The Real Estate Market in Flux

That brave new world we’ve been hearing about for decades is now on the horizon. Business after business is in the midst of profound, disruptive change. Netflix and Amazon have emerged as entertainment business powerhouses. Established automotive companies like General Motors and Volvo have announced commitments to an all-electric fleet. There is no reason to expect commercial real estate will be an exception. Research conducted by MIT’s Center for Real Estate, underwritten by Capital One’s Commercial Bank, uncovered a number of critical trends that have already begun to shape and, in some cases, disrupt real estate markets or will do so in the near future.

The trends catalogued in the Center’s report, Real Trends: The Future of Real Estate in the United States, will impact the decisions investors make as they consider their portfolios. Anticipating them will ultimately determine their success in navigating a rapidly changing market.

The report covers more than two dozen trends. These four highlights provide a flavor for the insights it contains:

  • Distribution. Successful metropolitan areas in the Northeast and California will become even more expensive for households, continuing the shift of a large proportion of national demographic growth and real estate development to the booming urban centers of the South and West.
  • Adaptive Reuse. Adaptive reuse continues to gain in popularity. Cities like adaptive reuse projects because they generate tax revenue while taking advantage of established infrastructure. Developers like reuse projects because of the possibility of tax credits for rehabilitating historic structures.
  • Autonomous Vehicles/Ridesharing. Autonomous cars will stimulate a new wave of suburban development by increasing the distances that people are willing to commute. Combined with ridesharing apps, self-driving cars will free up urban land now dedicated to parking for development and public spaces.
  • The Internet of Things. The Internet of Things (IoT)—combined with machine learning and big data analytics—will affect the way buildings are designed and managed. In addition to promoting more efficient building performance and reducing costs, the IoT will pave the way for more granular asset valuations and portfolio management and help developers and investors identify differentiating building uses and services.

The Demographic Backdrop

These trends and others the MIT researchers identify are taking place in the context of a steadily growing housing market. The most recent projections from the U.S. Census have the U.S. population growing from 319 million in 2014 to 417 million in 2060. It estimates that this growth alone will require an additional 38 million housing units at current residential densities.

Growth in the short term will be particularly intense. The population is expected to jump to 334 million by 2020, or the equivalent of about a million households a year. Add to this is the need to make up for shortfalls in housing construction during the recession and routine removals from stock, and it is not unreasonable to suggest that new housing completions can reach 1.65 million annually starting in 2018 without producing a glut of housing. Right now, we are playing catch-up.

Growth Shifts: The Booming Heartland

This growth, however, will not lift all markets evenly. The MIT researchers compiled a list of the 50 fastest growing counties in the United States between 2010 and 2016 and then focused on counties with at least 50,000 housing units at the start of that period. Suburban counties in booming metro areas popped out, in places like Atlanta, Denver, Indianapolis, Fargo, Jacksonville, Nashville, and the North Carolina Research Triangle.

The researchers then correlated this list with one for the fastest growing states—and found that Texas, Florida, and the Carolinas alone accounted for more than 30 percent of net residential real estate development over the six years. The overall picture: The Northeastern and Midwestern states and, to a lesser extent, California are generally seeing growth rates below the U.S. average, while Southern and Western states along with the Washington, D.C., metro area are growing faster.

They identified the fundamental cause of the split as inelastic housing supply. In cities like San Francisco and New York with regulatory and geographic barriers to new construction, economic success is translated into very expensive housing. No matter how appealing these cities are, households that can’t afford them move elsewhere. On the other hand, growing metro areas tend to be the ones that are both economically successful and accommodating to rapid real estate development.

Adaptive Reuse: Making the Old New Again

Given the attraction of urban cores, adaptive reuse has emerged over the last decade as an attractive option for affordable as well as market-rate housing. The MIT researchers believe adaptive reuse will continue to be a valuable addition to the developer toolbox. They note that adaptive reuse projects have numerous advantages besides leveraging underused structures. Because they are located in city centers, they can take advantage of established transportation networks and municipal services.

For instance, Capital One syndicated a $180 million loan to convert 180 Water Street, an office building in New York’s Financial District, into multifamily apartments. The sponsor, Metro Loft Management, has a 20-year track record in this precise niche: complex redevelopment of obsolete Class B/C office buildings in Lower Manhattan as high-end apartment rentals. The 180 Water Street project was a cost-effective alternative to new construction, though it did involve substantial challenges, in this case introducing light into the core of a 508,000-square-foot modernist tower. Metro Loft’s solution, carve out a 40-foot-wide courtyard in the core of the building starting at the second floor. The reconceptualized building now includes 573 apartments, with asking rents ranging from $2,690 for a studio to $7,190 for a three-bedroom.

Adaptive reuse has also proved a cost-effective approach for affordable housing and will continue to serve this purpose as long as tax credits remain available. For instance, in 2013, Capital One provided financing for Fells Point Station, a mixed-rate community offering affordable and under-market housing in Upper Fells Point, Baltimore’s oldest waterfront neighborhood. The project was designed around the shell of a former police station from the 1920s. Henson Development and Mission First Housing collaborated to renovate the original 16,000-square-foot brick and masonry structure and build a 37,000-square-foot addition. The project received funding generated by tax credits for qualified historic rehabilitation.

Autonomous Vehicles/Ridesharing: Impacts Suburban as Well as Urban Markets

Although there seems to be no slackening in the momentum behind self-driving cars, it would be a mistake to underestimate the technological, legal, security, and safety hurdles that must be surmounted for them to become ubiquitous. When that time arrives, however, the MIT researchers believe that their effect on the commercial real estate industry will likely be significant. To an unprecedented extent, the automobile has shaped the American landscape. Fundamental changes to this essential technology will change the way people live and work.

One of the most commonly held theories is that autonomous vehicles will transform the central city. The combination of driverless cars and ridesharing applications could induce city dwellers, never very enthusiastic car owners, to give up their vehicles, freeing land currently devoted to parking for development and public space.

At the same time, self-driving cars could stimulate a new wave of suburbanization. Because passengers will be able to work and even relax during their commute, autonomous vehicles may increase the distances people are willing to travel. The lack of public transportation will no longer be a deterrent for commercial development in edge cities and distant suburbs.

The Internet of Things: Smarter Building Management and Design

With the arrival of the Internet of Things (IoT), buildings of all kinds can be instrumented with networks of sensors and actuators. From a building management point of view, the combination of the IoT, machine learning, and predictive analytics will enable a new generation of buildings that are self-monitoring and self-regulating—and consequently more energy efficient, less costly to maintain, and more responsive to occupants’ needs. Wireless technologies make it cost-effective to retrofit existing buildings.

This data can be combined with data generated by the gamut of building systems, including utility meters, building mechanical systems, occupancy counters, and security cameras into a powerful building management system, capable of producing a robust real-time snapshot of building operations as well as forecasts of energy use and costs. This data, drawn from existing structures, can be then applied to predict the operational costs of buildings under development as well as shape their design.

But the ultimate promise of IoT-enabled building management systems goes beyond enhanced building performance, and cost cutting. It can pave the way for more granular asset valuation and portfolio management as well as the identification of differentiating building uses and services.

Staying Ahead of the Future

One thing MIT’s Real Trends report makes abundantly clear: a series of interrelated demographic, economic, and technological trends will disrupt long-held assumptions about real estate, challenging established business models and opening opportunities for those with the foresight to envision a future that breaks in significant ways with the present. One reason that Capital One commissioned the report is to provide members of the real estate community with a framework they can use to identify trends as they emerge in their market, assess their implications, and change course accordingly. Their future depends on it.

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