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Chapter 2: Investing in human capital and responding to long-term societal challenges
their respective costs ( 122 ) and ben- Chart 23: Positive impacts of subsidising young people
efits ( 123 ). On this basis it is assumed, in to take up higher education in Germany
the traditional economic jargon, that they Simulation with DG EMPL’s Labour Market Model: giving a subsidy to young
pursue further education so long as the adults to take up tertiary education (0.1 % of GDP)
marginal costs are lower than the mar-
ginal gains of higher education. High-skilled
Population Medium-skilled
Low-skilled
This endogenous educational choice is Total
High-skilled
‘switched on’ in this section — contrary Employment Medium-skilled
124
to the analyses mentioned earlier ( ). Low-skilled
Total
This means that an incentive is needed High-skilled
to attract more people to engage in Wage rate Medium-skilled
Low-skilled
Total
higher education ( 125 ). It is assumed that High-skilled
the government spends 0.1 % of GDP on Labour Medium-skilled
productivity
Low-skilled
subsidies to young people aged between Total
20 and 24 years if they take up tertiary Investment
GDP
education ( 126 ). The measure is financed -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
by lump-sum taxes levied on all house- %
holds and they are assumed to ‘have
no incentive effects other than shifting Source: Own calculations based on DG EMPL’s Labour Market Model.
income from the private to the public
sector’ ( 127 ). The results are similar in all Survey ( 129 ) ( 130 ). The 2014 Country level ( 132 ), and higher investment and bet -
14 countries covered by the model, but Specific Recommendation ( 131 ) urges ter skills improve workers’ productivity.
we use Germany as a basic example. Germany to spend more on education
and make efforts ‘at all levels of govern - Hence, the changing skills composition
The Europe 2020 target aims at having ment to meet the target for total public would be expected to trigger invest-
40 % of people aged between 30 and 34 and private expenditure on education and ment and labour productivity, which in
years with tertiary education in 2020, research of 10 % of GDP by 2015, and turn pulls up GDP by more than 0.2 %.
while Germany had set itself the national even more ambitious follow-up targets That is, a long-term multiplier of more
objective of increasing to 42 % the share should be aimed for in order to catch than two, which would bring an economic
of people aged between 30 and 34 years up with the most innovative economies’. expansion more than twice as strong as
who successfully achieve tertiary or the initial cost of the measure — which is
equivalent educational attainments by Chart 23 shows the long-term, steady- a very typical finding for skill-/education-
2020 ( 128 ) — reflecting the relevance of state results of the simulation. The sub- related policy measures ( ).
133
good quality vocational (apprenticeship) sidy increases the net-yield resulting
education in Germany in providing skills from taking up high education. Those 4.2. Maintaining HC:
relevant for the labour market. concerned adjust to the new situation Investment in training —
as more of them take the step from the case of Slovakia
In 2013, the share of tertiary edu- medium to high education. On this basis,
cated people in Germany was only the share of population with tertiary Informal training plays a major role in
around 33 % — below the EU average degrees would increase by 0.7 % com- the acquisition of the new skills needed
of 37 %, according to the Labour Force pared to the baseline scenario — this is to achieve higher labour productivity
mainly at the expense of medium-edu- growth and to limit human capital depre -
134
( ) Educational cost is also assumed to be a cated (-0.3 %) and some low-educated ciation over time ( ).
122
function of individual ‘abilities’ of which people (-0.1 %).
agents are assumed to have a correct
esteem. In Slovakia training intensity is low and
( ) It is also assumed that agents have a As a result of the changing skills mix, ‘despite government efforts to reform
123
perfect esteem on their individual abilities. total employment is expected to increase vocational education and training and
( ) For a similar exercise based on an older by 0.1 %, but the composition changes subsidise jobs for young people, the youth
124
version of LMM, see Berger et al. (2009:2),
pp. 50–56. strongly towards the highly educated. unemployment rate remains among
( ) The model assumes that the provision of This has important implications for the the highest in the EU’ according to the
125
higher education is oriented towards labour countries’ long-term growth perspective 2014 Country Specific Recommendation
market needs and that the additional
graduates are expected to be hired at least since physical investment is strongly
at the same rate as existing graduates. complementary to the average skill ( ) Capital intensity will be higher the stronger
132
126
( ) Currently, this corresponds to some skills are distributed towards higher skills:
EUR 2.7 bn per year and thus constitutes a high skills attract investment and vice versa.
medium-sized package. Today, this amount See Berger et al. (2009:1), p. 33.
would be arithmetically sufficient to grant to ( ) The strong negative impact on labour
133
each student of a German university support productivity of the highly educated is
of around EUR 1 100 per year. ( ) Germany had already exceeded national due to the expansion of high-educated
129
( ) Berger et al. (2009:2), p. 9. set targets in 2010 with a share of 43.5 % employment.
127
(Federal Ministry of Economic Affairs and
( ) Unlike the general EU2020 target, Germany Energy (2014), p. 31. ( ) For example: Berger et al. (2009:1),
134
128
includes ‘tertiary and equivalent’ education, 130 section 9.5.2; Heckman et al. (1998), HC
i.e., ISCED levels 4–6 (instead of 5–6) ( ) http://epp.eurostat.ec.europa.eu/portal/page/ accumulation function on p. 3. For empirical
into its own education-related objective portal/statistics/search_database (table evidence, see the micro-data analysis in
for 2020. ISCED level 4 includes t2020_41). section 2.3.1, based on the ‘PIAAC’ survey on
post-secondary education. ( ) European Commission (2014a), p. 4. adult skills.
