Washington DC

Transit Legacy Cities

Wendell Cox — Wed, 20 Feb 2013 08:50:08 -0500

Transit's greatest potential to attract drivers from cars is the work trip. But an analysis of US transit work trip destinations indicates that this applies in large part to just a few destinations around the nation. This is much more obvious in looking at destinations than the more typical method of analysis, which looks at the residential locations of commuters. This column is adapted from my new Heritage Foundation Backgrounder "Transit Policy in an Era of the Shrinking Federal Dollar."

Transit Legacy Cities

Transit commuting is heavily concentrated to destinations in just the six core cities (historical core municipalities) of New York, Chicago, Philadelphia, San Francisco, Boston and Washington (Backgrounder Chart 9). I call them the "transit legacy cities," because their high transit market shares relate to their development before the automobile became dominant. Because there is such a lack of clarity in the use of terms that apply to cities, it is important to emphasize that the transit legacy cities are municipalities, not the surrounding metropolitan areas or urban areas, where the majority of residents live (Note 1).

The transit legacy cities account for nearly 55 percent of the nation's transit commuters, by work trip destinations, according to the American Community Survey (2008-2010). By contrast, the transit legacy cities have an overall national employment market share barely one-tenth their national transit share (6 percent). Moreover, combined, the transit legacy cities cover a land area little larger than the core city (municipality) of Jacksonville, Florida.

At the same time, the "other side of the coin" is that commuting to other destinations is dominated by the automobile, from the suburbs in metropolitan areas with transit legacy cities, and even more so in the other 45 major metropolitan areas (with more than 1,000,000 population) and the balance of the nation.

Legacy Cities: Transit's Strength

The extent of the concentration in the six transit legacy cities is illustrated in Backgrounder Table 1. In some ways, transit is, first and foremost, really a New York story. More than one-third of all transit work-trip commuting is to destinations in the core city of New York. The dominance is even greater for high-capacity subways/elevated services, a mode in which where New York represents two-thirds of national commuting.

The Key: Large, Concentrated, Well Served Downtowns: The concentration of transit commuting in the six transit legacy cities reflects the factor that is probably more responsible than any other for attracting people from cars to transit. This is a highly concentrated downtown area (central business district, or "CBD") from which a dense network of rapid transit services radiates.

The six transit legacy cities are also home to the six largest CBDs in the nation, where transit's share of commuting is far higher than compared to the rest of the nation. Approximately three quarters of commuters to the sprawling Manhattan CBD in New York (south of 59th Street) commuted by transit in 2000. Less well known is that New York also contains the CBD with the second largest transit work trip destination, downtown Brooklyn (58 percent), which is followed by downtown Chicago (55 percent).

In addition, between nearly 40 percent and more than 50 percent of commuters used transit to the CBDs of Boston, San Francisco, Philadelphia and Washington. While covering a land area less than one-half the size of Orlando's Walt Disney World, these downtowns accounted for 35 percent of national transit commuting.

Outside the Transit Legacy Cities: Automobile and Work at Home Country

So what about the 94 percent of US commuters who work outside the transit legacy cities? The answer is that the automobile dominates, and transit has been overtaken by working at home. In the suburban areas of metropolitan areas with transit legacy cities, the car carries 18 times as many people to work locations as transit. In the core municipalities of the 45 major metropolitan areas without legacy cities, cars carry 29 times as many commuters as transit, and 51 times as many in the suburbs. Outside the nation's major metropolitan areas, cars carry 82 times as many commuters as transit (Backgrounder Table 1)

Further, outside the transit legacy cities, working at home (including telecommuting) provides access to twenty percent more jobs than transit (Backgrounder Table 3).

An American Love Affair with the Automobile?

The enduring myth of the American love affair with automobile is countered by the huge transit market shares to city downtowns . For example, commuters to Manhattan are five times as likely to use transit as cars. On the other hand, commuters to the edge city of Parsippany, on the I-287 corridor in suburban New Jersey are 50 times as likely to use their cars as transit. Yet both employment centers serve the same labor market. The issue is not preferences, it is rather rational choice. It would be irrational for most people to commute to Manhattan by car, principally because of the traffic congestion and cost, particularly for parking. It would similarly be irrational for most people to commute to Parsippany by transit, because it either could not be done at all, or it would take too long.

Transit's work trip destination market share is an effective measure of its relevance to the market.

And lest anyone should counter that the answer is more money, consider this.

A Cost Not A Revenue Problem

Portland (with a core city that is not a legacy city) has long been held out as a model for improving transit. Yet, after billions of dollars in federal and local tax subsidies, more than 50 times as many people travel to work to suburban locations by car as by transit. More than five times as many work at home as use transit, and working at home costs taxpayers virtually nothing. Yet, despite all these billions, Portland's transit system is in crisis. Tri-Met's Executive Director Neil McFarlane has warned of 70 percent service cuts over 12 years without substantial changes to union contracts.

Transit’s fundamental problem is not insufficient revenue but insufficient cost control. Since 1983, national transit expenditures have risen at an inflation-adjusted rate nine times that of its increase in commuters (Note 2). Even if costs were under control, it would be financially impossible to provide automobile-competitive transit throughout the modern urban area, as Professor Jean-Claude Ziv and I showed in our WCTRS paper (Megacities and Affluence: Transport and Land Use Considerations).

Celebrating Transit

Yet, beyond its inability to convert generous taxpayer subsidies into corresponding ridership increases, transit deserves credit for the large number of people it moves to jobs in the legacy cities. This success should be celebrated although it remains an impossible, prohibitively expensive, dream elsewhere.

Wendell Cox is a Visiting Professor, Conservatoire National des Arts et Metiers, Paris and the author of “War on the Dream: How Anti-Sprawl Policy Threatens the Quality of Life.”

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Note 1: Each of the transit legacy cities has a lower population than the surrounding suburbs. This ranges from nearly 45 percent of the population in the suburbs of the New York metropolitan area to little more than 10 percent in Washington.

Note 2: Within the first 30 days of my time on the Los Angeles County Transportation Commission, I became convinced that transit's principal problem was cost control (see Toward More Prosperous Cities). This was then and today remains clear from the above-inflationary escalation of unit costs. Regrettably that trend continues today and has seriously impeded transit's ability to increase ridership.

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Photo: Downtown Philadelphia (by author)

The New Places Where America's Tech Future Is Taking Shape

Joel Kotkin — Thu, 10 Jan 2013 11:46:13 -0500

Technology is reshaping our economic geography, but there’s disagreement as to how. Much of the media and pundits like Richard Florida assert that the tech revolution is bound to be centralized in the dense, often “hip” places where “smart” people cluster. Some, like Slate’s David Talbot, even fear the new tech wave may erode whatever soul is left to increasingly family free, neo-gilded age San Francisco.

Such claims have been bolstered by the tech boom of the past few years — especially the explosion of social media firms in places like Manhattan and San Francisco. Yet longer-term trends in tech employment suggest such favored media memes will ultimately prove well off the mark. Indeed, according to an analysis by the Praxis Strategy Group, the fastest growth over the past decade in STEM (science, technology, engineering and mathematics-related) employment has taken place not in the most fashionable cities but smaller, less dense metropolitan areas.

From 2001 to 2012, STEM employment actually was essentially flat in the San Francisco and Boston regions and declined 12.6% in San Jose. The country’s three largest mega regions — Chicago, New York and Los Angeles — all lost tech jobs over the past decade. In contrast, double-digit rate expansions of tech employment have occurred in lower-density metro areas such as Austin, Texas; Raleigh, N.C.; Columbus, Ohio; Houston and Salt Lake City. Indeed, among the larger established tech regions, the only real winners have been Seattle, with its diversified and heavily suburbanized economy, and greater Washington, D.C., the parasitical beneficiary of an ever-expanding federal power, where the number of STEM jobs grew 21% from 2001 to 2012, better than any other of the 51 largest U.S. metropolitan statistical areas over that period.

The question is whether the last two to three years, during which places like San Francisco, New York and Boston have enjoyed stronger STEM growth than their peripheries, represents a paradigm shift or is just a cyclical phenomenon. As with tech in general, the long-term trends are not so city-centric; over the past decade, the core counties nationwide overall have lost about 1.1% of their tech jobs while more peripheral areas have experienced a gain of 3.5%.

Today’s urban tech boom looks a lot like a rerun of the dot-com boom of the late 1990s. In that period media-savvy dot-com startups proliferated in such places as South of Market in San Francisco and the Silicon Alley in lower Manhattan. At their height, these firms and their founders were as likely to be covered in the fashion and lifestyle sections as on the business pages.

Yet by the early 2000s, many of these dot-com darlings had merged, been acquired or simply gone out of business. Anchored largely on hype, they fell victim to flawed business models, and rapid industry consolidation. In San Francisco, for example, tech employment crashed from a high of 34,000 in 2000 to barely 18,000 four years later. Silicon Alley suffered a similar downward trajectory, losing 15,000 of its 50,000 information jobs in the first five years of the decade.

The peaking social media boom, marked by the weak performance of Facebook’s IPO last year, suggest another bust at the end of the “hype cycle.” Urban darlings such as San Francisco’s Zynga and Chicago’s Groupon have floundered in spectacular fashion. More are likely to join them.

These firms may have generated buzz, but they have done not so well at the mundane task of making money. One problem may be that the most avid users of social media are largely young people from the “screwed” generation who lack much in the way of spending power — a clear turnoff to advertisers. Now , with venture capital flows declining overall, cooler heads in the Valley are shifting bets to more business-oriented engineering and research-intensive fields more grounded in marketplace realities.

And what about the future of the Valley — still home to virtually all the Bay Area’s top tech firms? Its glory days as a job generator and economic exemplar seem to have passed. Between 1970 and 1990 the number of people employed in tech in the Valley more than doubled to 268,000, and then burgeoned to over 540,000 in the 1990s. At the peak of the last tech boom in 2001, the unemployment rate in Santa Clara County was a tiny 3%; the Silicon Valley Manufacturing Group confidently predicted there would be another 200,000 jobs by 2010.

However, at what may be the peak of the current boom, the number of tech jobs in the Valley remains down from a decade ago and unemployment is over 7.7%, just around the national average. In reality, social media was never going to reverse the downward trajectory in the rate of job growth. Old-line companies like Hewlett-Packard or Intel, with over 50,000 employees in the U.S. alone, were capable of creating a broad range of opportunities for workers; in contrast, the social media big three of Facebook, LinkedIn and Twitter together have less than 6,500 employees.

As the social media industry matures and consolidates, employment is likely to continue shifting to less expensive, business-friendly areas. The Bay Area, where the overall cost of living is 68% higher than the national average and housing is the most expensive in the nation, may continue to attract and retain only the highest-end, best-paid workers. But for the most part they will follow the path of established tech firms such as Apple, Intel, Adobe, eBay and IBM to lower-cost places like Austin, Columbus and Salt Lake City. A similar phenomena also can be seen in other urban-centered industries, such as entertainment and finance where virtually all employment growth is in places like St. Louis, Des Moines and Phoenix, even as the largest centers, New York, Chicago, Boston, Los Angeles and San Francisco have suffered significant job losses.

