Authorized Authorized

128 WORLD DEVELOPMENT REPORT 2016
Figure 2.22 New economy skills, beyond levels of
education, pay off
Urban Vietnam: Average return to different task combinations, controlling for
education and demographics, 2012
Percent
25
20
15
10
5
0
–5
–10
Analytical*** Interactive* Manual Analytical Interactive*** Manual
Nonroutine
Routine
Source: Bodewig and others 2014. Data at http://bit.do/WDR2016-Fig2_22.
Note: Returns are estimated using a wage regression that controls for education, sex, experience, and
economic sector.
Significance level: * = 10 percent, *** = 1 percent.
Technology, Automation, and Economic Progress,
there were also concerns about automation in this
wave of technological change. Unemployment fears
have gone unrealized because new technologies, by
fostering entrepreneurship and improving productivity
and the allocation of resources, have led in due
time to more jobs elsewhere.
Will this time be different? Large factories and
electrification did lead, as now, to a polarization of
employment by hollowing out the middle of the skill
distribution. The share of employment of blue-collar
workers in manufacturing fell from 39 percent in 1850
to 23 percent in 1910, as new capital goods allowed
factory owners to unbundle and simplify tasks that
could now be performed by unskilled workers. Electrification
increased the relative demand for workers
intensive in clerical and managerial skills compared
with manual and dexterity skills among white-collar
workers. Among blue-collar workers, it increased the
demand for manual workers relative to the demand
for workers performing tasks intensive in dexterity
needed to operate machines before electrification. 147
Despite these similarities, the biggest difference
from past waves of technological progress is that
the polarization of the labor market today is affecting
both blue-collar and white-collar workers. 148 It is
probably easier for white-collar workers to transition
to other white-collar jobs, but in the aggregate, there
may be fewer well-paying jobs for a large and diverse
pool of potentially dislocated workers. Even if all
those jobs do not fully disappear—unlikely in a short
period—they will be significantly transformed.
And here is where a second lesson from history
is relevant. Individuals and governments adapted to
technological change, but this process took time and
required deep institutional changes in education,
Figure 2.23 Digital technologies go hand in hand with nonroutine new economy skills
ICT intensity and skills intensity, by occupation
Nonroutine analytical (scale 1 to 5)
5
4
3
2
1
a. ICT intensity and nonroutine analytical skills
Routine manual (scale 1 to 5)
5
4
3
2
1
b. ICT intensity and routine manual skills
0 1 2 3 4 5 6 7 8 9 10 11 12 13
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Intensity of ICT use at work
Intensity of ICT use at work
Source: Monroy-Taborda, Moreno, and Santos, forthcoming, for the WDR 2016, based on STEP household surveys (World Bank, various years). Data at http://bit.do/WDR2016-Fig2_23.
Note: Ninety-five percent confidence intervals. The y-axis is a standardized score (from 1 to 5) that reflects the intensity of the use of the particular type of skills as estimated by Autor,
Levy, and Murnane (2003) and expanded by Acemoglu and Autor 2011. The intensity of ICT use is an index between 0 (no use of technology at work) and 19 (most use of technology at
work). ICT intensity is averaged by occupation. ICT = information and communication technology.