recession, which wiped out trillions of dollars of wealth and more than 7 million US jobs. Relatively weak consumer demand since the end of the recession in 2009 has restrained hiring and there are also structural issues at play, including a growing mismatch between the increasingly technical needs of employers and the skills available in the labor force. And technology itself plays a role: companies continue to invest in labor-saving technologies that reduce demand for less-skilled workers.

So are we witnessing a failure of technology? Our answer is "no." Over the longer term, in fact, we see that technology continues to drive productivity and growth, a pattern that has been evident since the Industrial Revolution; steam power, mass-produced steel, and electricity drove successive waves of growth, which has continued into the 21st century with semiconductors and the Internet. Today, we see a dozen rapidly-evolving technology areas that have the potential for economic disruption as well in the next decade. They fall into four groups: IT and how we use it; machines that work for us; energy; and the building blocks of everything (next-gen genomics and synthetic biology).

Wide ranging impacts

These disruptive technologies not only have potential for economic impact—hundreds of billions per year and even trillions for the applications we have sized—but also are broad-based (affecting many people and industries) and have transformative effects: they can alter the status quo and create opportunities for new competitors.

While these technologies will contribute to productivity and growth, we must look at economic impact in a broader sense, which includes measures of surplus created and value shifted (for instance from producers to consumers, which has been a common result of Internet adoption). The greatest benefit we measured for autonomous vehicles—cars and trucks that can proceed from point A to point B with little or no human intervention. The largest economic impact we sized for autonomous vehicles is the enormous benefit to consumers that may be possible by reducing accidents caused by human error by 70 to 90 percent. That could translate into hundreds of billions a year in economic value by 2025.

Predicting how quickly even the most disruptive technologies will affect productivity is difficult. When the first commercial microprocessor appeared there was no such thing as a microcomputer—marketers at Intel thought traffic signal controllers might be a leading application for their chip. Today we see that social technologies, which have changed how people interact with friends and family and have provided new ways for marketers to connect with consumers, may have a much larger impact as a way to raise productivity in organizations by improving communication, knowledge-sharing, and collaboration.

There are also lags and displacements as new technologies are adopted and their effects on productivity are felt. Over the next decade, advances in robotics may make it possible to automate assembly jobs that require more dexterity than machines have provided or are assumed to be more economical to carry out with low-cost labor. Advances in artificial intelligence, big data, and user interfaces (e.g., computers that can interpret ordinary speech) make it possible to automate many knowledge worker tasks.

More good than bad

There are clearly challenges for societies and economies as disruptive technologies take hold, but the long-term effects, we believe, will continue to be higher productivity and growth across sectors and nations. In earlier work, for example, we looked at the relationship between productivity and employment, which are generally believed to be in conflict (i.e., when productivity rises, employment falls). And clearly, in the short term this can happen as employers find that they can substitute machinery for labor—especially if other innovations in the economy do not create demand for labor in other areas. However, if you look at the data for productivity and employment for longer periods—over decades, for example—you see that productivity and job growth do rise in tandem.

This does not mean that labor-saving technologies do not cause dislocations, but they also eventually create new opportunities. For example, the development of highly flexible and adaptable robots will require skilled workers on the shop floor who can program these machines and work out new routines as requirements change. And the same types of tools that can be used to automate knowledge worker tasks such as finding information can also be used to augment the powers of knowledge workers, potentially creating new types of jobs.

Over the next decade it will become clearer how these technologies will be used to raise productivity and growth. There will be surprises along the way—when mass-produced steel became practical in the 19th century nobody could predict how it would enable the automobile industry in the 20th. And there will be societal challenges that policy makers will need to address, for example by making sure that educational systems keep up with the demands of the new technologies.

For business leaders the emergence of disruptive technologies can open up great new possibilities and can also lead to new threats—disruptive technologies have a habit of creating new competitors and undermining old business models. Incumbents will want to ensure their organizations continue to look forward and think long-term. Leaders themselves will need to know how technologies work and see to it that tech- and IT-savvy employees are included in every function and every team. Businesses and other institutions will need new skill sets and cannot assume that the talent they need will be available in the labor market.

       

Event Information

Register for the Event
Featuring keynote remarks by Jason Furman, Chairman of the Council of Economic Advisers, and Alan Greenspan, former Chairman of the Federal Reserve Board

Productivity growth in the United States slowed sharply around 2005, which has contributed to slow growth in wages and downward revisions to estimates of long run economic growth. The global economy has grown incredibly fast since 1950, with global GDP expanding six-fold and average per capita income nearly tripling. A larger workforce and increased productivity spurred this growth. However, the global workforce is expected to grow more slowly over the coming years, and peak in size around 2050. If strong economic growth is to be achieved, in both the United States and globally, productivity must increase strongly.

On Wednesday, April 8, the Initiative on Business and Public Policy hosted an event exploring these and related issues. The event featured keynote remarks by Jason Furman, Chairman of the Council of Economic Advisers, and Alan Greenspan, former Chairman of the Federal Reserve Board. James Manyika and Jaana Remes of the McKinsey Global Institute considered the potential for faster global productivity growth. Marco Annunziata of General Electric will gave his perspective, and Martin Baily looked at explanations for slow growth in the U.S. economy.

