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

       

       

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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

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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

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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.

       

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.

       

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.

       

       

Twenty-five years ago, in March 1991, shaken by the fall of the Berlin Wall and the rise of nationalist-separatist movements in the Soviet Baltic and Caucasus republics, Mikhail Gorbachev held a historic referendum. He proposed the creation of a new union treaty to save the USSR. The gambit failed. Although a majority of the Soviet population voted yes, some key republics refused to participate. And so began the dissolution of the USSR, the event that current Russian President Vladimir Putin has called the “greatest geopolitical catastrophe” of the 20th century.

Today, in the wake of the referendum on leaving the European Union, British Prime Minister David Cameron seems to have put the United Kingdom on a similar, potentially catastrophic, path. Like the fall of the wall and the collapse of the Soviet Union, the fallout from Brexit could have momentous consequences. The U.K. is of course not the USSR, but there are historic links between Britain and Russia and structural parallels that are worth bearing in mind as the U.K. and the EU work out their divorce, and British leaders figure out what to do next, domestically and internationally.

A quick Russian history recap

The British and Russian empires formed at around the same time and frequently interacted. Queen Elizabeth I was pen pals with Ivan the Terrible. The union of the Scottish and English parliaments in 1707 that set the United Kingdom on its imperial trajectory coincided with the 1709 battle of Poltava, in which Peter the Great ousted the Swedes from the lands of modern Ukraine and began the consolidation of the Russian empire. The Russian imperial and British royal families intermarried, even as they jockeyed for influence in Central Asia and Afghanistan in the 19th century. The last Czar and his wife were respectively a distant cousin and granddaughter of British Queen Victoria. The Irish Easter Uprising and the Russian Revolution were both sparked by problems at home, imperial overstretch, and the shock of the World War I. 

Like the fall of the wall and the collapse of the Soviet Union, the fallout from Brexit could have momentous consequences.

Since the end of the Cold War, the U.K. and Russia have both had difficulty figuring out their post-imperial identities and roles. The U.K. in 2016 looks structurally a lot like the USSR in 1991, and England’s current identity crisis is reminiscent of Russia’s in the 1990s. After Gorbachev’s referendum failed to shore up the union, the Soviet Union was undermined by an attempted coup (in August 1991) and then dismantled by its national elites. In early December 1991, Boris Yeltsin, the flamboyant head of the Russian Federation, holed up in a hut deep in the Belarusian woods with the leaders of Ukraine and Belarus and conspired to replace the USSR with a new Commonwealth of Independent States (CIS). With Gorbachev and the Soviet Union gone by the end of December, the hangover set in. Boris Yeltsin was the first to rue the consequences of his actions. The CIS never gained traction as the basis for a new union led by Russia. 

The Ukrainians, Belarussians, and everyone else gained new states and new identities and used the CIS as a mechanism for divorce. Russians lost an empire, their geopolitical anchor, and their identity as the first among equals in the USSR. The Russian Federation was a rump state. And although ethnic Russians were 80 percent of the population, the forces of disintegration continued. Tatars, Chechens, and other indigenous peoples of the Russian Federation, with their own histories, seized or agitated for independence. Ethnic Russians were “left behind” in other republics. Historic territories were lost. Instead of presiding over a period of Russian independence, Boris Yeltsin muddled through a decade of economic collapse and political humiliation.

Separating the U.K. from Europe...could be as wrenching as pulling apart the USSR.

Is Britain laying the same trap?

Another Boris, the U.K.’s Boris Johnson, the former mayor of London and main political opponent of David Cameron, risks doing the same if he becomes U.K. prime minister in the next few months. Separating the U.K. from Europe institutionally, politically, and economically could be as wrenching as pulling apart the USSR. People will be left behind—EU citizens in the U.K., U.K. citizens in the EU––and will have to make hard choices about who they are, and where they want to live and work. The British pound has already plummeted. The prognoses for short- to medium-term economic dislocation have ranged from gloomy to dire. The U.K is a multi-ethnic state, with degrees of devolved power to its constituent parts, and deep political divides at the elite and popular levels. Scotland and Northern Ireland, along with Gibraltar (a contested territory with Spain), clearly voted to stay in the European Union. The prospect of a new Scottish referendum on independence, questions about the fate of the Irish peace process, and the format for continuing Gibraltar’s relationship with Spain, will all complicate the EU-U.K. divorce proceedings. 

