Why are wages less stable in skilled professions?

There is some evidence, in fact, that markets for highly skilled workers, such as engineers and other specialized professionals, exhibit systematic periods of boom and bust…1

Earnings tend to fluctuate significantly more in highly skilled professions than in others, rising to high levels for a number of years before plunging and, ultimately, rising again. Why is this the case? Here’s the explanation put forward by Harvard economist George Borjas in his leading textbook on Labor Economics.2

What’s going on?

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We change more than we expect (so keep your options open!)

How much will your personality, values and preferences change over the next decade? Probably more than you think, at least according to a recent paper, “The End of History Illusion” by a team of psychologists at Harvard and the University of Virginia.

In a number of separate experiments, the authors asked a total of over 19,000 people between 18 and 68 to measure their current personality, values and preferences. Half of them were also asked to complete the assessment as they believed they would have done ten years earlier, while the other half were asked to predict what they would say in ten years’ time.

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Which careers are most likely to be automated?

New and improved technologies will make jobs redundant, even as they open up new opportunities. This has always been the case, but with recent advances in Machine Learning and Mobile Robotics, changes in the labor market could be particularly extreme in the years to come. In fact, a recent paper suggests that up to 47% of American jobs could be vulnerable to automation within the next couple of decades.

That paper is “The Future of Employment: How Susceptible Are Jobs To Computerisation?”1 by Carl Frey and Michael Osborne of the Future of Humanity Institute (which is affiliated with 80,000 Hours). In the paper, widely discussed in outlets such as The Economist and The Financial Times, Frey and Osborne look at the likely impact of recent advances in order to determine which jobs are likely to be automated.

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