Download a McKinsey report on global productivity trends »

Video

• Opening keynote by Jason Furman
• Global growth: Can productivity save the day in an aging world?
• Closing keynote by Alan Greenspan

Audio

• Achieving strong economic growth

Transcript

• Uncorrected Transcript (.pdf)

Event Materials

• MGI_Global_growth_Full_report_February_2015pdf (3)
• 20150408_strong_economic_growth_transcript
• BAILY_slides
• GREENSPAN_slides
• REMES_MANYIKA_slides

       

Nearly 30 years ago, the economists Robert Solow and Stephen Roach caused a stir when they pointed out that, for all the billions of dollars being invested in information technology, there was no evidence of a payoff in productivity. Businesses were buying tens of millions of computers every year, and Microsoft had just gone public, netting Bill Gates his first billion. And yet, in what came to be known as the productivity paradox, national statistics showed that not only was productivity growth not accelerating; it was actually slowing down. “You can see the computer age everywhere,” quipped Solow, “but in the productivity statistics.”

Today, we seem to be at a similar historical moment with a new innovation: the much-hyped Internet of Things – the linking of machines and objects to digital networks. Sensors, tags, and other connected gadgets mean that the physical world can now be digitized, monitored, measured, and optimized. As with computers before, the possibilities seem endless, the predictions have been extravagant – and the data have yet to show a surge in productivity.

A year ago, research firm Gartner put the Internet of Things at the peak of its Hype Cycle of emerging technologies.

As more doubts about the Internet of Things productivity revolution are voiced, it is useful to recall what happened when Solow and Roach identified the original computer productivity paradox. For starters, it is important to note that business leaders largely ignored the productivity paradox, insisting that they were seeing improvements in the quality and speed of operations and decision-making. Investment in information and communications technology continued to grow, even in the absence of macroeconomic proof of its returns.

That turned out to be the right response. By the late 1990s, the economists Erik Brynjolfsson and Lorin Hitt had disproved the productivity paradox, uncovering problems in the way service-sector productivity was measured and, more important, noting that there was generally a long lag between technology investments and productivity gains.

Our own research at the time found a large jump in productivity in the late 1990s, driven largely by efficiencies made possible by earlier investments in information technology. These gains were visible in several sectors, including retail, wholesale trade, financial services, and the computer industry itself. The greatest productivity improvements were not the result of information technology on its own, but by its combination with process changes and organizational and managerial innovations.

Our latest research, The Internet of Things: Mapping the Value Beyond the Hype, indicates that a similar cycle could repeat itself. We predict that as the Internet of Things transforms factories, homes, and cities, it will yield greater economic value than even the hype suggests. By 2025, according to our estimates, the economic impact will reach $3.9-$11.1 trillion per year, equivalent to roughly 11% of world GDP. In the meantime, however, we are likely to see another productivity paradox; the gains from changes in the way businesses operate will take time to be detected at the macroeconomic level.

One major factor likely to delay the productivity payoff will be the need to achieve interoperability. Sensors on cars can deliver immediate gains by monitoring the engine, cutting maintenance costs, and extending the life of the vehicle. But even greater gains can be made by connecting the sensors to traffic monitoring systems, thereby cutting travel time for thousands of motorists, saving energy, and reducing pollution. However, this will first require auto manufacturers, transit operators, and engineers to collaborate on traffic-management technologies and protocols.

Indeed, we estimate that 40% of the potential economic value of the Internet of Things will depend on interoperability. Yet some of the basic building blocks for interoperability are still missing. Two-thirds of the things that could be connected do not use standard Internet Protocol networks.

Other barriers standing in the way of capturing the full potential of the Internet of Things include the need for privacy and security protections and long investment cycles in areas such as infrastructure, where it could take many years to retrofit legacy assets. The cybersecurity challenges are particularly vexing, as the Internet of Things increases the opportunities for attack and amplifies the consequences of any breach.

But, as in the 1980s, the biggest hurdles for achieving the full potential of the new technology will be organizational. Some of the productivity gains from the Internet of Things will result from the use of data to guide changes in processes and develop new business models. Today, little of the data being collected by the Internet of Things is being used, and it is being applied only in basic ways – detecting anomalies in the performance of machines, for example.

It could be a while before such data are routinely used to optimize processes, make predictions, or inform decision-making – the uses that lead to efficiencies and innovations. But it will happen. And, just as with the adoption of information technology, the first companies to master the Internet of Things are likely to lock in significant advantages, putting them far ahead of competitors by the time the significance of the change is obvious to everyone.

Editor's Note: This opinion originally appeared on Project Syndicate August 6, 2015.

       

November's U.S. Bureau of Labor Statistics (BLS) employment report showed continued improvement in the job market, with employers adding 211,000 workers to their payrolls and hourly pay edging up compared with its level a year ago. The pace of job growth was similar to that over the past year and somewhat slower than the pace in 2014. For the 69^th consecutive month, private-sector payrolls increased. Since the economic recovery began in the third quarter of 2009, all the nation’s employment gains have occurred as a result of expansion in private-sector payrolls. Government employment has shrunk by more than half a million workers, or about 2.5 percent. In the past twelve months, however, public payrolls edged up by 93,000.

The good news on employment gains in November was sweetened by revised estimates of job gains in the previous two months. Revisions added 8,000 to estimated job growth in September and 27,000 to job gains in October. The BLS now estimates that payrolls increased 298,000 in October, a big rebound compared with the more modest gains in August and September, when payrolls grew an average of about 150,000 a month.

Average hourly pay in November was 2.3 percent higher than its level 12 months earlier. This is a slightly faster rate of improvement compared with the gains we saw between 2010 and 2014. A tighter job market may mean that employers are now facing modestly higher pressure to boost employee compensation. The exceptionally low level of consumer price inflation means that the slow rate of nominal wage growth translates into a healthy rate of real wage improvement. The latest BLS numbers show that real weekly and hourly earnings in October were 2.4 percent above their levels one year earlier. Not only have employers added more than 2.6 million workers to their payrolls over the past year, the purchasing power of workers' earnings have been boosted by the slightly faster pace of wage gain and falling prices for oil and other commodities.