Like Russia and the Russians, England and the English are in the throes of an identity crisis.

Like Russia and the Russians, England and the English are in the throes of an identity crisis. England is not ethnically homogeneous. In addition to hundreds of thousands of Irish citizens living in England, there are many more English people with Irish as well as Scottish ancestry––David Cameron’s name gives away his Scottish antecedents––as well as those with origins in the colonies of the old British empire. And there are the EU citizens who have drawn so much ire in the Brexit debate. 

As in the case of the USSR and Russia where all roads led (and still lead) to Moscow, London dominates the U.K.’s population, politics, and economics. London is a global city that is as much a magnet for international migration as a center of finance and business. London voted to remain in Europe. The rest of England, London’s far flung, neglected, and resentful hinterland, voted to leave the EU—and perhaps also to leave London. At the end of the divorce process, without careful attention from politicians in London, England could find itself the rump successor state to the United Kingdom. If so, another great imperial state will have consigned itself to the “dust heap of history” by tying its future to a referendum. 

       

       

       

       

       

       

       

       

       

       

       

       

       

Published version of the CSED October 2007 Working Paper

ABSTRACT

Background

In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics. They do not endogenously engage, for example, in social distancing based on fear. Yet, adaptive behavior is well-documented in true epidemics. We explore the effect of including such behavior in models of epidemic dynamics.

Methodology/Principal Findings

Using both nonlinear dynamical systems and agent-based computation, we model two interacting contagion processes: one of disease and one of fear of the disease. Individuals can “contract” fear through contact with individuals who are infected with the disease (the sick), infected with fear only (the scared), and infected with both fear and disease (the sick and scared). Scared individuals–whether sick or not–may remove themselves from circulation with some probability, which affects the contact dynamic, and thus the disease epidemic proper. If we allow individuals to recover from fear and return to circulation, the coupled dynamics become quite rich, and can include multiple waves of infection. We also study flight as a behavioral response.

Conclusions/Significance

In a spatially extended setting, even relatively small levels of fear-inspired flight can have a dramatic impact on spatio-temporal epidemic dynamics. Self-isolation and spatial flight are only two of many possible actions that fear-infected individuals may take. Our main point is that behavioral adaptation of some sort must be considered.”

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Scholars from the Brookings Institution and the American Enterprise Institute are collaborating to promote transparency in redistricting. In January 2010, an advisory board of experts and representatives of good government groups was convened in order to articulate principles for transparent redistricting and to identify barriers to the public and communities who wish to create redistricting plans. This document summarizes the principles for transparency in redistricting that were identified during that meeting.

Benefits of a Transparent, Participative Redistricting Process

The drawing of electoral districts is among the most easily manipulated and least transparent systems in democratic governance. All too often, redistricting authorities maintain their monopoly by imposing high barriers to transparency and public participation. Increasing transparency and public participation can be a powerful counterbalance by providing the public with information similar to that which is typically only available to official decision makers, which can lead to different outcomes and better representation.

Increasing transparency can empower the public to shape the representation for their communities, promote public commentary and discussion about redistricting, inform legislators and redistricting authorities which district configurations their constituents and the public support, and educate the public about the electoral process.  

Fostering public participation can enable the public to identify their neighborhoods and communities, promote the creation of alternative maps, and facilitate an exploration of a wide range of representational possibilities. The existence of publicly-drawn maps can provide a measuring stick against which an official plan can be compared, and promote the creation of a “market” for plans that support political fairness and community representational goals.

Transparency Principles

All redistricting plans should include sufficient information so the public can verify, reproduce, and evaluate a plan. Transparency thus requires that:

• Redistricting plans must be available in non-proprietary formats.
• Redistricting plans must be available in a format allowing them to be easily read and analyzed with commonly-used geographic information software.
• The criteria used as a basis for creating plans and individual districts must be clearly documented.

