BLS Labor Market Projections in Retrospective

Tomorrow, the Employment Projections division of the Bureau of Labor Statistics will release its projections for the years 2012–2022. This is a red-letter day for me, something I look forward to every two years, and it will keep me quite busy over the coming weeks. (This blog may suffer as a result.)

I am sometimes asked how accurate these projections are. Of course, the BLS does not possess a crystal ball. Their economists work from a model of the economy that cannot possibly capture all of the forces that are at work, causing some occupations to expand and others to shrink. Today, on the eve of the next set of projections, I decided to look at the projections that the BLS made in 2002 for the year 2010.

The most noteworthy problem with the projections for 2010 is that they do not anticipate the Great Recession that we experienced a couple of years before that date—the worst economic slump since the 1930s. As a result, in 2002 the BLS seriously overestimated the size of the 2010 workforce, which was still in recovery from that downturn. The BLS projected a total 2010 workforce size of 168 million (15 percent growth from 2000), whereas the current estimate for 2010 is only 143 million (2 percent shrinkage from 2000).

The group of occupations that underperformed the most was Helpers, Construction Trades, shrinking by 44 percent instead of growing by the predicted 13 percent. This outcome reflects the collapse in housing that burst the pre-recession bubble; helpers, including apprentices, are the first to be laid off when not needed and the last to be hired back. Construction Trades Workers also saw a reduction in workforce size—25 percent—whereas the BLS had projected 13 percent growth. It’s interesting to contrast these occupations to the workforce of Construction Managers, which actually grew more than projected: by 70 percent rather than 16 percent.

Two other groups that underperformed substantially were Woodworkers—shrinking by 43 percent instead of growing by 9 percent—and Metal Workers and Plastic Workers—39 percent shrinkage instead of 9 percent growth. Evidently the BLS underestimated the amount of offshoring that the manufacturing industries would do. The BLS did project shrinkage for Textile, Apparel, and Furnishings Workers, but only 2 percent, whereas the actual contraction was 48 percent.

Besides construction and manufacturing, state and local governments took a big hit in the aftermath of the Great Recession. Starved for tax revenue, they had to lay off many workers. As a result, Protective Service Occupations grew by only 7 percent instead of the projected 26 percent, and K–12 teachers grew by 2 percent instead of the projected 17 percent.

Health-care workers were better insulated from the chill economic winds. For example, Health-Care Support Occupations grew by 31 percent, very close to the projected 33 percent. Health Diagnosing and Treating Practitioners grew by 24 percent, almost exactly at the projected 25 percent rate.

The boom in the petroleum industry is one positive trend that BLS did not anticipate. The workforce of Extraction Workers expanded by 17 percent instead of contracting by the projected 2 percent.

Business keeps chugging along. The workforce for Business and Financial Operations Occupations grew by 37 percent instead of the 17 percent projected. Management, however, underperformed, shrinking by 17 percent instead of growing by 12 percent.

By showing these figures, I don’t mean to tarnish the reputation of the Bureau of Labor Statistics. Some of the unanticipated trends that I mention here are likely to prove transitory once we get further away from the recessionary years. Overall, the BLS economists do us an immense service with their projections, and I will continue to cite the BLS projections as guideposts for career decisions. Of course, just as investors diversify their holdings and use other hedging strategies to guard against unanticipated outcomes, I advise career decision makers to diversify their skills and perhaps develop a career plan B. This is advisable not solely because of the inevitable imperfections of labor market projections; predictions of academic success and career satisfaction can also prove inaccurate. Just as the BLS can’t foresee every economic trend of the coming decade, neither can we predict everything that will be going on in our heads and hearts 10 years from now.

The Prison-Industrial Complex Is Losing Luster

The Department of Labor will release a new set of employment projections in only a couple of weeks from now, but I’m going to jump the gun and predict that the outlook for correctional officers and jailers will continue to be poor. The projection for the 2010–2020 period was for only 5 percent growth, compared to the average of 14 percent across all occupations. But isn’t the prison industry booming? If so, why such a lackluster outlook for the guards?

It’s true that the prison industry is currently doing very well. Nationwide, there are approximately 2.3 million inmates in state, federal, and private prisons. This is roughly double the number behind bars in 1990 and exceeds the number of prisoners in any other country.

However, there is a huge cost to this immense human inventory and to the infrastructure and labor force required to keep these prisoners behind bars. The federal government alone spends about $55 billion each year on its prisons. In the current climate of budget-cutting, even those who like to think of themselves as law-and-order crusaders are forced to question this expenditure.

Also, consider that violent crime is on a steady downward trend. To be sure, a very large fraction of those in prisons have either been convicted of nonviolent offenses, especially drug charges, or are being detained as undocumented aliens. But the state-by-state trend toward decriminalization of cannabis will result in fewer drug convictions. And the federal government has shifted its policy on drug offenders away from the harsh penalties enacted during heyday of the “war on drugs.” Finally, if—yes, it’s a big “if”—Congress can reform our immigration laws, we also should see a decline in those convicted of being here illegally.

Finally, the existence of a large workforce of correctional officers and jailers—an estimated 475,300 in 2010—creates public-health costs that are often overlooked but that are substantial. I am grateful to Caterina G. Spinaris, PhD, of Desert Waters Correctional Outreach for calling this to my attention, in response to a recent article in which I identified certain high-stress occupations. Research she participated in resulted in the estimate that 27% of corrections professionals suffer from post-traumatic stress disorder (PTSD). For security staff, the estimates were that 34.1% suffer from PTSD and 31.0% from depression. The Desert Waters research found significant, although lower, rates of PTSD and depression among other prison employees, such as clerical staff, chaplains, and maintenance workers.

These are all reasons to be hopeful that in the years ahead, prisons will not be the job-creators that they sometimes have touted as.

