Creative Class

This map from the Gallup Organization shows the well-being levels of the nations of the world.

Gallup collected the data through from interviews and telephone surveys with individuals across 155 nations between 2005 and 2009. It distinguishes three categories of well-being – suffering (low levels), struggling (medium levels), and thriving (high levels).

More than half of Americans (57 percent) report they are thriving, while 40 percent say they are “struggling,” and three percent report they are “suffering.” (more…)

Here’s a map of job creation from The Gallup Organization. It’s based on approximately 100,000 Gallup Daily tracking interviews conducted throughout 2009 with employed adults in all 50 states plus the District of Columbia. It provides a clear picture of the evolving economic geography of The Great Reset.

On the losing side of job creation, Rustbelt states, especially Michigan and less so Minnesota, continue to be hard hit, along with the “housing-crash” states of Nevada, California, and Arizona. Northeastern states -  Rhode Island, Delaware, New Jersey, Connecticut, and New Hampshire – also fare poorly. In the west, Oregon and Idaho also see low rates of job creation.

The best-performing states in terms of job creation are energy economies – North Dakota, Louisiana, West Virginia, Oklahoma, Texas, Alaska, and New Mexico, as well as Nebraska; and those with economies that benefit from federal spending, Maryland, Virginia, and D.C. More here.

Unemployment continues to rise in U.S. metro regions, according to the December figures released by the U.S. Bureau of Labor Statistics. “Unemployment rates were higher in December than a year earlier in 371 of the 372 metropolitan areas and lower in one area,” according to the report. The Detroit metro continued to post the highest level of unemployment – 14.9 percent  But Las Vegas saw the largest increase in their jobless rate, which grew by 4.4 percentage points over the past year. The number of metros with unemployment rates of more than 10 percent more than doubled from 42 in December 2008 to 138 in December 2009. Of regions with more than one million people, Oklahoma City and Greater Washington, D.C. posted the lowest unemployment rates – 6.0 and 6.2 percent, respectively.

The full list of unemployment by metro region is here.

As one looks around the economic landscape I am struck by the devastation. One number stands out above all others. One in five males between the ages of 25 and 55 is out of work! That is a staggering number. The numbers are not going back to anything “normal” anytime soon according to the IMF. Financial crises followed by recessions do not return to normal levels of employment for over a decade. Why you might ask? The answer I guess is that the levels of debt need to be worked down. Everyone owes everyone money and none pay anyone. Second, the recession destroys real capital. In this situation it was housing. It will take years to work off the excesses of the housing crisis.

So what does entrepreneurship have to do with the recession? If we take what we know today, entrepreneurs and innovation play a vital role in the economy. But can they help us in the great recession? In other words, what policy should we be pursuing to move the unemployment rate below 10 percent and back into the neighborhood of 5 percent? We know that new firms are important. They create most of the net jobs.  However, only a small percent, perhaps 4 percent, create almost all of the jobs in any given four-year period. And this seems to hold up in different times, different countries, and different industries.

So how do we forge a policy? Two stories are told out there. First we know that age and size are important variables. And we know that age appears to be more important than size. In other words, we should target firms based on age not size. The two stories out there are one by Zoltan Acs and the other by Carl Schramm. In a highly influential study, Acs found that the average high impact firm was about 20 years old and came in all sizes, small, medium, and large. Schramm, on the other hand, using a Census Bureau study, found that firms less than five years old created almost all of the jobs independent of size.  They both cannot be right.

However, if we are interested in short-term policy solutions and not real economic growth, we should help stimulate solo self-employed. They have a start-up rate that is three times as large as firms with employees. They start easily but also go out of business quickly. So an effective policy would be to make it easier for them to stay in business longer.

A simple policy would be to cut the self-employment tax, not over 15 percent of all new solo self-employed firms to zero for three years. If they hired any employees we should cut the employer share 7.5 percent for three years also. This would greatly increase the survival rate for these new firms. Of course this is not a long-term solution because many of these firm will contribute very little to productivity, economies of scale, or wealth creation. But they will pull down the unemployment rate.

The impact on the deficit would not be great since many of these people would not have survived to pay payroll taxes anyway. Once the economy picks up the issue of long-run growth can be addressed. But in the short run, let’s get people working.