Demographic forces may further accelerate these trends. The critical fuel for tech growth, educated labor, is now expanding faster in places like Columbus, Austin, Raleigh, Dallas and Houston than in Boston, San Jose and San Francisco. The old centers may still enjoy a lead in brains, but other places are catching up rapidly.

Companies may also discover that with many millennials starting to hit their 30s, some may seek to leave their apartments to buy houses and start families. In California new local regulations essentially ban the construction of new single-family homes in some of the state’s biggest metro areas, pricing this option out of reach for all but a few, and forcing a key demographic group to seek residence elsewhere.

Under these conditions, Silicon Valley will be forced to rely increasingly on inertia and mustering of financial resources than innovation. As a result, the nation’s tech map will continue to expand from the Bay Area, Boston, Seattle and Southern California to emerging metropolitan areas in North Carolina, Texas, Utah, Colorado and the Pacific Northwest. In the future parts of Florida, Phoenix, and even Great Plains cities like Sioux Falls and Fargo could also achieve some critical mass.

Ultimately, one of the main dynamics of the information age — that even sophisticated tasks can be done from anywhere — works against the dominion of single hegemonic industry centers like Wall Street, Hollywood and Silicon Valley. The tech sector is particularly vulnerable to declustering, due in large part thanks to the freedom from geography created by technologies of its own making. Silicon Valley may continue to reap riches from the periodic technology gold rush , but in the longer term, tech growth will continue its long-term dispersion to ever more parts of the country.

STEM Occupations in the Nation's 51 Largest Metropolitan Areas
MSA Name	2001 - 2012 Growth	2005 - 2012 Growth	2010 - 2012 Growth	2012 Location Quotient	LQ Change, 2001 - 2012
Washington-Arlington-Alexandria, DC-VA-MD-WV	21.1%	12.7%	3.7%	2.19	10.6%
Riverside-San Bernardino-Ontario, CA	18.6%	-1.4%	2.2%	0.57	1.8%
San Antonio-New Braunfels, TX	18.3%	17.2%	4.5%	0.83	1.2%
Baltimore-Towson, MD	17.9%	11.4%	3.9%	1.37	15.1%
Raleigh-Cary, NC	17.9%	14.6%	6.2%	1.53	0.0%
Las Vegas-Paradise, NV	17.2%	-2.6%	0.8%	0.52	4.0%
Salt Lake City, UT	16.3%	18.1%	7.4%	1.16	4.5%
Houston-Sugar Land-Baytown, TX	15.7%	17.2%	6.6%	1.20	-2.4%
Seattle-Tacoma-Bellevue, WA	15.4%	22.2%	6.7%	1.86	8.1%
Jacksonville, FL	13.0%	6.5%	2.4%	0.87	8.7%
Austin-Round Rock-San Marcos, TX	12.2%	17.2%	9.1%	1.82	-8.5%
San Diego-Carlsbad-San Marcos, CA	11.3%	8.0%	2.1%	1.38	6.2%
Columbus, OH	10.4%	12.8%	4.7%	1.27	7.6%
Orlando-Kissimmee-Sanford, FL	9.4%	-1.1%	0.8%	0.84	-3.4%
Indianapolis-Carmel, IN	6.9%	6.5%	2.7%	1.04	2.0%
Nashville-Davidson--Murfreesboro--Franklin, TN	6.7%	3.5%	2.4%	0.77	-1.3%
Sacramento--Arden-Arcade--Roseville, CA	6.4%	3.5%	0.4%	1.33	2.3%
Oklahoma City, OK	5.5%	9.6%	6.4%	0.89	-1.1%
Pittsburgh, PA	5.3%	10.3%	4.9%	1.07	5.9%
Virginia Beach-Norfolk-Newport News, VA-NC	4.8%	2.3%	0.5%	1.10	3.8%
Charlotte-Gastonia-Rock Hill, NC-SC	4.3%	8.2%	5.7%	0.99	-3.9%
Kansas City, MO-KS	4.0%	5.8%	4.6%	1.12	4.7%
Richmond, VA	3.8%	4.4%	3.4%	0.99	0.0%
Cincinnati-Middletown, OH-KY-IN	3.7%	5.5%	6.8%	1.02	4.1%
Buffalo-Niagara Falls, NY	3.2%	6.4%	3.6%	0.90	4.7%
Dallas-Fort Worth-Arlington, TX	3.1%	11.4%	5.5%	1.19	-5.6%
San Francisco-Oakland-Fremont, CA	2.5%	15.0%	9.9%	1.63	5.8%
Phoenix-Mesa-Glendale, AZ	2.3%	3.5%	3.9%	1.05	-6.3%
Minneapolis-St. Paul-Bloomington, MN-WI	2.2%	6.7%	5.9%	1.31	1.6%
Portland-Vancouver-Hillsboro, OR-WA	1.6%	6.4%	5.4%	1.19	-3.3%
Louisville/Jefferson County, KY-IN	0.9%	9.6%	6.9%	0.76	0.0%
Denver-Aurora-Broomfield, CO	0.5%	10.8%	3.7%	1.43	-2.1%
Atlanta-Sandy Springs-Marietta, GA	-1.0%	5.5%	6.5%	1.07	-2.7%
Boston-Cambridge-Quincy, MA-NH	-1.3%	11.2%	6.0%	1.64	-1.2%
Providence-New Bedford-Fall River, RI-MA	-1.5%	-1.6%	1.9%	0.88	2.3%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	-2.8%	-1.4%	1.4%	1.06	-1.9%
Hartford-West Hartford-East Hartford, CT	-4.5%	1.5%	0.3%	1.10	-3.5%
New York-Northern New Jersey-Long Island, NY-NJ-PA	-4.6%	2.8%	3.2%	0.90	-6.2%
St. Louis, MO-IL	-4.8%	-1.7%	1.4%	1.05	-0.9%
Milwaukee-Waukesha-West Allis, WI	-6.1%	-0.8%	4.0%	1.00	0.0%
Tampa-St. Petersburg-Clearwater, FL	-6.3%	-4.3%	2.5%	0.89	-3.3%
Miami-Fort Lauderdale-Pompano Beach, FL	-6.4%	-8.3%	0.6%	0.67	-8.2%
Los Angeles-Long Beach-Santa Ana, CA	-7.1%	-3.5%	3.1%	0.98	-5.8%
Memphis, TN-MS-AR	-7.3%	-4.0%	0.7%	0.62	-4.6%
Cleveland-Elyria-Mentor, OH	-8.8%	-2.1%	4.3%	0.89	1.1%
Chicago-Joliet-Naperville, IL-IN-WI	-10.8%	-1.4%	3.5%	0.87	-7.4%
Birmingham-Hoover, AL	-11.4%	-8.0%	-2.0%	0.76	-8.4%
Rochester, NY	-12.0%	-2.1%	4.1%	1.14	-10.2%
San Jose-Sunnyvale-Santa Clara, CA	-12.6%	12.4%	8.3%	3.18	-4.8%
New Orleans-Metairie-Kenner, LA	-16.0%	-7.4%	-2.4%	0.74	0.0%
Detroit-Warren-Livonia, MI	-17.7%	-10.3%	10.5%	1.42	-3.4%
Analysis by Mark Schill, Praxis Strategy Group
Data Source: EMSI 2012.4 Class of Worker - QCEW Employees, Non-QCEW Employees & Self-Employed

The LQ (location quotient) figure in the table above is the local share of jobs that are STEM occupations divided by the national share of jobs that are STEM occupations. A concentration of 1.0 indicates that a region has the same concentration of STEM occupations as the nation. The analysis covers 80 STEM occupations in all industries.

Joel Kotkin is executive editor of NewGeography.com and a distinguished presidential fellow in urban futures at Chapman University, and a member of the editorial board of the Orange County Register . He is author of The City: A Global History and The Next Hundred Million: America in 2050. His most recent study, The Rise of Postfamilialism, has been widely discussed and distributed internationally. He lives in Los Angeles, CA.

This piece originally appeared at Forbes.com.

Computer engineer photo by BigStockPhoto.com.

The Drive-It-Yourself Taxi: A Smooth Ride?

Scott Le Vine — Sat, 05 Jan 2013 10:07:02 -0500

Despite a corporate sponsor that paid handsomely for the naming rights, Londoners stubbornly refer to our bikesharing system as ‘Boris Bikes’, in a nod to our colourful Mayor, Boris Johnson. But what will we call our new drive-it-yourself taxis? My suggestion: ‘Boris Cabs’ – and they are now a reality here, thanks to Daimler’s car2go service, if you happen to live in one of three small and separate sections of town. But why did a one-way carsharing system have to limp into London, when more than a dozen other cities have welcomed these arrangements with open arms? In the US, car2go first appeared in Austin, Texas, and since then has moved into Washington, D.C, Miami, Portland Oregon, San Francisco, San Diego, and Seattle. It operates in Canada and, on the Continent, in Paris and Amsterdam, among other locations. So why no splashy launch across England's Capital, and no images of a smiling Boris cutting a ribbon?

First, roads in London are balkanised. Our regional transport agency (Transport for London) runs the main arteries, and they provide little on-street parking, the mother’s milk of one-way carsharing. That leaves the local streets in the the domain of the 33 boroughs that are each independent municipalities. Car2go is making a brave attempt to get off the ground here by starting with hundreds of cars (the press release reports 500; in practice,170 are in operation two weeks after the launch) in disconnected sections of town, something it has not resorted to anywhere else. Its standard practice is to strike a city-wide deal with whoever’s in charge of on-street parking, and no single agency fits that bill here. What’s the rush? Well, BMW is hot on their heels with its competing DriveNow system, with staff in London well into the advanced stages of planning.

Second, there is genuine uncertainty about the impacts". Will we take drive-it-yourself cabs to work, and avoid the crush on the Tube? It would be a very different experience than traditional carsharing — London is said to be Zipcar’s second-biggest market after NYC — which doesn’t work for the daily commute. In the Zipcar model (soon to be the 'Zipcar by Avis' model?) you take a car on a round-trip basis and pay by the hour, like filling a parking meter. The novelty of this new generation of drive-yourself cabs lies in their flexibility: as with a taxi meter, you pay by the minute for just the time it takes you to get from ‘A’ to ‘B’, then drop the car off and forget about it.

What does this mean for traffic congestion? CO2 emissions? What about the cute blue-and-white Smart Fortwo-model cars now parked in your neighbourhood – will they mean less parking for private car owners? Not bloody likely. The expectation is that, in time, enough private car owners will switch to using the fleet’s cars, meaning that on balance fewer cars will need to be parked. But try explaining this to car2go’s new neighbours who are not familiar with the subtleties and will be the ones dealing with the growing pains as we feel our way forward.