Where the Jobs Are

You may think of this week’s blog as a book report, if you choose. The book is The New Geography ofJobs (Houghton Mifflin Harcourt, 2012), by Enrico Moretti, and it is packed with significant ideas about what causes job growth in the new economy. Moretti is an economic geographer, and his fundamental point is that job growth in the United States is clustered within certain “brain hubs,” and this clustering phenomenon is accelerating and self-perpetuating. But he also points out the threats to these engines of job growth.

The idea of brain hubs—geographical centers, such as the Silicon Valley, where the most creative work is being done—has been around for awhile. Richard Florida has popularized this concept, emphasizing how much our economy depends on creative work and on the creative people who do it. The rapid growth of dynamic, job-creating metropolitan areas serves as an important correction to the “flat-world” thesis that Thomas Friedman has made much of—the idea that modern electronic communication and cheap international shipping allow work to be done anywhere in the world where costs are lowest. This dispersal of work is indeed true for low-skill jobs in manufacturing, call centers, and several other industries, but not for the creative industries.

What the flat-world industries have in common is that they are all mature. Industries that are new or the segments of mature industries where a lot of creative research and development projects are going on are clustered in a very few locations. For example, consider your smart phone. The manufacturing happens in China or another low-wage, low-skill location, but the R&D happens in the Silicon Valley. Even Nokia and Eriksson, which are headquartered in two Scandinavian countries, do almost all their R&D in the Silicon Valley.

Why does this work cluster in brain hubs? Both Richard Florida and Enrico Moretti emphasize the collaborative nature of creative work and the labor-market advantages to both employers and employees of having a concentrated pool of high-skilled workers. They also note that these creative workers create numerous job opportunities for lower-skilled workers, thus enriching all sectors of the community.

Where Moretti parts company with Florida is over the question of what makes brain hubs grow. This is an important question, because it can lead to policy suggestions for how to transform a stagnant city into a dynamic one. Florida believes that R&D centers grow when creative people are attracted to cities that are tolerant and have many cultural amenities, but Moretti argues that these municipal attributes are the result rather than the cause of brain-hub activity. As a counter-example, Moretti cites Berlin, which is one of the most tolerant and culturally endowed cities in Europe, yet has the highest unemployment rate in Germany.

Moretti maintains that brain hubs become increasingly dense with highly-skilled workers because each newly arrived creative person contributes additional attractive power to the community. As long as the center continues to do creative work, it will continue to strengthen its pull on creative workers from elsewhere. Of course, this trend may not continue forever. Once low-skill manufacturing became the primary function of the automobile industry, Detroit lost its appeal as a brain hub, and the industry scattered to Southern states and foreign countries. The film industry has also scattered to many places, but because the work is inherently creative, Hollywood maintains its dominance as the place to find work and workers. (In fact, the same persistence of hubs is true of almost every art form.)

So what gets a brain hub started in the first place? Moretti argues that it is mostly a matter of happenstance—specifically, the arbitrary geographic choice of a creative genius who sparks an industry. For Silicon Valley, the common wisdom is that the presence of Stanford University was the driving force, but Moretti points out that there are many other universities just as prestigious that have not sparked brain hubs. What made the difference was the decision by William Shockley, the inventor of the transistor, to locate at Stanford, which had the result that some of his students and colleagues created the first integrated circuit at Fairchild Semiconductor—and the rest is clustering history. For the Seattle high-tech hub, it was the decision of Bill Gates to relocate from Albuquerque (where he had started the microcomputer software industry) to his hometown. By the time Jeff Bezos was ready to try his hand at selling on the Web (by founding Amazon.com), he had little choice but to move to Seattle, rather than his hometown (ironically, Albuquerque). Hollywood was a backwater until D.W. Griffith set up shop there and created the film industry’s first blockbuster, Birth of a Nation.

The main threat to America’s brain hubs—and, therefore, to America’s economy—that Moretti identifies is a shortfall of human capital. Brain hubs gain their power by drawing in brainpower, and it is questionable whether the flow will continue to be adequate, given the decline of our educational system (which used to lead the world in college graduates) and given the barriers that our immigration system creates against the entry of high-skilled foreigners. Ironically, as the creative centers become increasingly different from the rest of the nation—and Moretti points out that these snowballing differences are cultural and political as well as economic—it becomes increasingly harder for the nation to achieve political consensus on the need to fix these looming problems.

Workforce Trends and Personality Types (part 3 of 3)

My previous two blogs (here and here) have been about the workforce trends of the previous decade. But you may be wondering about the future. That is, as our economy crawls back from the hole of the last recession, what will be the job-growth patterns for different personality types and for different levels of skill? To answer this question, I analyzed Department of Labor data on projected employment levels and sorted the findings by Holland personality types and levels of earnings.

To see what I found, compare the following two graphs.The first one is last week's graph, for the years 2002-2012. (Click here to see a bigger version.)

Now, let's look at what the Department of Labor projects for the rest of the current decade. (Click here to see a bigger version.)

Start by comparing the red bars, past and future. These show the past and projected growth in the number of all workers in the occupations linked to each Holland type. It should be no surprise that the red bars in the second chart are higher in almost every category: The workforce as a whole grew by only 2 percent 2002-12, but it is projected to grow by 14 percent 2010-20. The most dramatic improvement is the turnaround of the Realistic occupations, from negative territory to 13 percent growth. But do keep in mind that 13 percent is still slightly behind the overall growth of the workforce. Similarly, the Enterprising and Conventional occupations score much bigger gains in the second chart (12 percent) than in the first chart (2 percent), but that 2 percent gain actually matched the overall growth of the workforce 2002-12, whereas their 12 percent growth in the second chart lags slightly behind the workforce as a whole for 2010-20. The one personality type that scores smaller gains in the second chart is Investigative: 18 percent 2010-20, compared to 20 percent 2002-12. But eighteen percent still outpaces the overall average for growth.

