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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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.

       

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.

       

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

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

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

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

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

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

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

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

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

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

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

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

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

       

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

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

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

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

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

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

      

      

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

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

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

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

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

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

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

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

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

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

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

      

       

       

       

       

       

       

       

       

Financial advisors offer their clients many advantages, such as setting reasonable savings goals, avoiding fraudulent investments and mistakes like buying high and selling low, and determining the right level of risk for a particular household. However, these same advisors are often incentivized to choose funds that increase their own financial rewards, and the nature and amount of the fees received by advisors may not be transparent to their clients, and small-scale savers may not be able to access affordable advice at all.  What is in the best interest of an individual may not be in the best interest of his or her financial advisor.

To combat this problem, the Department of Labor (DoL) recently proposed a regulation designed to increase consumer protection by treating some investment advisors as fiduciaries under ERISA and the 1986 Internal Revenue Code.  The proposed conflict of interest rule is an important step in the right direction to increasing consumer protections.  It addresses evidence from a February 2015 report by the Council of Economic Advisers suggesting that consumers often receive poor recommendations from their financial advisors and that as a result their investment returns on IRAs are about 1 percentage point lower each year.   Naturally, the proposal is not without its controversies and it has already attracted at least 775 public comments, including one from us .

For us, the DoL’s proposed rule is a significant step in the right direction towards increased consumer protection and retirement security.  It is important to make sure that retirement advisors face the right incentives and place customer interests first.  It is also important make sure savers can access good advice so they can make sound decisions and avoid costly mistakes.  However, some thoughtful revisions are needed to ensure the rule offers a net benefit. 

If the rule causes advisors’ compliance costs to rise, they may abandon clients with small-scale savings, since these clients will no longer be profitable for them.  If these small-scale savers are crowded out of the financial advice market, we might see the retirement savings gap widen.  Therefore we encourage the DoL to consider ways to minimize or manage these costs, perhaps by incentivizing advisors to continue guiding these types of clients.  We also worry that the proposed rule does not adequately clarify the difference between education and advice, and encourage the DoL to close any potential loopholes by standardizing the general educational information that advisors can share without triggering fiduciary responsibility (which DoL is trying to do).  Finally, the proposed rule could encourage some advisors to become excessively risk averse in an overzealous attempt to avoid litigation or other negative consequences.  Extreme risk aversion could decrease market returns for investors and the ‘value-add’ of professional advisors, so we suggest the DoL think carefully about discouraging conflicted advice without also discouraging healthy risk.

The proposed rule addresses an important problem, but in its current form it may open the door to some undesirable or problematic outcomes.  We explore these issues in further detail in our recent paper.

      

Americans are enjoying longer lifespans than ever before. Living longer affords individuals the opportunity to make more contributions to the world, to spend more time with their loved ones, and to devote more years to their favorite activities – but a longer life, and particularly a longer retirement, is also expensive. The retirement security landscape is evolving as workers, employers, retirees, and financial services companies find their needs shifting. Once, many workers planned to stay with a single employer for most or all of their careers, building up a sizeable pension and looking forward to a comfortable retirement. Today, workers more and more workers will be employed by many different employers.  Additionally, generous defined benefit (DB) retirement plans are less popular than they once were – though they were never truly commonplace – and defined contribution (DC) plans are becoming ever more prevalent.  

Figure 1, below, shows the change from DB to DC that has occurred over the past three decades.

In the past many retirees struggled financially towards the end of their lives, just as they do now, but even so, the changes to the retirement security landscape have been real and marked, and have had a serious impact on workers and retirees alike. DB plans are dwindling, DC plans are on the rise, and as a result individuals must now take a more active role in managing their retirement savings. DC plans incorporate contributions from employees and employers alike, and workers much choose how to invest their nest egg.  When a worker leaves a job for retirement or for a different job he or she will often roll over the money from a 401(k) plan into an Individual Retirement Account (IRA). While having more control over one’s retirement funds might seem on its face to be a net improvement, the reality is that the average American lacks the financial literacy to make sound decisions (SEC 2012).

The Council of Economic Advisers (CEA) expressed concern earlier this year that savers with IRA accounts may receive poor investment advice, particularly in cases where their financial advisors are compensated through fees and commissions. “[The] best recommendation for the saver may not be the best recommendation for the adviser’s bottom line” (CEA 2015). President Obama echoed these concerns in a speech at AARP in February, asking the Department of Labor (DoL) to update its rules for financial advisors to follow when handling IRA accounts (White House 2015). The DoL receives its authority to craft such rules and requirements from the 1974 Employee Retirement Income Security Act (ERISA) (DoL 2015a).

