2. Graduates matter... For individuals because skills have an increasing impact on labour market outcomes and social participation For economies because failure to ensure a good skills match has both short- term consequences (skills shortages) and longer-term effects on economic growth and equality of opportunities … but more graduates do not automatically translate into higher incomes and higher productivity Success with converting skills into jobs and growth depends on whether we know what those skills are that drive economic outcomes the right mix of skills is being taught and learned in effective, equitable and efficient ways economies and labour-markets fully utilize their skill potential Governments build strong coalitions with the social partners to find sustainable approaches to who should pay for what, when and where .
3. A world of change – highereducation Expenditure per student at tertiary level (USD) Cost per student Graduate supply Tertiary-type A graduation rate
4. A world of change – highereducation Expenditure per student at tertiary level (USD) United States Cost per student Finland Japan Graduate supply Tertiary-type A graduation rate
5. A world of change – highereducation Expenditure per student at tertiary level (USD) Australia Finland United Kingdom Tertiary-type A graduation rate
6. A world of change – highereducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate
7. A world of change – highereducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate
8. A world of change – highereducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate
9. A world of change – highereducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate
10. A world of change – highereducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate
11. A world of change – highereducation Expenditure per student at tertiary level (USD) United States Australia United Kingdom Finland Tertiary-type A graduation rate
12. The increase in the number of graduates has not led to a decrease in their pay …which is what happened for low-skilled workers
13. Components of the private net present value for a male with higher education Net present value in USD equ.
15. Public cost and benefits for a male obtaining tertiary education Public costs Net present value, USD equivalent Public benefits Chart A8.5 USD
16. Making investment in skill development and utilisation more efficient Who should pay for what, when and how? Which is the right level of intervention (regional and local dimension)? How should financing and incentives (to employers and individuals) be structured? What are good models of policy evaluation to ensure efficiency/continuity of skills policies?
17. Who pays for tertiary qualificationsExpenditure on tertiary educational institutions as a percentage of GDP B3.2
19. Changes in employment shares by occupation1960-2009, selected OECD countries Australia, Austria, Belgium, Canada, Chile, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Korea, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom and United States.
20. Skill use by occupational groups Source: PIAAC Field trial
21. How the demand for skills has changedEconomy-wide measures of routine and non-routine task input (US) Mean task input as percentiles of the 1960 task distribution The dilemma for universities: The skills that are easiest to teach and test are also the ones that are easiest to digitise, automate and outsource (Levy and Murnane)
Lets look at the insights PIAAC provides about how skills translate into economic and social outcomes.Of course, everyone knows being skilled is an advantage: Skilled workers are more productive and therefore tend to earn more and have better employment prospects. Greater productivity, in turn, is the foundation for growth. Failure to ensure a good skills match has both short- term consequences (you see skills shortages) and becomes a longer-term drag on growth and equality of opportunities. The trouble is that there is no automaticity in these relationships: PIAAC data show that skills do not automatically translate into higher incomes and higherproductivity. Success with converting skills into jobs and growth depends on:Whether we have a good understanding of what those skills are that drive strong, sustainable and balanced economic outcomes; whether the right mix of skills is being taught and learned in effective, equitable and efficient ways; whether economies fully utilize their skill potential; and whether governments can build strong coalitions with the business sector and social partners to find sustainable approaches to who should pay for what, when and how. That is why an instrument such as PIAAC is so critical for policy development.
The pace of change is most clearly visible in higher education, and I want to bring two more dimensions into the picture here. Each dot on this chart represents one country. The horizontal axis shows you the college graduation rate, the proportion of an age group that comes out of the system with a college degree. The vertical axis shows you how much it costs to educate a graduate per year.
*Lets now add where the money comes from into the picture, the larger the dot, the larger the share of private spending on college education, such as tuition.The chart shows the US as the country with the highest college graduation rate, and the highest level of spending per student. The US is also among the countries with the largest share of resources generated through the private sector. That allows the US to spend roughly twice as much per student as Europe. US, FinlandThe only thing I have not highlighted so far is that this was the situation in 1995. And now watch this closely as you see how this changed between 1995 and 2005.
You see that in 2000, five years, later, the picture looked very different. While in 1995 the US was well ahead of any other country – you see that marked by the dotted circle, in 2000 several other countries had reached out to this frontier. Look at Australia, in pink.
What do weseefrom this?- Every country has seen improvements in terms of output The example of the UK shows that you can set ambitious national targets and actually get close to them within a decade What you cannot do is prevent others from surpassing themAnd in a global economy, it is no longer simply improvement by national standards, but the best prepared individuals, companies and countries that are the benchmarks for success. What international comparisons can do is to show how the goal post keeps changing.