Next, look at the purple, green, blue, and yellow bars, which indicate the workplace growth at various levels of pay. Note the shape of each cluster of bars, and compare the two charts. One striking change between the first chart and the second chart is that the hollowed-out middles that characterized three of the personality types--Artistic, Social, and Conventional--are much less hollowed-out in the projections for 2010-20 than they were in the 2002-12 era. It seems that the middle-skill occupations that were so severely stunted by the recession are now growing at a rate closer to the rate of the higher- and lower-paid occupations.

Now, let's look at each personality type in isolation:

Realistic. In the second chart, the Realistic bars have a substantial bulge at the middle level--a great contrast to the first chart, where only the occupations at highest level of skill expanded at all. Although all levels show some gains, the expansion will be smallest at the low end, which means that Realistic workers will need more than basic skills to find work. The contrast between the performance of Realistic occupation in the two charts confirms the popular notion that the Great Recession was a "mancession," disproportionately impacting jobs held mostly by men.

Investigative. In the past decade, growth was pretty much commensurate with level of skill as indicated by earnings. That trend continues during the present decade, with bigger gains at the high end, although the upward slope is not as pronounced. This pattern reflects how important innovation is to the U.S. economy: There will be a lot of growth for those with high levels of investigative skills.


Artistic. The most dramatic change here is the great improvement at the very highest bracket. The reason for such a big difference is that two of the occupations at the high end are focused on construction and therefore took a particularly bad hit in the recession: Architects, Except Landscape and Naval--Holland code AI, median earnings $73,090, which shrank by nearly 5,000 jobs, or 6 percent, in the past decade, but is projected to gain almost 28,000 jobs, or 25 percent; and Landscape Architects--AIR, $64,180, which lost 1,700 jobs, or 10 percent, but is projected to gain 3,500 jobs, or 16 percent.

Social. As in the past decade, this group of occupations shows the most growth overall, reflecting the continuing importance of health care and education in our economy.

Enterprising. The previous decade was hard on this group of occupations, but projections are for better growth overall. Like the Realistic group, this group shows an interesting bulge, rather than a hollowing-out, in the middle. Some of the better performers there are Retail Salespersons (EC, $21,110, +706,800); First-Line Supervisors/Managers of Office and Administrative Support Workers (ECS, $49,330, +203,400); and First-Line Supervisors/Managers of Construction Trades and Extraction Workers (ERC, $59,700, +131,000).

Conventional. At the low end, the projected gains among Combined Food Preparation and Serving Workers, Including Fast Food (CRE, $18,260) are not as impressive as they were in the past decade, dropping from 47 percent to 15 percent. It seems the fast food industry is cooling off. But gains are also less impressive at the high end, where Accountants and Auditors (CEI) are projected to have gains of 16 percent (190,700 jobs), down from 27 percent (240,650 jobs); and Financial Analysts (CIE) shifted down from 50 percent (79,890 jobs) to 23 percent (54,200 jobs). My guess is that the recession focused the attention of business on how to wring every penny out of the cash flow, a less important concern during a recovery. The really dramatic difference is in the middle of the distribution, largely caused by the reversal of Executive Secretaries and Administrative Assistants (CE, $47,500), from a loss of almost 605,000 jobs (43 percent) to a gain of 156,000 jobs (13 percent).

In planning a career, it helps to consider both your personality type and the level of skill you are aspiring to--the latter roughly equivalent to the amount of education you plan on getting. Then consider the job growth expected for this combination, so you'll have an idea of the level of opportunity you can expect. This kind of planning may be more useful than looking at the outlook for any one occupation, because there is a good chance that you will change occupations somewhere down the line, but it's less likely that you will be working in an occupation associated with an entirely different personality type or that you will be working at a very different level of skill.

Workforce Trends and Personality Types (part 2 of 3)

As our economy has changed, it has rewarded certain interests and skills more than others. Last week I measured one aspect of these differing rewards by looking at the workplace growth over the past decade for the six Holland personality types. It turned out that during this time period, which included a whopper of a recession, Investigative and Social types had the greatest growth (in percentage terms), the Artistic type grew modestly, the Enterprising and Conventional types merely kept pace with the overall growth of the workforce, and the Realistic type shrank substantially.

But these trends deserve a closer look.

The rates of growth that I calculated were based on all workers in occupations characterized by each personality type, and that approach concealed some important differences. It turns out that when you look at workers at different earning levels, there is often more variation within a personality type than there is between different types. And these differences say a lot about how job opportunities changed over the past decade.

Let's look at a new graph and see what it indicates. (Click here to see a bigger version.)

First, note the red bars. These are the percentage figures from last week, applying to all workers in the occupations linked to each Holland type.

The purple, green, blue, and yellow bars indicate the workplace growth at various levels of pay. You'll note that for four of the personality types, workforces shrank at some earning levels but increased at other earning levels. Let's look at each personality type.

Realistic. Although this workforce shrank overall (red bar), occupations at the highest level of pay (yellow bar) actually increased their workforces. Some of these highly-paid, growing occupations were Civil Engineers (Holland code RIC, earning $79,340, gaining 50,620 workers); Mechanical Engineers (RI, $80,580, +48,920); Electrical Power-Line Installers and Repairers (RIC, $63,250, +16,410); and Commercial Pilots (REI, $73,280, +15,420). The high level of pay that these occupations command--more than $60,000 per year--is an indication of the high level of skill that the occupations require. The take-away message is that this ten-year period was good for Realistic personality types who had a high level of skill but was much less kind to those with lower skills. It's also significant that Investigative is a secondary type for all four of the occupations that I mention here.

Investigative. You may notice that there is no purple bar for this personality type; that's because no Investigative occupation earns less than $20,000. For this personality type, growth was pretty much commensurate with level of skill as indicated by earnings. That means that Investigative personalities enjoyed the best of both worlds: earnings were high in occupations where job growth was greatest. Some of these highly-paid occupations with lots of job growth were Management Analysts (IEC, $78,600, +147,770); Industrial Engineers (IR , $78,860, +68,370); Pharmacists (ICS, $116,670, +62,170); and Medical Scientists, Except Epidemiologists (IAR, $76,980, +41,580).

