Creative Class

Last week, I posted on a Bureau of Labor Statistics (BLS) report on the metro regions with the highest-paying jobs in nine major occupations. But this report only listed the top two regions in each category. So I decided to take a closer look at the underlying BLS data to compile a more comprehensive mapping of regional pay. With the help of my colleague, Charlotta Mellander, we looked at the pay levels for three types of jobs – high-skill, high-pay, creative class jobs; traditional, blue-collar, working class jobs; and lower-skill, lower-pay service jobs.

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Ever wonder where the highest-paying jobs in your field are? Now, courtesy of the Bureau of  Labor Statistics (BLS), we have some answers.

Late last week, the BLS released a report (via Catherine Rampell of The New York Times Economix) showing the U.S. metros with the highest-paying jobs in nine major occupational categories including: business, finance, and management; professional and technical work; service; office work; construction; and blue-collar production jobs, among others. The BLS measures what it calls ”average pay relative” which includes wages, salaries, commissions, and bonuses. And, its calculations control for differences in the composition of jobs, industry, firm-level, and occupational characteristics, and the fact that data are collected at different times during the year. As the BLS defines it: “The average pay relative for all occupations and each occupational group equals 100.” A figure above 100 reflects the percentage above the national norm, while values below 100 reflect the percentage below that norm.

The chart below shows the pay profile for a series of U.S. metro regions. San Francisco is highest, followed by Greater New York, Salinas, California, and Greater Boston, which are all above the U.S. norm. (more…)

Last week, The Economist released its Big Mac Index (via Catherine Rampell of The New York Times Economix) which basically compares how much it costs to buy – you guessed it – a Big Mac in countries across the world. The magazine explains the index as a:

…lighthearted attempt to gauge how far currencies are from their fair value. It is based on the theory of purchasing-power parity (PPP), which argues that in the long run exchange rates should move to equalise the price of an identical basket of goods between two countries. Our basket consists of a single item, a Big Mac hamburger, produced in nearly 120 countries. The fair-value benchmark is the exchange rate that leaves burgers costing the same in America as elsewhere.

And it goes on to note a number of caveats about it:

The Big Mac numbers should be taken with a generous pinch of salt. They are not a precise predictor of currency movements. The bulk of a burger’s cost depends on local inputs such as rent and wages, which tend to be lower in poor countries. Consequently PPP comparisons are more reliable between countries with similar levels of income. (more…)

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Earlier this week, the American College of Sports Medicine released its new version of the American Fitness Index, which tracks the health and fitness level of America’s 50-largest metropolitan regions. The index is defined as a “composite of preventive health behaviors, levels of chronic disease conditions, health care access, and community resources and policies that support physical activity.” The table below shows the fitness levels for these 50 metros.

Source: American Fitness Index

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A new study (PDF) from the Bureau of Labor Statistics provides important insight on states where workers toil the longest hours and make the most money. The study by Dante DeAntonio uses data from the Current Employment Statistics – a monthly survey of more than 400,000 U.S. business establishments – to provide estimates for employment, hours, and earnings for all 50 U.S. states. Catherine Rampell summarized some key findings of the study earlier this week over at Economix.

Take a look at the map of the hardest-working states in terms of hours worked. Nevada tops the list with an average of 37 hours per week. Wyoming, Louisiana, Texas, Kentucky, and Alabama all average more than 36 hours per week. At the opposite end of the spectrum are Montana, the Dakotas, Hawaii, and New Hampshire which average less than 33 hours per week.

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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.

Yesterday, we looked at the relationship between drug use and economic patterns. We saw that drug use was associated with both higher levels of state economic output as well as higher levels of unemployment.

Today, I turn to the relationships between drug use and economic class. My colleague Charlotta Mellander charted the relationships between drug use and the percentage of a state’s economy that is made up of two classes: the creative class – that is, people who work in knowledge-based, artistic, and professional occupations; and the working class – those who work in production, transportation, and construction jobs.

While the associations between drug use overall are weak, the patterns for marijuana and cocaine are significant. Take the creative class: Both marijuana and cocaine use are positively and significantly related to states with higher concentrations of the creative class.

Correlation coefficient: 39**

Correlation coefficient: 36**

Now look at the results for the working class, where the pattern is reversed. Both marijuana and cocaine are negatively and significantly related to the concentration of working class jobs in state.

Correlation coefficient: -.35**

Correlation coefficient: -.36**

Note: * indicates statistical significance at the .05 level; ** indicates significance at the .01 level.

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 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.