Creating and evaluating redistricting plans and community boundaries requires access to demographic, geographic, community, and electoral data. Transparency thus requires that:

• All data necessary to create legal redistricting plans and define community boundaries must be publicly available, under a license allowing reuse of these data for non-commercial purposes.
• All data must be accompanied by clear documentation stating the original source, the chain of ownership (provenance), and all modifications made to it.

Software systems used to generate or analyze redistricting plans can be complex, impossible to reproduce, or impossible to correctly understand without documentation. Transparency thus requires that:

• Software used to automatically create or improve redistricting plans must be either open-source or provide documentation sufficient for the public to replicate the results using independent software.
• Software used to generate reports that analyze redistricting plans must be accompanied by documentation of data, methods, and procedures sufficient for the reports to be verified by the public.

Services offered to the public to create or evaluate redistricting plans and community boundaries are often opaque and subject to misinterpretation unless adequately documented. Transparency thus requires that:

• Software necessary to replicate the creation or analysis of redistricting plans and community boundaries produced by the service must be publicly available.
• The service must provide the public with the ability to make available all published redistricting plans and community boundaries in non-proprietary formats that are easily read and analyzed with commonly-used geographic information software.
• Services must provide documentation of any organizations providing significant contributions to their operation.

Promoting Public Participation

New technologies provide opportunities to broaden public participation in the redistricting process. These technologies should aim to realize the potential benefits described and be consistent with the articulated transparency principles.

Redistricting is a legally and technically complex process. District creation and analysis software can encourage broad participation by: being widely accessible and easy to use; providing mapping and evaluating tools that help the public to create legal redistricting plans, as well as maps identifying local communities; be accompanied by training materials to assist the public to successfully create and evaluate legal redistricting plans and define community boundaries; have publication capabilities that allow the public to examine maps in situations where there is no access to the software; and promoting social networking and allow the public to compare, exchange and comment on both official and community-produced maps.

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Official Endorsement from Organizations – Americans for Redistricting Reform, Brennan Center for Justice at New York University, Campaign Legal Center, Center for Governmental Studies, Center for Voting and Democracy, Common Cause, Demos, and the League of Women Voters of the United States.

Attending board members – Nancy Bekavac, Director, Scientists and Engineers for America; Derek Cressman, Western Regional Director of State Operations, Common Cause; Anthony Fairfax, President, Census Channel; Representative Mike Fortner (R), Illinois General Assembly; Karin Mac Donald, Director, Statewide Database, Berkeley Law, University of California, Berkeley; Leah Rush, Executive Director, Midwest Democracy Network; Mary Wilson, President, League of Women Voters.

Editors – Micah Altman, Harvard University and the Brookings Institution; Thomas E. Mann, Brookings Institution; Michael P. McDonald, George Mason University and the Brookings Institution; Norman J. Ornstein, American Enterprise Institute.

This project is funded by a grant from the Sloan Foundation to the Brookings Institution and the American Enterprise Institute.

       

Every 10 years — unfortunately, sometimes more frequently — legislative district lines are redrawn to balance population for demographic changes revealed by the census. What goes on is much more than a simple technical adjustment of boundaries, with ramifications that largely escape public notice.

Politicians often use redistricting as an opportunity to cut unfavorable constituents and potential challengers out of their districts. Barack Obama, for example, learned the rough and tumble of redistricting politics when Rep. Bobby Rush (D-Ill.) carved Obama's Chicago home out of Rush's congressional district after losing a 2000 primary challenge to Obama, then a state senator.

Incumbents can also use redistricting to move favorable constituents into their districts. Obama himself used the state legislative redistricting to extend his predominantly African American district north into a wealthy area of Illinois known as the Gold Coast. This new constituency allowed Obama to hone an effective biracial campaigning style that served him well when he ran for the U.S. Senate and the presidency.