Artistic. First, don't pay much attention to the spectacular purple bar that represents the under-$20,000 occupations. This actually represents only one occupation, Models, which was fast-growing but from a fairly small base (2,260 workers). The pay is so low partly because so many work part-time. More significant is what this personality type shares with Social and Conventional: a hollowed-out middle. The group of occupations in the $20,000-$40,000 range actually shrank slightly. The occupation most responsible for pulling down this group was Desktop Publishers, which lost about 18,000 workers, slightly more than half its workforce, largely because new technology enabled other workers to do desktop publishing for themselves. Another drag on this group was Photographers, losing 7,000 jobs, or 11 percent of its workforce. Again, technology was the cause; businesses that need photos can usually find what they want on websites that offer stock photos. It's interesting to note that the highest-paid group here grew only at the rate of the workforce as a whole: 2 percent. It included a mixture of winners such as Art Directors (AE, $80,880, 8,370) and losers such as Multi-Media Artists and Animators (AI, $61,370, -4,880). The latter occupation lost workers because of a mix of new technology and offshoring. The most growth was to be found in the $40,000-$60,000 group, where the outstanding occupations were Graphic Designers (AER, $44,150, +49,610); Interpreters and Translators (AS, $45,430, +31,720); and Music Directors and Composers (AE, $47,350, +15,960).

Social. This group of occupations is the perfect illustration of the holllowing-out of the workforce. The two income levels that gained the most workers were at the lowest and highest ends of the distribution. The big winners at the low end were Personal and Home Care Aides (SRC, $19,910, +534,190); and Waiters and Waitresses (SEC, $18,540, +245,900). At the high end, the standouts were Health Specialties Teachers, Postsecondary (SI, $81,140, +66,360); and Physical Therapists (SIR, $79,860, +61,170). A large number of college teaching occupations were also to be found among high-paid group. The take-away lesson for this personality type is that the growth has been in low-paying health-care jobs and in high-paying health-care and education jobs, and considerably less in the middle range.

Enterprising. This group of occupations experienced a unique growth pattern: the lower the income, the larger was the amount of job growth. This distribution therefore is the mirror image of the group of Investigative occupations. The greatest opportunities were at the low end--notably Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop (ES, $18,580, +46,230); and Amusement and Recreation Attendants (ECR, $18,710, +31,300). The shrinkage of jobs at the high end resulted largely from Chief Executives (EC, $168,140, -196,460); and General and Operations Managers (ECS, $95,440, -98,890). The recession accounts for some of the job loss in the executive suite; the outlook for these occupations over the next decade is for modest growth, tempered by a high level of competition.

Conventional. This group is another good illustration of a hollowed-out workforce. At the low end, there was an impressive gain among Combined Food Preparation and Serving Workers, Including Fast Food (CRE, $18,260, +943,740). At the high end, the outstanding winners were Accountants and Auditors (CEI, $63,550, +240,650); Compliance Officers, Except Agriculture, Construction, Health and Safety, and Transportation (CEI, $62,020, +80,830); and Financial Analysts (CIE, $76,950, +79,890). Once again, note how Investigative is a secondary type for all three occupations that were winners.

The trends of the past 10 years say a lot about the effects of automation and offshoring in a period marked by recession. As you can see, it makes sense to use a combination of one's personality type and one's level of skill to explain past job growth. Next week, I'll look at job growth projected for the future and see the relationship to these two factors. As you'll see, it's a very mixed picture.

Workforce Trends and Personality Types (part 1 of 3)

In last week's blog, I looked at some occupations that combine personality types that are often thought of as opposites. This week, I want to look at trends in the workforce from the standpoint of personality types. Which personality types are seeing greater opportunities, and which are seeing opportunities drying up?

(Last week, I said that this week's blog would compare the John Holland personality types using the statistical technique called correlation. I've since decided that this topic would be too dry for this venue. If you're curious about the results I found, please e-mail me at Laurence[at]myself.com.)

 To create the graph that follows, I looked at the workforce sizes reported by the Occupational Employment Statistics program for May 2002 and May 2012. I clustered the occupations by their primary Holland types, and here are the changes I found:

This graph should be no surprise if you have been following workforce trends. You can see that the only personality type that actually sees a decrease in workforce size is the Realistic type. This 7 percent decrease is largely the result of the shift away from manufacturing jobs, so many of which involve hands-on Realistic work. Note that this decrease does not necessarily mean that less manufacturing is now going on in the United States. It reflects a decrease in the number of jobs, not in the amount of economic activity. Automation has replaced many of the jobs formerly held by Realistic workers.

The biggest increases are in the workforces where Investigative and Social personality types are employed. These increases reflect the growing importance of research and development, health care, and education.

The increases for the Enterprising and Conventional personality types, 2 percent each, are identical to the overall growth of the American workforce. In other words, the occupations appealing to these personality types are holding their own but not gaining in importance.

For me, the biggest surprise was the 7 percent increase in the workforce for the Artistic type. It turns out that our media-rich culture accounts for much of this increase: The number of Graphic Designers increased by 49,610 workers (35 percent) and Interpreters and Translators by 31,720 workers (171 percent).

What can you do if your personality type aligns with a workforce that is shrinking or expanding at a tepid rate? Keep in mind that even a shrinking workforce offers many job opportunities, including hires that result from attrition and turnover. In addition, you may find satisfaction in an occupation in which your personality type plays a secondary role. For example, Electrical Engineers, which grew by 10 percent (14,380 workers), is coded IR, meaning that Realistic is its secondary personality type.

Finally, you may find more opportunity for your personality type by boosting your level of skill. Next week, I'll show why this can be a winning strategy.

Personality and Career: The “Bipolar” Occupations

Let me begin by explaining that in the title to this blog, I am not using the term “bipolar” in its clinical sense. That is, I’m not referring to people who have alternating periods of manic and depression. Instead, I’m using the term to refer to those occupations linked to personality types that are considered polar opposites. It’s interesting to consider why some occupations can bridge these divides.