Transport is a long game, so it will be years until we properly understand the impacts of drive-yourself cabs. My research suggests that likely impacts are:

1) A much larger market than traditional carsharing (about four times as many subscribers)
2) A roughly 4% reduction in personal car ownership
3) About a 1% decrease in car driving vehicle miles travelled (including personal cars, traditional carsharing, and drive-yourself cabs)
4) About a 1% decrease in the number of public transport journeys

We can be reasonably certain that some surprising impacts will be revealed during field trials, and if at some future point London’s authorities are not happy with the knock-on effects there’s nothing to stop us from regulating the industry like any other. But for the moment we don’t understand it well enough to do anything other than let the operators experiment and keep tabs on what’s happening.

We just don’t know what the impacts on traffic levels and CO2 will turn out to be, and, frankly, it’s unfair to – as some suggest – hold the industry to a no-net-traffic/CO2 standard. We don’t do that to Black Cabs or [advance-booking-only] minicabs, or indeed to the automotive or urban transport sectors more broadly. A fairer standard, admittedly more complex to administer, would be to assess whether net value is created after accounting for effects on traffic levels, emissions and more. In other words: get the prices right, just like the economics textbooks say.

The question that needs thinking through is what would transport in London look like if drive-yourself taxi systems went viral and we came to depend on them. What happens, for instance, when instead of 500 of these cabs there are 50,000, and the necessary communication links go down? How would the transport system work if on-road congestion became replaced by virtual queuing to get access to a car? And what about times when the system is under stress, like when a hurricane is approaching, for instance. Is it OK to just flip the switch off on the whole fleet? Who would make this decision, and what guidelines would they follow?

If the history of the car in cities has taught us anything, it is that we need to be humble about our ability to forecast the future. So what is the way forward for Boris Cabs in London? Start with a small fleet and short-duration contracts. Be clear on the objectives and flexible on the implementation. Keep our options open. It will be an interesting ride.

Scott Le Vine, AICP is a research associate in transport systems at Imperial College London and a trustee of the shared-mobility NGO Carplus, which serves as the UK’s carsharing trade body. He authored the recent study Car Rental 2.0: Car club [carsharing] innovations and why they matter.

Flickr photo: Car 2 Go in the 1700 block of Q Street, NW, Washington DC on Easter Sunday, 8 April 2012 by Elvert Barnes Photography

Where Americans Are Moving

Joel Kotkin — Tue, 27 Nov 2012 12:23:36 -0500

The red states may have lost the presidential election, but they are winning new residents, largely at the expense of their politically successful blue counterparts. For all the talk of how the Great Recession has driven people — particularly the “footloose young” — toward dense urban centers, Census data reveal that Americans are still drawn to the same sprawling Sun Belt regions as before.

An analysis of domestic migration for the nation’s 51 largest metropolitan statistical areas by demographer Wendell Cox shows that the 10 metropolises with the largest net gains from 2000 through 2009 are in the Sun Belt, led by Phoenix, and followed by Riverside-San Bernardino, Calif.; Atlanta; Dallas-Ft. Worth; and Las Vegas.

Migration has slowed from a high of nearly 2 million annually in 2006 to less than 800,000 last year, but the most recent numbers show that the Sun Belt states, though chastened by the recession, are far from dead, as often alleged. This part of America, widely consigned to what the Bolshevik firebrand Leon Trotsky called the “dustbin of history” by Eastern pundits, somehow manages to continue to draw Americans seeking opportunities, in particular from the large coastal metropolitan regions.

Migration data for the most recent one-year period available, July 2010 t0 July 2011, show the Great Recession has shaken the rankings up quite a bit within the circle of fast-growth regions. The biggest winner has been Texas. The Lone Star state boasts four of the 10 metro areas with the largest net migration gains for the past two years. Dallas ranks first, followed by Austin in third place, Houston in fifth and San Antonio in eighth. In contrast, some of the growth leaders over the 2000-09 period, notably Las Vegas, and to a lesser extent Phoenix, have tumbled considerably in the rankings. The lesson here: a strong economy has to be based on something more than gaming, tourism and home construction. Energy, technology, manufacturing and trade are far preferable as an economic base.

Also posting strong net migration gains for 2010-11 were Miami (second place), Washington, D.C. (sixth), and Seattle (ninth). In each of these areas, economic conditions appear to have improved. The once disastrous condo glut in the Miami area, which includes Dade, Broward and Palm Beach counties, has begun to clear up as foreign buyers pour into the region. Taxpayer-funded Washington is surging with new jobs and the highest incomes in the land. Seattle continues a long-term evolution toward the healthiest of the blue-state private economies. San Francisco, a consistent big loser for the last decade, jumped to 19th, presumably as a result of the current dot.com bubble.

Another huge turnaround can be seen in New Orleans, which ranked a dismal 43rd for 2000-09 as residents fled not only Katrina but a stagnant, low-wage, corruption-plagued economy. But in our 2010-11 ranking, the Crescent City surged to a respectable 16th, one of the biggest migration turnarounds in the country.

How about the biggest losers? From 2000-09, the metropolitan areas that suffered the biggest net domestic migration losses resemble something of an urbanist dream team: New York, which saw a net outflow of a whopping 1.9 million citizens, followed by the Los Angeles metro area (-1,337,522), Chicago, Detroit, and, despite recent improvements, San Francisco-Oakland. The raw numbers make it clear that California has lost its appeal for migrants from other parts of the U.S., and has become an exporter of people and talent (and income).

And despite the cheap money Bernanke-Geithner policies of the past few years that have benefited giant banks centered in the bluest big cities, people continue to leave these areas. The 2010-11 numbers show the deck chairs on the migratory titanic have stayed remarkably similar, with New York still ranking first among the 51 biggest metro areas for net migration losses, followed by Chicago, Los Angeles, Detroit and Philadelphia. In most of these cases only immigration from abroad, and children of immigrants, have prevented a wholesale demographic decline.

What can we expect now? It seems clear that the urban-centric policies of the Obama administration have not changed Americans’ migration patterns. The weak recovery has slowed migration, but expensive, overregulated and dense metropolitan areas continue to lose population to lower-cost, less regulated and generally less dense regions. This may speed up as recent tax hikes squeeze the hard-pressed middle class and if, as appears likely, the social media bubble continues to deflate.

If the economy somehow gains strength, it may only serve to further accelerate these trends. The incipient recovery in housing prices seems likely, at least in places like California and the Northeast, to create yet another bubble. This will give people more incentive to move to less expensive areas, particularly those who can cash in by selling a house in a pricier city and moving to a less expensive one. The differential in housing costs between New York and Tampa-St. Petersburg now stands at historic highs, and near peak bubble highs between Los Angeles and Phoenix; the traditional growth states are looking more attractive all the time for people looking to make quick money in an economy with shrinking opportunities elsewhere. This includes the massive wave of aging boomers, many of whom may see selling a house in California or the Northeast as a way to make up for less than adequate IRAs. The combination of low prices and warmer weather in the past has proven an irresistible one for those retiring or simply down-shifting their careers. This appeal is likely to grow as the senior population expands.

Other demographic factors could further drive this trend. As the millennial generation ages and starts looking for places to buy homes and raise families, many will seek out places that are both affordable and offer better economic opportunities. These will tend to be in the South and Southwest, particularly Texas, and Plains States metro areas such as Oklahoma City.

Finally we can expect immigrants, particularly from Asia, to continue to seek out housing bargains and new opportunities primarily in the Sun Belt states, as our recent study of changing Asian settlement patterns revealed. More will be shifting from the high-priced, low-growth big metros for opportunity cities such as Houston, Dallas-Fort Worth, Raleigh and Charlotte.

Overall we can expect domestic migration to pick up, and to follow the well-trodden path from the great cities of the Northeast and California to the Sun Belt’s resurgent boom towns. This may be bad news to many urban pundits and big city speculators, but it also should create new opportunities for more perceptive, and less jaded, investors.

2010-2011 Net Domestic Migration for the Nation's 51 Largest Regions
Rank by Net Flow	Metropolitan Area	Net Flow	Rate Per 1,000 Residents	Rank by Rate
1	Dallas-Fort Worth-Arlington, TX	39,021	6.04	10
2	Miami-Fort Lauderdale-Pompano Beach, FL	36,191	6.43	9
3	Austin-Round Rock-San Marcos, TX	30,669	17.47	1
4	Tampa-St. Petersburg-Clearwater, FL	27,157	9.68	3
5	Houston-Sugar Land-Baytown, TX	21,580	3.58	16
6	Washington-Arlington-Alexandria, DC-VA-MD-WV	21,517	3.80	15
7	Denver-Aurora-Broomfield, CO	19,565	7.59	7
8	San Antonio-New Braunfels, TX	19,515	8.97	4
9	Seattle-Tacoma-Bellevue, WA	17,598	5.07	13
10	Riverside-San Bernardino-Ontario, CA	15,131	3.54	17
11	Charlotte-Gastonia-Rock Hill, NC-SC	13,778	7.74	6
12	Raleigh-Cary, NC	13,262	11.53	2
13	Atlanta-Sandy Springs-Marietta, GA	12,419	2.33	18
14	Portland-Vancouver-Hillsboro, OR-WA	11,388	5.07	12
15	Orlando-Kissimmee-Sanford, FL	10,394	4.82	14
16	New Orleans-Metairie-Kenner, LA	10,153	8.59	5
17	Nashville-Davidson--Murfreesboro--Franklin, TN	9,323	5.81	11
18	Oklahoma City, OK	8,746	6.90	8
19	San Francisco-Oakland-Fremont, CA	5,880	1.35	22
20	Phoenix-Mesa-Glendale, AZ	5,585	1.32	24
21	Pittsburgh, PA	3,740	1.59	20
22	Jacksonville, FL	2,911	2.15	19
23	Sacramento--Arden-Arcade--Roseville, CA	2,856	1.32	23
24	Columbus, OH	2,219	1.20	26
25	Indianapolis-Carmel, IN	1,940	1.10	27
26	Louisville/Jefferson County, KY-IN	1,886	1.46	21
27	Richmond, VA	1,546	1.22	25
28	Salt Lake City, UT	915	0.80	28
29	San Diego-Carlsbad-San Marcos, CA	816	0.26	29
30	Minneapolis-St. Paul-Bloomington, MN-WI	536	0.16	30
31	Baltimore-Towson, MD	-1,341	-0.49	32
32	Boston-Cambridge-Quincy, MA-NH	-1,627	-0.36	31
33	Birmingham-Hoover, AL	-2,452	-2.17	35
34	Buffalo-Niagara Falls, NY	-2,558	-2.25	38
35	San Jose-Sunnyvale-Santa Clara, CA	-2,704	-1.46	34
36	Kansas City, MO-KS	-2,820	-1.38	33
37	Memphis, TN-MS-AR	-2,933	-2.22	37
38	Rochester, NY	-3,320	-3.15	40
39	Hartford-West Hartford-East Hartford, CT	-4,749	-3.92	45
40	Milwaukee-Waukesha-West Allis, WI	-4,862	-3.12	39
41	Providence-New Bedford-Fall River, RI-MA	-6,254	-3.91	44
42	Las Vegas-Paradise, NV	-6,353	-3.24	41
43	Virginia Beach-Norfolk-Newport News, VA-NC	-7,086	-4.22	47
44	Cincinnati-Middletown, OH-KY-IN	-7,149	-3.35	42
45	St. Louis, MO-IL	-10,260	-3.64	43
46	Cleveland-Elyria-Mentor, OH	-12,521	-6.04	51
47	Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	-13,133	-2.20	36
48	Detroit-Warren-Livonia, MI	-24,170	-5.64	49
49	Los Angeles-Long Beach-Santa Ana, CA	-50,549	-3.92	46
50	Chicago-Joliet-Naperville, IL-IN-WI	-53,908	-5.68	50
51	New York-Northern New Jersey-Long Island, NY-NJ-PA	-98,975	-5.22	48

Joel Kotkin is executive editor of NewGeography.com and is a distinguished presidential fellow in urban futures at Chapman University, and contributing editor to the City Journal in New York. He is author of The City: A Global History. His newest book is The Next Hundred Million: America in 2050, released in February, 2010.

