Creative Class

If a picture’s worth a thousand words, this chart has to be valued more than 10 times that.  Detroit is literally off the chart. The big losers, other than the Motor City, are sprawling Sun Belt metros: the Miami, Tampa, Orlando, So-Flo Triangle; So-Cal’s once-vaunted Inland Empire, L.A. and San Diego; Las Vegas; Portland; and Rustbelt cities Buffalo, Rochester, and St. Louis.

The big winners: D.C. and Baltimore. NY and Boston also do well, along with Silicon Valley and San Francisco, Austin, Seattle, and Denver. Salt Lake City and Oklahoma City are also in very good shape, as well as, surprisingly, certain Rustbelt Cleveland and Milwaukee.

Chart from Paul Kedrosky, original data from Indeed.

The U.S. unemployment rate is 9.7 percent, the highest in some time, but the burden of unemployment is  spread unevenly across the economy. Production workers face a 15.1 percent unemployment rate, while unemployment among construction and extraction workers stands at 17 percent. But unemployment among management and professional workers is only 5.4 percent. Researchers at the Martin Prosperity Institute (MPI) previously identified long-run differences in the unemployment rates faced by industrial workers and knowledge, professional, and creative workers.

New analysis by the MPI team tracks unemployment among management and professional – or creative class – workers from 1983 to the present. While unemployment among creative class workers as a whole is far below the rate faced by production and construction workers, there is considerable variation in unemployment among the various occupations, professions, and job types that make up the creative class.

Creative workers in arts, design, and entertainment occupations consistently face higher unemployment rates and significant spikes during recessions. In contrast to other creative fields, the unemployment rate for arts, design, and entertainment workers sometimes runs higher than the overall unemployment rate.

Computer, sciences, and engineering professionals experience lower rates of unemployment than arts, design, and entertainment workers. But the lowest rates of unemployment and the most stable employment are found in meds and eds occupations – health and education – where unemployment stays consistently low, even during downturns.

The full analysis is here.

Been busy with the final push on the book and also tweeting up a storm (so do follow me there). Hope to get back to more regular posting after the holiday. But news of rising unemployment and the two-track economy got me thinking about the changing nature of jobs and work and my favorite books on employment, labor, and work.

Ben Hamper’s Rivethead, a scorching account of mind-numbing, dehumanizing work on the assembly line.

Harry Braverman’s Labor and Monopoly Capital, the seminal analysis of the separation of mental and manual labor, conception from execution.

David Montgomery, The Fall of the House of Labor, a labor history classic.

In an age when the tendency to separate mental and manual labor has reached an extreme, it’s important to value all work and remember that each and every worker – in the laboratory, artist studio, factory floor, and retail shop – is creative. It’s also important that we continue to strive to improve the pay, working conditions, and creative content of all work.  We must do more than just create jobs. Our task is to create better, more fulfilling, more productive, and more humanizing kinds of work. The productivity of our society and well-being as individuals can be greatly enhanced by creating work that employs our full productive capabilities, enables us to use our chosen talents, and fully express who we are and who we want to be. In an era when so many people are alienated by work and choose to express themselves through consumption and lifestyle, work remains a key element – if not the key factor – of our identity.

How has the economic crisis affected the happiness and well-being of Americans? Newly released data from the Gallup-Healthways Well-Being Index enables us to take a look.

At the national level, not so much: The mid-year 2009 score is 65.1, a moderate decline from 65.5 in 2008. (Catherine Rampell of Economix provides a nice summary of the survey methods, indicators, and key findings.)

But, rising unemployment appears to have a significant relationship to the happiness of states, according to our analysis of the Gallup-Healthways data.

Not surprisingly, the biggest declines in overall happiness occurred in work-related well-being. The Gallup-Heathways Well-Being Index is made up of six separate sub-indexes – life evaluation, emotional health, work environment, physical health, healthy behavior, and access to basic necessities. Five of these indexes fell between 2008 and 2009, with the biggest decline occurring in the work environment index: More than three-quarters of states saw their work environment score fall in 2009.

This is broadly in line with happiness research. It had been long thought that happiness essentially levels off after a moderate income level is crossed. But an influential study by Betsy Stevenson and Justin Wolfers found a strong association between happiness and economic conditions. A 2005 study found that a significant increase in Finland’s unemployment rate (from three to 17 percent) did not produce a significant drop in overall well-being.

The new Gallup-Healthways Index also covers the 50 states. Interestingly enough, the “happiest states” in 2009 – Hawaii, Utah, and Montana – were more or less the same as in 2008; the same is true of the “unhappiest states” – West Virginia, Kentucky, and Arkansas. Drilling down a little further, Utah topped the list in life evaluation, Hawaii in emotional health, Idaho in work environment, North Dakota in physical health, Vermont in healthy behavior, and Iowa in basic access.