The personality taxonomy on which I’m basing this analysis is the hexagon of types described by John S. Holland. Holland’s hexagonal scheme is based on the idea that certain personality types are similar and more likely to be shared by people and by occupations (adjacent angles on the hexagon), whereas others are more distinct (opposite angles). The O*NET database follows Holland’s practice of assigning occupations to one primary personality type and one or two secondary types—in other words, positioning them between two angles of the hexagon rather than at just one angle.

I thought it would be interesting to look at occupations in the O*NET database for which the primary type and the first secondary type are at opposite ends of the hexagon. In other words, they should appeal to people who have interests and other preferences that are supposed to overlap only rarely. (Maybe you are one of these people.)

By far the largest group of these “bipolar” occupations consists of those that combine the Realistic and Social personality types. In case you need to be reminded of how these types are defined, Realistic personalities prefer hands-on work, whereas Social personality types prefer work that helps other people. These RS and SR occupations consist mainly of health-care careers. Here are a few:

Oral and Maxillofacial Surgeons (RSI)

Anesthesiologist Assistants (RSI)

Radiologic Technologists (RS)

Surgical Technologists (RSC)

Radiation Therapists (SRC)

Acupuncturists (SRI)

Dental Hygienists (SRC)

Respiratory Therapy Technicians (SRI)

Licensed Practical and Licensed Vocational Nurses (SR)

Orthotists and Prosthetists (SRI)

Athletic Trainers (SRI)

Midwives (SR)

Home Health Aides (SR)

Psychiatric Aides (SRC)

Occupational Therapy Assistants (SR)

When you read stories about the projected shortage of health-care workers, especially for hands-on roles, understand that the most important reason is the expected demand caused by an aging population. But perhaps a secondary reason is a shortage of supply that happens because it is difficult to find workers who enjoy the combination of hands-on work and caring for others.

Not all of the RS and SR occupations are in health care. Some of the RS occupations are in protective services in roles where they do hands-on work—for example, Lifeguards, Ski Patrol, and Other Recreational Protective Service Workers (RS), Municipal Firefighters (RSE), Forest Firefighters (RS), and Animal Control Workers (RSC). The SR occupations not concerned with health care are an odd mixture such as Park Naturalists (SRA), Coaches and Scouts (SRE), and Food Servers, Nonrestaurant (SRE).

The Investigative personality type (solving problems mentally) and the Enterprising type (leading and persuading) overlap mostly in a group of IE occupations that use quantitative methods to solve business problems:

Management Analysts (IEC)

Market Research Analysts and Marketing Specialists (IEC)

Business Intelligence Analysts (IEC)

Industrial Ecologists (IE)

Environmental Economists (IEC)

Industrial-Organizational Psychologists (IEA)

Urban and Regional Planners (IEA)

Whereas the SR occupations employ very large (and increasing) numbers of workers, the IE occupations are both fewer in number and tend to have smaller workforces. They also tend to earn much higher pay because they demand a high level of academically-acquired skills and operate in business settings.

Some of the EI occupations are similar: Business Continuity Planners (EIC), Sustainability Specialists (EIA), Fraud Examiners, Investigators and Analysts (EIC), and Search Marketing Strategists (EIC). I also find two law occupations—Lawyers (EI) and Administrative Law Judges, Adjudicators, and Hearing Officers (EIS)—plus two occupations in inquisitive protective services—Police Detectives (EI) and Criminal Investigators and Special Agents (EI). I’ve long been puzzled by the presence of police and lawyers among the Enterprising occupations, but I suppose it is because of the persuasive aspects of the work.

The last axis within the Holland hexagon runs between the Artistic (creative, independent) and Conventional (systematic, orderly) personality types. It’s interesting to find that there are no AC occupations and only one CA occupation: Proofreaders and Copy Markers (CA). Evidently it is extremely difficult to find work that combines the unstructured setting of the Artistic type with the structured setting of the Conventional type.

However, the approach I used for this blog—looking for occupations with primary and secondary types at opposite poles—is only one way to look at the relationships between pairs of Holland types. Another way is to do statistical analysis—specifically, to find the correlations between the ratings of occupations on the various types. In next week’s blog, I’ll look at the hexagon through this lens.

Deal-Making Careers

Recently I was speaking with a cousin who is contemplating a career change after working in the same industry for more than 30 years. I suggested to him that in choosing a new direction, he might want to leverage the enormous fund of knowledge and contacts he has acquired in his work. Why throw all that away?

This is the central idea of my book The Sequel, in which I look at various ways to make a mid-career occupational change without starting from scratch. One of the sequel careers that I discuss is brokering.

A lot of buying and selling goes on in every industry. People who have a lot of work experience in an industry usually are well informed about how these deals get made. They know who the main sellers are, what they have to offer, how much they’re likely to ask in payment, and what makes the difference between and good deal and a bad one. They also know about the buyers: where they come from, what they’re looking for, what they’re able to pay, and what makes the difference between a good customer and a bad one. Old industry hands may also know about arrangements besides price that are commonly involved in the deal, such as warrantees and common modes of delivery.

People with these kinds of knowledge may be able to make a career of bringing buyers and sellers together and earning a commission on the sales. That is what brokers do.

Brokers act as matchmakers. For example, a freight broker finds a business that needs to ship some kind of cargo and matches it with a carrier that can provide the appropriate kind of shipping service at an acceptable price. The freight broker never takes possession of the cargo and merely arranges the deal. The company producing the cargo appreciates the broker’s ability to quickly identify a reliable and low-priced shipper. The shipper appreciates the added business, which may result in more trucks plying their routes with full loads.

Brokers often advise and inform buyers to help them make a wise choice and understand the necessary paperwork. For example, a mortgage broker may counsel a borrower on how to correct a situation that harms the borrower’s credit rating or may explain the pros and cons of different loan arrangements. An energy broker may explain to a commercial client the benefits and risks of entering a contract with an electric company that locks in a specific rate for electric power for a year.