This piece originally appeared at Forbes.

Dallas photo by Bigstock.

Flocking Elsewhere: The Downtown Growth Story

Wendell Cox — Mon, 01 Oct 2012 01:38:19 -0400

The United States Census Bureau has released a report (Patterns of Metropolitan and Micropolitan Population Change: 2000 to 2010.) on metropolitan area growth between 2000 and 2010. The Census Bureau's the news release highlighted population growth in downtown areas, which it defines as within two miles of the city hall of the largest municipality in each metropolitan area. Predictably, media sources that interpret any improvement in core city fortunes as evidence of people returning to the cities (from which they never came), referred to people "flocking" back to the "city" (See here and here, for example).

Downtown Population Trends: Make no mistake about it, the central cores of the nation's largest cities are doing better than at any time in recent history. Much of the credit has to go to successful efforts to make crime infested urban cores suitable for habitation, which started with the strong law enforcement policies of former New York Mayor Rudy Giuliani.

However, to characterize the trend since 2000 as reflective of any "flocking" to the cities is to exaggerate the trend of downtown improvement beyond recognition. Among the 51 major metropolitan areas (those with more than 1 million population), nearly 99 percent of all population growth between 2000 and 2010 was outside the downtown areas (Figure 1).

There was population growth in 33 downtown areas out of the 51 major metropolitan areas. As is typical for core urban measures, nearly 80 percent of this population growth was concentrated in the six most vibrant downtown areas, New York, Chicago, Philadelphia, Washington, Boston and San Francisco.

If the next six fastest-growing downtown areas are added to the list (Dallas-Fort Worth, Houston, Los Angeles, Portland, San Diego and Seattle), downtown growth exceeds the national total of 205,000 people, because the other 39 downtown areas had a net population loss. Overall, the average downtown area in the major metropolitan areas grew by 4000 people between 2000 and 2010. That may be a lot of people for a college lacrosse game, but not for a city. While in some cases these increases were substantial in percentage terms, the population base was generally small, which was the result of huge population losses in previous decades as well as the conversion of old disused office buildings, warehouses and factories into residential units.

Trends in the Larger Urban Cores: The downtown population gains, however, were not sufficient to stem the continuing decline in urban core populations. Among the 51 major metropolitan areas, the aggregate data indicates a loss of population within six miles of city hall. In essence, the oasis of modest downtown growth was more than negated by losses surrounding the downtown areas. Virtually all the population growth in the major metropolitan areas lay outside the six mile radius core, as areas within the historical urban core, including downtown, lost 0.4 percent.

Even when the radius is expanded to 10 miles, the overwhelming majority of growth remains outside. Approximately 94 percent of the aggregate population growth of the major metropolitan areas occurred more than 10 miles from downtown (Figure 2). Figure 3 shows that more than one-half of the growth occurred 20 miles and further from city hall. Further, the population growth beyond 10 miles (10-15 mile radius, 15-20 miles radius and 20 mile and greater radius) from the core exceeded the (2000) share of population, showing the continuing dispersal of American metropolitan areas (Figure 4).

Chicago: The Champion? The Census Bureau press release highlights the fact that downtown Chicago experienced the largest gain in the nation. Downtown Chicago accounted for 13 percent of the metropolitan area's growth with an impressive 48,000 new residents. However, while downtown Chicago was prospering, people were flocking away from the rest of the city. Within a five mile radius of the Loop, there was a net population loss of 12,000 and a net loss of more than 200,000 within 20 miles (Figure 5). Only within the 36th mile radius from city hall is there a net population gain.

Cleveland: Comeback City and Always Will Be? In view of Cleveland’s demographic decline (down from 915,000 in 1950 to 397,000 in 2010), any progress in downtown Cleveland is welcome. But despite the frequently recurring reports, downtown Cleveland's population growth was barely 3,000. Despite this gain, the loss within a 6 mile radius was 70,000 and 125,000 within a 12 mile radius. Beyond the 12- mile radius, there was a population increase of nearly 55,000, which insufficient to avoid a metropolitan area population loss.

Other Metropolitan Areas: A total of 30 major metropolitan areas suffered core population losses, despite the fact that many had downtown population increases.

Five major metropolitan areas suffered overall population losses (Buffalo, Cleveland, Detroit, Pittsburgh and Katrina ravaged New Orleans).
St. Louis, with a core city that holds the modern international record for population loss (from 857,000 in 1950 to 319,000 in 2010), experienced a population decline within a 27 mile radius of city hall. Approximately 150 percent of the growth in the St. Louis metropolitan area was outside the 27 mile radius. Even so, there was an increase of nearly 6,000 in the population of downtown St. Louis.
There were population losses all the way out to a considerable distance from city halls in Memphis (16 mile radius), Cincinnati (15 mile radius) and Birmingham (14 mile radius). The three corresponding downtown areas also lost population.
Despite having one of the strongest downtown population increases (12,000), population declined within a 10 mile radius of the Dallas city hall. This contrasts with nearby Houston, which also experienced a strong downtown increase (10,000) but no losses at any radius of the urban core.
Milwaukee experienced a small downtown population increase (2,000), but had a population loss within an11 mile radius.

The other 21 major metropolitan areas experienced population gains throughout. Even so, most of the growth (77 percent) was outside the 10 mile radius. San Jose had the most concentrated growth, with only 24 percent outside a 10 miles radius from city hall. All of the other metropolitan areas had 60 percent or more of their growth outside a 10 mile radius from city hall.

As we have observed before, 2000 to 2010 was, unlike the 1970s and other decades, more friendly to the nation's core cities, although less so than the previous decade. Due to the repurposing of old offices and other structures, sometimes aided by subsidies, small downtown slivers may have done better than at any time since before World War II. But the data is clear. Suburban growth was stronger in the 2000s than in the 1990s. The one percent flocked to downtown and the 99 percent flocked to outside downtown.

Population Loss Radius: Major Metropolitan Areas
Miles from City Hall of Historical Core Municipality*

Major Metropolitan Areas (Over 1,000,000 Population	Share of Metropolitan Growth			Population Loss Radius (Miles)
Major Metropolitan Areas (Over 1,000,000 Population	"Outside Downtown" (2- Mile Radius)	Outside 5-Mile Radius	Outside 10-Mile Radius	Population Loss Radius (Miles)

MAJOR METROPOLITAN AREAS: TOTAL	98.7%	100.4%	93.5%	6

Atlanta, GA	99.6%	101.1%	99.9%	9
Austin, TX	98.1%	96.7%	81.9%	0
Baltimore, MD	106.5%	118.7%	99.5%	9
Birmingham, AL	104.2%	132.5%	124.9%	14
Boston, MA-NH	90.8%	76.9%	67.3%	0
Buffalo, NY	Entire Metropolitan Area Loss
Charlotte, NC-SC	99.1%	97.4%	75.0%	3
Chicago, IL-IN-WI	86.7%	103.3%	144.6%	35
Cincinnati, OH-KY-IN	105.1%	126.8%	135.2%	15
Cleveland, OH	Entire Metropolitan Area Loss
Columbus, OH	100.5%	104.3%	86.9%	7
Dallas-Fort Worth, TX	99.0%	101.0%	100.7%	10
Denver, CO	98.0%	100.3%	89.8%	5
Detroit, MI	Entire Metropolitan Area Loss
Hartford, CT	99.2%	92.7%	67.2%	0
Houston, TX	99.2%	99.5%	98.0%	0
Indianapolis. IN	102.1%	112.1%	89.6%	8
Jacksonville, FL	100.2%	106.3%	85.3%	8
Kansas City, MO-KS	99.5%	109.0%	113.3%	12
Las Vegas, NV	101.4%	98.0%	63.6%	4
Los Angeles, CA	97.3%	102.2%	97.6%	8
Louisville, KY-IN	102.5%	108.5%	90.9%	8
Memphis, TN-MS-AR	101.2%	118.5%	143.5%	16
Miami, FL	99.4%	93.0%	91.3%	0
Milwaukee,WI	95.9%	109.0%	107.5%	11
Minneapolis-St. Paul, MN-WI	97.4%	99.2%	100.1%	7
Nashville, TN	100.0%	101.4%	92.4%	7
New Orleans. LA	Entire Metropolitan Area Loss
New York, NY-NJ-PA	93.5%	81.7%	68.9%	0
Oklahoma City, OK	100.1%	96.8%	83.5%	2
Orlando, FL	99.7%	99.4%	84.2%	0
Philadelphia, PA-NJ-DE-MD	92.6%	98.8%	96.3%	7
Phoenix, AZ	100.7%	101.8%	93.6%	6
Pittsburgh, PA	Entire Metropolitan Area Loss
Portland, OR-WA	95.0%	91.5%	62.7%	0
Providence, RI-MA	96.2%	91.7%	70.1%	0
Raleigh, NC	99.6%	93.0%	67.7%	0
Richmond, VA	95.7%	91.7%	70.2%	0
Riverside-San Bernardino, CA	99.5%	97.2%	85.8%	0
Rochester, NY	146.9%	149.3%	82.5%	9
Sacramento, CA	99.9%	94.4%	79.5%	0
Salt Lake City, UT	98.9%	95.1%	84.1%	0
San Antonio, TX	101.1%	102.5%	86.7%	7
San Diego, CA	96.3%	94.1%	90.1%	0
San Francisco-Oakland, CA	90.7%	87.6%	82.2%	0
San Jose, CA	95.1%	79.1%	24.3%	0
Seattle, WA	96.5%	91.9%	81.4%	0
St. Louis,, MO-IL	94.8%	119.7%	148.9%	27
Tampa-St. Petersburg, FL	98.6%	97.8%	83.7%	0
Virginia Beach-Norfolk, VA-NC	93.1%	90.1%	82.3%	0
Washington, DC-VA-MD-WV	97.5%	94.5%	87.9%	0

Calculated from Census Bureau data
*Except in Virginia Beach-Norfolk, Where Virginia Beach is used

-------

Notes:

Population Weighted Density: In its report, the Census Bureau uses "population-weighted density," rather than average population density to compare metropolitan areas. The Census Bureau justified this use as follows:

"Overall densities of CBSAs can be heavily affected by the size of the geographic units for which they are calculated. Metropolitan and micropolitan statistical areas are delimited using counties as their basic building blocks, and counties vary greatly across the country in terms of their geographic size. With this in mind, one way of measuring actual residential density is to examine the ratio of population to land area at the scale of the census tract, which—of all the geographic units for which decennial census data are tabulated—is typically the closest in scale to urban and suburban neighborhoods".