From The Economist, December 30, 2009:

The rich world’s quiet revolution: women are gradually taking over the workplace

At a time when the world is short of causes for celebration, here is a candidate: within the next few months women will cross the 50 percent threshold and become the majority of the American workforce. Women already make up the majority of university graduates in the OECD countries and the majority of professional workers in several rich countries, including the United States. Women run many of the world’s great companies, from PepsiCo in America to Areva in France.

Women’s economic empowerment is arguably the biggest social change of our times.

From another article in the same issue:

The rich world has seen a growing demand for women’s labor. When brute strength mattered more than brains, men had an inherent advantage. Now that brainpower has triumphed the two sexes are more evenly matched. The feminization of the workforce has been driven by the relentless rise of the service sector (where women can compete as well as men) and the equally relentless decline of manufacturing (where they could not). The landmark book in the rise of feminism was arguably not Ms Friedan’s “The Feminine Mystique” but Daniel Bell’s “The Coming of Post-Industrial Society”.

Or perhaps Rise of the Creative Class is a landmark book for demonstrating why women have increasingly found a fit in the wage-earning world.

Your thoughts?

(Thanks to colleague MW for drawing my attention to the article.)

In cities across the world, office buildings are becoming greener. New construction is now typically LEED certified — often LEED Gold. Some older buildings are being retrofitted to meet US Energy Star standards.

The result is new workplaces that theoretically are healthier for the individuals working inside as well as for the planet. To be certified under LEED, a building has to offer higher levels of natural air and light, for example, than is typical in conventional construction. Moreover, materials used on the interiors also may have fewer toxins, which can affect employee health.

Over the past decade or so, the real estate industry has discussed and even debated the benefits of green buildings (versus their costs). One aspect of the discussion has centered around the employee workplace experience. Are people who work in green buildings better off? And are the companies and organizations who pay the rent seeing a difference in comparison to being in non-green structures?

A recent report by Norm G. Miller of the University of San Diego and Dave Pogue, director of sustainability at CBRE, offers new survey results from the responses of 534 tenants (companies or organizations who occupy buildings) who had recently moved into green office structures.  Some data:

First, from a human resource perspective:

• 18 percent reported lower employee turnover in the new buildings
• 22 percent reported higher employee morale
• 23 percent reported easier recruiting of employees
• 45 percent reported fewer sick days while another 45 percent reported no change

Second, the question of employee productivity:

• 55 percent agreed or strongly agreed with the statement, “Employees are more productive,” while 43 percent were neutral and only two percent disagreed.

Finally, other benefits:

• 74 percent of companies surveyed said the new building provided “a good image for clients and public.”

The authors also noted that companies occupying green buildings tended to have employees with higher-than-average wages. They therefore speculate that because of the salaries being paid these people, employers may want to ensure they maximize their productivity on the job.

This data is consistent with some other, often smaller, survey samples out there — such as from Gensler.

But aggregate statistics do not always tell the whole, human side of the story. What are your experiences?

Do you work in a certified, green building? Do you feel more productive or healthier than you have in other environments?

Would you select an employer based on the job being in a green building?

From WSJ writer Sue Shellenbarger’s Work & Family column (sub):

In the broadest, most-comprehensive survey yet of how occupation affects happiness, business owners outrank 10 other occupational groups in overall well-being, based on the landmark survey of 100,826 working adults.

The piece goes on to describe why, even during a stress-filled recession, business owners are generally happier than other working adults.

The findings, psychologists say, reflect the importance of being free to choose the work you do and how you do it, the way you manage your time, and the way you respond to adversity. Regardless of occupational field, the survey suggests that seeking out enjoyable work and finding a way to do it on your own terms, with some control over both the process and the outcome, is likely for most people to fuel satisfaction and contentment.

Does this sound like what you are seeing from entrepreneurs around you?

Check out the press release for more data and information from the Gallup-Healthways Well Being Index.

The bailout is big. But, where exactly is it going?

Thanks to the efforts of ProPublica, we can track bailout funds by state. The map below, based on their data, shows the geographic distribution of bailout spending.

The bailout is massively concentrated in just a few states. Total bailout funding, according to the ProPublica data, is $476.5 billion to date. One state, New York, has captured $175 billion of that, more than a third. Michigan is next with $80.7 billion or 17 percent of the total, followed by North Carolina with $56.3 billion, Virginia with $54.9 billion, and California with $34.4 billion. The top three states accounted for 66 percent of bailout spending; the top five 84 percent; and the top two more than 10 percent.

