Where I mix career information and career decision making in a test tube and see what happens

Wednesday, April 9, 2014

Job-Growth Projections for Men and Women

Today the Senate failed to pass legislation aimed at closing the pay gap between the sexes, and a lot of attention is being paid to the extent of that gap and what can be done about it. I have blogged about this issue several times, but for this week I decided to look at a different male/female issue: Who has the better outlook for job growth?

To answer this question, I assembled figures from the Bureau of Labor Statistics on the percentage of men and women in various occupations and the projected workforce growth (2012 to 2022) of those same occupations. Then I calculated the correlation between male/female presence and job growth.

Before I tell you my findings, here are two important caveats: (1) Figures for percentage of women are not available for many occupations. In most cases where figures are lacking, it is because the occupation is so heavily male that the sample of women incumbents is statistically insignificant. So instead of basing my correlations on detailed occupations, I based them on 22 families of occupations—for example, Management Occupations and Food Preparation and Serving Related Occupations. (2) My correlations are based on the present representation of the sexes in the occupations, not what the percentages will be by the time the projection period is over. It is possible that by 2022 we may see different gender ratios in some occupations.

Okay, now for my findings: The correlations between these occupational families and their outlook worked out to be 0.47 for women and -0.47 for men. In other words, there is a significant tendency for female presence in an occupational family to predict expansion of the workforce, whereas male presence tends to be linked to a shrinking workforce.

If you have been following trends in the economy, these findings should not be surprising. The fastest-growing (28.1 percent) segment of the economy is Health-Care Support Occupations, and many of the fastest-growing occupations in that segment are those (such as Registered Nurses) that are heavily dominated by women. Women are also prominent in another fast-growing (20.9 percent) segment, Personal Care and Service Occupations.

If you delve down to a level of greater detail, the correlations seem to be much less strong. I ran correlations using detailed occupations for which female percentages are reported and found results that were vanishingly close to zero. Now, understand that to create these calculations, I had to throw out a large number of occupations that had no female percentage reported, and in many cases these discarded occupations were virtually all-male. Many of them were in the Production Occupations sector, so I lost much of the drag of this sector (0.8 percent growth) on male prospects. On the other hand, many of these virtually-all-male occupations were in the Construction and Extraction Occupations sector, which is second only to Health-Care Support Occupations in projected growth (21.4 percent).

All things considered, I believe it likely that at a more detailed level, the relationship between gender presence and outlook is more tenuous. So if you seek an occupation with a good outlook, make a point of learning the growth projected for that specific occupation, and don't base your expectations solely on the female or male presence in the occupation.

Wednesday, April 2, 2014

Employment Trends for Engineers

As the “E” in “STEM,” engineering is an important field of knowledge that is vital to the American economy. I thought it would be interesting to see how employment in this field was affected during recent years of recession and recovery, so I created the following graph (from BLS figures):


My main takeaway from this chart is that employment in engineering occupations tends to be reasonably stable. Apart from the 2007–2008 employment decline of 26 percent for aerospace engineers, only one occupation saw a double-digit decline between any two years: the 12 percent 2008–2009 decline for computer hardware engineers. On the other hand, these occupations did not show great growth over this period either—with the exception of petroleum engineers, which grew by 127 percent. Their average growth over the 2007–2012 period is only 3 percent, if you remove petroleum engineers.

Although employment in the occupations changed within relatively modest boundaries, the fluctuations show quite distinct paths. Employment for most of them bottomed out in 2010, evidently the delayed result of the recession as employers ran out of rainy-day funds and needed to lay off workers.

Here’s another chart, with the same set of occupations, showing projected employment growth between 2012 and 2022:


Petroleum engineers is the standout occupation here, again. The recent upward slope of civil engineers resembles that of many of the other specializations, but the growth of this occupation really takes off in the decade ahead. The Occupational Outlook Handbook reports, “As infrastructure continues to age, civil engineers will be needed to manage projects to rebuild bridges, repair roads, and upgrade levees and dams. Moreover, a growing population means that new water systems will be required while the aging, existing water systems must be maintained to reduce or eliminate leaks of drinkable water.” By comparison, the projected growth for mechanical and industrial engineers is modest.

Over the course of a career, engineers tend to find advancement by going into management (for example, project management) rather than by becoming increasingly specialized. Employers often are reluctant to increase the pay of seasoned engineers when they can hire young graduates of engineering schools who are conversant with the latest technologies. Sales engineering is another potential route for career development, especially for those who have good people skills and are not averse to frequent travel. Technical writing is another possibility, but it is much less lucrative.