Some brokers facilitate the sale of a division within a business or even the entire business. Working with a broker in a confidential arrangement keeps news of the planned sale off the street so customers of the business do not lose confidence in it.

Brokers spend much of their time making decisions. The decisions need to be correct and can have a large impact. The pressure of time and competition can add to the stress of this work. Although brokers have a lot of independence, the context in which they make their decisions tends to be structured and even repetitious. Brokering provides the satisfaction of helping clients achieve their goals. This can be especially rewarding when people can live better lives by achieving goals such as a college degree or the purchase of a home.

Here are some occupations that act as brokers:

• Agents and Business Managers of Artists, Performers, and Athletes
• Cargo and Freight Agents
• Customs Brokers
• Energy Brokers
• Insurance Sales Agents
• Investment Underwriters
• Loan Officers
• Purchasing Agents and Buyers, Farm Products
• Purchasing Agents, Except Wholesale, Retail, and Farm Products
• Real Estate Brokers
• Sales Agents, Financial Services
• Securities and Commodities Traders

Besides knowledge of an industry, brokers often need to carry insurance to protect their clients from loss. Sometimes they are also required to be bonded, an additional expense when you set up a brokerage.

Knowledge of applicable laws is important in many industries, so it may be necessary for you to take one or more classes to become fully informed and, in many cases, prepare for a licensure exam. (A college degree is rarely necessary, although it can be helpful.) The license assures clients that you know the laws and may also indicate that you possess appropriate insurance. In some industries, a criminal background check is a common requirement. Because there is so much variation, you should check the requirements for your industry and state.

Transportation brokers need to register with the Federal Motor Carrier Safety Administration.

In many industries, a common entry route is to work first as an agent on the staff of a brokerage. Agents usually are not required to carry the level of responsibility, including legal liability, that a broker carries. Licensing and insurance requirements tend to be much lower. Real estate brokers usually begin as sales agents. In fact, work experience in sales is a requirement for a real estate broker’s license, although in some states it is waived for those with a bachelor’s degree in real estate.

It’s easier to set up a brokerage business in some industries, such as the highly regulated insurance industry, than in others where a few major players dominate.

The Pros and Cons of Federal Jobs

In response to this week’s shutdown of the federal government, I thought it would be a good time to look at the advantages and disadvantages of working for this employer.

Compared to jobs in the private sector, jobs with the federal government have many advantages:

• Federal jobs tend to be more secure. When agencies need to reduce their size, they usually do so by attrition (that is, not replacing people who leave). Employees can challenge termination or other personnel decisions through a formal appeals process.
• Hiring and promotion in federal jobs are guided by a stronger commitment to diversity and inclusion than you’ll find in most private-sector worksites.
• Federal jobs offer a wider selection of health-insurance plans than do private-sector employers. Retirees can continue their health-insurance coverage for the same fee they paid while working.
• Federal jobs offer better retirement benefits than many jobs in the private sector.
• Federal jobs offer 10 holidays per year.
• Federal jobs offer 13 vacation days per year to beginning workers, 20 days after 3 years, and 26 days after 15 years. To this, add 13 days of sick leave per year.
• Federal jobs often permit flexible work arrangements. For example, you may be able to work four 10-hour days per week or do some work from home. Workers are rarely required to work more than 40 hours. This can make a huge difference in some fields, such as law and accounting.
• High-quality day care for children is often available at federal job sites or sometimes is subsidized at off-site centers.
• Federal jobs can give you the satisfaction of serving the nation.

Federal employment is not a worker’s paradise, however:

• Competition for some federal jobs is intense.
• Contrary to what you may have heard about the growth of the federal workforce, it is not a fast-growing field. The Bureau of Labor Statistics projects that the federal workforce will shrink by 12.5 percent from 2010 to 2020, compared to 14.3 growth percent for all industries. If you don’t count Postal Service jobs, the federal workforce shrinks by “only” 8.2 percent, but that still compares quite poorly to the average across all career fields.
• A few federal jobs require security clearance, which may require background investigations that can drag on for months.
• The workplace structure tends to be more bureaucratic than in small private-sector businesses. In high-tech jobs, the workplace may be slower to adopt the newest technologies.
• Sometimes political pressures prevent workers from doing their jobs as they see fit.
• Although the many rules are designed to promote fairness, some workers find ways to manipulate the rules to gain an advantage.

What about pay? The answer depends on how you analyze the data. Federal workers earn more than private-sector workers, but they also are better educated. Most individual federal workers would earn more in an equivalent private-sector job. On the other hand, federal pay is extremely fair. In many private-sector jobs, you have to negotiate your salary and don’t know what other workers’ salaries are based on. The pay for federal jobs is supposed to be comparable to what is current in the private sector, with adjustments for local cost of living, and it is based on your salary grade.

The high level of competition for federal jobs, though listed here as a disadvantage, is an indication that work for the federal government is, on balance, very rewarding (when it’s not shut down by political blackmail).

You can read details about specific federal jobs in my book 150 Best Federal Jobs (JIST).

Are You a City Mouse or a Country Mouse?

If you’re making career plans, you may have a definite preference for the urban lifestyle or the rural lifestyle. Some people prefer the diversity, lively cultural scene, public transportation, really good restaurants, and fast pace of city life. Others would rather enjoy the big horizons, closeness to nature, traditional values, quiet, and slow pace of rural life.

If you have already made your choice of a career goal, you may have already settled this issue. Some careers, such as those in the performing arts, are very difficult to sustain in a rural area. On the other hand, many occupations in agriculture and mining require the open countryside that is scarce in urban areas.

But let’s assume that you have not yet made your career choice. One factor to consider is that, all things being equal, there tend to be more job openings in urban areas simply because there are so many businesses. Of course, you also face more competition in cities because there are so many workers with skills like yours. Another two-edged sword is the higher pay that urban jobs usually command; this may be offset by the higher cost of living (especially for housing and locally provided services) in urban areas.

