Can we measure the link between education and youth unemployment?

Youth unem­ploy­ment rate is defined as the per­cent­age of 15–24 year-olds cap­able and edu­cated to work (a.k.a. the youth labour force) who are unem­ployed. On a glob­al scale, this affects as many as 75 mil­lion young people who are trained but remain out of work¹ (com­pared to 621 mil­lion for “NEETS”), with vary­ing pro­por­tions depend­ing on the coun­try. As such, par­tic­u­larly in developed eco­nom­ies, the youth labour mar­ket is one of the key indic­at­ors of a healthy eco­nom­ic sys­tem; not to men­tion the import­ant social repercussions.

In lib­er­al mar­ket eco­nom­ies like the UK or USA, when there is pres­sure on fin­an­cial mar­kets such as the Cov­id or 2008 fin­an­cial crises, it is the young­est who are laid off first. And in those coun­tries, there are also less appren­tice­ship places dur­ing these peri­ods, so the young­er gen­er­a­tion struggle to find early-stage career work. Hence, there is a clear social func­tion of the edu­ca­tion sys­tem in integ­rat­ing youth into the middle mar­ket. That’s why the efforts of oth­er coun­tries like Aus­tria and Ger­many to keep up appren­tice­ship places dur­ing crises have proven bene­fi­cial to main­tain­ing a lower youth unem­ploy­ment rate.

To bet­ter under­stand the factors involved, over the years there has been much research into the rela­tion­ship between edu­ca­tion and the employ­ment. A rel­ev­ant mod­el that was cre­ated by Buse­mey­er in Tram­pusch² over a dec­ade ago used a 4‑fold typo­logy to describe the link between edu­ca­tion and the labour mar­ket. Their mod­el essen­tially dis­tin­guished between the com­mit­ment of the state towards edu­ca­tion and train­ing, whilst con­sid­er­ing con­tri­bu­tions from private com­pan­ies. These can either be low or high, so essen­tially lead­ing to four types of skills regimes; for example, if con­tri­bu­tion of both is low, we can speak of “lib­er­al” sys­tems like the UK and USA. High state input and low private con­tri­bu­tions include coun­tries like France and Sweden, or inversely low state com­mit­ments with high input from com­pan­ies are seen in Japan. Where­as in Aus­tria, Ger­many, Den­mark and Switzer­land which can be con­sidered as “col­lect­ive skills regimes” com­mit­ments are high on both sides.

Although, this ana­lys­is didn’t neces­sar­ily com­pare wheth­er one or oth­er sys­tem was bet­ter, it did provide a clas­si­fic­a­tion of how voca­tion­al edu­ca­tion and train­ing and its rela­tion to indus­tries dif­fers across countries.

Anoth­er way of look­ing at the edu­ca­tion-employ­ment link­age is to assume an optim­al equi­lib­ri­um between the two and hence a shared input from both pub­lic edu­ca­tion sys­tems and private entit­ies (fig. 1).

This approach has been tested by research­ers at the KOF Swiss Eco­nom­ic Insti­tute of the ETH Zurich by devel­op­ing the so-called edu­ca­tion-employ­ment-link­age (EEL) index. They looked at the most prom­in­ent voca­tion­al edu­ca­tion pro­grammes in OECD coun­tries and asked experts and stake­hold­ers about this link via sur­veys. For instance, they asked about the extent to which employ­ers con­trib­ute to the design of cur­ricula or to skills assess­ment. Using that they came up with an index based on qual­it­at­ive cri­ter­ia that they weighted to gen­er­ate a quant­it­at­ive index.

Using the EEL index, it is there­fore pos­sible to rank coun­tries accord­ing to how close the cooper­a­tion between edu­ca­tion and employ­ment is. In a way, this also proves the skills regimes approach, because col­lect­ive skills regimes (such as Aus­tria or Ger­many) turned out to rank high on the EEL index. How­ever, the Swiss research­er could draw more in-depth con­clu­sions. As such, they noted a cor­rel­a­tion between EEL index (KOF EELI) and youth unem­ploy­ment rate – coun­tries that scored bet­ter were those with less youth unem­ploy­ment (KOF YLMI). 