Countries make very significant investments in skills, but data from PISA and PIAAC show that there is considerable scope for making investments in skill development and utilisation more efficient. PIAAC will help us answer difficult questions about who should pay for what, when and how when it comes to skills development. It will also allow us to examine how regional and local levels can intervene most effectively, and how different countries structure financing and incentives for learners and employers for the upgrading of skills.
Another way to look at this is to examine changes in occupational profiles: Over recent decades there has been a steady change in the industrial and occupational structure of employment. There has been particularly strong growth in occupations requiring higher skills. And in some emerging countries these changes have been much more radical and will therefore require substantive modification in the skills supply over a very short period of time.
Don’t be misled that these changes are somehow averaging out, you can’t just shift workers from one occupation to another. On the contrary, the challenges which those changes in occupational profiles pose for skills policies become clear when you take into account that different occupations require very different skill profiles. Its just very hard to transform an unemployed steelworker into a productive computer specialist.With PIAAC, we are now able to track those skill profiles within a comparative framework: Let me mark the average in white.The violet shade shows you that low-skilled service workers (like a servant in a restaurant) need a lot of motor skills but few computer skills. People producing goods need more of everything but the profile is quite similar. Low-skilled information workers (like clerks or bookkeepers) are using a pretty rounded skill profile, High-skilled information workers use an even wider range, and you see that literacy skills and oral communication are particularly important. For managers, planning their time and the time of others is particularly important. And when you move to high-skilled knowledge workers (like yourselves) you need more of everything but a lot better skills in oral communication, reading and computers. So as you move from producing goods to high-level knowledge work, you need to develop not just more but also different skills. With PIAAC, we now have an opportunity to map competitive advantages of countries.
Levy and Murnane show how the composition of the US work force has changed. What they show is that, between 1970 and 2000, work involving routine manual input, the jobs of the typical factory worker, was down significantly. Non-routine manual work, things we do with our hands, but in ways that are not so easily put into formal algorithms, was down too, albeit with much less change over recent years – and that is easy to understand because you cannot easily computerise the bus driver or outsource your hairdresser. All that is not surprising, but here is where the interesting story begins: Among the skill categories represented here, routine cognitive input, that is cognitive work that you can easily put into the form of algorithms and scripts saw the sharpest decline in demand over the last couple of decades, with a decline by almost 8% in the share of jobs. So those middle class white collar jobs that involve the application of routine knowledge, are most at threat today. And that is where schools still put a lot of their focus and what we value in multiple choice accountability systems.The point here is, that the skills that are easiest to teach and test are also the skills that are easiest to digitise, automatise and offshore. If that is all what we do in school, we are putting our youngsters right up for competition with computers, because those are the things computers can do better than humans, and our kids are going to loose out before they even started. Where are the winners in this process? These are those who engage in expert thinking – the new literacy of the 21st century, up 8% - and complex communication, up almost 14%.
Perhaps most importantly, PIAAC allows us to look at how well today’s skill supply matches demand. It does so by comparing the actual skills of workers as measured by PIAAC with the extent of their engagement in related activities at work. For example, if workers have literacy skills that roughly correspond to PIAAC Level 3, (that’s what you need for coping with moderately complex literacy demands), and they engage in literacy related activities at work at least once a week, then we consider them in a high-skill equilibrium. On average across OECD countries, that is true for 33% of workers. If workers are found to have literacy skills below Level 3, and they report engaging in literacy related activities less than once a week, they are deemed to be in a low-skill equilibrium (26%). On average across countries, 25% are found to be in a surplus situation – where workers have higher literacy skills than what their jobs demand; and about 17% are found to be in a deficit situation – they are not sufficiently skilled for their jobs.Now again, you can look at this by occupational sectors. The goods producing sector, that does not require high skills, employs lots of low-skilled workers, but it also employs a fair share who could actually deal with higher literacy requirements. The situation is similar in the low-skill service sector. Low-skill information workers are moving closer to a high-skill match situation. The situation is a bit more pronounced for high-skill information workers and managers. When you move to high-skill knowledge workers you find generally a good high-skilled match but you also see some skill deficits.As you would expect, you find that knowledge workers are more likely to be in a high-skill equilibrium and non-knowledge economy workers are more likely to be in a low-skill equilibrium. Both types of workers experience surpluses and deficits, but deficits are more common among knowledge economy workers while surpluses are more common among non-knowledge economy workers. And that is a good illustration why you can have unemployment and skill shortages at the very same time.