Wednesday, March 26, 2014

Fame and Skill Go Together

A few days ago, The New York Times ran an op-ed piece called “The Geography of Fame.” It was written by an economist, Seth Stephens-Davidowitz, who used Wikipedia as a database and extracted the birthplaces—specifically, the counties of birth—of more than 150,000 Americans who are listed in the online encyclopedia. He combined this data set with figures on the number of births in each county and computed, for each county in the United States, the odds that a baby boomer born there would become notable enough to be listed on Wikipedia. He limited his study to baby boomers, those born between 1946 and 1964, in order to allow his subjects a full lifetime in which to achieve notability.

His most striking finding was that the counties that produced the highest density of Wikipedia personages tended to encompass college towns. For example, among the top 13 were the counties that are home to the Universities of Iowa, Michigan, Missouri, Wisconsin, and Florida, as well as the counties of Tompkins, NY (home of Cornell) and Mercer, NJ (home of Princeton). The second most significant attribute of counties that produce famous people was the presence of a very large city. (All of these cities, such as Boston, New York, and Washington, also are the sites of universities.)

These two findings were remarkably similar to what I discovered when I did an analysis of the metropolitan areas where high-skill jobs are particularly concentrated. (I reported on my findings in my blog of August 10, 2011.) For example, here are the top 10 metropolitan areas with a high density of occupations requiring a high level of communication skills:

1. Durham, NC
2. Washington-Arlington-Alexandria, DC-VA-MD-WV
3. Trenton-Ewing, NJ
4. San Jose–Sunnyvale–Santa Clara, CA
5. Boston-Cambridge-Quincy, MA-NH
6. Hartford–West Hartford–East Hartford, CT
7. Gainesville, FL
8. Bridgeport-Stamford-Norwalk, CT
9. San Francisco–Oakland–Fremont, CA
10. Rochester, MN

Most of these are college towns, and several are very large cities.

I also found that many metro areas came up repeatedly when I looked at different skills. For the nine skills that I looked at, Boston-Cambridge-Quincy, MA-NH appeared on seven of the top-20 lists. The metro area where I live, Trenton-Ewing, NJ (home of Princeton), appears on five of the nine lists, as does New Haven, CT, the home of Yale.

One factor that Stephens-Davidowitz noted but that I missed was the influence of immigrants. You may not be surprised to find that college towns and metropolises attract many immigrants, but the economist also found that when two counties with similar populations and college attendance are compared, the county with the higher concentration of immigrants tends to produce more notable Americans. Having immigrant parentage, he discovered, also increases your chances of elevation to Wikipedia.

Now, I’ll admit that there is no easy way to determine the skill level of the people profiled on Wikipedia. But I’m sure you’ll agree that most of them did not achieve their fame purely by luck. And this supposition is borne out by the fact that the same environments that produce famous people are also home to the highest-skill jobs.

Wednesday, March 12, 2014

Don’t Let Schooling Interfere with Your Education

I owe Mark Twain the title of this week’s blog. His career makes an interesting case study and attests to the wisdom of his dictum, because the famous writer had little formal education. He never went to college but instead apprenticed as a printer. While working as a typesetter, he took up writing as an avocation, contributing humorous articles to a newspaper owned by his brother. He learned his next occupation, Mississippi riverboat pilot, again through on-the-job training, but eventually the Civil War put an end to most civilian traffic on the river. Next, taking advantage of his brother’s appointment as secretary to the governor of Nevada Territory, he spent a couple of years pushing papers in government offices.

After failing in his attempt to strike it rich as a miner (later detailed in Roughing It), he fell back on journalism in Virginia City. Then, while working as a journalist in San Francisco, he published his first big commercial success, “The Celebrated Jumping Frog of Calaveras County,” and over the following years he evolved from a journalist with a knack for travelogue writing to the novelist who now ranks among America’s greatest. He had a parallel career as a lecturer that grew out of his travel writing. He also pursued an avocation as an inventor, perhaps an outgrowth of the technical skills he had learned in his boyhood, but he had only mixed success. As an investor, he was particularly inept and at one point had to declare bankruptcy.

Nowadays, a career path like this would be hard to follow. Nevertheless, we can learn certain important lessons from it.