So I’m not going to try to influence your thinking on this issue. I’ll assume that you have a definite preference for either urban or rural living but have not yet settled on a career goal, either as a first occupation or as a midcareer shift. So let me show to you which occupations have a high concentration in either urban or rural settings, and maybe you can find one that matches your skills and not just your preferences for location.

To calculate the urban percentage for each occupation for which I could get information, I identified the 38 largest metropolitan areas out of all 380 metro areas for which the Bureau of Labor Statistics reports workforce size (in the Occupational Employment Statistics data). For each occupation, I summed the number of workers employed in these 38 metro areas and then divided it by the total number of workers in that same occupation throughout the United States.

For the following list, I set the cutoff for this urban percentage at 70. In other words, this list shows those occupations for which at least 70 percent of the workers are employed in the largest cities. The occupations are ordered to put those with the highest urban percentage at the top of the list.

Occupation                                                                   Urban Percentage

Fashion Designers                                                     85%

Agents and Business Managers of Artists, Performers, and Athletes   82%

Parking Lot Attendants                                               80%

Film and Video Editors                                               79%

Media and Communication Workers, All Other     78%

Art Directors                                                                  78%

Political Scientists                                                       75%

Sound Engineering Technicians                              74%

Multimedia Artists and Animators                            74%

Software Developers, Applications                          74%

Producers and Directors                                            74%

Economists                                                                  73%

Financial Analysts                                                       72%

Sales Engineers                                                          72%

Securities, Commodities, and Financial Services Sales Agents            72%

Brokerage Clerks                                                        72%

Medical Scientists, Except Epidemiologists          72%

Manicurists and Pedicurists                                      71%

Software Developers, Systems Software               71%

Marketing Managers                                                   71%

Writers and Authors                                                    71%

Actors                                                                             71%

Computer Network Architects                                   70%

Information Security Analysts                                    70%

Market Research Analysts and Marketing Specialists               70%

Computer and Information Systems Managers    70%

Baggage Porters and Bellhops                                70%

To calculate the rural percentage for occupations, I used a procedure similar to what I used for the urban percentage. However, instead of using workforce figures that applied to metropolitan areas, I used figures for the 172 nonmetropolitan areas for which the BLS reports occupational earnings. These nonmetro areas are regions such as east central Pennsylvania, the Low Country of South Carolina, coastal Oregon, and the Upper Peninsula of Michigan.

In the following list, the cutoff percentage is 25, which means that at least 25 percent of the workforce of each occupation is employed in the 172 nonmetropolitan areas. The occupations with the highest rural percentages are at the top of the list.

Occupation                                                                   Rural Percentage

Mine Shuttle Car Operators                                       71%

Roof Bolters, Mining                                                    66%

Logging Equipment Operators                                 63%

Postmasters and Mail Superintendents                 53%

Forest and Conservation Technicians                    51%

Roustabouts, Oil and Gas                                         51%

Farm Equipment Mechanics and Service Technicians             47%

Sawing Machine Setters, Operators, and Tenders, Wood        45%

Loading Machine Operators, Underground Mining    43%

Service Unit Operators, Oil, Gas, and Mining         40%

Continuous Mining Machine Operators                  40%

Wellhead Pumpers                                                     40%

Slaughterers and Meat Packers                               40%

Highway Maintenance Workers                                39%

Helpers--Extraction Workers                                     39%

Rotary Drill Operators, Oil and Gas                         38%

Log Graders and Scalers                                          38%

Woodworking Machine Setters, Operators, and Tenders, Except Sawing            35%

Legislators                                                                    35%

Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders    34%

Agricultural Equipment Operators                            33%

Meat, Poultry, and Fish Cutters and Trimmers      33%

Farmworkers, Farm, Ranch, and Aquacultural Animals           32%

Explosives Workers, Ordnance Handling Experts, and Blasters            31%

Derrick Operators, Oil and Gas                                29%

Correctional Officers and Jailers                              28%

Textile Knitting and Weaving Machine Setters, Operators, and Tenders               28%

Water and Wastewater Treatment Plant and System Operators             28%

Electrical Power-Line Installers and Repairers    27%

Operating Engineers and Other Construction Equipment Operators    27%

Fallers                                                                            26%

Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders                26%

Foresters                                                                       25%

Welders, Cutters, Solderers, and Brazers              25%

Mine Cutting and Channeling Machine Operators     25%

First-Line Supervisors of Farming, Fishing, and Forestry Workers        25%

Excavating and Loading Machine and Dragline Operators      25%

Racial Disparity in Earnings

Today, even as I am writing this, people are gathered on the Mall in Washington, DC, to mark the fiftieth anniversary of the march on Washington at which Dr. Martin Luther King, Jr., gave his most famous speech. It’s useful to remember that the actual name of that event was the March on Washington for Jobs and Freedom. I thought this would be a good occasion to take a look at the employment situation of African American workers.

Figures on unemployment are relatively easy to obtain. For example, you can quickly find that 13.8 percent of the African American population in the labor force is unemployed, compared to 7.2 percent in the White population. (These are actually 2012 figures.)

What I thought would be more interesting would be to look at the racial mix of various occupations and see the impact on earnings. Recently, I have been doing a lot of analysis using correlations, so I decided to see how racial presence in occupations is correlated with median earnings in those occupations. Understand that correlation is not the same as causation, but it indicates that two things are happening together, for whatever reason. In this case, I was trying to determine whether concentration of any race tends to happen together with the level of median earnings.

What I found was not surprising but also not pleasant to contemplate. The correlation between percentage of African American workers in occupations and median income in those same occupations was –0.37. If you’re not familiar with correlation, let me explain what this negative correlation means: To some extent (specifically, 37 on a scale of 0 to 100), the greater the percentage of African Americans working in an occupation, the lower the median income of that occupation is likely to be. For Hispanic/Latino workers, the negative correlation is actually even greater: –0.48.

