Archive for July, 2009

Richard Florida
by Richard Florida
Wed Jul 22nd 2009 at 10:00am UTC

Housing and the Crisis, Part I

Wednesday, July 22nd, 2009

Housing prices continue to fall nationally but the economic impacts of the crisis are being felt unevenly across the country. Housing values are off roughly a third from their peak in mid-2006, according to the Case-Shiller Home Price Index. Phoenix and Las Vegas have taken the biggest hits, suffering declines of more than 50 percent in the past year. Miami, San Diego, L.A., and Tampa have also been hard hit. Detroit has seen housing prices sink to mid-90s levels. Housing prices have declined less significantly in greater D.C., Chicago, Seattle, Atlanta, New York, Portland, Boston, Denver, Dallas, and Charlotte. But the Case-Shiller data only covers 20 large metro regions.

This week, I take a look at how housing prices have fared across the full set of more than 300 American metropolitan areas. The posts are based on statistical analysis by my colleague Charlotta Mellander. Today and tomorrow, I’ll look at how housing prices have fared since their 2006 peak. Later in the week, I’ll look at the relationship between housing prices and incomes and wages.

The graph below compares housing prices in 2009 to their 2006 baseline price. It’s based on “residual analysis,” comparing the change in housing prices between 2006 and 2009.

Clearly, the two are related – the correlation is 0.903 and the R2 is 0.815. But the slope of the fitted line suggests that, on average, housing values in these regions have dropped by approximately 15 percent. Metros above the line have lost less value than their 2006 worth would predict, while those below the line have lost more.

Under-performers: These are regions where housing values have slipped even more than predicted. Among large metros, the under-performers include: Los Angeles (where values are off $79,789 more than expected based on the national trend), San Francisco (-$79,029), Las Vegas ($-72,421), Phoenix (-$69,897), and Miami (-$53,021). Cape Coral, FL saw the biggest relative decline (- $111,797), followed by Riverside, CA (-$103,683), Sacramento, CA (-$91,640), and Sarasota, FL (-$82,353). Akron, OH (-$59,635) and Lansing, MI (-$57,574) also saw significant declines. Housing values were down slightly more than would have been expected in Atlanta (-$27,413), Chicago (-$16,580), and greater D.C. (-$14,411). 2009 data for Detroit were not available.

Over-performers: The analysis turned up a number of over-performing regions. By that I mean regions with housing values performed better than expected relative to the national trend. Over-performers include: Honolulu (where housing values remain $160,414 more than expected), Boulder ($72,172), Salt Lake City ($68,935), Seattle ($61,997), New York ($58,407), Raleigh, NC ($57,552), Portland, OR ($42,173), Baltimore ($39,896), Austin ($38,181), Philadelphia ($29,011), Boston ($13,644), Houston ($8,693), and Dallas ($5,661).

Stay tuned for more tomorrow.

Richard Florida
by Richard Florida
Tue Jul 21st 2009 at 10:45am UTC

Where Unemployment Is Worse than Expected

Tuesday, July 21st, 2009

The impacts of the economic crisis continue to be felt unevenly across the country. I’ve previously looked at the factors associated with higher rates of regional unemployment. But which places have seen the biggest jumps in unemployment since the crisis hit?

To get at this, my colleague Charlotta Mellander conducted a straightforward statistical exercise called a “residual analysis.” It’s a simple way to track how a location performs relative to the performance of all other locations. Basically, the analysis examines to what extent the initial unemployment rate in May 2008 seems to have had an impact on the change in unemployment over the last year. Technically speaking,  Mellander ran a regression analysis predicting change in unemployment over this last year (May 2008 to May 2009) as a function of the initial level of unemployment at the beginning of the period (May 2008). She then compared the predicted values to the actual values.

The first graph shows the pattern for U.S. states.

The hardest hit states are ones that were doing badly even before the crisis hit. The fitted line is steep; the correlation between the two is 0.59 and significant; and the R2, 0.345. States below the line experienced a smaller than predicted increase in unemployment levels, while those above the line saw a larger than predicted increase.

Michigan has the highest unemployment rate, but Oregon (+3.0) has taken the biggest relative hit. Alabama (+1.8), Indiana (+1.6), South Carolina (+1.6), and Wisconsin (+1.4) have also taken bigger than expected hits. North Dakota has the lowest rate of unemployment but Alaska (-2.8), Mississippi (-2.1), Arkansas (-1.2), Connecticut (-1.2), Iowa (-1.1), and Nebraska (-1.2) have done better than expected.