First, many skills can be learned informally, perhaps through leisure-time pursuits, and these can later be the basis of a career change. Although formal educational credentials (and the technical skills they represent) are more important now than ever before, employers often express frustration at being unable to find job candidates who have the right soft skills. Therefore, although I recognize the importance of a college degree, I urge young people to round out their college educations with activities that will cultivate soft skills. These may be part-time jobs, internships, student organizations, or volunteer activities. Probably the most important characteristic to look for in these extracurricular activities is collaborative work, because it builds people skills and communication skills that are rarely central to academic coursework. This is the core of the message in the title of this week’s blog.

Second, be ready to take advantage of unexpected opportunities. Growing up in a small riverfront town, Mark Twain became aware of the opportunities that being a riverboat pilot offered for high pay and the chance to escape small-town life. But when that livelihood dried up, he was ready to use a personal connection to shift to a new occupation that led him to unanticipated career opportunities. These did not always work out, but because Twain had a fund of skills and the resilience to recover from setbacks, he eventually found his way to his main claim to fame. He was able to reinvent himself several times. In fact, he even reinvented his name from Samuel Clemens to Mark Twain.

Finally, if you change from one industry to another (whether willingly or from necessity), try to find ways to use your accumulated fund of knowledge in your new field. Mark Twain based his jumping frog story on an anecdote he heard while working as a miner in Nevada. He drew on his riverboat experience when he wrote Life on the Mississippi and Huckleberry Finn, and the mechanical knowledge he acquired as a printer’s apprentice figures in A Connecticut Yankee in King Arthur’s Court.

Few can achieve the immortal fame of Mark Twain, but we all can benefit from emulating the traits that allowed him to grow and advance from his initial job as a small-town printer: a constant love of learning, alertness to opportunities, resilience, and the resourcefulness to exploit what he had already learned.

Wednesday, March 5, 2014

Occupations with Rising Shares of Overqualified Workers

The press often features anecdotes about people with college degrees who are working in jobs with much lower educational requirements. These anecdotes often are used to illustrate the hard times that have befallen college graduates since the Great Recession. I thought it would be interesting to look at labor market statistics and see whether or not these anecdotes indicate an actual trend.

For my analysis, I consulted the figures that the Department of Labor reports for the educational attainment of incumbents in various occupations. These figures are ultimately derived from the Current Population Survey and represent both part-time and full-time workers. I compared the figures reported for 2008 and 2012 to get an idea of the impact of the recession.

I found that for all workers in all occupations, the number of incumbents who had some college education or a degree, as opposed to a high school diploma or less, increased by 3 percent between 2008 and 2012. Understand that this 3 percent represents the total of people in five categories of attainment, ranging from “some college, no degree” to “doctorate or professional degree.” For any one category, the increase was 1 percent or less.

Overall, this small increase in workers with college under their belts is not a major trend. Rather than reflect increasing entry requirements and stiffer competition for jobs, it may result from increases in the share of working-age people with college experience. The retirements and job losses of leading-edge baby boomers are helping to increase this share. To be sure, it is possible that the 3 percent increase may be so small because many college-educated people are staying out of the workforce until jobs suited to their level of education become available. But that explanation still gives the lie to the notion that there are growing tends of thousands of baristas, shipping clerks, and carpenter’s helpers who hold bachelor’s degrees.

Now, let’s turn from the workforce as a whole and consider some particular occupations that do show a significant uptick in the percentage of workers with college education. Here are some that stand out.

Probation Officers and Correctional Treatment Specialists. Between 2008 and 2012, the percentage of those with some college increased by 10.7 percent, and the percentage of those with a bachelor’s degree by 20.7 percent. The BLS considers a bachelor’s degree the appropriate preparation for this occupation, but clearly this requirement is being enforced more in recent years than it used to be. The workforce for the occupation actually shrank over this time period—by 12.3 percent, compared to 3.7 percent shrinkage for the workforce in all  occupations—and the BLS considers “heavy workloads and high job-related stress” to be characteristics of the work, probably contributing to turnover. This shrinkage and turnover help to explain why the educational makeup of the workers could change so greatly in only four years.

Brokerage Clerks. The percentage of those with some college increased by 6.5 percent, and the percentage of those with a bachelor’s degree by 16.2 percent. Unlike the previous occupation, this one is considered to require only a high school diploma or its equivalent, plus moderate-term on-the-job training. However, this is the highest-paying of all the kinds of financial clerks, with median annual earnings of $42,440, compared to $35,310 for loan interviewers and clerks and $24,610 for gaming cage workers. Perhaps more important, some workers may enter this occupation (as opposed to other kinds of clerical jobs) as a pathway to employment as Securities, Commodities, and Financial Services Sales Agents. In addition, those incumbents with some college may have been better able to survive the layoffs that occurred as this occupation shrank by 9.0 percent over the 2008–2012 time period.