Critically, these decisions are made with little or no public input or accountability. While Arizona and California are among the few states that give the public a chance to see and participate in how the boundaries are set, by using open redistricting commissions, most states gerrymander legislative lines behind closed doors. Figures from both major parties tilt the electoral playing field so much that one party is essentially assured of winning a given district, controlling the state legislature or winning the most seats in the state's congressional delegation. In other words, the democratic process is subverted. In this system, politicians select voters rather than voters electing politicians.

A 2006 Pew survey found that 70 percent of registered voters had no opinion about congressional redistricting. Among the few that expressed an opinion, some mistook the question to be about school districts rather than congressional districts.

For many reasons it has been hard to fault the public. An immense amount of population data must be sifted and then assembled, much like a giant jigsaw puzzle, to ensure that districts satisfy complex federal requirements relating to equal population and the Voting Rights Act, and varying state requirements that may include compactness and respect for existing political boundaries or communities. And access to these data and the software necessary to assemble and analyze them have long been out of public reach.

In the previous round of redistricting, according to a 2002 survey of authorities we conducted with our colleague Karin Mac Donald, most states did not provide any tools, facilities, dedicated assistance or software to support the public in developing redistricting plans. Many states failed to provide even minimal transparency by making data available, providing information about their plans online or accepting publicly submitted plans. Many redistricting authorities have not made firm plans to support transparency or public participation in the current round of redistricting.

In the coming year, however, technological advancements will enable anyone with a Web browser and an interest in how he or she is represented to draw district maps of his or her community and state that meet the same requirements as official submissions. Under the direction of scholars at the Brookings Institution and the American Enterprise Institute, and with consultation from an array of experts in redistricting issues, we have developed a set of principles for transparency and public participation. These principles have been endorsed by an array of stakeholders, including Common Cause and the League of Women Voters of the United States.

Americans will be able to participate directly in their democracy by offering plans to be compared with the politician-drawn maps. The public and even the courts will no longer have to accept that whatever is devised by politicians in the backroom.

The Wizard of Oz appeared powerful because he hid behind a curtain -- until it was pulled back. The time has come to pull back the curtain on redistricting. A good place to start is by passing Rep. John Tanner's Redistricting Transparency Act, which has 38 co-sponsors from both parties. If Congress will not act, state governments can follow the lead of the few states that provide for meaningful transparency and public participation. Failure to provide for transparency and public participation should be recognized for what it is: an obviously self-serving act, placing the interests of politicians above the public interest.

       

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The drawing of legislative district boundaries is among the most self-interested and least transparent systems in American democratic governance. All too often, formal redistricting authorities maintain their control by imposing high barriers to transparency and to public participation in the process. Reform advocates believe that opening that process to the public could lead to different outcomes and better representation.

On January 20, Brookings hosted a briefing to review how redistricting in the 50 states will unfold in the months ahead and present a number of state-based initiatives designed to increase transparency and public participation in redistricting. Brookings Nonresident Senior Fellows Micah Altman and Michael McDonald unveiled open source mapping software which enables users to create and submit their own plans, based on current census and historical election data, to redistricting authorities and to disseminate them widely. Such alternative public maps could offer viable input to the formal redistricting process.

After each presentation, participants took audience questions.

Learn more about Michael McDonald's Public Mapping Project »

Video

• Injecting Transparency into Redistricting
• GOP Could Re-Draw 145 Districts
• Towards a New Political Culture
• Coalitions Pushing for Greater Transparency
• The Public Mapping Project

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• Toward Public Participation in Redistricting
• Toward Public Participation in Redistricting
• Toward Public Participation in Redistricting

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• Download Micah Altman's and Michael McDonald's Presentation (.pdf)
• Download Tim Storey's Presentation (.pdf)
• Download Clare Dyer's Presentation (.pdf)
• Download the Redistricting Authority in the States Factsheet (.pdf)
• Download Micah Altman's and Michael McDonald's Report (.pdf)
• Download the District Builder Summary (.pdf)

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Now that the 2010 Census is concluded, states will begin the process of reapportionment—re-drawing voting district lines to account for population shifts. Nonresident Senior Fellow Michael McDonald says redistricting has been fraught with controversy and corruption since the nation’s early days, when the first “gerrymandered” district was drawn. Two states—Arizona and California—have instituted redistricting commissions intended to insulate the process from political shenanigans, but politicians everywhere will continue to work the system to gain electoral advantage and the best chance of re-election for themselves and their parties.