131
125
their respective costs ( 122 ) and ben- Chart 23: Positive impacts of subsidising young people
efits ( 123 ). On this basis it is assumed, in to take up higher education in Germany
the traditional economic jargon, that they Simulation with DG EMPL’s Labour Market Model: giving a subsidy to young
pursue further education so long as the adults to take up tertiary education (0.1 % of GDP)
marginal costs are lower than the mar-
ginal gains of higher education. High-skilled
Population Medium-skilled
Low-skilled
This endogenous educational choice is Total
High-skilled
‘switched on’ in this section — contrary Employment Medium-skilled
124
to the analyses mentioned earlier ( ). Low-skilled
Total
This means that an incentive is needed High-skilled
to attract more people to engage in Wage rate Medium-skilled
Low-skilled
Total
higher education ( 125 ). It is assumed that High-skilled
the government spends 0.1 % of GDP on Labour Medium-skilled
productivity
Low-skilled
subsidies to young people aged between Total
20 and 24 years if they take up tertiary Investment
GDP
education ( 126 ). The measure is financed -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
by lump-sum taxes levied on all house- %
holds and they are assumed to ‘have
no incentive effects other than shifting Source: Own calculations based on DG EMPL’s Labour Market Model.
income from the private to the public
sector’ ( 127 ). The results are similar in all Survey ( 129 ) ( 130 ). The 2014 Country level ( 132 ), and higher investment and bet -
14 countries covered by the model, but Specific Recommendation ( 131 ) urges ter skills improve workers’ productivity.
we use Germany as a basic example. Germany to spend more on education
and make efforts ‘at all levels of govern - Hence, the changing skills composition
The Europe 2020 target aims at having ment to meet the target for total public would be expected to trigger invest-
40 % of people aged between 30 and 34 and private expenditure on education and ment and labour productivity, which in
years with tertiary education in 2020, research of 10 % of GDP by 2015, and turn pulls up GDP by more than 0.2 %.
while Germany had set itself the national even more ambitious follow-up targets That is, a long-term multiplier of more
objective of increasing to 42 % the share should be aimed for in order to catch than two, which would bring an economic
of people aged between 30 and 34 years up with the most innovative economies’. expansion more than twice as strong as
who successfully achieve tertiary or the initial cost of the measure — which is
equivalent educational attainments by Chart 23 shows the long-term, steady- a very typical finding for skill-/education-
2020 ( 128 ) — reflecting the relevance of state results of the simulation. The sub- related policy measures ( ).
133
good quality vocational (apprenticeship) sidy increases the net-yield resulting
education in Germany in providing skills from taking up high education. Those 4.2. Maintaining HC:
relevant for the labour market. concerned adjust to the new situation Investment in training —
as more of them take the step from the case of Slovakia
In 2013, the share of tertiary edu- medium to high education. On this basis,
cated people in Germany was only the share of population with tertiary Informal training plays a major role in
around 33 % — below the EU average degrees would increase by 0.7 % com- the acquisition of the new skills needed
of 37 %, according to the Labour Force pared to the baseline scenario — this is to achieve higher labour productivity
mainly at the expense of medium-edu- growth and to limit human capital depre -
134
( ) Educational cost is also assumed to be a cated (-0.3 %) and some low-educated ciation over time ( ).
122
function of individual ‘abilities’ of which people (-0.1 %).
agents are assumed to have a correct
esteem. In Slovakia training intensity is low and
( ) It is also assumed that agents have a As a result of the changing skills mix, ‘despite government efforts to reform
123
perfect esteem on their individual abilities. total employment is expected to increase vocational education and training and
( ) For a similar exercise based on an older by 0.1 %, but the composition changes subsidise jobs for young people, the youth
124
version of LMM, see Berger et al. (2009:2),
pp. 50–56. strongly towards the highly educated. unemployment rate remains among
( ) The model assumes that the provision of This has important implications for the the highest in the EU’ according to the
125
higher education is oriented towards labour countries’ long-term growth perspective 2014 Country Specific Recommendation
market needs and that the additional
graduates are expected to be hired at least since physical investment is strongly
at the same rate as existing graduates. complementary to the average skill ( ) Capital intensity will be higher the stronger
132
126
( ) Currently, this corresponds to some skills are distributed towards higher skills:
EUR 2.7 bn per year and thus constitutes a high skills attract investment and vice versa.
medium-sized package. Today, this amount See Berger et al. (2009:1), p. 33.
would be arithmetically sufficient to grant to ( ) The strong negative impact on labour
133
each student of a German university support productivity of the highly educated is
of around EUR 1 100 per year. ( ) Germany had already exceeded national due to the expansion of high-educated
129
( ) Berger et al. (2009:2), p. 9. set targets in 2010 with a share of 43.5 % employment.
127
(Federal Ministry of Economic Affairs and
( ) Unlike the general EU2020 target, Germany Energy (2014), p. 31. ( ) For example: Berger et al. (2009:1),
134
128
includes ‘tertiary and equivalent’ education, 130 section 9.5.2; Heckman et al. (1998), HC
i.e., ISCED levels 4–6 (instead of 5–6) ( ) http://epp.eurostat.ec.europa.eu/portal/page/ accumulation function on p. 3. For empirical
into its own education-related objective portal/statistics/search_database (table evidence, see the micro-data analysis in
for 2020. ISCED level 4 includes t2020_41). section 2.3.1, based on the ‘PIAAC’ survey on
post-secondary education. ( ) European Commission (2014a), p. 4. adult skills.
131
125