The second graph repeats the analysis for U.S. metropolitan regions. It excludes two extreme outliers in California – Yuma and El Centro – which started the period with 20 percent plus rates of unemployment.

The hardest hit metros are also those that were doing badly before the crisis. The fitted line is again steep; the correlation coefficient is high, 0.59; and the R2, 0.351.

The crisis has hit hardest at smaller Rustbelt metros, especially those in Indiana: Elkhart-Goshen, IN; (+7.3); Kokomo, IN (+7.2); Decatur, GA (+3.2); Sheboygan, WI (+2.7); Fort Wayne, IN  (+2.3); and Youngstown, OH (+2.2).

While Detroit has faced staggering unemployment, the difference between its actual and predicted unemployment is +1.6. Among large metros, Portland (+3.1), Charlotte (+2.2), and, San Jose (+1.9) experienced even bigger than expected increases in unemployment. Las Vegas (1.5), Boise (1.29), and Orlando (+1.29) have also been hard hit. San Francisco (+.93), Miami (+.49), L.A., Chicago (+.31), Atlanta, and San Diego (+.21) also performed worse than their May 2008 unemployment levels predicted.

Several Oregon metros took worse than expected hits: Bend-(+4.6), Eugene-Springfield (+3.8), Portland (+3.0), Salem (+2.5), Medford (+2.4), Corvallis(+1.9). Metros that border Oregon like Spokane, Washington (+0.8) and Boise, Idaho (+1.3) also have high differentials.

Three Texas cities – Dallas (-1.0), Houston (-0.9), and Austin (-1.0) – performed considerably better than expected. Minneapolis-St. Paul (-0.4) did too. Cities along the Bos-Wash mega-region – Boston (-0.4), D.C. (-0.3), New York (-0.1), and even Philadelphia (-0.3) – also did better than predicted. Surprisingly, Phoenix also outperformed expectations (-.2), albeit modestly.

College towns number among the best performers, doing much better than predicted: Champaign-Urbana, Illinois, home to University of Illinois (-2.2); Iowa City, University of Iowa (-1.81); Manhattan Kansas, Kansas State University (-1.82); College Station, Texas, Texas A&M (-1.74); New Haven, Connecticut, Yale University (-1.54); State College, Pennsylvania, Penn State University (-1.47); Boulder, Colorado, University of Colorado (-.93); Austin, Texas, University of Texas (-1.0); Ann Arbor, Michigan, University of Michigan (-.94); and Ithaca, New York, Cornell University (-.97), among others.

David Eaves
by David Eaves
Tue Jul 21st 2009 at 6:27am UTC

Open City Challenges – The Counter Reaction

Tuesday, July 21st, 2009

Interesting piece over at Washington Monthly about how some bureaucracies are having a reactionary (but albeit unsurprising) reaction to open data initiatives. The article focuses on how the data used by one application, Stumble Safely “helps you find the best bars and a safe path to stumble home on” by mashing together DC Crime Data, DC Road Polygons, DC Liquor Licenses, DC Water, DC Parks, and DC Metro Stations.

However, arming citizens with precise knowledge doesn’t appear to make one group of people happy: The Washington, D.C. police department. As the article notes:

But a funny thing has happened since Eric Gundersen launched his application: Stumble Safely has become less useful, rather than more so. When you click on the gray and red crime-indicating dots that have appeared on the map in the past few months, you don’t get much information about what exactly happened—all you get is a terse, one-word description of the category of the incident (“assault,” or “theft”) and a time, with no details of whether it was a shootout or just a couple of kids punching each other in an alley.

This isn’t Gundersen’s fault—it’s the cops’. Because while Kundra and the open-data community were fans of opening up the city’s books, it turned out that the Metropolitan Police Department was not. Earlier this year, as apps like Stumble Safely grew in number and quality, the police stopped releasing the detailed incident reports—investigating officers’ write-ups of what happened—into the city’s data feed. The official reason for the change is concern over victims’ and suspects’ privacy. But considering that before the clampdown the reports were already being released with names and addresses redacted, it’s hard to believe that’s the real one. More likely, the idea of information traveling more or less unedited from cops’ keyboards to citizens’ computer screens made the brass skittish, and the department reacted the way bureaucracies usually do: it made public information harder to get. The imperatives of Government 2.0 were thwarted by the instincts of Government 1.0.