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• States Attempt to Reform Redistricting

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Full video archive of this event is also available via C-SPAN here.

The drawing of legislative district boundaries is arguably among the most self-interested and least transparent systems in American democracy. Every ten years redistricting authorities, usually state legislatures, redraw congressional and legislative lines in accordance with Census reapportionment and population shifts within states. Most state redistricting authorities are in the midst of their redistricting process, while others have already finished redrawing their state and congressional boundaries. A number of initiatives—from public mapping competitions to independent shadow commissions—have been launched to open up the process to the public during this round of redrawing district lines.

On July 18, Brookings hosted a panel of experts to review the results coming in from the states and discuss how the rest of the process is likely to unfold. Panelists focused on evidence of partisan or bipartisan gerrymandering, the outcome of transparency and public mapping initiatives, and minority redistricting.

After the panel discussion, participants took audience questions.

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Editors Note: This post is an extended version of a previous post.

Cozzens, Susan and Dhanaraj Thakur (Eds). 2014. Innovation and Inequality: Emerging technologies in an unequal world. Northampton, Massachusetts: Edward Elgar.

Historically, the debate on innovation has focused on the determinants of the pace of innovation—on the premise that innovation is the driver of long-term economic growth. Analysts and policymakers have taken less interest on how innovation-based growth affects income distribution. Less attention even has received the question of how innovation affects other forms of inequality such as economic opportunity, social mobility, access to education, healthcare, and legal representation, or inequalities in exposure to insalubrious environments, be these physical (through exposure to polluted air, water, food or harmful work conditions) or social (neighborhoods ridden with violence and crime). The relation between innovation, equal political representation and the right for people to have a say in the collective decisions that affect their lives can also be added to the list of neglect.

But neglect has not been universal. A small but growing group of analysts have been working for at least three decades to produce a more careful picture of the relationship between innovation and the economy. A distinguished vanguard of this group has recently published a collection of case studies that illuminates our understanding of innovation and inequality—which is the title of the book. The book is edited by Susan Cozzens and Dhanaraj Thakur. Cozzens is a professor in the School of Public Policy and Vice Provost of Academic Affairs at Georgia Tech. She has studied innovation and inequality long before inequality was a hot topic and led the group that collaborated on this book. Thakur is a faculty member of the school College of Public Service and Urban Affairs at Tennessee State University (while writing the book he taught at the University of West Indies in Jamaica). He is an original and sensible voice in the study of social dimensions of communication technologies.

We’d like to highlight here three aspects of the book: the research design, the empirical focus, and the conceptual framework developed from the case studies in the book.

Edited volumes are all too often a collection of disparate papers, but not in this case. This book is patently the product of a research design that probes the evolution of a set of technologies across a wide variety of national settings and, at the same time, it examines the different reactions to new technologies within specific countries. The second part of the book devotes five chapters to study five emerging technologies—recombinant insulin, genetically modified corn, mobile phones, open-source software, and tissue culture—observing the contrasts and similarities of their evolution in different national environments. In turn, part three considers the experience of eight countries, four of high income—Canada, Germany, Malta, and the U.S.—and four of medium or low income—Argentina, Costa Rica, Jamaica, and Mozambique. The stories in part three tell how these countries assimilated these diverse technologies into to their economies and policy environments.

