Recession-Proof Jobs and the Hazards of Prognostication
You may have noticed a recent spate of articles about recession-proof jobs. These articles tend to take one of two approaches: they either identify occupations and industries that are considered to be relatively insensitive to economic downturns, or they offer suggestions about how to make your present job less vulnerable to loss during a recession.
We editors at JIST certainly have noticed the flurry of interest in these topics, and we have responded by creating a book called 150 Best Recession-Proof Jobs that combines these two themes, with emphasis on the former. The book is due out this autumn, and working on it made me acutely aware of the hazards of predicting the future, especially because even as I was writing the book I was reading The Black Swan: The Impact of the Highly Improbable, by Nassim Nicholas Taleb. Taleb's highly engaging book argues that prognostication is essentially futile because of an innate human inability to foresee earth-shaking random events.
In all of my books about careers I rely on the forecasts of the Office of Occupational Statistics and Employment Projection at the Bureau of Labor Statistics, because they are generally accepted as the best available. I think we Americans often forget how lucky we are to have a government office dedicated to making these projections and freely sharing them with us. To appreciate them fully, you only need to try to provide career information in foreign countries where such forecasts are not being promulgated, either because a lack of government resources prevents their being made, or because a lack of democracy prevents their being shared with the populace.
To compile a list of recession-proof jobs, I had to choose between two available methodologies. One approach was to follow the ratings given in an article in Occupational Outlook Quarterly called "Matching Yourself to the World of Work: 2004," by Henry T. Kasper, an economist at BLS. The article rates approximately 280 occupations on various characteristics, one of which is economic sensitivity. I chatted with the author and learned that these ratings were not based on a specific research effort but were based on his general knowledge of the trends affecting the workforce. The advantage of using these ratings would be that they are based on the expertise of someone working in the office that makes economic projections. The disadvantage would be that the ratings are four years old and apply to occupational titles that in many cases are at a high level of aggregation; for example, the various kinds of designers are represented by one occupation called Designers.
The second approach available to me was suggested by a 1997 article in Monthly Labor Review called "Which Industries are Sensitive to Business Cycles?" by Jay Berman and Janet Pfleeger. These economists, who were (at the time of writing) also working in the projections office, used a statistical procedure that calculated a figure called the Pearson product moment correlation coefficient to indicate how closely fluctuations in workforce size (for each industry) have followed fluctuations in the economy as a whole, as measured by gross domestic product. It occurred to me that I could replicate this procedure to compare fluctuations in occupational workforce size with fluctuations in the economy and thus measure the sensitivity of occupations. The advantage of using this approach would be that I could create ratings at a detailed level of occupational specificity—e.g., for eight kinds of designers rather than for one. The disadvantage would be that the calculations had to be based on only eight years of economic data: from 1999 to 2006, a period that spanned an economic boom and a recession, but not as long a span as I would have preferred. Unfortunately, comparable workforce figures are available only since 1999, when BLS adopted its present taxonomy for reporting occupational statistics.
In the end I combined the two approaches, using the strengths of each method to compensate for the shortcomings of the other. I used the 280 ratings from the OOQ as my basis, updating them where needed by consulting the occupational projections in this year's edition of the Occupational Outlook Handbook and adapting them for a more detailed set of occupational titles by using MLR-based calculations to tease out the different levels of economic sensitivity among, for example, the eight kinds of designers. I also used a listing in still another BLS publication, Occupational Projections and Training Data, to identify occupations that are at risk for offshoring.
However, even as I was applying this hybrid methodology, reading The Black Swan made me acutely conscious of a limitation that applies to all projections done by BLS: They are based on historical trends—that is, the notion that what has happened in the past will continue in the future. Taleb's point is that unexpected events inevitably will occur and cause the future economy to differ in some ways from the past economy. You need only think about the past decade to realize that each business cycle is somewhat different from the one that came before. The technology boom of the late 1990s and the recession that followed did not raise and lower exactly the same industries and jobs as the housing boom and bust that followed. For example, it seems likely that construction jobs will be more seriously affected by the recession of 2008 than they were by the recession of 2001. In a future recession, some other sector of the economy may suffer the most severe setbacks.
Fortunately, prognosticators have one tool to rely on that tends to resist the impact of unexpected events: demographics. Only a pandemic on the scale of the 13th century's Black Death or the discovery of a fountain of youth is likely to prevent my generation, the Baby Boomers, from becoming decrepit and in need of increased medical care over the next few decades, so a career in health care is a reasonably safe bet. Demographic projections also suggest that classroom teachers in most parts of our country will continue to find children to teach.
The continuing advance of technology, although it sometimes derails predictions, also ensures that adults will have many new skills to learn, and therefore it is hard to imagine any way the education industry can have a future that is not rosy—unless technology develops a way for us to upload instruction to our brains instantaneously, as Neo learned his martial-arts skills in "The Matrix." In other words, the very unpredictability of technology makes the need for education predictable.
Because most predictions are risky, I made a point of including in this book a chapter about how to make your current job recession-proof, with suggestions about focusing on the core mission of your employer, keeping skills up to date, maintaining a good network of contacts, and being resilient. I prefaced the section by noting that even if every job-related prediction in the book turns out to be inaccurate, these tips will be useful because they can help you hang onto a threatened job or shift to a new job with minimal disruption to your life. Reading The Black Swan gave me a useful injection of humility and caution about predicting the future.
Dr. Shatkin can be reached at laurence@myself.com
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