Still, it’s clear that the economic crisis has been harder on some states that others. Older industrial states of Michigan, Indiana, and Ohio have seen their unemployment rates soar in the double digits, while the housing crisis has wreaked havoc on once fast-growing states like Florida and Arizona.

The availability of state-level data for before (2008) and after (2009) the crisis provides a useful lens for examining the effects of worsening economic conditions on state happiness.

So my collaborator, regional economist Charlotta Mellander, looked at the relationships between happiness and economic factors like output, income, and unemployment. Let me emphasize that what I am reporting here are correlations or associations. While these findings do not imply causation, they remain interesting nonetheless.

First off, the relationship between happiness and economic output has apparently become weaker. The relationship between the two which was correlated (.33) and statistically significant in 2008, is no longer so (.27 and not statistically significant in 2009).

Second, the relationship between income on happiness also seems to have weakened (falling from a correlation of .43 in 2008 to .30 in 2009 – both significant at the .01 level).

Third, unemployment appears to be the biggest short-run factor affecting state happiness. Two measures of unemployment – a higher state unemployment rate and a bigger increase in that rate between 2008 and 2009 – were associated with both lower levels of state well-being and a bigger drop in state well-being between 2008 and 2009.

The first chart graphs the relationship between 2009 state unemployment rate and state well-being. Hawaii and Utah, above the line; and West Virginia, Kentucky, and Arkansas below it, are clearly outliers. Still, the fitted line shows a reasonably close association between unemployment and happiness among states. The correlation coefficient of -.44 between the two (statistically significant at the .01 level) lends additional support to this.

The second chart graphs the relationship between state happiness and the change in the unemployment rate between 2008 and 2009. Hawaii and Utah, and West Virginia, Kentucky, and Arkansas are again outliers. But the fitted line shows a clear association between the two. And while the correlation coefficient between the two is weaker than above (-.34 and statistically significant at the 0.05 level) it nonetheless supports the association.

The connection between state happiness and unemployment also came through when we looked at the relationships between the change in state well-being between 2008 and 2009 and the two measures of unemployment – the 2009 unemployment rate and change in unemployment between 2008 and 2009. The correlations for each are statistically significant (-.30 for the 2009 unemployment rate and -.34 for change in the unemployment rate between 2008 and 2009, both significant at the .05 level).

Given all of this, it’s safe to say that unemployment plays a reasonably big role in the happiness – or should I say, unhappiness – of states.

The U.S. economy has shed 7.2 million jobs since the onset of the recession. But the economic pain of unemployment has not been spread equally, according to a new analysis by my colleagues at the Martin Prosperity Institute.

The graph below, compiled by Ulrich Atz, tracks the unemployment rate for three broad groups or classes of employment – the working class, the service class, and the creative class from 1971 to May 2009.

The report finds that:

Unemployment for all three groups has spiked since the onset of the recession.  But the downturn has hit hardest on working class. . . The working class has been hard hit by every downturn since 1971. Working class unemployment spiked from 6.2 percent in 1973 to 14.5 percent in the 1975 downturn.  It spiked again from 7.7 percent in 1979 to 16.8 percent in 1983.  It reached 12.0 percent in 1992.

In contrast, the unemployment rate for the creative class has hardly ever reached the 4 percent mark.  Unemployment rates among the working and service class are typically about 3-4 and 2-3 times respectively the rate of those in the creative class.

A closer look at monthly data (available starting in 2000) reveals that unemployment rates among the working and service classes typically move together while creative class unemployment lags the other two by several months.

The full analysis is here.

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.

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.

That’s the overall rate of unemployment, according to the Bureau of Labor Statistics’ newly released U-6 measure which includes “marginally attached workers” as well as those who work part-time for economic reasons. That’s quite a bit higher than the widely reported 9.4 percent figure also released today.

And, unemployment continues to fall unevenly by gender, race, class, and occupation.

Race: The unemployment rate for whites was 8.6 percent compared to 12.7 percent for Hispanics, 14.9 percent for blacks, and 16.8 percent for black men.

Gender: Men continue to experience higher rates of unemployment than women, with the gap widening to three full percentage points – 10.5 percent vs. 7.5 percent (for those over 16 years of age) – due to the concentration of men in manufacturing jobs.

Human Capital/Education: Unemployment is even more uneven by education or human capital level. The unemployment rate for college graduates is 4.8 percent, half that for high school (only) graduates (10 percent), and one-third of the 15.5 percent rate facing those without a high school diploma.

Class: And there remain huge differences in unemployment by occupation. The highest rates of unemployment remain concentrated in working class occupations. For production, transportation, and moving occupations overall, the rate is 13.7 percent, up from 6.3 percent last year. For production workers it’s 15.6 percent; movers and transportation workers, 11.8 percent; and construction and extraction jobs, 19.7 percent. For service occupations, the unemployment rate is nearly 10 (9.4) percent.