The second aspect to highlight is the deliberate choice of elements for empirical focus. First, the object of inquiry is not all of technology but a discreet set of emerging technologies gaining a specificity that would otherwise be negated if they were to handle the unwieldy concept of “technology” broadly construed. At the same time, this choice reveals the policy orientation of the book because these new entrants have just started to shape the socio-technical spaces they inhabit while the spaces of older technologies have likely ossified. Second, the study offers ample variance in terms of jurisdictions under study, i.e. countries of all income levels; a decision that makes at the same time theory construction more difficult and the test of general premises more robust.[i] We can add that the book avoids sweeping generalizations. Third, they focus on technological projects and their champions, a choice that increases the rigor of the empirical analysis. This choice, naturally, narrows the space of generality but the lessons are more precise and the conjectures are presented with according modesty. The combination of a solid design and clear empirical focus allow the reader to obtain a sense of general insight from the cases taken together that could not be derived from any individual case standing alone.

Economic and technology historians have tackled the effects of technological advancement, from the steam engine to the Internet, but those lessons are not easily applicable to the present because emerging technologies intimate at a different kind of reconfiguration of economic and social structures. It is still too early to know the long-term effects of new technologies like genetically modified crops or mobile phone cash-transfers, but this book does a good job providing useful concepts that begin to form an analytical framework. In addition, the mix of country case studies subverts the disciplinary separation between the economics of innovation (devoted mostly to high-income countries) and development studies (interested in middle and low income economies). As a consequence of these selections, the reader can draw lessons that are likely to apply to technologies and countries other than the ones discussed in this book.

The third aspect we would like to underscore in this review is the conceptual framework. Cozzens, Thakur and their colleagues have done a service to anyone interested in pursuing the empirical and theoretical analysis of innovation and inequality.

For these authors, income distribution is only one part of the puzzle. They observe that inequalities are also part of social, ethnic, and gender cleavages in society. Frances Stewart, from Oxford University, introduced the notion of horizontal inequalities or inequalities at the social group level (for instance, across ethnic groups or genders). She developed the concept to contrast vertical inequalities or inequalities operating at the individual level (such as household income or wealth). The authors of this book borrow Stewart’s concept and pay attention to horizontal inequalities in the technologies they examine and observe that new technologies enter marketplaces that are already configured under historical forms of exclusion. A dramatic example is the lack of access to recombinant insulin in the U.S., because it is expensive and minorities are less likely to have health insurance (see Table 3.1 in p. 80).[ii] Another example is how innovation opens opportunities for entrepreneurs but closes them for women in cultures that systematically exclude women from entrepreneurial activities.

Another key concept is that of complementary assets. A poignant example is the failure of recombinant insulin to reach poor patients in Mozambique who are sent home with old medicine even though insulin is subsidized by the government. The reason why doctors deny the poor the new treatment is that they don’t have the literacy and household resources (e.g. a refrigerator, a clock) necessary to preserve the shots, inject themselves periodically, and read sugar blood levels. Technologies aimed at fighting poverty require complementary assets to be already in place and in the absence of them, they fail to mitigate suffering and ultimately ameliorate inequality. Another illustration of the importance of complementary assets is given by the case of Open Source Software. This technology has a nominal price of zero; however, only individuals who have computers and the time, disposition, and resources to learn how to use open source operative systems benefit. Likewise, companies without the internal resources to adapt open software will not adopt it and remain economically tied to proprietary software.

These observations lead to two critical concepts elaborated in the book: distributional boundaries and the inequalities across technological transitions. Distributional boundaries refer to the reach of the benefits of new technologies, boundaries that could be geographic (as in urban/suburban or center/periphery) or across social cleavages or incomes levels. Standard models of technological diffusion assume the entire population will gradually adopt a new technology, but in reality the authors observe several factors intervene in limiting the scope of diffusion to certain groups. The most insidious factors are monopolies that exercise sufficient control over markets to levy high prices. In these markets, the price becomes an exclusionary barrier to diffusion. This is quite evident in the case of mobile phones (see table 5.1, p. 128) where monopolies (or oligopolies) have market power to create and maintain a distributional boundary between post-pay and high-quality for middle and high income clients and pre-pay and low-quality for poor customers. This boundary renders pre-pay plans doubly regressive because the per-minute rates are higher than post-pay and phone expenses represent a far larger percentage in poor people’s income. Another example of exclusion happens in GMOs because in some countries subsistence farmers cannot afford the prices for engineering seeds; a disadvantage that compounds to their cost and health problems as they have to use more and stronger pesticides.

