Spousal Joint Retirement: A reform based
approach to identifying spillover effects
Francois Gerard, Department of Economics, UC Berkeley
and
Lena Nekby, Department of Economics, Stockholm University
and SULCIS
Introduction
• Recent pension reforms aim at raising retirement
ages by strengthening work incentives for the
elderly.
• How current and future reforms will affect the
labor supply of the elderly is thus a central
question of interest for policymakers.
• Retirement decisions, at least within couples, are
highly interdependent.
– Coile (2003) estimates that omitting spousal
retirement incentives significantly underestimates
the overall impact of typical reforms by 13% to 20%.
Introduction
• Joint retirement accounts for nearly a third of
retirement patterns in the US and Europe (Blau,
1998; Coile, 2003; Hurd, 1990; Pozzoli and Ranzani, 2009).
– Blau: Between 11% -16% of couples exit the labor
force in the same quarter and between 30%-41%
within 1 year of each other (Retirement History
Survey RHS).
– Pozzoli & Ranzani: In Europe (SHARE data 2004)
78% of working males are married and 24% have a
working wife.
• participation rate of women aged 50-64 is 65%
or higher in Denmark, Finland, Norway, Sweden
Introduction
• Questions to answer:
– Are there spillover effects of the reform on own
retirement due to changes in spousal retirement
incentives?
– Can we use the reform to quantify the causal effect
of spousal retirement on own retirement?
• The literature to date has not been able to clearly
identify the impact of a partner’s retirement
decision on one's own decision so the question
remains unanswered
Introduction
• Spillover effects on individual retirement decision
may be due to
– income effects (cross-earnings effects, cross-health
effects)
– joint assets, joint wealth
– complementarity (or substitution) of leisure between
spouses
– correlation in preferences – assortative mating
• correlation in pension incentives
Introduction
• Many studies find significant and economically
relevant correlations between individual
retirement decisions and partner’s incentives (An
et al, 1999; Blau, 1998; Coile, 2003; Johnson and Favreault,
2001; Zweimuller et al., 1998).
– These studies lack a clear identification strategy.
• Another strand in the literature estimates
structural models of retirement behavior within
couples (Hurd, 1990; Gustman and Steinmeier, 2000;
Maestas, 2002)
• Coile (2003): Men are very responsive to their wives‘
pension incentives but women are not responsive to
their husbands' incentives.
– Husbands react to changes in wives’ legal minimum
retirement age, wives don’t react vice versa (Zweimuller et
al 1995)
• An et. al. (1999) finds strong complementarities in
leisure times, symmetrically for husband and wife.
– Neither party is found likely to substitute own for
purchased care when the spouse is in poor health.
– Johnson & Favreault (2001): Both men and women are
less likely to retire if spouses have left labor market due to
health reasons.
• Blau (1998): high incidence of joint retirement, which
cannot be explained by financial incentives
– preferences for sharing leisure has important implications
for analysis of the effects of retirement policy.
• Pozzoli & Ranzani (2009): joint retirement is
significantly correlated with education, age, and health
status, together with partner's employment status,
partner's education and partner's health status.
– females are more likely to take care of their sick
partners, and retire earlier, whereas husbands do
not.
• Gustman & Steinmeier (2000): Interaction between
spouses modeled as a non-cooperative game
– correlation of retirement preferences important for
joint retirement as is the increase in leisure value
from having a spouse retired.
• Maestas (2002): lifecycle model with cooperative
bargaining
– Complementarity in leisure important
– Women chose to retire early because they want to,
not because their husbands want them to.
• Recent work exploits exogenous changes from
pension reforms to estimate causally the impact
of own retirement incentives on own retirement
behavior (Glans 2008; Mastrobuoni, 2009).
• Our study extends this work to spillovers within
couples
• Recent paper by Selin (2011) looks at same
question using same reform!
– Looks only at male reactions to changes in
retirement incentives among female spouses
• Looks only at men married to women aged 63
– Has only one reference year
• wifes aged 63 in the year 2000 who therefore
belong to the last cohort (1937) unaffected by
the reform
– Only one (generous) definition of retirement
• postive pension income
The 2000 Pension Reform
• The 2000 pension reform introduced a defined
contribution system in comparison to the old
defined benefit system
• The new national pension system consists of
three parts; income pension (Notional Defined
Contribution), premium pension and guarantee
pension
– plus occupation-based and private pensions.
• Contributions to income pensions are recorded in
individual accounts which represent individual
claims to future pension benefits.
– Annual contributions to the NDC are used to finance
current pension benefit obligations as in a pay-asyou-go system.
The 2000 Pension Reform
increased work incentives
• Income and premium pension are based on
lifetime earnings including pensionable income
from sickness benefits, parental leave,
unemployment insurance, studies (with national
student loans) and military service.