Unemployment is significantly lower for the creative class. For management and business occupations – including hard-fit financial jobs – overall the unemployment rate is 4.6 percent, up from 2.7 percent last year; and for professional and technical occupations it is 4.2 percent, up from 2.5 percent a year ago.

The unemployment rate surged to 9.4 percent today. But unemployment continues to fall heavily on certain demographic and class groups and in certain cities and regions of the country, according to the latest figures from the Bureau of Labor Statistics.

Greater Detroit still posts the highest rate for large regions (those with a million or more people), 13.6 percent, down from 14 percent in March. Los Angeles, Tampa Bay, Las Vegas, and San Jose also have rates above 10 percent. Greater Portland, Oregon saw the largest jump in its unemployment rate (+6.9 percentage points), followed by Detroit (+6.6 points) and greater Charlotte (+6.4 points). Iowa City (3.2 percent), Des Moines (4.6 percent), and Salt Lake City (five percent) post the lowest unemployment rates.

Ryan Avent notes the resilience of Washington, D.C. and of the Bos-Wash mega-region across the board as well as college towns. He also points to the surprising strength of the “eastern Rust Belt” especially Buffalo, Scranton, Syracuse, and Pittsburgh. These places all  experienced the kind of hit Detroit is taking today roughly a generation ago. They have had time to stabilize the economic trauma and to begin to rebuild around universities, heath care, technology, and creative industries.

Large increases in regional unemployment remain heavily concentrated in regions with large fractions of blue-collar working class jobs. The change in unemployment from April ‘08 to April ‘09 is closely correlated (0.39) with the regional concentration of working class jobs – that is, jobs in industrial production, transportation, and construction, according to an analysis by my colleague Charlotta Mellander.

Regions with higher levels of the creative class and higher levels of human capital have fared much better. (Year-over-year, change in unemployment is negatively correlated with both the creative class, -0.29, and human capital levels, -0.35, the percentage of adults with at least a bachelor’s degree).

Unemployment does not appear to be related to regional income levels (the correlation between the two is insignificant). And it tends to fall more heavily on regions with higher housing prices (with a significant positive correlation between the two of 0.18) – perhaps an artifact of the bubble.

Interestingly, regions with large concentrations of lower-end service jobs (like food prep, building maintenance, and personal care services, which are typically seen as the worst and least secure kinds of jobs) are holding up much better than those with large working class concentrations. (Change in unemployment is negatively correlated, -0.29,  with large concentrations of these standardized service jobs).

Seems to me, we’d be much better off developing new strategies to improve wages and working conditions in this sector – by say speeding the dissemination of better management models and improving innovation and productivity – instead of bemoaning the loss of blue-collar jobs or, worse yet, bailing out failed manufacturing firms.

James Surowiecki notes that:

“[In] 2008, for the first time in sixteen years, the finance and insurance industry shrank. Since 1980, this sector’s share of the economy has grown by almost half. Now, apparently, the worm has turned.”

A couple of months earlier, Eric Janzen predicted that:

As more and more risk pollution rises to the surface, credit will continue to contract, and the FIRE economy—which depends on the free flow of credit—will experience its first near-death experience since the sector rose to power in the early 1980s. The FIRE economy—which depends on the free flow of credit—will experience its first near-death experience since the sector rose to power in the early 1980s.

The FIRE economy – which stands for finance, insurance, and real estate – is extraordinarily concentrated geographically. FIRE made up a whopping 40 percent of Charlotte, North Carolina’s economy in 2006. But that didn’t make it the most FIRE-dependent economy in the nation. That distinction goes to Des Moines, Iowa. FIRE made up roughly a third of total economic activity in Bridgeport and Hartford, Connecticut; Bloomington, Illinois; and greater New York, as well as resort towns like Naples, Florida; Myrtle Beach, South Carolina; and Ocean City, New Jersey.

But, as of yet, the popping of the FIRE bubble doesn’t appear to be having any substantial effect on regional unemployment. There was no statistical relationship at all between the FIRE share of regional economies and the unemployment, measured as either the Feb. 2009 unemployment rate and as the change in that rate between Feb. 2008 and Feb. 2009, according to number-crunching by my colleague Charlotta Mellander. There was a slight positive correlation between real estate and both the unemployment rate (0.13) and the year-over-year change in unemployment (0.17).

But one aspect of real estate economies – construction – does appear to put regions at substantially greater risk. The correlation was higher between regional share of the construction industry and the unemployment rate (0.18) and even more so for year-over-year change in unemployment (0.23).

Hard to say why, but one reason may be that regions with a large share of finance and insurance jobs are economically more diverse. Or perhaps finance and insurance workers have skills that are more flexible, enabling them to shift jobs relatively more easily than say construction workers or blue-collar workers in general.

One thing is clear: the recession continues to hit hardest at older industrial regions and those with sprawl-driven, construction-heavy economies. Those with large shares of finance and insurance jobs seem to be adjusting relatively well.