Model Makers, Metal and Plastic and Patternmakers, Metal and Plastic. (The BLS does not offer separate figures for these two kinds of metal and plastic machine workers.) The percentage of those with some college increased by 15.5 percent. Although the percentage of those with a bachelor’s degree increased by only 8.0 percent, that is still an impressive figure for an occupation that is considered to require only a high school diploma or its equivalent, plus moderate-term on-the-job training. But here again, as in the preceding occupation, one contributing factor may be the high pay that this occupation commands. These workers average $22.04 (Model Makers) and $20.40 (Patternmakers) per hour. Among other metal and plastic machine workers, the only ones who earn more are Computer Numerically Controlled Machine Tool Programmers, Metal and Plastic ($22.08). Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic, average only $13.77. In addition, the offshoring of manufacturing has drastically shrunk this occupation—by 37.6 percent over the 2008–2012 time period. Those workers who have survived the layoffs are likely to be the highly skilled—and therefore highly schooled—workers who can operate computerized equipment.

Medical Transcriptionists. The percentage of those with some college increased by 14.7 percent, although the percentage of those with a bachelor’s degree increased by only 4.1 percent. Unlike the two preceding occupations, this one is considered to require postsecondary training, which is offered by many vocational schools, community colleges, and distance-learning programs. Although just above one-third of the workers had no education beyond high school in 2008, that noncollege share has decreased partly because the work has become more complex, partly because the workforce has shrunk by 19.9 percent, and partly because—unlike so many occupations requiring less than a bachelor’s—the outlook is reasonably good. The workforce is projected to expand by 7.6 percent between 2012 and 2022, which is about the average for all occupations.

Parking Lot Attendants. If I had to cite one example that fits the stereotype of college-educated workers holding a job that requires much less education, it would be this one. But it’s noteworthy that while the percentage of workers with college experience increased by 8.8 percent, the percentage with a bachelor’s actually decreased by 2.1 percent. This occupation does not pay particularly well compared to others with similar skills, the technical skill level is not increasing, nor did it shrink in size (5.7 percent) nearly as much as the preceding occupations. The outlook—7.3 percent projected growth—is comparable to that of Medical Transcriptionists, but this is a high-turnover occupation where few workers stay for long. If I had to hazard a guess for the increase in the number of workers with some college, I would say those who persist in it (and therefore drive up their representation among the rapidly turning-over workers) are those under financial pressure to pay off college loans. The jobs also are concentrated in cities, where the educational level of available workers tends to be higher. But these are only guesses.

Monday, February 24, 2014

Post-Recession Gains and Losses by Women



The Great Recession that ended the previous decade is sometimes referred to as the “Mancession” because it inflicted such a severe impact on male employment. This recession was brought on by a collapse of the housing market, and that in turn led to a severe reduction in worker demand within the heavily male construction industry. Making matters worse, the recession accelerated the job-diminishing effects of automation and offshoring in manufacturing, another heavily male domain. Service jobs, where women dominate, suffered less from this recession.

As the economy has slowly recovered from the recession, male and female gains have been uneven. How you compare them depends partly on how you define employment. Although the unemployment rate for women is now lower than the rate for men, the jobs women have regained in the recovery are more often lower-paying, part-time, and not self-employed.

I thought it would be interesting to look at a different measure than unemployment rate, earnings, or hours of work. Instead, I was curious about changes in the percentage of women in various occupations. Using figures from the Current Population Survey for 2007 and 2010, I created the following two tables. Because changes to very small occupations affect only a very small number of workers, I looked only at occupations that had workforces of more than 100,000 wage and salary workers in 2010.

The first table shows the 10 occupations that had the greatest gains, in percentage terms, between the 2007 percentage of female workers and the 2010 percentage.