The BLS household survey also shows robust job gains last month. Employment rose 244,000 in November, following a jump of 320,000 in October. More than 270,000 adults entered the labor force in November, so the number of unemployed increased slightly, leaving the unemployment rate unchanged at 5.0 percent. In view of the low level of the jobless rate, the median duration of unemployment spells remains surprisingly long, 10.8 weeks. Between 1967 and the onset of the Great Recession, the median duration of unemployment was 10.8 weeks or higher in just seven months. Since the middle of the Great Recession, the median duration of unemployment has been 10.8 weeks or longer for 82 consecutive months. The reason, of course, is that many of the unemployed have been looking for work for a long time. More than one-quarter of the unemployed—slightly more than two million job seekers—have been jobless for at least 6 months.  That number has been dropping for more than five years, but remains high relative to our experience before the Great Recession.

If there is bad news in the latest employment report, it's the sluggish response of labor force participation to a brighter job picture. The participation rate of Americans 16 and older edged up 0.1 point in November but still remains 3.5 percentage points below its level before the Great Recession. About half the decline can be explained by an aging adult population, but a sizeable part of the decline remains unexplained. The participation rate of men and women between 25 and 54 years old is now 80.8 percent, exactly the same level it was a year ago but 2.2 points lower than it was before the Great Recession. Despite the fact that real wages are higher and job finding is now easier than was the case earlier in the recovery, the prime-age labor force participation rate remains stuck well below its level before the recession. How strong must the recovery be before prime-age adults are induced to come back into the work force? Even though the recovery is now 6 and a half years old, we still do not know.

      

Employers continued to boost payrolls in 2015, capping six straight years of job gains. It was the third year in a row in which employment gains topped 210,000 a month. In the 12 months ending in November, public and private payrolls increased 220,000 a month, or about 1.9 percent over the year. Virtually all the growth in payrolls was in the private sector, which added 212,000 jobs a month. The public sector added modestly to its payrolls last year, but the number of government employees remains more than one million (4.4 percent) below the peak level attained in 2010. 

Nearly all major industries except mining contributed to job gains in the past 12 months, though gains in manufacturing were weaker than in any year since the expansion began in 2010.  Payrolls in the mining industry tumbled more than 10 percent, hurt by a steep fall in oil and gas prices and the decline in exploration for new energy reserves. The construction industry continued to add to payrolls last year at about the same pace as in the previous two years, although the level of employment is still about 1.2 million (15 percent) below the peak level achieved in 2006.

Based on the age composition of the U.S. population, between 65,000-80,000 new jobs are needed every month to keep the unemployment rate from rising. Since late 2010, monthly payroll gains have comfortably exceeded this threshold. As a result, the jobless rate has declined steadily. In the 12 months through November 2015, the unemployment rate dropped another 0.8 percentage point, falling to 5.0 percent. The jobless rate is now within a half percentage point of its level immediately before the Great Recession. Since reaching a peak in the autumn of 2009, the unemployment rate has been cut in half.

We’ve also seen improvement in other indicators of job market distress in the past year. The number of Americans who want full-time jobs but have been forced to take part-time positions fell more than 11 percent in the 12 months through November 2015. About 9 million workers who wanted a full-time job were employed part-time in the middle of 2010. That number has fallen to about 6 million in recent months.  Similarly, the number of Americans in long spells of unemployment continues to shrink. Workers reporting they were unemployed 6 months or longer fell to 2.05 million in November, representing a considerable improvement since 2010. In that year, more than 6 million jobless workers reported they had been looking for work for at least a half a year.

The most welcome news for Americans who hold jobs is that inflation-adjusted wage levels improved last year.  Real average hourly earnings increased 1.8 percent between November 2014 and November 2015, and real weekly earnings climbed 1.6 percent.  These gains represent a considerable improvement compared with earlier years in the recovery, when real wage gains were negligible.  Nonetheless, nominal wage gains in 2015 were only slightly faster than they were in earlier years of the recovery. The reason for the startling turnaround in real wage growth is that consumer prices increased very little over the past year.  In the 12 months ending in November, the CPI edged up just 0.5 percent, almost a full percentage point more slowly than the average rate of consumer inflation in the previous three years.  The slowdown was driven by lower prices for energy and other key commodities.  (The “core” consumer inflation rate, which strips out the effects of price changes in energy and food, was 2.0 percent last year, a bit higher than the rate in the previous year.) 

Back when politicians and voters cared more about inflation than they currently do, Brookings economist Arthur Okun proposed an economic indicator called the “misery index” to summarize the dual hardships of inflation and unemployment. To measure economic misery Okun suggested adding the current unemployment rate and a measure of consumer price inflation.  In Chart 1 below I have added the civilian unemployment rate and the trailing 12-month percentage change in the CPI.  In the 11 months of 2012 through November, the misery index averaged just 5.4, its lowest level since the 1950s and well below its average levels in the 1990s (8.8) and in the period from 2000 to 2007 (7.8). When inflation is benign and has remained subdued for a long time, Americans may forget the pain they feel when price increases are frequent and large. Okun’s misery index fell to an exceptionally low level in 2015, even if a small majority of Americans continues to believe the economy is getting worse.