The Census Bureau rightly points out the problem with comparing metropolitan area density. However, it is a problem of the federal government's making, by virtue of using metropolitan area building blocks (counties) that are sometimes too large for designation of genuine metropolitan areas. These difficulties have been overcome by the national census authorities in Japan in Canada, for example, where smaller building blocks are used (such as municipalities or local government authorities).

Further, the Census Bureau already has a means for measuring population density at the census tract level, which is "the closest in scale to urban and suburban neighborhoods." This is the urban area.

"Population-weighted density" is an interesting concept that can provide an impression of the density that is perceived by the average resident of the metropolitan area. Unfortunately, in its report, the Census Bureau is less than precise with its terminology and repeatedly fails to modify the term density with the important "population-weighted" qualification. This could lead to considerable misunderstanding.

The Census Bureau did not provide average population densities based for the mileage radii. Because of large bodies of water (such as Lake Michigan in Chicago can reduce land areas, it was not possible to estimate population densities by radius.

Census Bureau Revision of Incorrect Report: We notified the Census Bureau of errors in its press release and report on September 27. The problems included substitution of San Francisco population data for Salt Lake City as well as metropolitan population in the supporting spreadsheet file. On September 28, the Census Bureau issued a revised press release and report to rectify the errors. Later the erroneous spreadsheet was withdrawn and had not been re-posted as of October 1. We have made corrections to the spreadsheet for this analysis.

Note: Larger "Downtown" Populations in Smaller Metropolitan Areas: Because of the broad 2-mile radius measure used by the Census Bureau, most of the population increase characterized as relating to downtown occurred outside the major metropolitan areas. This is simply because in smaller metropolitan areas, such an area (12.6 square miles) will necessarily contain a larger share of the metropolitan area. Further, many smaller metropolitan areas are virtually all suburban and had experienced little or no core population losses over the decades that have been so devastating to many large core municipalities. On average, 2.7 percent of the population of major metropolitan areas was within a two-mile radius of city hall in 2010. By comparison, in smaller metropolitan areas, approximately 12.7 percent of the population was within a two mile radius.

Photograph: Chicago Suburbs: (where nearly all the growth occurred), by author

A Look at Commuting Using the Latest Census Data

Aaron M. Renn — Tue, 25 Sep 2012 01:38:10 -0400

Continuing my exploration of the 2011 data from the American Community Survey, I want to look now at some aspects of commuting.

Public Transit

Public transit commuting remains overwhelmingly dominated by New York City, with a metro commute mode share for transit of 31.1%. There are an estimated 2,686,406 transit commuters in New York City. All other large metro areas (1M+ population) put together add up to 3,530,932 transit commuters. New York City metro accounts for 39% of all transit commuters in the United States.

If one were to guess the #2 city for transit commuting, another older, pre-auto, centralized city on the lines of New York (say Chicago) might be the obvious guess. It would also be wrong. It’s actually Washington, DC that has the second highest transit commute share among large metros at 14.8%. Here’s the complete top ten:

Rank	Metro Area	2011
1	New York-Northern New Jersey-Long Island, NY-NJ-PA	2,686,406 (31.1%)
2	Washington-Arlington-Alexandria, DC-VA-MD-WV	439,194 (14.8%)
3	San Francisco-Oakland-Fremont, CA	299,204 (14.6%)
4	Chicago-Joliet-Naperville, IL-IN-WI	503,535 (11.6%)
5	Boston-Cambridge-Quincy, MA-NH	267,568 (11.6%)
6	Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	251,285 (9.3%)
7	Seattle-Tacoma-Bellevue, WA	137,858 (8.1%)
8	Portland-Vancouver-Hillsboro, OR-WA	66,619 (6.3%)
9	Los Angeles-Long Beach-Santa Ana, CA	355,811 (6.2%)
10	Baltimore-Towson, MD	80,472 (6.1%)

Not only are New York and Washington top two cities for public transit commuting, they are also the two cities that have been dominant in increasing transit’s market share. Both cities showed material share gains since 2000, over three and a half percentage points each, for transit. Among large cities, Seattle was the only one that managed to post a share gain of even one percent.

Rank	Metro Area	2000	2011	Change in % of Workers Age 16 and Over
1	New York-Northern New Jersey-Long Island, NY-NJ-PA	2,181,093 (27.4%)	2,686,406 (31.1%)	3.74%
2	Washington-Arlington-Alexandria, DC-VA-MD-WV	278,842 (11.2%)	439,194 (14.8%)	3.61%
3	Seattle-Tacoma-Bellevue, WA	106,784 (7.0%)	137,858 (8.1%)	1.17%
4	Orlando-Kissimmee-Sanford, FL	12,601 (1.6%)	24,901 (2.5%)	0.91%
5	Hartford-West Hartford-East Hartford, CT	15,755 (2.8%)	21,794 (3.7%)	0.91%
6	Charlotte-Gastonia-Rock Hill, NC-SC	9,532 (1.4%)	19,227 (2.3%)	0.91%
7	San Francisco-Oakland-Fremont, CA	278,207 (13.8%)	299,204 (14.6%)	0.81%
8	Los Angeles-Long Beach-Santa Ana, CA	287,392 (5.6%)	355,811 (6.2%)	0.67%
9	Miami-Fort Lauderdale-Pompano Beach, FL	67,685 (3.2%)	95,536 (3.8%)	0.61%
10	Nashville-Davidson–Murfreesboro–Franklin, TN	5,574 (0.8%)	10,705 (1.4%)	0.55%

Vaunted Portland only managed to eke out a share gain of 0.07%, which could be entirely statistical noise. Its performance lagged even auto-centric cities like Charlotte and Nashville.

Bicycling

Every city out there seems to be vying to be the bike friendliest city in the world. Yet bicycling has yet to make much of an impact on commuting. Only 7 out of 51 large metros even post 1% mode share for cycling:

Row	Geography	2011
1	Portland-Vancouver-Hillsboro, OR-WA	23,941 (2.3%)
2	San Francisco-Oakland-Fremont, CA	38,419 (1.9%)
3	San Jose-Sunnyvale-Santa Clara, CA	16,013 (1.9%)
4	Sacramento–Arden-Arcade–Roseville, CA	15,804 (1.8%)
5	Austin-Round Rock-San Marcos, TX	8,847 (1.0%)
6	New Orleans-Metairie-Kenner, LA	5,307 (1.0%)
7	Phoenix-Mesa-Glendale, AZ	18,007 (1.0%)
8	Seattle-Tacoma-Bellevue, WA	15,949 (0.9%)
9	Denver-Aurora-Broomfield, CO	12,052 (0.9%)
10	Los Angeles-Long Beach-Santa Ana, CA	50,080 (0.9%)

Portland grew bicycle mode share by 1.51% Perhaps this explains its poor transit performance. Cycling is canabalizing transit growth.

Walking

The low level of bicycling can perhaps best be illustrated by comparing it to walking. Even in Portland more people walk to work than ride bikes.

Rank	Metro Area	2011
1	New York-Northern New Jersey-Long Island, NY-NJ-PA	540,733 (6.3%)
2	Boston-Cambridge-Quincy, MA-NH	121,537 (5.3%)
3	San Francisco-Oakland-Fremont, CA	87,409 (4.3%)
4	Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	101,107 (3.7%)
5	Seattle-Tacoma-Bellevue, WA	62,238 (3.7%)
6	Pittsburgh, PA	36,857 (3.4%)
7	Portland-Vancouver-Hillsboro, OR-WA	35,242 (3.4%)
8	Rochester, NY	15,573 (3.2%)
9	Washington-Arlington-Alexandria, DC-VA-MD-WV	94,698 (3.2%)
10	Chicago-Joliet-Naperville, IL-IN-WI	134,399 (3.1%)

Working from Home

Looking at telecommuting gives a much different list of top cities, this one dominated by “wired” metros like Austin and Raleigh. The share of telecommuters in these cities is bigger than walking or biking, or even transit in many cities. This is an oft-overlooked part of the green transport agenda. The most green commute possible is the one you never have to make.

Rank	Metro Area	2011
1	Austin-Round Rock-San Marcos, TX	62,593 (7.1%)
2	Raleigh-Cary, NC	37,030 (6.6%)
3	Portland-Vancouver-Hillsboro, OR-WA	67,223 (6.4%)
4	San Francisco-Oakland-Fremont, CA	131,029 (6.4%)
5	San Diego-Carlsbad-San Marcos, CA	89,547 (6.3%)
6	Denver-Aurora-Broomfield, CO	76,025 (5.9%)
7	Phoenix-Mesa-Glendale, AZ	105,570 (5.8%)
8	Sacramento–Arden-Arcade–Roseville, CA	52,143 (5.8%)
9	Atlanta-Sandy Springs-Marietta, GA	132,979 (5.5%)
10	Seattle-Tacoma-Bellevue, WA	87,839 (5.2%)

Commute Times

Unsurprisingly, large cities – including New York and Washington again at the top – feature the longest average commute times. Larger cities tend to have worse congestion and feature longer commutes. As transit commutes are generally longer than driving, the high transit mode share helps to drive up commute times in those cities.

Rank	Metro Area	2011
1	New York-Northern New Jersey-Long Island, NY-NJ-PA	34.9
2	Washington-Arlington-Alexandria, DC-VA-MD-WV	34.5
3	Riverside-San Bernardino-Ontario, CA	31.0
4	Chicago-Joliet-Naperville, IL-IN-WI	30.9
5	Atlanta-Sandy Springs-Marietta, GA	30.6
6	Baltimore-Towson, MD	30.3
7	Boston-Cambridge-Quincy, MA-NH	29.2
8	San Francisco-Oakland-Fremont, CA	29.2
9	Los Angeles-Long Beach-Santa Ana, CA	28.6
10	Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	28.5

Whether New York might prefer a more auto-oriented layout in order to reduce commute times is a different matter. There’s no precedent for such a huge region having anything less than terrible congestion and commute times. And clearly New York would not be New York with such a radical change. The same forces that drive up commute times in places like New York and Washington are some of the same forces that sustain them as centers of elite economic production.