A technological transition, as used here, is an inflection point in the adoption of a technology that re-shapes its distributional boundaries. When smart phones were introduced, a new market for second-hand or hand-down phones was created in Maputo; people who could not access the top technology get stuck with a sub-par system. By looking at tissue culture they find that “whether it provides benefits to small farmers as well as large ones depends crucially on public interventions in the lower-income countries in our study” (p. 190). In fact, farmers in Costa Rica enjoy much better protections compare to those in Jamaica and Mozambique because the governmental program created to support banana tissue culture was designed and implemented as an extension program aimed at disseminating know-how among small-farmers and not exclusively to large multinational-owned farms. When introducing the same technology, because of this different policy environment, the distributional boundaries were made much more extensive in Costa Rica.

This is a book devoted to present the complexity of the innovation-inequality link. The authors are generous in their descriptions, punctilious in the analysis of their case studies, and cautious and measured in their conclusions. Readers who seek an overarching theory of inequality, a simple story, or a test of causality, are bound to be disappointed. But those readers may find the highest reward from carefully reading all the case studies presented in this book, not only because of the edifying richness of the detail herein but also because they will be invited to rethink the proper way to understand and address the problem of inequality.[iii]
 

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So we’ve almost reached the end of the year 2015, which could go down in the history of global sustainable development efforts as one of the more significant years, with the trifecta of the approval of the Sustainable Development Goals (SDGs), the agreement on the Addis Agenda on Financing for Development (FfD) and the (shortly to be completed) Paris COP21 Climate Summit. Yet, all will depend on how the agreements with their ambitious targets are implemented on the ground.

Effective implementation will require a theory of change—a way to think about how we are to get from “here” in 2015 to “there” in 2030. The key problem is what has very appropriately been called by some “the missing middle,” i.e., the gap between the top-down global targets on the one hand and the bottom-up development initiatives, projects, and programs that are supported by governments, aid agencies, foundations, and social entrepreneurs.

One way to begin to close this gap is to aim for scaled-up global efforts in specific areas, as is pledged in the Addis Agenda, including efforts to fight global hunger and malnutrition, international tax cooperation and international cooperation to strengthen capacities of municipalities and other local authorities, investments and international coopera­tion to allow all children to complete free, equitable, inclusive and quality early childhood, primary and secondary education, and concessional and non-concessional financing.

Another way is to develop country-specific national targets and plans consistent with the SDG, Addis, and COP21 targets, as is currently being done with the assistance of the United Nations Development Program’s MAPS program. This can provide broad guidance on policy priorities and resource mobilization strategies to be pursued at the national level and can help national and international actors to prioritize their interventions in areas where a country’s needs are greatest.

However, calling for expanded global efforts in particular priority areas and defining national targets and plans is not enough. Individual development actors have to link their specific projects and programs with the national SDG, Addis, and COP21 targets. They systematically have to pursue a scaling-up strategy in their areas of engagement, i.e., to develop and pursue pathways from individual time-bound interventions to impact at a scale in a way that will help achieve the global and national targets. A recent paper I co-authored with Larry Cooley summarizes two complementary approaches of how one might design and implement such scaling-up pathways. The main point, however, is that only the pursuit of such scaling-up pathways constitutes a meaningful theory of change that offers hope for effective implementation of the new global sustainable development targets.

Fortunately, over the last decade, development analysts and agencies have increasingly focused on the question of how to scale up impact of successful development interventions. Leading the charge, the World Bank in 2004, under its president Jim Wolfensohn, organized a high-level international conference in Shanghai in cooperation with the Chinese authorities on the topic of scaling up development impact and published the associated analytical work. However, with changes in the leadership at the World Bank, the initiative passed to others in the mid-2000s, including the Brookings Institution, ExpandNet (a group of academics working with the World Health Organization), Management Systems International (MSI), and Stanford University. They developed analytical frameworks for systematically assessing scalability of development initiatives and innovations, analyzed the experience with more or less successful scaling-up initiatives, including in fragile and conflict-affected states, and established networks that bring together development experts and practitioners to share knowledge.