The good news in 2015 is that unemployment continued to fall and real wages began to rise.  The less welcome news is that key measures of labor force participation failed to improve.  For example, the labor force participation rate of Americans between 25 and 54 was the same in November 2015 as it was in November 2014. More worryingly, it was 2.1 percentage points below its level in November 2007, just before the Great Recession.  So far we have seen no rebound in participation among people in prime working ages, despite abundant signs that it’s easier to land a job. 

Low participation is the main explanation for depressed employment rates among prime-age Americans.  Participation rates are not only low in comparison to levels seen before the Great Recession, they are also now below those in other rich countries.  Charts 2 and 3 compare employment-to-population rates among 25-54 year-olds in seven OECD member countries (Canada, France, Germany, Japan, Sweden, the United Kingdom, and the United States).  The charts show employment rates separately for men and women in two different years, 2000 and 2014.  The countries are ranked, from left to right, by their employment rates in 2014. In 2000 the U.S. had the second highest male employment rate (Chart 2) and the second highest female employment rate (Chart 3) of the seven countries listed.  By 2014, the U.S. had the lowest male and female employment rates among the countries compared.  Although several nations saw declines in their prime-age male employment rate, only the U.S. also experienced a decline in its prime-age female employment rate.  The other six countries all saw increases in female employment.

The main reason for the drop in prime-age U.S. employment was the decline in prime-age participation. An enduring puzzle of the current recovery is the failure of participation rates to rebound, even in the face of steady improvement in the job market.

      

Editor’s note: The following remarks were prepared and delivered by Gary Burtless at a roundtable sponsored by the American Tax Policy Institute on January 7, 2016. Video of Burtless’ remarks are also available on the Institute’s website. Download the related slides at the right. 

We are here to discuss income inequality, alternative ways to evaluate its size and trend over time, and how it might be affected by tax policy.  My job is to introduce you to the problem of defining income and to show how the definition affects our understanding of inequality.

To eliminate suspense from the start: Nothing I am about to say undermines the popular narrative about recent inequality trends.  For the past 35 years, U.S. inequality has increased.  Inequality has increased noticeably, no matter what income definition you care to use.  A couple of things you read in the newspaper are untrue under some income definitions. For example, under a comprehensive income definition it is false to claim that all the income gains of the past 2 or 3 decades have gone to the top 1 percent, or the top 5 percent, or the top 10 percent of income recipients.  Middle- and low-income Americans have managed to achieve income gains, too, as we shall see.

Tax policy certainly affects overall inequality, but I shall leave it for Scott, David, and Tracy to take that up. Let me turn to my main job, which is to distinguish between different reasonable income measures.

The crucial thing to know is that contradictory statements can be made about some income trends because of differences in the definition of income.  In general, the most pessimistic statements about trends rely on an income definition that is restrictive in some way.  The definition may exclude important income items, items, for example, that tend to equalize or boost family incomes.  The definition may leave out adjustments to income … adjustments that tend to boost the rate of income gain for low- or middle-income recipients, but not for top-income recipients.

The narrowest income definition commonly used to evaluate income trends is Definition #1 in my slide, “pretax private, cash income.”  Columnists and news reporters are unknowingly using this income definition when they make pronouncements about the income share of the “top 1 percent.”  The data about income under this definition are almost always based on IRS income tax returns, supplemented with a bit of information from the Commerce Department’s National Income and Product Account (NIPA) data file.

The single most common income definition used to assess income trends and inequality is the Census Bureau’s “money income” definition, Definition #2 on the slide.  It is just the same as the first definition I mentioned, except this income concept also includes government cash transfer payments – Social Security, unemployment insurance, cash public assistance, Veterans’ benefits, etc.

A slightly more expansive definition (#3) also adds food stamp (or SNAP) benefits plus other government benefits that are straightforward to evaluate. Items of this kind include the implicit rent subsidy low-income families receive in publicly-subsidized housing, school lunch subsides, and means-tested home heating subsidies.

Now we come to subtractions from income. These typically reflect families’ tax obligations.  The Census Bureau makes estimates of state and federal income tax liabilities as well as payroll taxes owed by workers (though not by their employers).  Since income and payroll taxes subtract from the income available to pay for other stuff families want to buy, it seems logical to also subtract them from countable income. This is done under income Definition #4.  Some tax obligations – notably the Earned Income Credit (EIC) – are in fact subtractions from taxes owed, which would not be a problem in the case of families that still owe positive taxes to the government.  However, the EIC is refundable to taxpayers, meaning that some families have negative tax liabilities:  The government owes them money.  In this case, if you do not take taxes into account you understate low-income families’ incomes, even as you’re overstating the net incomes available to middle- and high-income families.

Now let’s get a bit more complicated.  Forget what I said about taxes, because our next income definition (#5) also ignores them.  It is an even-more-comprehensive definition of gross or pretax income.  In addition to all those cash and near-cash items I mentioned in Definition #3, Definition #5 includes imputed income items, such as: 

• The value of your employer’s premium contribution to your employee health plan;
• The value of the government’s subsidy to your public health plan – Medicare, Medicaid, state CHIP plans, etc.
• Realized taxable gains from the sale of assets; and
• Corporate income that is earned by companies in which you own a share even though it is not income that is paid directly to you.

This is the most comprehensive income definition of which I am aware that refers to gross or pre-tax income.

Finally we have Definition #6, which subtracts your direct and indirect tax payments.  The only agency that uses this income definition is principally interested in the Federal budget, so the subtractions are limited to Federal income and payroll taxes, Federal corporate income taxes, and excise taxes.

