Insight Primer - Human Capital and Skills Needs
1. Dominant Relations affecting Human Capital and Skills
The starting point for analysis is forward projection of likely growth in ICT consumption. Figure 1 shows ICT consumption for the four regions: USA, EU, Japan, and the rest of the world. ICT consumption is determined in terms of three categories: private, individual, consumption; ICT needs for economy; and ICT consumption resulting from the development of new products and services that enhance ICT use both by individuals as well organizations. This is shown for Europe in Fig. 2. Fig. 3 indicates consumption per capita for the three regions.
Fig 1
Fig 2
Fig 3
Initial ICT consumption derives from published data thus
ICT AS A % OF GNP
|
Country |
1999 |
|
Western Europe |
5.80 |
|
United States |
7.29 |
|
Japan |
5.03 |
With growth rates thus ICT_cons % growth
|
Country |
Year 2000 |
Year 2001 |
|
Europe (including Eastern Europe) |
10.7 |
9.1 |
|
United States |
8.1 |
8.1 |
|
Japan |
6.1 |
5.9 |
|
Rest of the World |
11.0 |
10.6 |
|
Total |
9.4 |
8.8 |
The specific focus here is not on total ICT labour, but rather on highly professional, innovative R&D and production management personnel, and particularly on the category of tertiary (university) educated (ICT) labour. It is assumed that the less skilled labour closer to the digital divide could be recruited from domestic population by proper education and life-long learning policies.
Fig 4
Fig 5
Fig 6
Fig 7
The starting point for labour consideration is population thus
|
Country |
Population, 2000 |
Compounded Growth Rates 1990-2000 |
|
USA |
275,563 |
.98 |
|
EU |
377,793 |
.49 |
|
EU Candidates |
170,874 |
.34 |
|
Japan |
126,550 |
.24 |
Total Population has however to
be modified by appropriate breakdowns into age cohorts of which the
following is just one example:
It will be observed that the population
in the candidate countries is much younger than that in the EU-15 shown
below
The impact on the EU objectives is illustrated below. The gap between labour demands for highly skilled innovative professionals far exceeds domestic supply as shown in Figure 8. This results in professional labour immigration on an annual basis as shown in Figure 9 (bars) and accumulative (line). It is assumed that the immigration labour will come with working permits and will stay for a period of our analysis or is replaced in that period by a new group of immigrants. The cumulative ICT professionals reach over six million by the year 2050.
Fig 8
Fig 9
Assuming that the immigration professionals
are allowed to bring their families, which will certainly be a requirement
to attract them, and that family size is 5, the total population is
compared with the domestic population in Figure 10.
Fig 10
Fig 11
Fig. 11 is perhaps the most interesting (and controversial!). It shows the impact of human labour—highly skilled professionals—on unemployment. Imported human capital has a positive impact on growth. In addition, it will create jobs in two ways: by meeting the needs of household and other support; e.g., housing, retail, services, etc.; it will create an opportunity for the unemployed to cross the digital divide, e.g., with sufficient training the unemployed could fill low or medium skilled jobs in data preparation, low level programming, etc. The top-down curve shown in Figure 11 gives the unemployment average of 8% over the period. The bottom curve shows the jobs created by human capital imported assuming a 1:1 ratio. The next curve shows the additional jobs if two new jobs are created by one imported professional—which is probably the upper limit. The unemployment is anticipated to reduce by one-third to two-thirds from the level when the ICT industry growth is below what technologically would be feasible. In terms of numbers this is just an illustration indicating that the importation of human capital increases economic growth while also having a positive impact on the reduction of unemployment.In the educational scenario it is assumed that tertiary education goes even beyond 34% as anticipated by IIASA and will reach 50% as indicated in Figures 12 and 13. The impact on human capital deficit is slight. Figure 14 indicates that the cumulative immigration of professionals will go down to only about five million.
Fig 12
Fig 13
Fig 14
Educational considerations are underpinned by the
age cohort structure of the population, using estimates such as that
below:
| Table
22. Estimated share of the population above 15 years of age (in
millions) |
||||||||
| Region |
2000 |
2030 |
||||||
| No education |
Primary |
Secondary |
Tertiary |
No education |
Primary |
Secondary |
Tertiary |
|
| M F |
M F |
M F |
M F |
M F |
M F |
M F |
M F |
|
| N. America |
1 1 |
8 8 |
59 64 |
53 53 |
2 2 |
10 9 |
76 79 |
69 78 |
| S. Asia |
180 284 |
108 74 |
149 65 |
23 9 |
96 279 |
370 329 |
250 113 |
52 27 |
| China & CPAa |
52 133 |
192 91 |
270 180 |
19 10 |
12 46 |
141 195 |
477 408 |
41 29 |
| Pacific OECDa |
0 0 |
12 14 |
33 36 |
16 15 |
0 0 |
5 6 |
40 44 |
19 18 |
| W. Eur. |
8 14 |
42 53 |
96 94 |
35 29 |
3 6 |
23 29 |
114 112 |
59 62 |
| E. Eur. a |
1 2 |
14 20 |
28 25 |
5 4 |
0 0 |
8 10 |
35 36 |
5 6 |
| World |
386 656 |
628 606 |
888 690 |
224 179 |
241 570 |
1014 1013 |
1498 1272 |
359 322 |
For countries included in this
region see note to Table 21.
M = male, F = FemaleLabour productivity increases would have
a much more dramatic impact.
Assuming labour productivity increases by 200%, Figure 15 shows the decline in cumulative professional immigration population becomes less than half, i.e., 2.5 million, as shown in Figure 16. The impact on total population is shown in Figure 17.
fig 15
Fig 16
Fig 17
Finally, the question is asked what would be the impact of outsourcing, i.e., exporting R&D and other highly skilled, innovative, activities outside the European Union?Figures 18 and 19 indicate that about 20% of industry will have to be outsourced in order to achieve the same objective as increasing labour productivity as shown in Figure 2.
Fig 18
Fig 19
