how the labour market drives mismatch and its penalties

How the Labour Market Drives Mismatch and its Penalties

PeopleWalkingBy Guillermo Montt.

In a previous post, we showed how across countries that took part in the Survey of Adult Skills, 39% of workers are mismatched by field of study. These are workers who graduated from a particular field but work in another, unrelated occupation. We also showed that many field-mismatched workers are also over-qualified, leading to a large wage penalty and non-ignorable costs for economies.

Let’s take one step back and ask: why are workers mismatched in the first place?

Many, if not most, students choose a field of study based on what they want to become and do to earn a living. Yet almost four in ten workers end up doing something unrelated. This is sometimes by choice but not always.

Results from the Survey of Adult Skills (PIAAC) (2015) show that the more a field is saturated – when the supply of graduates exceeds the demand by firms – the more it forces its graduates to seek work in another field, and the more it forces them to work at a level for which they are over-qualified. The more a field is saturated, the more likely its graduates will receive an important wage penalty.

Results also show that workers benefit when the skills they have earned are transferable to other sectors as they can put a larger part of their skill set to use when in other sectors. These workers are more likely to work in another field at the corresponding qualifications level; they do not experience a wage penalty. This happens, in part, because employers recognise and value skills earned in other fields; it is also the result of the fact that the skills developed are, in fact, useful in a wide variety of settings.

Saturation and transferability influence the likelihood of mismatch and impact wages in different ways


Note: + (-) indicates a positive (negative) relationship between the two variables. For example, field saturation increases the changes of a worker being mismatched by field and overqualified, which, in turn, reduces wages. This is a simplified version of the original figure. For the specific estimates and more details, see Figure 4 in Montt (2015).

Mismatch with or without over-qualification can also be voluntary. Some workers are mismatched temporarily, as they prefer to be in employment while they find a job that better suits their skill set (e.g. youth entering the labour market or workers previously unemployed who choose or are forced to re-enter the labour market quickly). Others choose to work in another field because doing so increases their salary (e.g. mathematicians or philosophers working in the financial trading sector). Others follow career paths that lead them to other occupations (e.g. engineers who become sales managers at technology-rich firms). Mismatch may also result from the fact that even if jobs were available, workers having to juggle family responsibilities and other constraints take jobs in unrelated sectors or become overqualified to gain flexibility.

Indeed, mismatch by field of study is more likely as workers age and the size of the penalty decreases with age, as experience becomes a better signal of skills (OECD, 2014). Mismatch by field also more likely among women (15%) and among workers in part-time contracts (14%).  Mismatch is also more likely among the lower educated, possibly because the job-specific skills in low-skills occupations may require lower investments by the part of employers and workers making it easier to move across fields.

Does any of this make a difference for policy makers?

Understanding the causes of mismatch sheds light on what adequate policy responses. Mismatch may not be negative per se, as it only brings about wage penalties when linked to over-qualification. Over-qualification is more likely among saturated fields and less among fields offering more transferable skills.

One first policy lever is to monitor the supply of graduates into the labour force and anticipate saturation via skills assessment and anticipation exercises. Second, education and training systems could promote the transferability of fields by helping employers recognise the value of skills earned in other fields. Similarly, skill development programmes for adults could also emphasise skills that are transferable across sectors and fields. Third, promote the recognition of skills across fields of study in training programmes and through comprehensive qualifications frameworks. And fourth, in line with the OECD Jobs Strategy promote flexible work arrangements to prevent those in need of flexible working hours to become over-qualified.

Notwithstanding the above, questions still remain to further research:

  • To what extent do the generosity of unemployment benefits or the existence of / participation in active labour market policies reduce mismatch for previously unemployed workers?
  • Does working while studying within VET or apprenticeship programmes or outside these formal arrangements reduce mismatch for youth in transition to the labour market?
  • Does the existence of skills anticipation systems allow for a better alignment of skill supply and demand?
  • More broadly, should countries envision a labour market with no mismatch as a policy goal or one where mismatch is not costly for workers or employers?
  • Is there a desirable level of mismatch that can allow for cross-polinisation and increase innovation and productivity?

These are all questions that will be addressed by OECD research in the near future. The answers will inform skills policies that will promote a full use of workers’ skills and reduce any wage penalties and losses in productivity.