Before we go into why you should care about any of these definitions, let me mention a somewhat less important issue, namely, how we define the income-sharing group over which we estimate inequality.  The most common assessment unit for income included under Definition #1 (“Pre-tax private cash income”) is the Federal income tax filing unit.  Sometimes this unit has one person; sometimes 2 (a married couple); and sometimes more than 2, including dependents.

The Census Bureau (and, consequently, most users of Census-published statistics) mainly uses “households” as reference units, without any adjustment for variations in the size of different households.  The Bureau’s median income estimate, for example, is estimated using the annual “money income” of households, some of which contain 1 person, some contain 2, some contain 3, and so on.

Many economists and sociologists find this unsatisfactory because they think a $20,000 annual income goes a lot farther if it is supporting just one person rather than 12.  Therefore, a number of organizations—notably, the Luxembourg Income Study (LIS), the Organisation of Economic Cooperation and Development (OECD), and the Congressional Budget Office (CBO)—assume household income is equally shared within each household, but that household “needs” increase with the square root of the number of people in the household.  That is, a household containing 9 members is assumed to require 1½ times as much income to enjoy the same standard of living as a family containing 4 members.  After an adjustment is made to account for the impact of household size, these organizations then calculate inequality among persons rather than among households.

How are these alternative income definitions estimated?  Who uses them?  What do the estimates show?  I’ll only consider a two or three basic cases.

First, pretax, private, cash income. By far the most famous users of this definition are Professors Thomas Piketty and Emmanuel Saez.  Their most celebrated product is an annual estimate of the share of total U.S. income (under this restricted definition) that is received by the top 1 percent of tax filing units.

Here is their most famous chart, showing the income share of the top 1 percent going back to 1913. (I use the Piketty-Saez estimates that exclude realized capital gains in the calculation of taxpayers’ incomes.) The notable feature of the chart is the huge rise in the top income share between 1970—when it was 8 percent of all pretax private cash income—and last year—when the comparable share was 18 percent.  

I have circled one part of the line—between 1986 and 1988—to show you how sensitive their income definition is to changes in the income tax code.  In 1986 Congress passed the Tax Reform Act of 1986 (TRA86). By 1988 the reform was fully implemented.  Wealthy taxpayers noticed that TRA86 sharply reduced the payoff to holding corporate earnings inside a separately taxed corporate entity. Rich business owners or shareholders could increase their after-tax income by arranging things so their business income was taxed only once, at the individual level.  The result was that a lot of income, once earned by and held within corporations, was now passed through to the tax returns of rich individual taxpayers. These taxpayers appeared to enjoy a sudden surge in their taxable incomes between 1986 and 1988.  No one seriously believes rich people failed to get the benefits of this income before 1987.  Before 1987 the same income simply showed up on corporate rather than on individual income tax returns.

A final point:  The chart displayed in SLIDE #6 is the source of the widely believed claim that U.S. inequality is nowadays about the same as it was at the end of the Roaring 1920s, before the Great Depression.  That is close to being true – under this income definition.

Census “money income”: This income definition is very similar to the one just discussed, except that it includes cash government transfer payments.  The producer of the series is the Census Bureau, and its most famous uses are to measure trends in real median household income and the official U.S. poverty rate. Furthermore, the Census Bureau uses the income definition to compile estimates of the Gini coefficient of household income inequality and the income shares received by each one-fifth of households, ranked from lowest to highest income, and received by the top 5 percent of households.

Here is a famous graph based on the Bureau’s “median household income” series.  I have normalized the historical series using the 1999 real median income level (1999 and 2000 were the peak income years according to Census data).  Since 1999 and 2000, median income has fallen about 10 percent.  If we accept this estimate without qualification, it certainly represents bad news for living standards of the nation’s middle class. The conclusion is contradicted by other government income statistics that use a broader, more inclusive income definition, however.

And here is the Bureau’s most widely cited distributional statistic (after its “official poverty rate” estimate).  Since 1979, the Gini coefficient has increased 17 percent under this income definition. (It is worth noting, however, that the portion of the increase that occurred between 1992 and 1993 is mainly the result of methodological changes in the way the Census Bureau ascertained incomes in its 1994 income survey.)

When you hear U.S. inequality compared with that in other rich countries, the numbers are most likely based on calculations of the LIS or OECD.  Their income definition is basically “Cash and Near-cash Public and Private income minus Income and Payroll taxes owed by households.”  Under this income definition, the U.S. looks relatively very unequal and America appears to have an exceptionally high poverty rate.  U.S. inequality has been rising under this income definition, as indeed has also been the case in most other rich countries. The increase in the United States has been above average, however, helping us to retain our leadership position, both in income inequality and in relative poverty.

We turn last to the most expansive income definition:  CBO’s measure of net after-tax income.  I will use CBO’s tabulations using this income definition to shed light on some of the inequality and living standard trends implied by the narrower income definitions discussed above.

Let’s consider some potential limitations of a couple of those definitions.  The limitations do not necessarily make them flawed or uninteresting.  They do mean the narrower income measures cannot tell us some of the things that users claim they tell us.

An obvious shortcoming of the “cash pretax private income” definition is that it excludes virtually everything the government does to equalize Americans’ incomes.  Believe it or not, the Federal tax system is mildly progressive.  It claims a bigger percentage of the (declared) incomes of the rich than it does of middle-income families’ and especially the poor.  Any pretax income measure will miss that redistribution.