Note: An early version of this piece contained an incorrect version of "Working from Home" table.

Aaron M. Renn is an independent writer on urban affairs and the creator of Telestrian, a data analysis and mapping tool. He writes at The Urbanophile.

Light trails photo by Bigstock.

Facebook’s False Promise: STEM's Quieter Side Of Tech Offers More Upside For America

Joel Kotkin — Wed, 06 Jun 2012 11:09:04 -0400

Facebook‘s botched IPO reflects not only the weakness of the stock market, but a systemic misunderstanding of where the true value of technology lies. A website that, due to superior funding and media hype, allows people to do what they were already doing — connecting on the Internet — does not inherently drive broad economic growth, even if it mints a few high-profile billionaires.

Of course Facebook is a social phenomenon that has affected how people live and interact, but its economic impact — and future level of profitability — is less than clear. This stands in sharp contrast to Apple‘s iTunes, which has become a new distribution platform for small software companies and musicians, not to mention the role of Amazon in the distribution of books and other products.

From the standpoint of economic development, it’s time to focus on the growing divergence between two different aspects of technology. One is largely an information sector that focuses on such things as information software (think Facebook or Google), publishing and entertainment. For most journalists and urban theoreticians, this is the “sexy” sector, particularly since it tends to employ people just like them: younger, products of elite college educations, often living in “hip and cool” places like San Francisco, Manhattan or west Los Angeles.

Then there’s a larger, less-heralded group of workers that my colleague Mark Schill at Praxis Strategy Group has focused on: those in STEM (science-, technology-, engineering- and mathematics-related) jobs. These workers perform technology work across a broad array of industries, including but not limited to computers, media and the Internet, representing some 5.3 million jobs in the nation’s 51 largest metropolitan areas. This compares to roughly 2.2 million jobs classified as in the information sector in these 51 regions.

These STEM occupations are about harnessing technology to improve productivity in mundane traditional industries and the service sector. STEM workers are as likely, if not more so, to be working for manufacturers, retailers or energy producers as for software firms. These workers epitomize the notion of technology, as the French sociologist Marcel Mauss once put it, as “a traditional action made effective.”

The information sector may be increasingly important, but it is STEM workers, working in a diverse set of industries (including information), who hold the broader hope for the U.S. economy. Over the past decade, the information sector has created many stars, but about as many flameouts. Overall information employment peaked in 2000 at 3.6 million jobs; by 2011 this number had dropped by almost a million. Things have not much improved even in the current “boom”; between February and May this year, the sector lost over 8,000 jobs.

Essentially the information sector has created a huge amount of churn, as the nature of its employment changes with shifts in technology. For example, the software sector within information has seen real growth, adding some 10,000 jobs the past two years, while other parts of the information sector have suffered significant drops. These include, sadly for aged scribblers, traditional publishing, such as newspapers and book publishing, which has gone from nearly 1 million jobs in 2002 to under 740,000 in May of this year.

With Facebook stock in the tank, and other major social media sites languishing, the current “boom” may prove among the shortest-lived in recent memory. Shares of less well-anchored companies — meaning those with only a vague outlook for long-term profits — such as Zynga and Groupon have fallen dramatically. The market for the next round of ultra-hyped IPOs also seems to be dissipating rapidly. The carnage has led at least one analyst to suggest Facebook’s fall could “destroy the U.S. economy.”

Fortunately the overall picture in technology is more hopeful than you’d understand from reading about social media startups. STEM employment has grown 3% over the past two years, more than twice the national average. In the 51 largest metros areas, 150,000 STEM jobs were added from 2009 through 2011. More important still, this reflects a long-term pattern: Over the past decade, STEM employment — despite a drop during the recession — expanded 5.4%.

These two different classifications underpin geographical differences between and within regions. Sometimes the “hot” areas don’t look so great when it comes to actual job creation in these generally well-paying fields.

Silicon Valley’s social media boom, for example, may have propelled it once again, at least temporarily, into the ranks of the fastest-growing employment centers. Yet it’s not seeing the gains in STEM jobs that took place during earlier Valley booms in the ’80s or ’90s that were broader based, encompassing manufacturing and industry-oriented software. Indeed STEM employment in the Valley still has not recovered from the 2001 tech bust — the number of STEM jobs is down 12.6% from 10 years ago.

Metropolitan STEM Job Growth, Sorted by 10-year Growth
MSA Name	2001-2011 Growth	2009-2011 Growth	2011 Concentration
Las Vegas-Paradise, NV	25.5%	-3.4%	0.51
Washington-Arlington-Alexandria, DC-VA-MD-WV	20.8%	4.4%	2.16
San Antonio-New Braunfels, TX	20.1%	3.0%	0.82
Nashville-Davidson--Murfreesboro--Franklin, TN	18.5%	3.1%	0.74
Riverside-San Bernardino-Ontario, CA	18.3%	-1.6%	0.55
Seattle-Tacoma-Bellevue, WA	18.1%	7.6%	1.95
Salt Lake City, UT	17.5%	4.5%	1.17
Jacksonville, FL	17.4%	3.0%	0.88
Baltimore-Towson, MD	17.2%	3.9%	1.36
Raleigh-Cary, NC	14.9%	1.4%	1.56
Houston-Sugar Land-Baytown, TX	14.3%	3.6%	1.25
Orlando-Kissimmee-Sanford, FL	14.2%	-1.4%	0.90
San Diego-Carlsbad-San Marcos, CA	13.1%	6.5%	1.38
Austin-Round Rock-San Marcos, TX	8.8%	2.4%	1.75
Charlotte-Gastonia-Rock Hill, NC-SC	8.1%	2.1%	0.97
Columbus, OH	7.8%	3.8%	1.32
Buffalo-Niagara Falls, NY	7.7%	2.4%	0.96
Virginia Beach-Norfolk-Newport News, VA-NC	7.5%	-3.1%	1.05
Miami-Fort Lauderdale-Pompano Beach, FL	7.5%	2.8%	0.73
Indianapolis-Carmel, IN	7.5%	1.2%	1.06
Oklahoma City, OK	7.3%	2.9%	0.89
Dallas-Fort Worth-Arlington, TX	6.2%	3.7%	1.21
Cincinnati-Middletown, OH-KY-IN	6.1%	4.6%	1.08
Sacramento--Arden-Arcade--Roseville, CA	6.0%	-1.6%	1.19
Louisville/Jefferson County, KY-IN	5.6%	4.3%	0.77
Phoenix-Mesa-Glendale, AZ	5.4%	1.5%	1.00
Portland-Vancouver-Hillsboro, OR-WA	5.2%	4.2%	1.24
Atlanta-Sandy Springs-Marietta, GA	4.8%	4.3%	1.10
Denver-Aurora-Broomfield, CO	4.0%	2.8%	1.47
Richmond, VA	3.8%	0.4%	1.14
Providence-New Bedford-Fall River, RI-MA	3.6%	2.4%	0.90
Pittsburgh, PA	3.1%	3.6%	1.07
Hartford-West Hartford-East Hartford, CT	3.1%	1.2%	1.18
Minneapolis-St. Paul-Bloomington, MN-WI	2.6%	3.1%	1.37
Tampa-St. Petersburg-Clearwater, FL	2.4%	2.0%	0.88
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	2.2%	0.3%	1.19
Kansas City, MO-KS	1.9%	-2.6%	1.15
New York-Northern New Jersey-Long Island, NY-NJ-PA	1.2%	2.9%	1.00
San Francisco-Oakland-Fremont, CA	0.8%	3.7%	1.60
Memphis, TN-MS-AR	0.0%	0.7%	0.56
Boston-Cambridge-Quincy, MA-NH	0.0%	4.8%	1.64
Los Angeles-Long Beach-Santa Ana, CA	-2.2%	1.7%	0.98
Milwaukee-Waukesha-West Allis, WI	-2.3%	0.2%	1.04
St. Louis, MO-IL	-3.5%	-1.4%	1.05
Birmingham-Hoover, AL	-3.9%	-3.4%	0.70
Cleveland-Elyria-Mentor, OH	-4.9%	1.2%	0.93
Chicago-Joliet-Naperville, IL-IN-WI	-5.2%	1.1%	0.96
New Orleans-Metairie-Kenner, LA	-6.7%	3.6%	0.71
Rochester, NY	-8.9%	2.1%	1.19
San Jose-Sunnyvale-Santa Clara, CA	-12.6%	4.9%	3.09
Detroit-Warren-Livonia, MI	-14.9%	8.8%	1.42
Total in Top 51 Regions	4.2%	3.0%

Data source: EMSI Complete Employment, 2012.1. The "2011 Concentration" figure is a location quotient. That's the local share of jobs that are STEM occupations divided by the national share of jobs that are STEM occupations. A concentration of 1.0 indicates that a region has the same concentration of STEM occupations as the nation.

This piece originally appeared in Forbes.

Computer engineer photo by BigStockPhoto.com.

The Best Cities For Tech Jobs

Joel Kotkin — Thu, 17 May 2012 09:51:26 -0400

With Facebook poised to go public, the attention of the tech world, and Wall Street, is firmly focused on Silicon Valley. Without question, the west side of San Francisco Bay is by far the most prodigious creator of hot companies and has the highest proportion of tech jobs of any region in the country — more than four times the national average.

Yet Silicon Valley is far from leading the way in expanding science and technology-related employment in the United States.

To determine which metropolitan areas are adding the most tech-related jobs, my colleague Mark Schill at Praxis Strategy Group developed a ranking system for Forbes that measures employment growth in the sectors most identified with the high-tech economy (including software, data processing and Internet publishing), as well as growth in science, technology, engineering and mathematics-related (STEM) jobs across all sectors. The latter category captures tech employment growth that is increasingly taking place not just in software or electronics firms, but in any industry that needs science and technology workers, from manufacturing to business services to finance. We tallied tech sector and STEM job growth over the past two years and over the past decade for the 51 largest metropolitan statistical areas in the United States. We also factored in the concentration of STEM and tech jobs in those MSAs. (See the end of this piece for a full rundown of our methodology.)

Anyone who has followed tech over the past 30 years or more understands the cyclical nature of this industry — overheated claims of a “tech-driven jobs boom” often are followed by a painful bust. This is particularly true for Silicon Valley. The remarkable confluence of engineering prowess, marketing savvy and, perhaps most critically, access to startup capital may have created the greatest gold rush of our epoch, but the Valley at the end of 2011 employed 170,000 fewer people than in 2000.

Most of the job losses came in manufacturing, and business and financial services, sectors with a significant number of STEM workers. Even though the current boom has sparked an impressive 8% expansion in the number of tech jobs in the San Jose-Sunnyvale-Santa Clara metropolitan statistical area over the past two years, and 10% over the past decade, the area still has 12.6% fewer STEM jobs than in 2001. Overall, the recent growth and concentration of tech and STEM jobs remains good enough for the San Jose metro area to take seventh place in our ranking of the Best Cities For Tech Jobs. Next-door neighbor San Francisco, ranked 13th, has enjoyed similar tech and STEM growth over the past two years, but over 2001-2011, its total STEM employment inched up only a modest 0.8%.

