Jobs can be thought of as a series of tasks, some of them levaing less space for autonomy and worker creativity. Such tasks have been termed ``routine'', as it is possible to write routines for machines to run them. We explore whether the importance of routine tasks is correlated to wage dispersion within occupations.

1. Within occupation wage dispersion
and the task content of jobs
Lucas van der Velde
Warsaw School of Economics GRAPE |FAME
lvandervelde@grape.org.pl
Our contribution
* Link wage dispersion inside occupations and
task content of jobs
* Study wage dispersion in a panel of EU countries
* Explore alternative hypothesis concerning:
• Nature of tasks
• Winner-takes-all markets
• Reallocation induced wage dispersion
Is inequality within occupations relevant? Yes
0 .1 .2 .3
Value of the Theil index
BGR
LVA
GBR
LTU
EST
POL
CYP
FRA
SVK
CZE
LUX
3 digit ISCO codes
0 .1 .2 .3
Value of the Theil index
ROM
PRT
DEU
ESP
ITA
HUN
NLD
GRC
BEL
FIN
NOR
SWE
2 digit ISCO codes
Within occupations Between occupations
Over 50% of wage inequality
comes from within occupations
Notes: Theil decomposition of hourly
wage inequality in EU. ISCO 08 identify
groups. Source: EU-SES 2010
Possible links between task content and wage dispersion within occupations
Jung and Mercenier (2014)
• Non-routine tasks output is more elastic on
ind. productivity than routine tasks output
• Why? Wage structure
Autor and Acemoglu (2011)
• Reallocation induces changes in within-
occupation wage dispersion
• Why? Changes in characteristics
Brynjolfsson and McAfee (2016)
• New technologies create winner-takes-all
markets in non-routine tasks
• Why? Market structure
Main results
Specication
log(y) = α0 + βRTI + Dγ + ,
where
• y is a measure of wage dispersion:
Ratio of percentiles
Unconditional and conditional wages
• RTI measure of task content from O*NET
(Acemoglu and Autor 2011)
• β is coecient of interest → H1: β 0
• D indicate country and year F.E.
Unconditional wage Conditional wages
(1) (2) (3) (4) (5)
log(p90/p10)
RTI -0.10*** -0.09*** -0.08*** -0.07*** -0.07***
(0.01) (0.01) (0.00) (0.00) (0.00)
R2 0.45 0.48 0.52 0.53 0.55
log(p90/p50)
RTI -0.05*** -0.04*** -0.05*** -0.04*** -0.05***
(0.00) (0.00) (0.00) (0.00) (0.00)
R2 0.41 0.42 0.46 0.47 0.50
log(p50/p10)
RTI -0.06*** -0.04*** -0.04*** -0.03*** -0.02***
(0.00) (0.00) (0.00) (0.00) (0.00)
R2 0.35 0.39 0.45 0.46 0.51
• ↓ RTI ⇒ ↑ Wage dispersion
• Relation is stronger at top
of distribution
Notes: Estimates based on EU-SES, years 2002,
2006 and 2010. The number of observations in
all regressions is 1862. Wages are conditional
on gender, age, education, size of rm, industry,
and in Column (5) rm xed eects. Columns
(2), (4), and (5) include a control for average
wages in occupation. *,**,*** indicate signi-
cance at the 10%, 5% and 1% signicance level.
Robust standard errors in parentheses.
Which tasks drive the results?
−.05
0
.05
Coeff.95%CI.
NR. cognitive NR. personal NR. manual R. manual R. cognitive
Dep. variable: ln(p90/p10) ln(p90/p50) ln(p50/p10)
→ ↑ Non-Routine tasks
(cognitive and personal)
⇒ ↑ Wage dispersion
→ ↑ Manual tasks
⇒ ↓ Wage dispersion
Notes: Dependent variable is con-
ditional wage dispersion, obtained
as in Column (5). Model includes
all tasks in a single regression with
country and year xed eects and
average wage as a covariate.
What about other eects?: Alternative specications
Reallocation frictions - Acemoglu Autor (2011)
(I) log(y) = α0 + β1RTI + β2∆t−5,t + Dγ +
−.04
−.03
−.02
−.01
0
.01
RTI
Task content
−1
0
1
2
3
Change in emp. share of occupation (5 years)
Worker reallocation
Dep. variable: ln(p90/p10) ln(p90/p50) ln(p50/p10)
Winner-takes-all - Brynjolfsson McAfee (2016)
(II) log(y) = α0 + β1RTI + β2Inc.share + Dγ +
−.08
−.06
−.04
−.02
0
RTI
Task content
0
.005
.01
.015
Inc. share of top 10% / share of bottom 10%
Winner−takes−all
Dep. variable: ln(p90/p10) ln(p90/p50) ln(p50/p10)
Notes: Dependent variable is conditional wage dispersion, obtained as in Column (5). Specication (I) includes a measure of worker
reallocation: change inemp. share of occupation i in previous 5 years. Only EU-SES 2002 and 2006 used (I). Specication (II)
includes a proxy for winner-takes-all market: income share of the rst decile over the share of the bottom decile in each occupation. All
EU-SES years used in the right panel.
Conclusions
• Occupations with more non-routine content
present greater wage dispersion
• Eect is relatively small → 1 std. dev. in
RTI is related to a 2% to 10% increase in
dispersion between top 90 and bottom 10
• Result is not driven by
→ Dierences in worker composition
→ Frictions related to reallocation
→ Winner-takes-all markets
• Policy implications
→ Within occupation wage dispersion likely
to increase in the future as routine jobs are
automated.
→ Is there a role for ALMP? reskilling could
help workers at the bottom, but not address
dispersion at the top.
Acknowledgements
Earlier versions of this paper received valuable comments
from J. Svejnar, A. Szulc, J. Tyrowicz, K. Staehr, S. Es-
trin and participants of WLE in Trier (2017) , and the IEA
2017 and GRAPE economic seminars. This research was
supported by a grant from the National Science Centre,
UMO-2016/21/N/HS4/02108. Remaining errors are ours.