More seriously, it excludes all government transfer payments.  You may think the rich get a bigger percentage of their income from government handouts compared with middle class and poorer households.  That is simply wrong.  The rich get a lot less.  And the percentage of total personal income that Americans derive from government transfer payments has gone way up over the years.  In the Roaring 1920s, Americans received almost nothing in the form of government transfers. Less than 1 percent of Americans’ incomes were received as transfer payments.  By 1970—near the low point of inequality according to the Piketty-Saez measure—8.3 percent of Americans’ personal income was derived from government transfers.  Last year, the share was 17 percent. None of the increase in government transfers is reflected in Piketty and Saez’s estimates of the trend in inequality.  Inequality is nowadays lower than it was in the late 1920s, mainly because the government does more redistribution through taxes and transfers.

Both the Piketty-Saez and the Census “money income” statistics are affected by the exclusion of government- and employer-provided health benefits from the income definition. This slide contains numbers, starting in 1960, that show the share of total U.S. personal consumption consisting of personal health care consumption.  I have divided the total into two parts. The first is the share that is paid for out of our own cash incomes (the blue part at the bottom).  This includes our out-of-pocket spending for doctors’ charges, hospital fees, pharmaceutical purchases, and other provider charges as well as our out-of-pocket spending on health insurance premiums. The second is the share of our personal health consumption that is paid out of government subsidies to Medicare, Medicaid, CHIP, etc., or out of employer subsidies to employee health plans (the red part). 

As everyone knows, the share of total consumption that consists of health consumption has gone way up.  What few people recognize is that the share that is directly paid by consumers—through payments to doctors, hospitals, and household health insurance premium payments—has remained unchanged.  All of the increase in the health consumption share since 1960 has been financed through government and employer subsidies to health insurance plans. None of those government or employer contributions is counted as “income” under the Piketty-Saez and Census “money income” definitions.  You would have to be quite a cynic to claim the subsidies have brought households no living standard improvements since 1960, yet that is how they are counted under the Piketty-Saez and Census “money income” definitions.

Final slide: How much has inequality gone up under income definitions that count all income sources and subtract the Federal income, payroll, corporation, and excise taxes we pay?  CBO gives us the numbers, though unfortunately its numbers end in 2011.

Here are CBO’s estimates of real income gains between 1979 and 2011.  These numbers show that real net incomes increased in every income category, from the very bottom to the very top.  They also show that real incomes per person have increased much faster at the top—over on the right—than in the middle or at the bottom—over on the left.  Still, contrary to a common complaint that all the income gains in recent years have been received by folks at the top, the CBO numbers suggest net income gains have been nontrivial among the poor and middle class as well as among top income recipients.

Suppose we look at trends in the more recent past, say, between 2000 and 2011.  That lower panel in this slide presents a very different picture from the one implied by the Census Bureau’s “money income” statistics.  Unlike the “money income numbers” [SLIDE #9], these show that inequality has declined since 2000.  Unlike the “money income numbers” [SLIDE #8], these show that incomes of middle-income families have improved since 2000.  There are a variety of explanations for the marked contrast between the Census Bureau and CBO numbers.  But a big one is the differing income definitions the two conclusions are based on.  The more inclusive measure of income shows faster real income gains among middle-income and poorer households, and it suggests a somewhat different trend in inequality.

      

I came across an interesting chart in yesterday’s Morning Money tipsheet from Politico that struck me as a something that sounded intuitively correct but was, in fact, not. It's worth a comment on this blog, which has served as a forum for discussion of jobs numbers throughout the recovery.

Between last week’s BLS employment report and last night’s State of the Union, we’ve heard a lot about impressive job growth in 2015. For my part, I wrote on this blog last week that the 2.6 million jobs created last year makes 2015 the second best calendar-year for job gains of the current recovery.

The tipsheet’s "Chart of the Day," however, suggested that job growth in 2015 was actually lower-than-average if we adjust for the change in the size of the labor force. This is what was in the tipsheet from Politico:

---

CHART OF THE DAY: NOMINAL JOB GROWTH — Via Hamilton Place Strategies: "Adjusting jobs data to account for labor force shifts can help shed some light on voters' economic angst, even as we see good headline statistics. … Though 2015 was a good year in terms of job growth during the current recovery and had higher-than-average job growth as compared to recent recoveries, 2015 actually had lower-than-average job growth if we adjust for the change in the size of the labor force." http://bit.ly/1OnBXSm

---

I decided to look at the numbers.

The authors propose that we should "scale" reported job gains by the number of workers, which at first seems to make sense. Surely, an increase in monthly employment of 210,000 cannot mean the same thing when there are already 150 million employed people as when there are just 75 million employed people.

But this intuition is subtly wrong for a simple reason: The age structure of the population may also differ in the two situations I have just described. Suppose when there are 75 million employed people, the population of 20-to-64 year-old people is growing 300,000 every month. Suppose also when there are 150 million employed people, the population of 20-to-64 year-olds is shrinking 100,000 per month. 

Most informed observers would say that job growth of 210,000 a month is much more impressive under the latter assumptions than it is under the first set of assumptions, even though under the latter assumptions the number of employed people is twice as high as it is under the first assumptions.

BLS estimates show that in the seven years from December 2008-December 2015, the average monthly growth in the 16-to-64 year-old (noninstitutionalized) U.S. population was 85,200 per month. That is the lowest average growth rate of the working-age population going back to at least 1960. Here are the numbers:

Once we scale the monthly employment gain by the growth in the working-age population, the growth of jobs in recent years has been more impressive—not less—than suggested by the raw monthly totals. Gains in employer payrolls have far surpassed the growth in the number of working-age Americans over the past five years.

Headline writers have been impressed by recent job gains because the job gains have been impressive.

