Real-World Data Showing Trends in Job Security

Nobody’s job is completely secure, but some jobs are more resistant than others to the ups and downs of the economy. I have written books and blogs on this subject and have also created a video about it. Now, here is some new, real-world data that provides additional insights into this matter. The data may give you some insights into what careers you might pursue or avoid.

Last week, the Bureau of Labor Statistics released estimates for employment and wages in May 2012. I decided to look at the changes in employment in various occupational groups over two time periods: the Great Recession, which for my purposes I define as the difference in employment between May 2007 and May 2009; and the recovery, which I define as the difference in employment between May 2010 and May 2012. I find these particular dates useful because they provide symmetry: Each is a two-year period, and the employment in all occupations decreased by 3 percent in the first period and increased by 3 percent in the second period.

This symmetry ceases when you look at specific groups of occupations, and that’s what makes the chart below so useful. (You can see it full-sized here.) Note that the bars indicate change in percentage terms, not in absolute terms. Keep reading below the chart for my comments on what it reveals.

As I noted, the workforce for all occupations, taken together, declined during the recession and expanded during the recovery by the same percentage. And some families of occupations show a similar behavior, more or less symmetrical. The Sales and Related occupations are a good example of how employment can fluctuate in response to how much disposable income consumers have and are willing to part with for nonessentials. The Building and Grounds Cleaning and Maintenance occupations and the Farming, Fishing, and Forestry occupations were probably responding to similar forces. Many of the jobs in these three categories are low-skill, and employers can lay off workers without worrying about how to replace them when the economy rallies. They lack security, but they have been able to bounce back.

There tends to be a higher level of skill among the Installation, Maintenance, and Repair occupations; the Arts, Design, Entertainment, Sports, and Media occupations; and the Architecture and Engineering occupations. Nevertheless, they show similar symmetrical behavior and illustrate how even some middle-skill occupations are sensitive to fluctuations in the economy. It’s interesting to note that among the Architecture and Engineering workers, the occupations that continued to decline even during the recovery tended to be either related to construction, which was especially hard-hit by a recession set off by the explosion of a housing bubble (for example, Architects, Landscape Architects, and Surveyors), or were at a middle-skill level at which workers could be replaced by automation (for examples, various kinds of drafters and engineering technicians). The high-skill engineering occupations tended to recover.

Among asymmetrical occupational groups, some lost workers both in the recession and in what should have been a recovery. One of the most extreme examples is the Construction and Extraction occupations, which were hurt badly by the overbuilding that preceding the recession. The good performance of the petroleum industry has been unable to offset the many job losses in this field. (Nevertheless, the long-term outlook for many construction occupations is considered good.) The non-recovery of the Office and Administrative Support occupations cannot be blamed on a similar sustained slow-down in business activity—for a contrast, look at how well the Business and Financial Operations occupations have recovered. Instead, the continuing job loss in this field is explained by the expanded use of office automation. Again, the middle-skill and especially the low-skill jobs are unlikely to come back.

Other asymmetrical occupational groups achieved some expansion during the recovery, but much less than what would be sufficient to restore the recession’s losses. Good examples are the Production occupations and the Transportation and Material Moving occupations. Both of these fields actually recovered quite well from the recession in terms of productivity but did not replace the large number of low-skill workers who were replaceable by automation. (Offshoring was also a major factor for Production jobs.)

A fortunate few categories actually experienced workforce growth during the recession and sustained this expansion during the recovery. These tend to be groups consisting mostly of high-skilled workers: the Management occupations; the Business and Financial Operations occupations; the Computer and Mathematical occupations; the Life, Physical, and Social Science occupations; the Postsecondary Teachers; and the Healthcare Practitioners and Technical occupations. The exception that is notable for the comparatively low skill of the workers is the Personal Care and Service occupations. This group is dominated by the Hairdressers, Hairstylists, and Cosmetologists; the Childcare Workers; and the Personal Care Aides—all of whom perform essential services that cannot be automated and are not easy to do without even during hard times. A mostly low-skill group comparable to the Personal Care and Service occupations is the Food Preparation and Serving Related occupations, which experienced only a very small loss in the recession. We Americans seem limited in our ability to switch from restaurants to brown-bagged and home-cooked meals, even during bad times.

Finally, several families of occupations exhibited what might be called countercyclical behavior: they gained workforce size during the recession but lost workers during what should have been a recovery. These include the Community and Social Service occupations and the Education, Training, and Library occupations. They are actually needed more during hard times than during good times, but because they are paid largely out of the public coffers, they tend to experience cutbacks a few years after the trough of the recession, when state and local governments have run out of rainy-day funds and stimulus support from Washington. They may be expected to recover as tax receipts start returning to normal levels with the acceleration of business activity, but the anti-tax climate that now dominates many parts of the nation is likely to continue to hobble these occupations. Something similar accounts for the lackluster recovery of the Protective Service occupations.

It may seem puzzling to find the Healthcare Support occupations showing countercyclical behavior, especially in contrast to the recession-be-damned growth of the Healthcare Practitioners and Technical occupations. Actually, most of the occupations in this group, with middle-skill workers such as Occupational Therapy Aides, Massage Therapists, Dental Assistants, and Medical Assistants, showed continuous growth during both time spans. What has dragged down this group as an aggregate is the nearly one-million-strong Home Health Aides, who have not recovered like the Personal Care Aides. Home Health Aides are low-skilled workers who are easy to replace when a fully recovered economy justifies hiring. Both of these care-aide occupations are projected to grow by about 70 percent between 2010 and 2020.

The take-away lesson from this chart is very similar to what I concluded in a recent blog about a similar but less-detailed chart: Your best bet is a high-skill job, or at least a middle-skill job that is difficult to automate (such as many in health care), because these not only pay well but tend to thrive in both good times and bad times. 

Our society has not yet devised a way to prevent future economic downturns. Nor are we able to agree on and apply what it takes to shorten them, as the experience of Europe (and, to a lesser extent, the United States) shows. Given that a roller coaster economy seems to be here to stay, doesn’t it make sense to pursue a career that has comparative security?

Update, following the 4/5/13 release of data from BLS: Here's a graph from the Washington Post site that uses lines instead of bars, a slightly different set of industries, and a slightly different timescale. But it shows the same trends.

Another update, because manipulating data is fun: This graph uses the same method as the bar graph above, but (like the Washington Post graph) it represents industries.