This is just one in a long list of ways that old-style government (1.0) is reacting against technology. The end result sadly however is that the action taken by the police doesn’t reduce crime, it just reduces the public’s confidence in the police force. This is just a small example of the next big debate that will take place at all levels of government: Will your government try to control information and services or will it develop trust by being both accountable and open to others building on its work? You can’t have it both ways and I suspect citizens – particularly creatives – are going to strongly prefer the latter.

Richard Florida
by Richard Florida
Sat Jul 18th 2009 at 10:00am UTC

Innovation and Economic Crises

Saturday, July 18th, 2009

This past week, I’ve look at the trends in U.S. innovation, commenting on Michael Mandel’s powerful and compelling thesis about the deceleration and interruption of American innovation. With the help of my MPI team, I’ve tracked patent data since 1980, examined patent trends for U.S. resident and foreign, non-resident inventors, and looked at the geographic distribution of patenting.

Overall, the trend in patenting is up – both in absolute numbers and controlling for population. Innovation has increased over the past decade, but not at the breakneck pace of the 1980s and 1990s. There have been two dips in patenting over the past decade – the first in the wake of the tech crisis of 2001 and the second, more recently, concurrent with the onset of the housing and financial bubbles and the subsequent economic crisis.

American innovation has shifted and become more geographically concentrated. Places like Silicon Valley and Seattle have seen a steady increase in innovation while older, industrial centers like Pittsburgh and Detroit have declined significantly. Innovation in large cities like New York and Chicago has stagnated. And American innovation has grown increasingly dependent on non-resident, foreign inventors.

Today, I focus on a broader historical question: How do economic crises affect American innovation? Does innovation slow down or speed up during periods of crisis?

Joseph Schumpeter long ago argued that crises were seedbeds of innovation and entrepreneurship. Innovations developed during crises generate the gales of creative destruction that launch new technologies, remake existing industries, and give birth to entirely new ones – setting in motion new rounds of economic growth. Economists Gerhard Mensch and Christopher Freeman have examined the historical timing of innovations, with Freeman famously arguing that the pace of innovation is actually relatively constant: Innovations bunch up during crises, only to be unleashed as economic conditions are restored.

The graph above is reproduced by economist Alfred Kleinknecht. It shows patent activity from 1750 to 1970. It tracks actual patents granted from 1901 to 2005. There are clear spikes in innovative activity during the Long Depression of the 1870s and 1880s and the Great Depression of the 1930s.

The historical literature also suggests that crises are periods of significant innovation. Joel Mokyr and Naomi Lamoreaux have documented the rise of important innovations like the incandescent light, the steam turbine, and the transformer during the Long Depression. Economic historian Alexander Field finds the 1930s to be the “most technologically progressive” decade of the 20th century.

The chart below, compiled by the MPI’s Patrick Adler based upon a reading of the historical literature, identifies some of the major innovations of the Long Depression and the Great Depression. If the past is any guide, we should expect some acceleration of innovation – and particularly of the dramatic innovation Mandel wants to see – in the coming decade.

The graph below, compiled by my colleague Charlotta Mellander, updates the story, charting patents granted per 10,000 people from the 1890s to 2007. The rate of innovation rose significantly after the Long Depression. It then dipped during the Great Depression before trailing off considerably during the World War II period. American innovation rebounded remarkably in the post-war period before trailing off in the 1970s. Since the early 1980s, however, American innovation has surged to record highs. There have been two dips in innovation in the 2000s. But as of 2006 or 2007, innovation has fallen only slightly from its record pace.

So what’s happened to U.S. innovation? Like virtually every other facet of the economy, it has been – and continues to be – reshaped by globalization. As we saw on Thursday, foreign non-resident inventors have become a key element growing U.S. patenting and a big piece of the American innovation system. Beginning around 1980, non-resident inventors essentially closed the gap with U.S. inventors. By the late 1990s, they had pulled even and were at times outpacing U.S. inventors. This is part and parcel of the globalization of the economy and the fact that the U.S. is the biggest market and most innovative nation on the planet.

