Ageing and productivity
Pekka Ilmakunnas
Vegard Skirbekk
Jan van Ours
Matthias Weiss
SET-UP
• Setting the Stage
• The Grand View
• Empirical studies– Absenteeism– Working capacity– Productivity: team level – plant level
• Conclusions and policy implications
SETTING THE STAGE
Labour force participation rates; 2003
0
10
2030
40
50
60
7080
90
100
15 to 19 20 to 24 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69
EU 15
Italy
Japan
USA
Population Western Europe 2010-2050 (1000)
0
5,000
10,000
15,000
20,000
2050 20
30 2010
2050
2030
2010
Old age dependency ratio & participation rates 50-64
• Old age dep. ratio = Population 65+ / 20-64
• Increase 2000-2050: moderate – very large
• Participation rates 50-64: high – low
• Extremes– Scandinavian countries, Switzerland, US– Southern Europe (including Italy)
Participation rates 2003 – males
80 85 90 95 10010
20
30
40
50
60
70
80
90
Australia
AustriaBelgium
Canada Denmark
Finland
France
Germany
Greece
Iceland
Ireland
Italy
Japan
Lux
Netherlands
NZNorway
Portugal
Spain
Sweden Switzerland
UKUS
Age 50-54
Ag
e 6
0-6
4
“Older people should be forced to retire
when jobs are scarce”
37,5 40 42,5 45 47,5 50 52,5 55 57,5 60 62,5 65 67,5 700
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
USSweden
Denmark
Norway
UKNetherlands
GermanyFrance
Italy
Spain
Employment rate men 55-64
Agre
em
ent w
ith s
tate
ment
Age of labour market entry and exit by birth cohort and educational attainment;
Italy
Men
0
10
20
30
40
50
60
70
80
15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74
Birth cohort
Ag
e
Duration of labour market attachment
Men
0
10
20
30
40
50
60
1915-19 1940-45 1915-19 1940-45 1915-19 1940-45 1915-19 1940-45 1915-19 1940-45
Finland France Germany Italy UK
Education 1 Education 2 Education 3
Norway 1801 and 2001, ages 41-90
both genders
Setting the Stage - conclusions
• Long term developments: people grow older and work fewer years
• Work fewer years: preferences, incentives and misperceptions
• Future: increase labour supply of older workers
• Question: Age Productivity?
THE GRAND VIEW
Some causes of age-variation in
productivity
Motivation, Energy
Job Experience
Mental Abilities, Personality
Work PerformancePhysical Abilities, Health, Strength
Education
Age
Firm Characteristics
Region, Industry Type
Components individual productivity
• Physical strength
• Experience
• Cognitive abilities:– Crystallized: verbal ability; age – Fluid: speed, memory; age
Importance of various abilities
0.0
0.1
0.2
0.3
0.4
Ability
Im
port
ance
Productivity variation of the life cycle Combining abilities
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
-19 20-24 25-34 35-44 45-54 55-65Age
Pro
du
cti
vit
y P
ote
nti
al
Alternative relationships
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
-19 20-24 25-34 35-44 45-54 55-65
Age
Pro
du
cti
vit
y P
ote
nti
al
Manager -Communication
Numerical -Analytical
Changes over time
• Supply: better health, better mental performance, longevity
• Demand: physical strength less important, reduced working day
The Grand View – conclusions
• Abilities not constant over age and cohorts
• Various components are affect differently by ageing
Measuring productivity (not easy)
• Managers’ ratings of employees
• Employees self-assessment
• Measure productivity directly
• Linked employer-employee datasets
EMPIRICAL STUDIES on AGE and PRODUCTIVITY
Extensive margin: absenteeism
Subjective measure: work capacity
Intensive margin: team & plant level
Absenteeism – data
• Germany: Assembly plant of a German car manufacturer – any work day 2003-2004
• Finland: Quality of Working Life Survey (QWLS) 2003
Individual absence rates assembly line German car manufacturer
Age and absenteeism survey of Finnish employees
0.2
.4.6
.81
Share
with a
bsences
Age
0.5
11
.52
Num
be
r of
ab
sence
s
Age
05
10
15
20
25
Days o
f absen
ce
Age
05
10
15
Dura
tio
n o
f a
typic
al a
bse
nce
Age
Absenteeism - conclusions
• Age: negative effect on incidence, positive effect on duration; overall positive effect on absence rate
• Age diversity: higher absence rates
Working capacity: self assessment
Assuming that your top working capacity would score 10 points
While your total inability to work would score 0 points
How many points would you give your working capacity at the moment?
01
23
45
67
89
10
Wo
rkin
g c
ap
aci
ty
20 25 30 35 40 45 50 55 60 65Age
Top working capacity and the effect of chronic illness
0.2
.4.6
Pro
bab
ility o
f to
p w
ork
ing c
ap
acity
-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60 61-Age
No chronic illness Chronic illness
Working capacity - conclusions
• Age Working capacity • Fall not dramatic, 0.3 points in 10 years
• Faster drop for jobs in which physical strength is required
• Technological change: influence of age becomes smaller
Productivity – intensive margin
• Individual productivity available only in special cases
• Plant level & firm level data effects of:– Age– Age diversity
Age – Productivity – team level
• DaimlerChrysler; 2003-2004
• Productivity = quality = 1/errors
• Decreases with age
• Increases with job tenure
• More age diverse teams make more mistakes
Age – Productivity – plant level
• Finnish Linked Employer-Employee Data (FLEED); 1990-2002
• Industrial plants – total factor productivity
• No effect of age diversity
Relationship changes over time1
.61
.71
.81
.92
2.1
2.2
2.3
2.4
2.5
log
(TF
P)
30 35 40 45 50Average age
1990 19952000
Accounting for plant cohort and tenure effects
22
.12
.22
.32
.42
.5
log
(TF
P)
30 35 40 45 50Average age
Tenure and cohort contro lled Plant cohort controlledNeither contro lled
Conclusions
• Age-productivity relationship complex and multidimensional
• Relationship changes over time (across cohorts) and is affected by other factors
• Absenteeism • Work capacity • Productivity • Age diversity?
Policy implications
• Retirement plans– Anticipating early retirement reduces investments in
human capital; actuarial neutral pension schemes
• Wage policies– Reduce seniority as a basis for wages
• Human resource management– More easy to try to prevent dismissals of older workers
than it is to encourage hiring of older workers
• Employment Protection Legislation– Experience rating of dismissal costs
Negative effects of age on Negative effects of age on productivity should not be productivity should not be
underestimatedunderestimated
Should not be exaggerated eitherShould not be exaggerated either