The DoL recently proposed a regulation designed to increase consumer protection by treating some investment advisors as fiduciaries under ERISA and the 1986 Internal Revenue Code (DoL 2015b). The proposed rule has generated heated debate, and some financial advisors have responded with great concern, arguing that it will be difficult or impossible to comply with the rule without raising costs to consumers and/or abandoning smaller accounts that generate little or no profit. Advisors who have traditionally offered only the proprietary products of a single company worry that the business model they have used for many years will no longer be considered to be serving the best interests of clients.

Rather than offering detailed comments on the DoL proposals, this paper will look more broadly at the problem of saving for retirement and the role for professional advice. This is, of course, a well-travelled road with a large literature by academics, institutions and policy-makers, however, it is worthwhile to think about market failures, lack of information and individual incentives and what they imply for the investment advice market.

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

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

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

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

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

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

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

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

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

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

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

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

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

      

Introduction

I would like to thank the Department for giving me the opportunity to testify on this important issue. The document I submitted to you is more general than most of the comments you have received, talking about the issues facing retirement savers and policymakers, rather than engaging in a point-by-point discussion of the detailed DOL proposal¹.

Issues around Retirement Saving

1. Most workers in the bottom third of the income distribution will rely on Social Security to support them in retirement and will save little. Hence it is vital that we support Social Security in roughly its present form and make sure it remains funded, either by raising revenues or by scaling back benefits for higher income retirees, or both.

2. Those in the middle and upper middle income levels must now rely on 401k and IRA funds to provide income support in retirement. Many and perhaps most households lack a good understanding of the amount they need to save and how to allocate their savings. This is true even of many savers with high levels of education and capabilities.

3. The most important mistakes made are: not saving enough; withdrawing savings prior to retirement; taking Social Security benefits too early² ; not managing tax liabilities effectively; and failing to adequately manage risk in investment choices. This last category includes those who are too risk averse and choose low-return investments as well as those that overestimate their own ability to pick stocks and time market movements. These points are discussed in the paper I submitted to DoL in July. They indicate that retirement savers can benefit substantially from good advice.

4. The market for investment advice is one where there is asymmetric information and such markets are prone to inefficiency. It is very hard to get incentives correctly aligned. Professional standards are often used as a way of dealing with such markets but these are only partially successful. Advisers may be compensated through fees paid by the investment funds they recommend, either a load fee or a wrap fee. This arrangement can create an incentive for advisers to recommend high fee plans.

5. At the same time, advisers who encourage increased saving, help savers select products with good returns and adequate diversification, and follow a strategy of holding assets until retirement provide benefits to their clients.

Implications for the DoL’s proposed conflicted interest rule

1. Disclosure. There should be a standardized and simple disclosure form provided to all households receiving investment advice, detailing the fees they will be paying based on the choices they make. Different investment choices offered to clients should be accompanied by a statement describing how the fees received by the adviser would be impacted by the alternative recommendations made to the client.

2. Implications for small-scale savers. The proposed rule will bring with it increased compliance costs. These costs, combined with a reluctance to assume more risk and a fear of litigation, may make some advisers less likely to offer retirement advice to households with modest savings. These households are the ones most in need of direction and education, but because their accounts will not turn profits for advisors, they may be abandoned. According to the Employee Benefits Security Administration (EBSA), the proposed rule will save families with IRAs more than $40 billion over the next decade. However, this benefit must be weighed against the attendant costs of implementing the rule. It is possible that the rule will leave low- and medium-income households without professional guidance, further widening the retirement savings gap. The DoL should consider ways to minimize or manage these costs. Options include incentivizing advisors to continue guiding small-scale savers, perhaps through the tax code, and promoting increased financial literacy training for households with modest savings. Streamlining and simplifying the rules would also help.

3. Need for Research on Online Solutions. The Administration has argued that online advice may be the solution for these savers, and for some fraction of this group that may be a good alternative. Relying on online sites to solve the problem seems a stretch, however. Maybe at some time in the future that will be a viable option but at present there are many people, especially in the older generation, who lack sufficient knowledge and experience to rely on web solutions. The web offers dangers as well as solutions, with the potential for sub-optimal or fraudulent advice. I urge the DoL to commission independent research to determine how well a typical saver does when looking for investment advice online. Do they receive good advice? Do they act on that advice? What classes of savers do well or badly with online advice? Can web advice be made safer? To what extent do persons receiving online advice avoid the mistakes described earlier?