The Established Winners

So which areas offer better long-term, broad-based prospects for tech growth? The most consistent performer over the period we assessed is the Seattle-Tacoma-Bellevue, Wash., metro area, which takes first place on our list. Its 12% tech job growth over the past two years and 7.6% STEM growth beat the Valley’s numbers. More important for potential job-seekers, the Puget Sound regions has grown consistently in good times and bad, boasting a remarkable 43% increase in tech employment over the decade and an 18% expansion in STEM jobs. Seattle withstood both recessions of the past decade better than most regions, particularly the Valley. The presence of such solid tech-oriented companies as Microsoft, Amazon and Boeing — and lower housing costs than the Bay Area — may have much to do with this.

Our top five includes two government-dominated regions: the Washington-Arlington-Alexandria MSA places second with 20.6% growth in tech employment since 2001 and 20.8% growth in STEM jobs; and Baltimore-Towson, Md., places fifth with 38.8% growth in tech jobs in the same period and 17.2% growth in STEM. Over the past two years, their tech growth has been a steady, if not spectacular 4%. One key to the stability may be the broadness of the tech economy in the greater D.C. area; as the Valley has become dominated by trends in web fashion, the Washington tech complex boasts substantial employment in such fields as computer systems design, custom programming and private-sector research and development.

Diversity in tech may also explain the success of other tech hotspots around the country. No. 3 San Diego-Carlsbad-San Marcos, Calif., has ridden growth in such fields as biotechnology and other life and physical sciences research. Over the past decade, tech employment has grown by almost 30% and STEM jobs by 13% in this idyllic Southern California region, and over the past two years, by 15.7% and 6.5%, respectively. Like San Diego, No. 11 Boston is also a well-established tech star, enjoying 11.3% tech growth over the last decade and nearly 10% over the past two years, with a diversified portfolio that includes strong concentrations in biotechnology, software publishing and Internet publishing. STEM employment, however, has remained flat over the past 10 years though.

New Tech Hotspots

Which areas are the likely “up and comers” in the next decade? These are generally places that have been building up their tech capacity over the past several decades, and seem to be reaching critical mass. One place following a strong trajectory is Salt Lake City, No. 4 on our list, which has enjoyed a 31% spurt in tech employment over the past 10 years. Some of this can be traced to large-scale expansion in the area by top Silicon Valley companies such as Adobe, Electronic Arts and Twitter.

These companies have flocked to Utah for reasons such as lower taxes, a more flexible regulatory environment, a well-educated, multilingual workforce and spectacular nearby natural amenities. Perhaps most critical of all may be housing prices: Three-quarters of Salt Lake area households can afford a median-priced house, compared to 45% in Silicon Valley and about half that in San Francisco.

Several other top players with above average shares of tech jobs are emerging as powerful alternatives to Silicon Valley. Like Salt Lake City, eighth-place Columbus, Ohio, boasts above-average proportions of tech and STEM jobs in the local economy, and benefits from being both affordable and business friendly. The Ohio state capital has enjoyed 31% growth in tech jobs over the past decade and 9.5% in the past two years. Raleigh-Cary, N.C., ranked ninth, is another relatively low-cost, low-hassle winner, expanding its tech employment a remarkable 32.3% in the past decade and STEM jobs 15%.

Possible Upstarts

Several places with historically negligible tech presences have broken into our top 10. One is No. 6 Jacksonville, Fla., which has enjoyed a 72.4% surge in tech employment and 17.4% STEM job growth since 2001, mostly as a result of a boom early in the decade in data centers, computer facilities management, custom programming and systems design. Another surprising hotspot: No. 10 Nashville, Tenn., where growth in data processing and systems design fueled tech industry growth of 43% along with 18.5% STEM employment growth over the past decade.

Who’s Losing Ground

Some mega-regions with established tech centers have been falling behind, notably No. 47 St. Louis, No. 45 Chicago, No. 41 Philadelphia and No. 39 Los Angeles. These areas still boast strong concentrations of STEM-based employment and prominent high-tech companies, but have suffered losses in fields such as aerospace and telecommunications. Remarkably despite the social media boom, the country’s two dominant media centers — L.A. and No. 33 New York — have also performed poorly enough that their STEM and tech concentrations have fallen to roughly the national average.

Valley Uber Alles?

Silicon Valley may be churning out millionaires like burritos at a Mexican restaurant, but looking into the future, one has to wonder if its dominance will diminish. Limited developable land, an extremely difficult planning environment, high income taxes and impossibly stratospheric housing costs may lead more companies and people to relocate elsewhere, particularly if the big paydays needed to make ends meet wind down. Mark Zuckerberg and company can bask in their big IPO this week, but the Valley may soon need to consider what it must do to compete with the many other regions that are inexorably catching up with it.

Best Metropolitan Areas for Technology Jobs Rankings

Region	Rank	Index Score
Seattle-Tacoma-Bellevue, WA	1	76.0
Washington-Arlington-Alexandria, DC-VA-MD-WV	2	66.4
San Diego-Carlsbad-San Marcos, CA	3	66.0
Salt Lake City, UT	4	58.5
Baltimore-Towson, MD	5	57.7
Jacksonville, FL	6	57.6
San Jose-Sunnyvale-Santa Clara, CA	7	57.2
Columbus, OH	8	52.9
Raleigh-Cary, NC	9	51.9
Nashville-Davidson--Murfreesboro--Franklin, TN	10	51.7
Boston-Cambridge-Quincy, MA-NH	11	51.4
San Antonio-New Braunfels, TX	12	50.7
San Francisco-Oakland-Fremont, CA	13	48.5
Houston-Sugar Land-Baytown, TX	14	47.6
Cincinnati-Middletown, OH-KY-IN	15	47.4
Austin-Round Rock-San Marcos, TX	16	46.8
Atlanta-Sandy Springs-Marietta, GA	17	46.5
Portland-Vancouver-Hillsboro, OR-WA	18	46.3
Detroit-Warren-Livonia, MI	19	46.0
Dallas-Fort Worth-Arlington, TX	20	44.2
Denver-Aurora-Broomfield, CO	21	42.9
Pittsburgh, PA	22	42.9
Buffalo-Niagara Falls, NY	23	42.3
Charlotte-Gastonia-Rock Hill, NC-SC	24	42.1
Indianapolis-Carmel, IN	25	41.5
Minneapolis-St. Paul-Bloomington, MN-WI	26	41.0
Providence-New Bedford-Fall River, RI-MA	27	40.5
Miami-Fort Lauderdale-Pompano Beach, FL	28	40.1
Richmond, VA	29	39.1
Phoenix-Mesa-Glendale, AZ	30	38.7
Louisville/Jefferson County, KY-IN	31	38.6
New Orleans-Metairie-Kenner, LA	32	38.0
New York-Northern New Jersey-Long Island, NY-NJ-PA	33	37.8
Hartford-West Hartford-East Hartford, CT	34	37.6
Tampa-St. Petersburg-Clearwater, FL	35	36.0
Oklahoma City, OK	36	35.7
Orlando-Kissimmee-Sanford, FL	37	35.0
Riverside-San Bernardino-Ontario, CA	38	33.8
Los Angeles-Long Beach-Santa Ana, CA	39	33.7
Las Vegas-Paradise, NV	40	33.4
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	41	33.3
Sacramento--Arden-Arcade--Roseville, CA	42	33.2
Cleveland-Elyria-Mentor, OH	43	29.9
Rochester, NY	44	29.5
Chicago-Joliet-Naperville, IL-IN-WI	45	26.0
Memphis, TN-MS-AR	46	25.8
St. Louis, MO-IL	47	24.9
Kansas City, MO-KS	48	24.4
Virginia Beach-Norfolk-Newport News, VA-NC	49	24.3
Milwaukee-Waukesha-West Allis, WI	50	24.1
Birmingham-Hoover, AL	51	11.3

Mark Schill is Vice President of Research at Praxis Strategy Group, an economic development and research firm working with communities and states to improve their economies.

Rankings Methodology

Our Best Cities for Technology Jobs ranking is a weighted index measuring growth and concentration of technology-related employment in the nation’s 51 largest metropolitan regions. The 51 regions are scored against each other on a 1-to-100 scale. The index includes both tech industry employment data and occupation-based employment data. Our technology industry component covers 11 six-digit NAICS sectors covering information industries such as software publishing, Internet publishing, data processing, and tech-related business services such as computer systems design, custom programming, engineering services, and research and development. The technology industry data covers 4.5 million jobs nationally. The occupation-based component includes 95 science, technology, engineering, and mathematics (STEM) occupations as classified by the federal Standard Occupation Classification system. This covers 8 million STEM workers that could be employed in any industry. Employment data in our analysis is courtesy of EMSI, Inc. and is based upon over 90 federal and state data sources.

The index comprises four weighted measures: 50% STEM occupation growth, 25% technology industry growth, 12.5% STEM occupation concentration, and 12.5% technology industry concentration. Growth measures are evenly balanced between the 2001-2011 growth rate and the 2009-2011 growth rate, while the concentration measure are job location quotients from 2011.

Note that there is likely to be some double-counting of STEM workers working in tech industries. The tech industries are also obviously employing others, such as salespeople, managers, janitors, etc.

Though these types of rankings typically include only industry data, we felt the STEM jobs data captured “tech” more cleanly so we weighted it higher. However we felt it still important to include the data covering the industries that most identify with the high-tech economy. The heavier weight on STEM helps minimize the effect of a double-counted STEM worker in a tech company.

Seattle photo courtesy of BigStockPhoto.com.

Smart Growth: The Maryland Example

Ed Braddy — Thu, 05 Apr 2012 01:38:12 -0400

This is Part Two of a two-part series.

Evidence that people just don’t like Smart Growth is revealed in findings from organizations set up to promote Smart Growth. In 2009, the Washington Post reported, “Scholars at the National Center for Smart Growth Research and Education found that over a decade, smart growth has not made a dent in Maryland's war on sprawl.”

Citing the “most comprehensive review to date” from the same Center, the Baltimore Sun in 2011 argued that Maryland had made “little progress with Smart Growth” despite adopting laws and policies hailed across the country as models for growth management.

One of the innovative policies was the establishment of Priority Funding Areas (PFAs) where development was to be directed and incentivized with money for cash-strapped jurisdictions. Yet the representative bodies closest to the people continued to permit development outside the PFAs.

Assessing the failure of incentives to concentrate development, the Center concluded: “As the Maryland experience suggests, without statutory requirements, tools that matter to the state are not always those that matter to local governments.”

The anti-democratic outlook among Smart Growthers was evident in a comment by Gerrit Knapp, the director of the National Center for Smart Growth Research and Education, who said, “What makes incentives so politically attractive is that governments and individuals can choose to ignore them if they wish. Unfortunately, in Maryland over the last decade, that's exactly what many have been doing.”