This has altered the American system of innovation in a deep and fundamental way – changing it from a system that for the better part of a century was based on producing and commercializing innovations to one that is more attuned to attracting inventors and innovation globally. This shift is also reflected in the changing geography and regional concentration of U.S. innovation – the decline of old, integrated, regional innovations systems in locations like Pittsburgh and Detroit and the rise of new, globally focused clusters like Silicon Valley.

Innovation is no longer an American game – or, for that matter, a game of any one nation. The countries of the world are now all part of a much more global innovation system. Strategically, this shift means from organizing to generate new breakthrough innovations to organizing to absorb innovations coming from many different sources worldwide.

The U.S. is uniquely positioned because of its size, scale, universities, and venture capital system; its sophisticated end-users and customers; and its ability to attract global talent – to harness and reap the benefits of this global system. Its major innovation clusters reinforce this advantage and they will be hard to displace. That said, for the first time, the overall rate of American innovation has come to depend on foreign inventors. Anything that might slow the immigration or inflow of foreign inventors – or redirect their inventions and patents – would undoubtedly damage the rate of American innovation.

The key question for the future is less about the slowdown in innovation and more about which people and places will prosper in this new age of accelerating global innovation.

Richard Florida
by Richard Florida
Fri Jul 17th 2009 at 9:45am UTC

The New Geography of American Innovation

Friday, July 17th, 2009

The past couple of days, I’ve looked at the trends in overall patents and nationality of inventor. Today I turn to the regional distribution of innovation across U.S. regions.

It’s well-known that high-tech industries are concentrated and clustered in areas like Silicon Valley, Greater Boston, Seattle, Austin, and North Carolina’s Research Triangle. Paul Krugman won a Nobel Prize for his pioneering work on the relationships between urbanization, trade, and economies of scale. And Michael Porter has shown how and why innovative firms cluster.

The graph below, compiled by Scott Pennington of the Martin Prosperity Institute, shows patent trends from 1976 to 2007 for the top 10 U.S. regions. The graph identifies a clear shift in the geography of patenting. The level of innovation has fallen off considerably in older industrial regions like Pittsburgh and Detroit. It has also fallen off in Sunbelt regions like Dallas with a large presence in computers and communications and Houston with its strong concentration of resource and energy industries. On the other hand, innovation has increased substantially in high-tech regions like Silicon Valley, San Francisco, and Seattle and also in Los Angeles. Two other large regions – New York and Chicago – more or less conform to Mandel’s thesis: Both saw dramatic growth in the late 1990s followed by precipitous drops in the 2000s which erased those gains. Overall, American innovation has become more geographically concentrated and spikier.

The decline of industrial regions as centers of invention reinforces the point made by Henry Ergas two decades ago: The U.S. innovation system is skewed heavily toward “shifting” (the creation of new breakthrough technologies and products) and away from “deepening” (the application of new inventions and technologies to the continuous, incremental upgrading of older industries). The decline of GM and Chrysler – and in particular the latter’s acquisition by Fiat to gain access to new technology – stand as testimony to that. The decline of innovation and commercialization in older industrial regions means that in certain key areas of technology, the U.S. has essentially ceded the potential to develop new industrial goods and consumer products to other countries – from established competitors Germany and Japan to emerging ones like India and China – which possess the industrial infrastructures to embed them in commercial products.

Richard Florida
by Richard Florida
Thu Jul 16th 2009 at 1:00pm UTC

Map of the Day

Thursday, July 16th, 2009

Check out this map of job postings by metro area (h/t: Steven Pedigo).

The map controls for population.

D.C. has the most openings, and Baltimore is second. San Jose, Austin, Hartford, Seattle, Salt Lake City, Denver, Boston, Las Vegas, Charlotte, and San Francisco all are doing reasonably well, relatively speaking.

Detroit comes in dead last, with the fewest openings Miami. Buffalo, Rochester, L.A., and Chicago are doing poorly.

An interactive version and the full list of cities is here.

Richard Florida
by Richard Florida
Thu Jul 16th 2009 at 9:53am UTC

Global Sources of American Innovation

Thursday, July 16th, 2009

Yesterday, we looked at overall trends in U.S. innovation measured by patents. Today, we break out U.S. patents between U.S.-resident and non-resident or foreign inventors patenting in the U.S.