      

The pace of employment gains slowed in January from the torrid pace of the previous three months. The latest BLS jobs report shows that employers added 151,000 to their payrolls in January, well below monthly gains in October through December. In that quarter payrolls climbed almost 280,000 a month. For two reasons, the deceleration in employment gains was not a complete surprise. First, the rapid growth payrolls in the last quarter did not seem consistent with other indicators of growth in the quarter. Preliminary GDP estimates suggest that output growth slowed sharply in the fourth quarter compared with the previous two. Second, I see few indicators suggesting the pace of economic growth has picked up so far this year.

It’s worth noting that employment gains in January were far faster than needed to keep the unemployment rate from increasing. In fact, if payrolls continue to grow at January’s pace throughout the year, we should expect the unemployment rate to continue falling. As usual in the current expansion, private employers accounted for all of January’s employment gains. Government payrolls shrank slightly. The number of public employees is about the same as it was last July. Over the same period, private employers added about 213,000 workers a month to their payrolls. In January employment gains slowed in construction and in business and professional industries. Payrolls shrank in mining. Since mining payrolls reached a peak in September 2014, they have fallen 16 percent. Manufacturing payrolls rose slightly in January, but payroll gains have been very slow over the past year. Employment in the temporary help industry contracted in January. The industry has seen no net change in payrolls since October.

Average hourly pay in private companies edged up in January. The average nominal wage was 2.5 percent higher than its level 12 months earlier. This is a faster rate of improvement compared with what we saw earlier in the recovery, when annual pay gains averaged about 2.0 percent a year. The modest acceleration in nominal pay gains has occurred against the backdrop of slowing consumer price inflation. The combination has given workers real wage gains approaching 2.0 percent over the past year.

The BLS household survey showed a small drop in unemployment. The jobless rate fell to 4.9 percent, just 0.3 points above its average level in 2007, the last year before the Great Recession. The drop in unemployment was the result of a rise in the number of survey respondents who were employed. The labor force participation rate increased in January, and it has increased 0.3 points since October.

This rebound in labor force participation is modest compared with the drop that occurred between 2008 and 2015. From 2007 to January 2016 the adult participation rate fell 3.4 percentage points. Roughly half the drop is traceable to population aging, but the other half is due to factors related to the deep slump or to long-term factors that have affected Americans’ willingness to enter or remain in the workforce. If we assume all of the drop was due to factors that have temporarily discouraged jobless adults from seeking work, then we can recalculate the unemployment rate to reflect the rate we would see if all of these discouraged workers were reclassified as unemployed. That calculation suggests the current unemployment rate would be about 7.4 percent rather than 4.9 percent.

It is of course unlikely all the adults who’ve dropped out the labor force would stream back in if job finding got easier and real wages continued to rise. It is encouraging to see, however, that participation is now climbing after a long period of decline. Over the past four months, the labor force participation rate of 25-54 year-olds increased 0.5 percentage points.

      

      

Social Security is the most popular legacy of Franklin Roosevelt's New Deal. Last year almost 60 million Americans received benefits from the program. Payments amounted to over $875 billion, nearly a quarter of all federal spending.  For more than two decades, most discussion of Social Security, at least in Washington, has centered on its funding shortfall. Contributions to the program are not high enough to pay for all benefits scheduled under current law. The Social Security Trust Fund is expected to be depleted around 2030. If Congress does not address the funding problem before reserves are exhausted, monthly payments will have to be cut about one-fifth.

Despite the projected shortfall, Democrats in Congress have begun to argue that Social Security benefits should be expanded rather than cut.  Senators Bernie Sanders and Brian Schatz have offered proposals to boost monthly pensions while at the same time shoring up Social Security finances through tax hikes on high-income Americans. 

That Democratic voters and lawmakers embrace these ideas is not surprising. But opinion polling suggests such reforms also enjoy broad support among self-identified independents and Republicans. For example, 57 percent of Republicans (versus 71 percent of Democrats) favor increasing cost-of-living adjustments in the benefit formula. Forty-eight percent of Republicans (versus 67 percent of Democrats) favor boosting the minimum benefit available to low-wage workers who have contributed for many years to the program.  Seventy-four percent of Republicans (versus 88 percent of Democrats) favor raising taxes in order to protect benefits. These polling numbers were obtained in 2013, but more recent polls show similar opinions. Even if debates among Washington insiders and GOP lawmakers focus on how to trim benefits in order to keep Social Security solvent, poll results suggest Senator Sanders holds views closer to those of the typical voter.

One question for both voters and policymakers is whether the aged population is really the most deserving target for additional government spending.  Much of the discussion of voter disaffection in the current election cycle has focused on the stagnation of middle class incomes and the rise in inequality.  While these represent major problems for families headed by a working-age person, they have not been notably troublesome for the nation’s elderly.  The incomes of the elderly, unlike those of the nonelderly, have increased steadily over the past three or four decades.  For low- and middle-income retirees, incomes have clearly improved. The same cannot be said for the incomes of low- and middle-income working-age families. Income inequality among the elderly has increased, to be sure, but much more slowly than among working-age families.

In new research with my colleagues Barry Bosworth and Kan Zhang, I have examined trends in real incomes and inequality among the nation’s elderly and compared them with the same trends in working-age families. We show that inequality has increased among both the elderly and nonelderly, but it has increased much faster among families headed by prime-age and younger adults than among families headed by someone past age 62.  More to the point, real money incomes have increased much faster among middle- and low-income aged families compared with middle- and low-income working-age families. 