• Pensions can be withdrawn at the earliest from
age 61 but pensions are reduced until the age of
65 at which time they are adjusted back to
regular levels.
– There is no upper age limit for commencing pension
payments (in previous system, work after age 70 did
not lead to higher pensions).
• In the new system, pensions are higher the later
they are withdrawn due to a lower number of
years with expected pension payments and
higher lifetime contributions.
Old System
• Folkpension (independent of previous income)
and supplementary benefit (ATP):
ATP = 0.60*BPA*ATP points
ATP points = (pensionable income-BPA)/BPA
(BPA=36,600 SEK in year 2000)
– ATP points earned during 15 highest years of
income since age 16 (or average over available
years)
– Pensions could be withdrawn from beginning of the
month an individual turns 61 (with a permanent
reduction by 0.5% for each month left until age 65
– Postponement possible until age 70 (with 0.7
percent permanent increase for each postponed
month)
Distribution of pension across new
(orange) and old (grey) system by
cohort
Two approaches:
1. Graph actual and simulated retirement and joint
retirement behavior under various assumptions
in order to see how much of actual behavior can
be explained by the average behavior of
individuals (in a given cohort, sector etc)
2. Difference-in-difference & triple difference
analyses of reform effect
–
–
Compare cohorts affected by the reform with those
not affected by the reform before and after the
reform kicks in (2000).
Given treatment effect on own retirement behavior,
estimate treatment effect of having a spouse
affected by the reform in comparison to having a
spouse not affected by the reform before and after
the reform kicks in.
Difference-in-difference strategy
(and triple difference)
– Also use the fact that local public sector workers
simultaneously experienced a reform of
occupational pensions towards a defined
contribution system (enhancing the effect of the
general pension reform in comparison to private
sector workers).
– Use reform to instrument effect of spousal retirement
on own retirement, focusing only on those not
directly affected by the reform (?)
Data
• IFAU database
– Information on all individuals aged 16-65 from 19852000 and all individuals aged 16-74 from 2001-2007
• Information on employment, sector, income,
education from 1985
• Information on various sources of pension
income from 1990: early retirement, folkpension,
ATP, disability pensions (old system) and
income pension, premium pension, occupational
pensions (aggregated), guarantee pension (new
system)
Restrictions
• Couples who have the same spouse throughout
the observation period
– Depart from LOUISE data (1990-2008)
– Keep only cohorts born 1930-1950
– Missing are couples where:
• one spouse falls outside LOUISE age range
• dies during the observation period
• Family identification is missing
• No match between LOUISE and Employment
(Sys) data
• 54% of over 3 million individuals observed are
with same spouse throughout the observation
period
– 24% constantly single
– 18% change spouse
– 4% ?
Defining Retirement
• Four definitions of retirement:
1. No work: income equal to zero
2. Some pension: sum of all pension sources
greater than zero
3. More pension: sum of income plus sick benefits
less than sum of pension income
4. Permanent drop: Permanent drop in income
(including sick benefits) of at least 33% from
one year to the next
–
This measure (& no work) can be measured from
1985
• Today focus on ”drop income” and ”some
pension”
Defining sector of employment
• No direct information on occupational pensions
available
• Two definitions (based on data from 1985-2008)
of four defined sectors:
– State, County, Municipality, Other (Private Swedish,
Private Foreign)
1. Sector with majority of observations before the
age of 60
2. Sector with maximum income before the age of
60
Panel 1985-2008 of individuals and
their spouses born 1934-1941
Female
1938
Male
1937
49.3
68.0
58.5
66.2
39.5
64.6
52.7
60.9
Sector (based on income)
State
Municipality
County
Other
10,1
32,0
13,8
39,7
16,5
12,8
2,4
67,1
Sector (based on no. of observations)
State
Municipality
County
Other
9,8
31,2
13,8
42,2
15,4
12,1
2,2
70,2
Birth year
Retired (year 2000, cohort 1937):
No work
Some pension
More pension
Drop income
Joint Retirement (drop income)
Same year
Within 1 year
Within 2 years
Within 5 years
9,34
22,9
34,0
59,1
Own retirment by cohort & sector