4. Pitfalls of MyRA. Another suggestion by the Administration is that small savers use MyRA as a guide to their decisions and this option is low cost and safe, but the returns are very low and will not provide much of a cushion in retirement unless households set aside a much larger share of their income than has been the case historically.

5. Clarifications about education versus advice. The proposed rule distinguished education from advisement. An advisor can share general information on best practices in retirement planning, including making age-appropriate asset allocations and determining the ideal age at which to retire, without triggering fiduciary responsibility. This is certainly a useful distinction. However, some advisors could frame this general information in a way that encourages clients to make decisions that are not in their own best interest. The DoL ought to think carefully about the line between education and advice, and how to discourage advisors from sharing information in a way that leads to future conflicts of interest. One option may be standardizing the general information that may be provided without triggering fiduciary responsibility.

6. Implications for risk management. Under the proposed rule advisors may be reluctant to assume additional risk and worry about litigation. In addition to pushing small-scale savers out of the market, the rule may encourage excessive risk aversion in some advisors. General wisdom suggests that young savers should have relatively high-risk portfolios, de-risking as they age, and ending with a relatively low-risk portfolio at the end of the accumulation period. The proposed rule could cause advisors to discourage clients from taking on risk, even when the risk is generally appropriate and the investor has healthy expectations. Extreme risk aversion could decrease both market returns for investors and the “value-add” of professional advisors. The DoL should think carefully about how it can discourage conflicted advice without encouraging overzealous risk reductions.

The proposed rule is an important effort to increase consumer protection and retirement security. However, in its current form, it may open the door to some undesirable or problematic outcomes. With some thoughtful revisions, I believe the rule can provide a net benefit to the country.

^{1. Baily’s work has been assisted by Sarah E. Holmes. He is a Senior Fellow at the Brookings Institution and a Director of The Phoenix Companies, but the views expressed are his alone.}

^{2. As you know, postponing Social Security benefits yields an 8 percent real rate of return, far higher than most people earn on their investments. For most of those that can manage to do so, postponing the receipt of benefits is the best decision.}

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Executive Summary ¹

The regional banks play an important role in the economy providing funding to consumers and small- and medium-sized businesses. Their model is simpler than that of the large Wall Street banks, with their business concentrated in the U.S.; they are less involved in trading and investment banking, and they are more reliant on deposits for their funding. We examined the balance sheets of 15 regional banks that had assets between $50 billion and $250 billion in 2003 and that remained in operation through 2014.

The regionals have undergone important changes in their financial structure as a result of the financial crisis and the subsequent regulatory changes:

• Total assets held by the regionals grew strongly since 2010. Their share of total bank assets has risen since 2010.

• Loans and leases make up by far the largest component of their assets. Since the crisis, however, they have substantially increased their holdings of securities and interest bearing balances, including government securities and reserves.

• The liabilities of the regionals were heavily concentrated in domestic deposits, a pattern that has intensified since the crisis. Deposits were 70 percent of liabilities in 2003, a number that fell through 2007 as they diversified their funding sources, but by 2014 deposits made up 82 percent of the total.

• Regulators are requiring large banks to increase their holdings of long term subordinated debt as a cushion against stress or failure. The regionals, as of 2014, had not increased their share of such liabilities.

• Like the largest banks, the regionals increased their loans and leases in line with their deposits prior to the crisis. And like the largest banks, this relation broke down after 2007, with loans growing much more slowly than deposits. Unlike the largest banks, the regionals have increased loans strongly since 2010, but there remains a significant gap between deposits and loans.

• The regional banks’ share of their net income from traditional sources (mostly loans) has been slowly declining over the period.

• The return on assets of the regionals was between 1.5 and 2.0 percent prior to the crisis. This turned sharply negative in the crisis before recovering after 2009. Between 2012 and 2014 return on assets for these banks was around 1.0 percent, well below the pre-crisis level.

As we saw with the largest banks, the structure and returns of the regional banks has changed as a result of the crisis and new regulation. Perhaps the most troubling change is that the volume of loans lags well behind the volume of deposits, a potential problem for economic growth. The asset and liability structure of the banks has also changed, but these banks have a simpler business model where deposits and loans still predominate.

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This paper was revised in October 2015.