Our estimates of the annual rate of change in real money income are displayed in the chart below. The changes are estimated over the period from 1979 to 2012 based on data reported in the Census Bureau’s annual income survey. The top panel shows changes in families with a head who is less than 62. The bottom panel shows changes in families with a head older than 62.  Each bar shows the annual rate of change in real income at the indicated position of the income distribution, either for nonaged families (in the top panel) or for aged families (in the bottom panel).  At the top of the two income distributions—that is, at the 98^th income percentile—real income gains are virtually the same in the two groups.  Further down the income ladder, the income gains differ noticeably, with bigger differences the further down we go.  Middle- and low-income working-age families have clearly fared much worse than families with an equivalent position in the old-age income distribution.

Estimates of income growth based solely on pre-tax cash incomes, such as the ones in the chart, almost certainly understate the improvement families have seen in their living standards, as I have argued elsewhere (here and here).  However, the understatement is bigger in the case of elderly and low-income Americans than it is for the nonelderly and affluent.  If we adjust family incomes to reflect the taxes families owe and the monetary value of their noncash benefits, the relative improvement in the standard of living of older Americans is even greater than is shown in the chart. Under almost any plausible income definition, the elderly have fared better than the nonelderly, especially at the bottom of the income distribution.

The income statistics do not prove the policy reforms urged by Congressional Democrats are unneeded or undesirable. Their proposals spring from an accurate reading of a long-term trend toward less pension coverage — ironically, a trend that has mainly affected working-age adults.  Whereas workers in the 1950s through the 1970s enjoyed continuous improvement in their access to employer-provided retirement benefits, the improvement ceased after 1980. Since that time, private-sector workers have seen reductions in the coverage and generosity of their employer-sponsored pensions. If the private sector voluntarily provides less retirement protection, it does not seem unreasonable to expect the government to provide more.

A crucial reason the nation’s elderly population fared better compared with the nonelderly after 1980 is that Social Security and Medicare provided them government protection that was far more generous (and more costly to taxpayers) than the protection available to working-age adults and their youngsters. The gap was especially glaring in the case of families headed by low-wage breadwinners, who have suffered sizeable reductions in pay and employment opportunities. In the years since 1980, their losses have been only modestly compensated through changes in the tax code and expansions of public health insurance.

Changes in the labor market make it important to protect future retirement benefits provided through Social Security. The same labor market developments make it even more urgent to expand the employment opportunities and improve the protections and work supports offered to working-age breadwinners.  In 2016, the weakening of future income protection for the aged is mostly theoretical. In contrast, the sinking fortunes of less skilled working-age adults are anything but theoretical. They are plain to anyone who can read Census and Bureau of Labor Statistics reports. If taxpayers can identify additional resources to pay for major new initiatives, my vote is for programs that improve the prospects of struggling wage earners. The equity arguments for such an initiative seem to me more persuasive than the case for an across-the-board benefit hike targeted on retirees.

---

Editor's note: This piece originally appeared in Real Clear Markets. 

      

Researchers have long known that the rich live longer than the poor. Evidence now suggests that the life expectancy gap is increasing, at least here the United States, which raises troubling questions about the fairness of current efforts to protect Social Security.

There's nothing particularly mysterious about the life expectancy gap. People in ill health, who are at risk of dying relatively young, face limits on the kind and amount of work they can do. By contrast, the rich can afford to live in better and safer neighborhoods, can eat more nutritious diets and can obtain access to first-rate healthcare. People who have higher incomes, moreover, tend to have more schooling, which means they may also have better information about the benefits of exercise and good diet.

Although none of the above should come as a surprise, it's still disturbing that, just as income inequality is growing, so is life-span inequality. Over the last three decades, Americans with a high perch in the income distribution have enjoyed outsized gains.

Using two large-scale surveys, my Brookings colleagues and I calculated the average mid-career earnings of each interviewed family; then we estimated the statistical relationship between respondents' age at death and their incomes when they were in their 40s. We found a startling spreading out of mortality differences between older people at the top and bottom of the income distribution.

For example, we estimated that a woman who turned 50 in 1970 and whose mid-career income placed her in the bottom one-tenth of earners had a life expectancy of about 80.4. A woman born in the same year but with income in the top tenth of earners had a life expectancy of 84.1. The gap in life expectancy was about 3½ years. For women who reached age 50 two decades later, in 1990, we found no improvement at all in the life expectancy of low earners. Among women in the top tenth of earners, however, life expectancy rose 6.4 years, from 84.1 to 90.5. In those two decades, the gap in life expectancy between women in the bottom tenth and the top tenth of earners increased from a little over 3½ years to more than 10 years.

Our findings for men were similar. The gap in life expectancy between men in the bottom tenth and top tenth of the income distribution increased from 5 years to 12 years over the same two decades.

Rising longevity inequality has important implications for reforming Social Security. Currently, the program takes in too little money to pay for all benefits promised after 2030. A common proposal to eliminate the funding shortfall is to increase the full retirement age, currently 66. Increasing the age for full benefits by one year has the effect of lowering workers' monthly checks by 6% to 7.5%, depending on the age when a worker first claims a pension.

For affluent workers, any benefit cut will be partially offset by gains in life expectancy. Additional years of life after age 65 increase the number years these workers collect pensions. Workers at the bottom of the wage distribution, however, are not living much longer, so the percentage cut in their lifetime pensions will be about the same as the percentage reduction in their monthly benefit check.

Our results and other researchers' findings suggest that low-income workers have not shared in the improvements in life expectancy that have contributed to Social Security's funding problem.

It therefore seems unfair to preserve Social Security by cutting future benefits across the board. Any reform in the program to keep it affordable should make special provision to protect the benefits of low-wage workers.

Editor's note: This piece originally appeared in The Los Angeles Times.