But let’s remain prudent. Even though we have good argu­ments to believe there is a caus­al link, we don’t yet have the proof bey­ond cor­rel­a­tions.  Also, this sort of research is usu­ally car­ried out in these one-off stud­ies, like snap­shots of cer­tain indus­tries in cer­tain coun­tries at cer­tain points in time. We can com­pare coun­tries, but for example we only have the EEL index for the year 2016 and there isn’t a com­par­able index for oth­er years – so it would be inter­est­ing to have a longer time series.

Going bey­ond the cur­rent ana­lys­is, this then begs the next ques­tion: if there is a strong link between edu­ca­tion and employ­ment, can we improve soci­ety as a whole? Even though youth unem­ploy­ment rates can be a mark­er of eco­nom­ic health, the cur­rent mod­els don’t factor in for oth­er lar­ger soci­et­al indic­at­ors; like work-life bal­ance, qual­ity of life, or gen­er­al hap­pi­ness. We are still far away from hav­ing a com­pre­hens­ive mod­el of these relationships. 

Fur­ther­more, a high­er com­mit­ment edu­ca­tion scheme appears to be bet­ter but only in cer­tain aspects that we are look­ing at. Yes, more young people find jobs but once you start look­ing at oth­er eco­nom­ic indic­at­ors such as pro­ductiv­ity and innov­a­tion, there impact of a close edu­ca­tion-employ­ment-link­age is less clear. Also, in terms of labour mar­ket trends, pre­dic­tions are becom­ing less and less suc­cess­ful in know­ing what skills are needed to the point where much of what we hear is polit­ic­al rhet­or­ic; we have no sci­entif­ic evid­ence in which route we should go. It is there­fore under­stand­able that key skills such as numer­acy and lit­er­acy, which can be con­sidered uni­ver­sal, are emphas­ised. Of course, issues like prob­lem solv­ing, cre­ativ­ity, and team­work – con­sidered “21^st Cen­tury” skills – are also cru­cial but these are less trans­fer­rable across dif­fer­ent pro­fes­sion­al domains. 

All in all, we mustn’t for­get that the way work is organ­ised is in the hands of com­pan­ies who employ people. This is the main lever­age I would say. You can try to change and improve the edu­ca­tion sys­tem as much as you want but if there is not the right sort of jobs pro­posed by employ­ers then it won’t have a pos­it­ive effect on employ­ment rate. Hence, job design and job qual­ity are key! 

Let’s take two extreme cases. On one spec­trum, we are see­ing a tend­ency for com­pan­ies to organ­ise work in a way that can be done by any­body. This includes micro-work such as that traded by Amazon Mech­an­ic­al Turk. Here, tasks are divided into such tiny pieces, like click­ing on an image on a screen or scan­ning a product on a shelf, that no or little train­ing is required. How­ever, there is a danger here that these meth­ods be used as elab­or­ate ways of human exploitation.

On oth­er hand, after recov­ery from the COVID crisis, in some coun­tries in Europe, the labour mar­ket is already back at rates from before the crisis. Some even have lower unem­ploy­ment rates than before. The pan­dem­ic made many people con­sider what they con­sider a qual­ity job, and the new gen­er­a­tion of gradu­ates are demand­ing much more from employ­ers than they did 20–30 years ago. It is put­ting pres­sure on busi­nesses push­ing them to think about how to change work. In my view the “Great Resig­na­tion” is not a sin­gu­lar phe­nomen­on of the COVID crisis, but the her­ald of a chan­ging labour mar­ket. As such, in years to come we will need to see a dif­fer­ence in work-organ­isa­tion to make jobs more attractive.

A ques­tion that remains, how­ever, is what role will the state play in where we are headed?

Fur­ther reading 

• http://www.people.fas.harvard.edu/~iversen/PDFfiles/Busemeyer%26Iversen2011.pdf
• http://hozekf.oerp.ir/sites/hozekf.oerp.ir/files/kar_fanavari/manabe%20book/TVET/The%20Wiley%20handbook%20of%20vocational%20education%20and%20training.pdf#page=157
• https://​www​.researchg​ate​.net/​p​u​b​l​i​c​a​t​i​o​n​/​2​9​9​3​9​5​9​8​1​_​S​u​c​c​e​s​s​_​f​a​c​t​o​r​s​_​f​o​r​_​t​h​e​_​D​u​a​l​_​V​E​T​_​S​y​s​t​e​m​_​P​o​s​s​i​b​i​l​i​t​i​e​s​_​f​o​r​_​K​n​o​w​-​h​o​w​-​T​r​a​nsfer