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^{1. William Bekker served as research assistant on this project until June 2015 where he compiled and analyzed the data. He was co-author of the first part of this series and his contributions were vital to the findings presented here. New research assistant Nicholas Montalbano has contributed to this paper.  We thank Michael Gibson of the Federal Reserve for helpful suggestions.}

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The White House Council of Economic Advisers (CEA) was created by Congress in 1946 to advise the president on ways “to foster and promote free competitive enterprise” and “to promote maximum employment, production and purchasing power.” President Truman, who signed the Employment Act of 1946 into law, was unenthusiastic about the Council and didn’t nominate members for nearly six months. Yet the CEA, comprised of three individuals whom Congress says are to be “exceptionally qualified,” has not only survived but also prospered for 70 years and remains an important part of the president’s economic policy decisionmaking.

On February 11, the Hutchins Center on Fiscal and Monetary Policy at Brookings marked this anniversary by examining the ways the CEA and other economists succeed and fail when they set out to advise elected politicians and tap the expertise of some of the “exceptionally qualified” economists who have chaired the Council over the past four decades.

You can join the conversation and tweet questions for the panelists at #CEAat70.

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• Panel 1: The CEA in Moments of Crisis
• Panel 2: The CEA and Policymaking
• Panel 3: Current Economic Policy Issues

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• The Council of Economic Advisers: 70 years of advising the president

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The financial crisis is now eight years behind us, but its legacy lingers on. Many Americans are concerned about their financial security and are particularly worried about whether they will have enough for retirement. Guaranteed benefit pensions are gradually disappearing, leaving households to save and invest for themselves. What role could equities play for retail investors?

Another concern about the lingering impact of the crisis is that business investment and overall economic growth remains weak compared to expectations. Large companies are able to borrow at low interest rates, yet many of them have large cash holdings. However, many small and medium sized enterprises face difficulty funding their growth, paying high risk premiums on their borrowing and, in some cases, being unable to fund investments they would like to make. Equity funding can be an important source of growth financing.

On Friday, April 15, the Initiative on Business and Public Policy at Brookings examined what role equity markets can play for individual retirement security, small business investment and whether they can help jumpstart American innovation culture by fostering the transition from startups to billion dollar companies.

You can join the conversation and tweet questions for the panelists at #EquityMarkets.

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• Keynote address by Richard G. Ketchum
• Panel Discussion
• Keynote address by Roger Ferguson

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• Not just for the professionals? Understanding equity markets for retail and small business investors

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Australia's economic performance has been the standout among advanced economies for several decades. With economic growth at nearly twice the pace of US or Germany over the past decade, a remarkable 25 years without a recession and a large, highly competitive mining sector despite the end of the resources boom, Australia remains a strong economic participant in a region of the world where future global growth is likely to be generated.

But with drivers of growth over the past 25 years unlikely to be the engines of growth in coming decades, now is not a time for complacency. And if there's one lesson from Britain's decision to leave the EU, it's that that disruptive forces are sweeping through the global economy. Australia, with its cohesive politics and economic success, has been able to avoid the worst of these problems, but the dangers are present if the economic challenges are not met.

To start with, the impacts of the reforms of the 1980s and 1990s are fading. The investment boom in mining is over, and the prices for mining and agricultural exports will probably remain subdued with slower growth in China. While Australia's incomes were boosted by the improved terms of trade, this has partially reversed. The housing boom will inevitably eventually slow.

As evidenced by the results of the Brexit referendum, there is a distrust of the political and economic elites that have led the world's biggest economies. Disruptive, rapid changes in technology have not led to broad-based productivity growth. Workers in many countries have been left with stagnant incomes and governments with rising public debt.

Industry policy has a bad name among American economists who see it as a manifestation of "capture" where special interests are able to obtain subsidies from taxpayers or special protections that are not in the national interest. The modern theory of industry policy, however, recognises that a well-designed policy can actually help markets work better, therefore helping an economy like Australia's make the transition to a new growth path when faced with changing economic conditions. Productivity is the key to high growth and rising incomes – and well-designed industry policy can help.

Structure of trade competitiveness

Take, for example, Australia's manufacturing sector. Mostly because of comparative advantage, it is the smallest among all advanced economies relative to the size of its economy. In 2010, Germany had 21.2 per cent of its workforce in manufacturing while Australia's was 8.9 per cent. While it's not surprising that Australia's structure of trade competitiveness differs from Germany's because of its enormous export strength of mining and agriculture, it will benefit by taking advantage of its highly skilled workforce and the potential to develop industries based on this human capital – including advanced manufacturing industries.