Title
2007
2010
2010 Workforce
Gain
Highway Maintenance Workers
0.5%
2.3%
142,530
360%
Automotive Service Technicians and Mechanics
0.7%
1.8%
587,510
157%
Aircraft Mechanics and Service Technicians
2.1%
3.8%
117,510
81%
First-Line Supervisors/ Managers of Mechanics, Installers, and Repairers
5.4%
8.7%
415,900
61%
Network and Computer Systems Administrators
14.7%
22.3%
333,210
52%
Engineers, All Other
10.0%
13.8%
139,610
38%
Electricians
1.7%
2.2%
514,760
29%
Administrative Services Managers
32.7%
40.9%
240,320
25%
Computer, Automated Teller, and Office Machine Repairers
10.6%
13.0%
110,320
23%
Library Technicians
62.3%
76.4%
109,240
23%

All of these are occupations that either require a lot of hands-on work or work with high tech. (Library Technicians these days spend a lot of time with databases rather than shelving books.) The increase of women working as Aircraft Mechanics and Service Technicians may partly reflect the downsizing of the military as the Iraq and Afghanistan wars have wound down; women working in this occupation overwhelmingly come from a military background. Regarding Highway Maintenance Workers, my guess is that this occupation gained many workers because of funding from President Obama’s stimulus package.

The next table shows the 10 occupations that had the greatest declines in female participation in the workforces.

Title
2007
2010
2010 Workforce
Decline
Telecommuni-cations Line Installers and Repairers
7.5%
3.7%
156,350
-51%
Operating Engineers and Other Construction Equipment Operators
2.7%
1.5%
334,730
-44%
Civil Engineers
11.5%
7.1%
249,120
-38%
Fire Fighters
5.3%
3.4%
302,400
-36%
Sheet Metal Workers
3.7%
2.5%
131,600
-32%
Bus and Truck Mechanics and Diesel Engine Specialists
1.1%
0.8%
222,770
-27%
Construction Managers
8.1%
5.9%
191,430
-27%
Cost Estimators
15.4%
11.4%
183,790
-26%
Parts Salespersons
17.4%
13.2%
201,610
-24%
Parking Lot Attendants
15.4%
11.8%
124,590
-23%

All of these occupations have traditionally been dominated by male workers, and many of the occupations are in the heavily male construction and manufacturing industries. Because many of the women who have been working in these occupations were hired there only recently, their job losses reflect the tendency of distressed businesses to lay off workers with the least seniority.

As the recovery continues, it will be interesting to see how the male-female balances recalibrate. I hope to post an update as newer demographic statistics become available.

Thursday, February 13, 2014

What Skills Reward Improvement with the Highest Payoff?


I have sometimes looked at the monetary payoff for skills by running correlations between skills and earnings. This time, to use the most recent skill ratings (from O*NET release 18) and earnings estimates (for May 2012) available from the Department of Labor, I decided to use a different technique.

In the O*NET database, occupations are rated on 35 skills on a scale (representing level of mastery) that ranges from 0 to 7. (Actually, the highest rating of any occupation on any skill is 6.1.) I divided the occupation-skill combinations into five levels of skill:

Level
Rating
Example
1
less than 2
Barbers, rated 1.1 on Equipment Selection
2
2 or greater but less than 3
Librarians, rated 2.4 on Mathematics
3
3 or greater but less than 4
Veterinarians, rated 3.8 on Learning Strategies
4
4 or greater but less than 5
Hydrologists, rated 4.2 on Writing
5
5 or greater
Physicists, rated 5.6 on Active Learning

Then, within each skill level, I computed the weighted average earnings of all the occupations linked to each skill. To calculate a weighted average, I multiplied the workforce size of each occupation by its median earnings, summed these products, and divided this sum by the sum of all the workforces. This gave me an average dollar figure for each skill that gave greater weight to occupations with larger workforces.

Next, I calculated the difference between the earnings at levels 1 and 2, levels 2 and 3, and levels 3 and 4. (I did not look at the difference between levels 4 and 5 because only 17 of the 35 skills are rated that high for any occupation.) Finally, I computed the average of those three differences.

By using this approach, I achieved a measure of what difference in earnings is achievable by an increase in skill level. These are the skills that showed the largest differences:

Skill
Average Boost in Pay
Complex Problem Solving
 $26,930
Judgment and Decision Making
 $24,398
Active Learning
 $23,196
Time Management
 $23,159
Science
 $22,463
Negotiation
 $21,789
Coordination
 $21,367
Systems Analysis
 $21,329
Writing
 $20,929
Management of Personnel Resources
 $20,864

This approach is actually not that different from a correlation, because it attempts to show how an increase in one factor (skill level) is associated with an increase in another factor (pay). However, this approach has the advantage of showing you in dollar terms what it would mean to improve your mastery of a skill.

Of course, getting into a higher-paying occupation often is not simply a matter of improving skill. You may need some credential that reflects your higher level of skill: for example, a college degree, a certificate, or journeyworker status within a trade. But your achievement of this credential depends on your improving certain skills. And it makes sense to focus on the credentialing programs that boost the highest-payoff skills.