For Whites and Asians, however, the correlations are positive: 0.24 for Asians and 0.43 for Whites.

Note that this simple analysis masks a lot of information. It does not tell us what positions the workers of each races are holding within the occupations. It also does not tell us the full-time or part-time status of the workers. (Actually, a slightly higher percentage of White workers are part-timers.) It does not include earnings of self-employed workers. It does not account for loss of earnings among those who are counted in an occupation but who currently are unemployed. For actual earnings comparisons, a better indicator might be that full-time African American male workers are currently earning 75.3 percent of the earnings of White male workers. For women, the figure is 85.0 percent. These actual earnings comparisons are consistent with what I found about tendencies in occupations.

These statistics are one more indication that we do not yet live in a postracial society. Understand that the solution to this situation is not simply a matter of achieving colorblindness in hiring, although that certainly would help and is something we have not yet achieved. In an experiment described in a paper (PDF) called “Are Emily and Greg More Employable than Lakisha and Jamal?,” resumes were randomly assigned African American– or White-sounding names and sent to employers in the Chicago and Boston areas. The resumes with White-sounding names resulted in 50 percent more callbacks for interviews.

Even if hiring were not biased, the career prospects of African Americans are damaged by a justice system that stops, arrests, and imprisons African Americans at a much higher rate than Whites, even for offenses that are known to be committed at equal rates. Imprisoning people not only puts a stain on the convict’s record that reduces employability but, especially for young people, breaks up families and thus damages the prospects of the next generation.

I am not blind to the advances in racial justice that have been made over the past 50 years. But our nation has a lot further to go to realize Dr. King’s dream, and doing so will take positive action, not passive waiting around for change to occur.

Changes in Skill-Income Payoff Over 10 Years

Everybody knows that a high level of skills is associated with high earnings, but perhaps you have been wondering which skills have the highest payoff. I actually answered that question just about a year ago in a blog that I wrote called “Transferable Skills with the Biggest Payoff.”  When I did the research for that blog, I wanted to use a statistical approach to seeing which skills are linked to the highest earnings, so I computed the correlations between the skill ratings of occupations and their median income. In the blog, you can see that Judgment and Decision Making, Complex Problem Solving, and Active Learning were the transferable skills with the highest payoff.

Now, a year later, I have been thinking about career trends and decided it would be useful to see whether these correlations changed over time. So I ran correlations again, using 2002 and 2012 earnings data from the Bureau of Labor Statistics. If you want to understand how I calculated correlations, as well as the significance of correlations as a technique, I suggest you look at the earlier blog.

As you might expect, the payoff for some skills increased over that ten-year span and decreased for others. Even the largest differences were not very big: the correlation of one skill gained by .06. Keep in mind that correlations are computed on a scale in which 1.0 means total correlation. You may think of the numbers as equivalent to percentages, which means that the biggest gain in correlation was equivalent to 6 percent.

So here are the skills that gained the most from 2002 to 2012, which is to say that their connection to earnings increased the most:

	2002 Correlation	2012 Correlation	Gain
Technology Design	0.34	0.40	0.06
Management of Material Resources	0.41	0.45	0.05
Management of Financial Resources	0.46	0.50	0.04
Installation	-0.08	-0.05	0.04
Management of Personnel Resources	0.57	0.60	0.03

I find it really interesting that three of these skills are managerial. What I take away from this is that compensation for management has probably been increasing over the last decade relative to compensation for other occupations.

I’m not surprised to see Technology Design posted the largest gains. Here’s how this skill is defined: “Generating or adapting equipment and technology to serve user needs.” It is well known that technology jobs are in high demand, but this skill is about practical uses of technology rather than scientific principles. The increasing correlation of this skill with earnings gives reinforcement to the idea that what increasingly drives the U.S. economy is innovation in applications of technology—think of the iPhone, for example.

I’m intrigued by the large gain for Installation. You’ll notice that the correlation is still in negative territory, which means that the more of this skill you use, the lower your earnings are likely to be. However, over the past decade the correlation got .04 closer to zero, which means that having this skill as an important part of your work has become less of an income liability. Perhaps the occupations with a heavy emphasis on installation are becoming better compensated as the level of technology that they use increases. In other words, as technology becomes simultaneously more complex and more important in everyone’s lives, it is becoming increasingly necessary to pay good wages to people who can install the sophisticated software and hardware that we use constantly.

Only four skills had lower correlations to earnings in 2012 than in 2002, meaning that there is less of a payoff now than there was then. These are the four:

	2002 Correlation	2012 Correlation	Loss
Repairing	-0.18	-0.19	-0.02
Operation and Control	-0.18	-0.19	-0.02
Equipment Maintenance	-0.19	-0.20	-0.01
Science	0.58	0.57	-0.01

Note that three of the four have negative correlations, meaning that they already were associated more with low earnings than with high earnings and only got more so. These three skills—Repairing, Operation and Control, and Equipment Maintenance—are characteristic of rust-belt occupations that are being replaced by robots and foreign workers.

I was quite surprised, however, to see that Science had lost ground. The contrast with the performance of Technology Design is instructive and tells me that applied scientific knowledge has gained in earnings even while abstract scientific knowledge has lost slightly. It is consistent with the disappointing national trend toward diminished funding for basic scientific research and reminds me of how a member of my family recently quit her job in medical research and became a software developer. I looked at how the correlation for Science changed on a year-by-year basis and found that it actually climbed during the first half of the decade, peaking in 2008, and then began its downward slide. This suggests that the Great Recession brought on the comparative decrease in pay for scientific research jobs.

It’s important to understand that none of the nine skills I focus on in this blog is among those with particularly high correlations with income. The movement you see here happened in the middle and bottom of the pack. If income is very important to you, I suggest you look at the earlier blog and aim at occupations that involve Judgment and Decision Making, Complex Problem Solving, Active Learning, and other skills with the highest correlations.