How does the geography of the bailout look when we control for the size of state economies – say, by population and economic output? With the number-crunching help of Ronnie Sanders and map-making assistance of Scott Pennington, both of the Martin Prosperity Institute, we decided to take a look.

The second map shows the geography of bailout funding per person. The average per state, excluding the District of Columbia and based on the ProPublica data, is $1,570.34 bailout dollars per person. Again, two states dominate the tally – New York, where the bailout adds up to $8,978.83 per person, and Michigan where it’s $8,067.28. There are just five additional states where bailout funds top $1,000 per person: Virginia ($7,044.47), North Carolina ($6.104.69), Minnesota ($1,379.21), Connecticut ($1,085.33), and Iowa ($1,065.76).

The third map shows the geography of the bailout as a percent of state economic output or gross state product. The bailout, again based on the ProPublica data, was three percent of total state output, with each state on average receiving 1.8 percent of its GDP. Michigan takes the top spot here, with bailout funds equivalent to a whopping 21.1 percent of its total economic output. New York is next at 15.3 percent; followed by North Carolina, 14.1 percent; and Virginia, 13.8 percent. No other state received bailout funding that was more than three percent of its output.

By any measure, the bailout has been massively concentrated geographically.

Yesterday, we looked at the relationship between drug use and class. We found that drug use was significantly associated with the percentage of the creative class in a state, and negatively so with the percentage of people employed in the working class.

Today, I dig a bit deeper into the relationship between drug use and specific types of professional, knowledge-based, and creative jobs – management, business and finance, architecture and engineering, science, health-care, education, and arts and entertainment. The patterns here are quite interesting.

Occupations sort relatively neatly along the lines of marijuana versus cocaine use. The short of it is that marijuana use is more positively associated with science (.35), education (.38), artistic professions (.35), and engineering and architecture (.29), while cocaine use is positively associated with lawyers (.41) and, to a lesser extent, with business and finance occupations (.27), computer jobs (.25), and management fields (.26).

Drug use overall is significantly associated with the state-wide concentrations of three major types of occupations – science (.35), architecture and engineering (.34), and arts, design, and entertainment (.33). And, in all three cases, this correlation appears to be driven by marijuana use; none of them are significantly associated with cocaine. Management occupations are also positively associated with overall drug use, though the correlation (.26) is somewhat weaker.

Here’s what my colleague and collaborator, Cambridge University psychologist Jason Rentfrow, had to say about our results:

I think it’s interesting that cocaine is high for finance, law, and quant professions. Although we can’t infer whether it’s people in those jobs actually doing drugs, those professions are generally regarded as intense and lavish. So it’s interesting that an expensive stimulant like cocaine is used more often in places where comparatively large numbers of people work in intense and high-paying jobs… It’s also interesting that marijuana is popular in places with artists, designers, and architects because those are jobs that encourage divergent thinking and marijuana is a psychoactive drug that’s associated with creativity.

What I think is particularly interesting about the results is that most professions possess elements of income, education, and personality. Even in those cases where lawyers and architects make similar amounts of money, they’re very different lines of work and appeal to different types of people.

Correlation coefficient: .41**

Correlation coefficient: .35*

Correlation coefficient: .29*

Correlation coefficient: .32*

Correlation coefficient: .38**

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

Yesterday, I looked at the relationship between drug use and politics. We saw that states that voted for Obama had higher levels of marijuana and cocaine use than those that voted for McCain. But perhaps economic factors lie behind those political trends. We know that Obama drew from less affluent minority voters and also from more well-educated, creative class voters. Perhaps the associations between drug use and voting patterns reflect deeper economic patterns.

The conventional wisdom is that economic hardship is a key factor in drug use. Anyone who watches crime shows like The Wire gets this picture really fast.

To get a first approximation of this, we examined the relationship between drug use and unemployment. Not surprisingly, the use of illegal drugs is correlated with state unemployment (.31). And the correlations are even a bit higher when we look at marijuana (.36) and cocaine use (.36).

Correlation coefficient: 0.31*

But things get more interesting when we look at the relationship between drug use and economic development. While there is no relationship between economic output and illegal drug use overall, there is a significant relationship between state economic output and marijuana, and an even stronger correlation between economic output and cocaine use, as the charts below show.

Correlation coefficient: 0.31*

Correlation coefficient:  0.61**

But there’s more to the story. Tomorrow, I turn to the relationship between drug use and the class structure of state economies.

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