This “unfortunate” behavior by free people is consistent with the conclusion of Robert Bruegmann, author of Sprawl: A Compact History, who found that low density development was “the preferred settlement pattern everywhere in the world where there is a certain measure of affluence and where citizens have some choice in how they live.”

Deconstructing Density

Under the new PlanMaryland, Priority Funding Areas essentially become urban growth boundaries. People still can choose to live outside PFAs, but new housing can be built at no greater than one unit per 20 acres, making such dwellings unaffordable to all but the extremely rich. Ninety percent of new development must be inside the PFAs at a minimum density of 3.5 units per acre.

The impact of increased densities is hard to gauge when presented in this manner, but 3.5 units per acre converts to 2,240 units per square mile. Maryland averages 2.62 people per dwelling unit, so the minimum population density for almost all new development will be on a scale of 5,846 people per square mile, a density higher than Portland or San Francisco, and just shy of Copenhagen, Denmark.

Furthermore, reviewing previous drafts of PlanMaryland leads one to believe that this minimum density will be the exception to the rule of even higher densities. The earliest draft available for public comment, April 2011, was unapologetic about the need for significantly higher densities, saying this “threshold for new development – a relatively low density of 3.5 units per acre – is not accommodating growth in PFAs as needed to minimize continued impacts on our rural and resource lands and industries.”

A later draft, September 2011, established ranges for “medium density” (3.5 to 10 units per acre) and “high density” (10+ units per acre) and repeatedly showed a preference for the high density classification, which converts to a scale of at least 16,704 people per square mile.

For example, on page 18 is the complaint that incentive-based planning “hindered high-density urban development,” and page 35 says there would be dramatic per capita savings “if 25 percent of the low-density development projected to be built from 2000 to 2025 was shifted to high-density development.”

But a strange thing happened on the road to the final draft: high density was euphemized. The sixteen-page Executive Summary does not once mention density. “Low density” makes numerous appearances in the final draft in the context of wasteful land use patterns, and “high density” appears just once.

Instead, PlanMaryland relies on the phrase “compact development”. A comparison table, laughably labeled “Low Density versus Compact Development,” steers clear of medium or high density labels even though, when converted to population per square mile, the “compact” living arrangement would be more than seven times Maryland’s current density.

To discern the density thresholds that Maryland planners have in mind, consider, PlanMaryland claims that “Compact development leads people to drive 20 to 40 percent less, at minimal or reduced cost, while reaping fiscal and health benefits.”

This appears to be lifted from the influential 2007 Growing Cooler report, sponsored by the National Center for Smart Growth Research and Education, Smart Growth America, and other advocacy organizations. The authors call on “all housing growth” to be built at an average density of 13 units per acre (21,798 people per square mile), in order to increase the overall metropolitan density to 9 units per acre (15,091 people per square mile) by the year 2025. There’s not a lot of room for detached single family homes in this scenario.

PlanMaryland’s Best Practices section highlights White Flint in North Bethesda for redeveloping “an auto-dominated suburban strip into an environment where people walk to work, shops and transit.” This project puts 1,400 apartments on 32 acres, for a density of 44 units per acre.

Hyattsville’s Arts District is recognized because “this mixed-use community features row homes, condominiums, live-work units, shops and a new community center,” but there is no room for detached, single family homes among the 500 dwellings crowded onto 25 acres, or 20 units per acre. Also featured is Carroll Creek Park that has 300 residential units, all multi-family, mixed among commercial and office space along a linear 1.3-mile strip.

As a “Traditional Neighborhood Development,” Kentlands is closer to the norm, and features some single family housing among its mix of shops, apartments, and condos, but the 1,655 residential units on 352 acres is still 35 percent higher than the “minimum” densities mentioned in PlanMaryland, and thirteen times the state’s current density level.

These places are architecturally striking and aesthetically attractive, but they are unaffordable to most of the state’s population. Furthermore, the dearth of detached single family housing, the predominance of multi-family dwellings mixed with (not nearby) other uses, and dramatically higher densities are not at all what an overwhelming majority of people want in Maryland or anywhere else.

The emergence of Smart Growth in Maryland is indicative of the movement in general: For successful implementation, it would be necessary to replace incentives with mandates, and continue to rely on euphemistic language to avoid a candid discussion of density.

In October, I spoke -- along with Wendell Cox and a few others -- at a technical forum on PlanMaryland, addressing many areas of concern including density. Signed into law by Governor Martin O’Malley in December 2011, PlanMaryland weakens the authority of local governments, eviscerates property rights, and expresses hope for declining interest in the single family home.

Defenders will argue that most people support Smart Growth; after all, O’Malley and others like him were popularly elected. Yet these politicians never campaign on the specifics of Smart Growth, such as how many people per square mile they believe is necessary, or what kinds of restrictions they will impose on single family housing in the suburbs, or the impacts on affordability.

The September draft of PlanMaryland said, “PlanMaryland, we believe, is what the public says it wants and deserves in government.” Tellingly, this statement is missing from the final report. That’s because what planners want and what people prefer are starkly different.

Photo: New residential smart growth, from the state of Maryland's, "Smart, Green, and Growing" site.

Ed Braddy is the executive director of the American Dream Coalition, a non-profit organization promoting freedom, mobility and affordable homeownership. Mr. Braddy often speaks on growth management related issues and their impact on local communities or at ed@americandreamcoalition.org

Smart Growth and The New Newspeak

Ed Braddy — Wed, 04 Apr 2012 01:38:46 -0400

It’s a given in our representative system that policies adopted into law should have popular support. However, there is a distinction to be made between adopting a policy consistent with what a majority of people want, and pushing a policy while making dubious claims that it harnesses “the will of the people.”
The former is a valid exercise in democracy; the latter is a logical fallacy. Smart Growth advocates are among the most effective practitioners of Argumentum ad Populum, urging everyone to get on the bandwagon of higher densities, compact mixed-uses, and transit orientation because all the “cool cities” are doing it.

Smart Growth advocates also claim this is what people prefer, even if it is not how they currently live. The two core features of Smart Growth land use — high densities and multi-family dwellings — are simply not preferred by most Americans in most places, despite the trendy push for Livability, New Urbanism, Resilient Cities, Smart Codes, Traditional Neighborhood Design, Transit Oriented Developments or any other euphemistic, clever name currently in fashion.

Survey Says!

In the internal data of the 2011 Community Preference Survey commissioned by the National Association of Realtors, no specific question was asked about density, but 52 percent of respondents said, if given a choice, they would prefer to live in traditional suburbs, small towns or the rural countryside. Another 28 percent chose a suburban setting that allowed for some mixed uses (Question 5). Taken together, this shows an overwhelming preference for low densities. Only 8 percent of the respondents favored a central city environment.

As for vibrant urbanism, only 7 percent were “very interested” in living in a place “at the center of it all.” Most people wanted to live “away from it all” (Question 17). An astonishing 87 percent said “privacy from neighbors” was important to them in deciding where to live. One can reasonably infer that a majority of this majority would favor low density places with separated uses rather than crowded, noisy mixed use locations that blur the line between public and private.

When presented with a range of housing choices, 80 percent preferred the “single-family detached house” (Question 6). Only eight percent chose an apartment or condominium. Furthermore, 61 percent preferred a place where “houses are built far apart on larger lots and you have to drive to get to schools, stores, and restaurants” over 37 percent who wanted a place where “houses are built close together on small lots and it is easy to walk to schools, stores and restaurants” (Question 8).

So -- absent the loaded terms and buzzwords that are central to Smart Growth -- a large majority of randomly selected people from across the country showed a strong preference for the land use pattern derisively referred to as “sprawl.”

Yet the press release from the National Association of Realtors proclaimed that “Americans prefer smart growth communities.” This is because on Question 13, respondents were given a description of two communities:

Community A, a subdivision of only single family homes with nothing around them. Not even sidewalks!

Community B: lots of amenities all “within a few blocks” of home. Of course, the description neglected to mention the population density and degree of residential stacking required to put all those dwellings in such close proximity to walkable retail. This was a significant omission, since the first housing option offered in Community B was “single family, detached,” on “various sized lots.”

Community B received 56 percent support.

So, with just one response to an unrealistic scenario, out of twenty answers that included many aversions to Smart Growth, the myth that people prefer Smart Growth was spread. The National League of Cities released a Municipal Action Guide to thousands of elected and appointed officials declaring the preference for Smart Growth, and the online network Planetizen, among others, uncritically helped spread the news.

Missing from the triumphalism was this important caveat in the 98-page analysis of the results by the consultants who conducted the survey:

“Ideally, most Americans would like to live in walkable communities where shops, restaurants, and local businesses are within an easy stroll from their homes and their jobs are a short commute away; as long as those communities can also provide privacy from neighbors and detached, single-family homes. If this ideal is not possible, most prioritize shorter commutes and single-family homes above other considerations.”

In addition to spinning the results of preference surveys, Smart Growthers also ignore them. Maryland is a case study in how to disregard what people want while claiming the opposite. In drafting a statewide growth management plan that anticipated “increased demand for housing, an aging population, and diverse communities,” Maryland officials ignored a robust 55+ Housing Preference Survey from Montgomery County that specifically addressed this concern.

The survey showed that most seniors planned to remain in their present homes upon retirement. Only 30 percent planned to move, and, of that group, only a small percentage would consider an apartment or condominium. This should have mattered to Maryland officials trying to gauge housing preferences for their senior population. Instead, the architects of PlanMaryland looked elsewhere to find studies that reinforced their assumptions.

The Great Conflation

There is an abundance of examples like these, and the key to understanding how they influence decision-makers lies in the conflation of specific amenities with the overarching concept of Smart Growth. For example, Todd Litman’s Where We Want to Be, published by the Victoria Transport Policy Institute, claims that “preference for smart growth is increasing due to demographic, economic and market trends such as aging population, rising future fuel prices, increasing traffic congestion, and increasing health and environmental concerns.”

Does this mean most seniors – such as those in Maryland – want to live in high density, mixed use, transit-oriented apartments even when they say they don’t? Hardly. Litman concedes that “most Americans prefer single-family homes,” but finds “a growing portion want neighborhood amenities associated with Smart Growth including accessibility, walkability, nearby services, and improved public transport.”

Those amenities are things like sidewalks, which evidently are now a Smart Growth invention, and shops that are close to (but not mixed into) residential areas. Litman’s clever construction – e.g., sidewalks equal walkability equal Smart Growth policy – is convincing to officials who mistakenly conclude that their constituents must want Smart Growth when, in fact, they do not.

This has been Part One of a Two-Part Series on Smart Growth by Ed Braddy.

Photo by W. Cox: Rail station in Evry, a suburb of Paris

Ed Braddy is the executive director of the American Dream Coalition, a non-profit organization promoting freedom, mobility and affordable homeownership. Mr. Braddy often speaks on growth management related issues and their impact on local communities. He can be reached at ed@americandreamcoalition.org.