Numerous studies have shown that, over the past two or three decades, the role of foreign scientists, technologists, and entrepreneurs in U.S. innovation has increased. Recent studies by AnnaLee Saxenian and Vivek Wadhwa and others find that anywhere between a third and half of all Silicon Valley start-ups during the 1990s had a foreign entrepreneur or scientist on their core founding team. As I have previously argued, foreign-born scientists currently make up 17 percent of all bachelor’s degree holders, 29 percent of master’s degree holders, 38 percent of PhDs, and nearly 25 percent of American scientists and engineers. My earlier research shows that Japanese companies – and some European companies as well – chose to locate research labs in the U.S. to access a diverse mix of scientific talent they cannot attract in their home countries.

The graph below shows the overall trend in patenting for U.S.-resident and non-resident foreign inventors between 1980 and 2005. Non-resident inventors have just about pulled even with U.S. inventors in patenting, and their rate of inventive activity more or less tracks that of U.S.-based inventors. But here again, even with two dips since 2000, the rate and level of innovation over the past decade remains up.

Clearly, foreign inventors have become a key feature of the U.S. innovation system. Without them the level of innovation would be much lower. Another way of saying this is that the American system of innovation has become increasingly dependent upon non-resident inventors. Foreign inventors patent in the U.S. to secure intellectual property protection in the large U.S. market. Clusters of sophisticated and demanding consumers and end-users help make the U.S. the place to be for high-end innovation, as Amir Bhidé points out in The Venturesome Economy.

While foreign patenting boosts the overall rate of innovation in the U.S., there is a considerable chance that these patented innovations are commercialized and produced off-shore, and thus that the U.S. economy will accrue less overall economic benefit from those technologies. While this is not direct evidence for Mandel’s innovation interrupted thesis, it provides a possible mechanism that might limit the commercialization and overall economic impact of innovation in the U.S.

Richard Florida
by Richard Florida
Thu Jul 16th 2009 at 8:05am UTC


Thursday, July 16th, 2009

Check out this great new collection of essays by a variety of thought leaders on a wide range of global trends. McKinsey organized it, and it’s titled What Matters. They were nice enough to include two pieces from moi – one on talentopolis, the second on a new kind of economic indicator (can you guess?).

Richard Florida
by Richard Florida
Wed Jul 15th 2009 at 2:43pm UTC

Who’s Your NBA City?

Wednesday, July 15th, 2009

You can add professional basketballer Hedo Turkoglu to the list of people who have relocated to Toronto thanks to its cosmopolitanism. Turkoglu, one of the most sought-after free agents on the market this year, is moving to Toronto with his wife because of its large Turkish community and international flavor. Turkoglu has reportedly rebuffed the Portland Trailblazers, a team that is thought to have more upside, to join the Raptors who did not make the playoffs last year. Money quote from his agent Lon Babby:

“It’s a uniquely cosmopolitan and international community and it suits him and his family best…The comfort level was just best in Toronto.”

Where will the Turkoglu’s new home be? From the looks of it, they will have a ton of options.

Kwende Kefentse
by Kwende Kefentse
Wed Jul 15th 2009 at 12:39pm UTC

Innovation from the King

Wednesday, July 15th, 2009

As a kid born in the early 80s, a young black man, and DJ, when I heard that Michael Jackson died I was floored. It’s really hard to put into words what his run in 80s meant to me and other kids like me. As a DJ, Michael was the ultimate back door, a key that would fit every locked dance floor, to be reached for only in emergencies and handled with great care. As a dancer, when Fred Astaire calls you his heir, there’s not much left to say. What he did with his feet seemed impossible. Sometimes it was.

Never more mystifying was his impossible lean from the Smooth Criminal video (@ approx. 7:15). At first I thought that it was camera tricks, but then I heard that he did it live at shows – no wires, no cables. Just lean. How does a man defy gravity like that live on stage? In the posthumous craze, one of the more interesting bits of information that shook loose was the innovation that made that possible:

Michael invented and patented a special shoe and rig. Google Patent Search provides the details.

Richard has often talked about his interest in music as a “fruit-fly” industry. That is to say that the the study of the music industry is analogous to the scientific study of fruit flies to better understand more complex biological systems. Through studying music we can understand how innovations flow through other creative industries. Musical creatives don’t just innovate musically, but they’re often linked to technological innovation. This is true about individual innovations, from Jimi Hendrix to Grand Master Flash, as well as system wide innovations, as was evidenced by the MP3 revolution. This is just another example of the same from arguably the greatest of all time.

R.I.P. Mike.