By now, many international development agencies (including GIZ, JICA, USAID, African Development Bank, IFAD and UNDP), foundations (including the Bill & Melinda Gates Foundation and Rockefeller Foundation) and leading development NGOs (including Heifer International, Save the Children and the World Resources Institute), among others, have focused on how best to scale up development impact, while the OECD recently introduced a prize for the most successful scaling-up development initiatives. The International Fund for Agricultural Development (IFAD) is perhaps the most advanced among the agencies, having developed a systematic operational approach to the innovation-learning-scaling-up cycle. In a collaborative effort with the Brookings Institution, IFAD reviewed its operational practices and experience and then prepared operational design and evaluation guidelines, which can serve as a good example for other development agencies. The World Bank, while yet to develop a systematic institution-wide approach to the scaling-up agenda, is exploring in specific areas how best to pursue scaled-up impact, such as in the areas of mother and child health, social enterprise innovation, and the “science of delivery.”

Now that the international community has agreed on the SDGs and the Addis Agenda, and is closing in on an agreement in Paris on how to respond to climate change, it is the right time to bridge the “missing middle” by linking the sustainable development and climate targets with effective scaling-up methodologies and practices among the development actors. In practical terms, this requires the following steps:

• Developing shared definitions, analytical frameworks, and operational approaches to scaling up among development experts;
• Developing sectoral and sub-sectoral strategies at country level that link short- and medium-term programs and interventions through scaling-up pathways with the longer-term SDG and climate targets;
• Introducing effective operational policies and practices in the development agencies in country strategies, project design, and monitoring and evaluation;
• Developing multi-stakeholder partnerships around key development interventions with the shared goal of pursuing well-identified scaling-up pathways focused on the achievement of the SDGs and climate targets;
• Developing incentive schemes based on the growing experience with “challenge funds” that focus not only on innovation, but also on scaling up, such as the recently established Global Innovation Fund; and
• Further building up expert and institutional networks to share experience and approaches, such as the Community of Practice on Scaling Up, recently set up by MSI and the Results for Development Institute.

       

       

       

       

       

       

       

As government funding for disability insurance is expected to run out next year, Congress should re-evaluate the costs of the program.

Nine million people in America today are receiving Social Security Disability Insurance, double the number in 1995 and six times the number in 1970. With statistics like that, it’s hardly surprising to see some in Congress worry that more will enroll in the program and costs would continue to rise, especially since government funding for disability insurance is expected to run out by the end of next year. If Congress does nothing, benefits would fall by 19% immediately following next year’s presidential election. So, Congress will likely do something. But what exactly should it do?

Funding for disability insurance has nearly run out of money before. Each time, Congress has simply increased the share of the Social Security payroll tax that goes for disability insurance. This time, however, many members of Congress oppose such a shift unless it is linked to changes that curb eligibility and promote return to work. They fear that rolls will keep growing and costs would keep rising, but findings from a report by a government panel conclude that disability insurance rolls have stopped rising and will likely shrink. The report, authored by a panel of the Social Security Advisory Board, is important in that many of the factors that caused disability insurance to rise, particularly during the Great Recession, have ended.

• Baby-boomers, who added to the rolls as they reached the disability-prone middle age years, are aging out of disability benefits and into retirement benefits. 


• The decades-long flood of women increased the pool of people with the work histories needed to be eligible for disability insurance. But women’s labor force participation has fallen a bit from pre-Great Recession peaks, and is not expected again to rise materially. 


• The Great Recession, which led many who lost jobs and couldn’t find work to apply for disability insurance, is over and applications are down. A recession as large as that of 2008 is improbable any time soon. 


• Approval rates by administrative law judges, who for many years were suspected of being too ready to approve applications, have been falling. Whatever the cause, this stringency augurs a fall in the disability insurance rolls.