When computers made their way into workplaces, in the 1980s, typists had a problem. As computers replaced traditional typewriters, the skills of typists who did not know how to work with a word processor grew obsolete. Nevertheless, few would argue that information technology permanently increased unemployment. Although the unemployment rate did spike in the 1980s, it eventually went back down again, so the average unemployment rate in the 1990s was similar to the rate in the 1970s. The labor force adjusted to a new technology replacing an older one.
In the wake of the 2008 financial crisis, there was a lively debate among policy makers and academics about whether a similar gap “between the skills workers have and the skills businesses say they need” contributed to the increase in unemployment. Research has since shown that the skills gap has a cyclical effect on unemployment, explaining as much as one-third of the increase in unemployment following the Great Recession.
It is usually taken for granted that the skills gap is a problem of skills supply, and public concerns often focus on a lack of STEM skills and soft skills. So proposed solutions tend to involve reforming education and worker training programs. The most popular approach has been to reduce tuition fees for selective fields of study, usually STEM majors.
However, I argue that this view is not correct. Research that I and my colleagues have conducted suggests that the skills gap persists mainly because employers are unwilling or unable to pay market price for the skills they require.
There are three possible reasons for why a skills gap exists. First, workers do not adjust to changes in the demand by acquiring new skills. Second, employers do not take the supply of skills into account when they make hiring decisions. Third, employers do not take into account the relative shortage or abundance of particular skills when they set wages. Using U.S. data on job finding and filling rates, wages, and profits across states and industries since 1979, we measured the contribution of each of these three reasons on mismatch unemployment. We found that wage setting is the main reason why workers don’t have the skills employers are looking for.
The workforce can adjust to changes in the demand for skills by acquiring new skills, through training, or by replacing older workers with younger ones who have up-to-date skills. For example, an unemployed typist looking for work in the 1980s could learn how to use a computer or fill a vacant position left by another typist who moved on to another job or retired.
Firms can also respond to changes in the supply of skills. In the 1980s, for instance, organizations could train their typists in word processing or keep some typist positions open. While hiring less-skilled workers hurts a firm’s productivity, the data shows that companies still did this in order to take advantage of the fact that hiring these workers is so much cheaper.
Our data shows that these kinds of adjustments do indeed happen, and that they happen fast enough to prevent unemployment from going up. There aren’t many occupations that are both easy to find and high-paying, which is what we would expect if the workforce were not adjusting and companies were struggling to find talent. Similarly, there are few jobs that are easy to fill and that generate high profits for the company.
Yet the skills gap remains, because the adjustments that workers and firms make will only eliminate the gap if wages reflect the relative supply and demand for various skills across occupations. But our data shows that this is not happening: Many jobs in industries that generate high profits (retail trade, educational services, mining, and forestry) tend to pay low wages and are therefore unattractive to workers, whereas jobs in industries that pay higher wages (finance, computer and electronics manufacturing, paper and printing) are not very profitable.
Imagine that a particular set of skills — say, STEM skills — enables workers to be particularly productive but their pay does not go up to reflect this higher productivity. It is not surprising that workers do not acquire more of these skills, since they do not reap any of the benefits of their increased productivity. In the UK, for instance, less than half of STEM graduates work in scientific occupations, and there is no wage premium for having a STEM degree in other occupations.
On the other hand, firms are more interested in hiring workers with these STEM skills, as they are very productive and cheap. Thus companies open lots of vacancies for STEM positions but find it very difficult to fill them.
Companies often advocate for better education to fix the skills gap, but our results indicate that this is unlikely to work for a simple reason: Students have a choice about what skills they acquire in school and how they use these skills in the labor market. Encouraging universities to educate more physicists and engineers will not make a difference if these additional STEM graduates then choose to work for investment banks that offer higher salaries.
Unfortunately, our research does not provide an explanation for why wages do not reflect relative labor market conditions across occupations or skills. However, the data clearly indicates that wages for workers with scarce skills are too low compared to wages for workers with a more abundant skill set. It would seem that this provides a profitable opportunity for companies that are able to be flexible in their compensation policy. By paying more for certain skills, an employer would have no trouble attracting workers with those skills in sufficient quantity and quality, giving the company an undeniable edge over its competitors.
via HBR.org http://ift.tt/1U20Kgy