One of the traditional strengths of the American economy is the close link that exists between leading universities and businesses – an area Australian policymakers are seeking to improve upon. At MIT and Stanford, professors of engineering, biology, finance or economics finish their lectures and head off to the companies they run or advise. They often enlist graduate or undergraduate students to help them with their commercial projects and these collaborations often result in jobs as well as experience. There is a danger in this model if pure research loses out to business interests, but the interaction between academia and the practical needs of companies can largely improve both research and business profitability. It's worth recalling that even the giants of science in the 18th century were motivated by the need to improve navigation or build new machines or design buildings. Funding for research should support greater industry-university cooperation as highlighted by the Watt Review.

Another important element in Australia's continued economic success is the growth of its service industries. With most jobs in these industries, the performance and productivity of services will be the largest determinant of Australia's living standards. Productivity comparisons between Australia and the United States show that Australian productivity lagged behind the US as recently as the mid-1990s, but there has since been substantial catch-up taking place. Smart regulation that promotes competition and rewards innovation are necessary to bring up the laggards. While there is a continuing debate about the possible end of productivity growth in advanced economies, Australia can still do much to catch up to global best practice.

The winners of this weekend's election will be charged with answering an important question: what is the role of government in a modern economy? How they answer that will determine future prosperity for all Australians.

High taxes, large government, poorly regulated markets (particularly labour markets), excessive debt and poor infrastructure undermine the drivers of growth. The realities of a fragile global economy and the need to build a solid foundation to generate productivity growth in Australia must be at the core of the policies that follow this election campaign.

Martin Baily is a senior fellow at the Brookings Institution in Washington and a former chair of the US President's Council of Economic Advisers. He has been invited by the Australian Ministry of Industry Innovation and Science to report on lessons from the US for policies to enhance economic growth, innovation and competitiveness.

Warwick McKibbin AO, is the director of the Centre for Applied Macroeconomic Analysis in the ANU Crawford School of Public Policy and is a non-resident senior fellow at the Brookings Institution.

Editor's note: this opinion first appeared in Australian Financial Review.

       

       

       

       

       

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On June 23, voters in the United Kingdom will go to the polls for a referendum on the country’s membership in the European Union. As one of the EU’s largest and wealthiest member states, Britain’s exit, or “Brexit”, would not only alter the U.K.’s institutional, political, and economic relationships, but would also send shock waves across the entire continent and beyond, with a possible Brexit fundamentally reshaping transatlantic relations.

On May 6, the Center on the United States and Europe (CUSE) at Brookings, in cooperation with the Heinrich Böll Stiftung North America, the UK in a Changing Europe Initiative based at King's College London, and Wilton Park USA, will host a discussion to assess the range of implications that could result from the United Kingdom’s referendum. 

After each panel, the participants will take questions from the audience.

Join the conversation on Twitter using #UKReferendum

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• Brexit—in or out? Implications of the United Kingdom’s referendum on EU membership

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• 20160506_uk_eu_brexit_transcript

       

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. 

       

       

       

       

       

       

       

       

       

       

       

       

       

       

       

       

       

       

       

Event Information

By the end of May, citizens of Europe will have left the polling booths and a new European Parliament will have been directly elected for the eighth time in the institution’s history. Since the last elections were held in 2009 on the heels of the global financial crisis, the eurozone has developed stronger economic stability mechanisms, kept its membership intact, and even added additional members. Yet Europe also faces a resurgence of extreme nationalism, political fragmentation within nation-states, and frustration and protest driven by high rates of unemployment. There are very different visions for the future of Europe.

On June 3, the Global Economy and Development program at Brookings hosted a discussion on Europe’s future and what Europe’s election results mean for critical choices like the formation of the new European Commission, fiscal policies, U.S.-EU relations, TTIP negotiations and the future of the EU-United Kingdom relationship. Some of the issues that were addressed are also analyzed in Europe’s Crisis, Europe’s Future, a recently published book (Brookings Press, April 2014) co-edited by Kemal Derviș and Jacques Mistral.

Join the conversation on Twitter using #EuroFuture

Video

• European Monetary Union Has Political Consequences
• The European Elections and the Future of Europe
• People Are Feeling Apathetic about Europe
• European Elections Proof of Frustrations
• Jobs and Growth at Heart of Europe's Problem
• Britain Wants Eurozone to Succeed
• The European Elections and the Future of Europe

Audio

• The European Elections and the Future of Europe

Transcript

• Uncorrected Transcript (.pdf)

Event Materials

• 20140603_european_elections_transcript