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
C_ret_dropinc
1
ret_dropinc woman other1
1
ret_dropinc woman kom1
45
50
55
60
65
70
45
50
55
age
36
37
70
37
1
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
1
ret_dropinc woman other1
0
C_ret_dropinc
65
36
ret_dropinc woman kom1
45
50
55
60
65
70
45
50
55
age
60
65
70
age
37
38
37
38
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
0
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
1
ret_dropinc woman other1
1
ret_dropinc woman kom1
C_ret_dropinc
60
age
45
50
55
60
65
age
38
70
45
50
55
60
65
age
39
38
39
70
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
C_ret_dropinc
1
ret_dropinc woman other1
1
ret_dropinc woman kom1
45
50
55
60
65
70
45
50
55
age
39
40
39
65
70
65
70
40
.1 .2 .3 .4 .5 .6 .7 .8 .9
0
0
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
1
ret_dropinc woman other1
1
ret_dropinc woman kom1
C_ret_dropinc
60
age
45
50
55
60
65
age
40
70
45
50
55
60
age
41
40
41
0
0
1
1
0
0
45
45
1
1
50
50
50
55
60
55
55
38
65
36
60
37
65
age
60
65
39
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
45
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
0
0
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
1
1
ret_dropinc man kom2
ret_dropinc man other2
age
70
45
70
45
70
45
50
ret_dropinc man kom2
50
ret_dropinc man kom2
50
55
age
37
age
38
60
55
55
38
65
36
60
37
age
60
39
70
37
ret_dropinc man other2
age
65
65
70
38
ret_dropinc man other2
70
0
0
1
1
45
45
50
50
55
60
39
55
40
65
age
60
65
41
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
0
0
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
.1 .2 .3 .4 .5 .6 .7 .8 .9
C_ret_dropinc
1
1
ret_dropinc man kom2
ret_dropinc man other2
age
70
70
45
45
50
ret_dropinc man kom2
50
55
age
40
60
39
55
40
40
ret_dropinc man other2
age
60
41
65
70
65
70
Joint Retirement: Females
0
.01
.02
.03
.04
Both Retired within a year Women 1935
55
60
65
70
age
m_bothclose
m_pbothcloser3
m_pbothcloser1
0
.01
.02
.03
.04
Both Retired within a year Women 1940
55
60
65
age
m_bothclose
m_pbothcloser3
m_pbothcloser1
70
Joint Retirement: Males
0
.01
.02
.03
.04
.05
Both Retired within a year Men 1935
55
60
65
70
age
m_bothclose
m_pbothcloser3
m_pbothcloser1
0
.02
.04
.06
Both Retired within a year Men 1940
55
60
65
age
m_bothclose
m_pbothcloser3
m_pbothcloser1
70
Joint Retirement: Females (incl.
Sector)
0
.01
.02
.03
.04
Both Retired within a year Women 1935 SEC
55
60
65
70
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
m_pbothcloser2
m_pbothcloser2_sec
0
.01
.02
.03
.04
.05
Both Retired within a year Women 1940 SEC
55
60
65
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
m_pbothcloser2
m_pbothcloser2_sec
70
0
.02
.04
.06
Joint Retirement: Males (incl.
Sector)
Both Retired within a year Men 1935 SEC
55
60
65
70
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
m_pbothcloser2
m_pbothcloser2_sec
0
.02
.04
.06
Both Retired within a year Men 1940 SEC
55
60
65
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
m_pbothcloser2
m_pbothcloser2_sec
70
Joint Retirement, Same Year
Both Retired in same year Women 1940 SEC
0
0
.005
.005
.01
.01
.015
.02
.015
Both Retired in same year Women 1935 SEC
55
60
65
70
55
age
m_pbothretr2
m_pbothretr2_sec
65
70
m_pbothretr2
m_pbothretr2_sec
Both Retired in same year Men 1940 SEC
.02
.015
.01
0
.005
0
.005
.01
.015
.02
.025
Both Retired in same year Men 1935 SEC
m_bothret_restr
m_pbothretr4
m_pbothretr4_sec
.025
m_bothret_restr
m_pbothretr4
m_pbothretr4_sec
60
age
55
60
65
70
55
age
m_bothret_restr
m_pbothretr4
m_pbothretr4_sec
60
65
age
m_pbothretr2
m_pbothretr2_sec
m_bothret_restr
m_pbothretr4
m_pbothretr4_sec
m_pbothretr2
m_pbothretr2_sec
70
Joint retirement within one year:
some pension definition
Both Retired within a year Women 1940 SEC
0
0
.01
.01
.02
.02
.03
.03
.04
.04
.05
Both Retired within a year Women 1935 SEC
55
60
65
70
55
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
60
65
70
age
m_pbothcloser2
m_pbothcloser2_sec
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
Both Retired within a year Men 1940 SEC
0
0
.02
.02
.04
.04
.06
.06
.08
.08
Both Retired within a year Men 1935 SEC
m_pbothcloser2
m_pbothcloser2_sec
55
60
65
70
55
age
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
60
65
age
m_pbothcloser2
m_pbothcloser2_sec
m_bothclose_restr
m_pbothcloser4
m_pbothcloser4_sec
m_pbothcloser2
m_pbothcloser2_sec
70
Probability of retirement X years
apart:
Probability of retirement x years apart Women 1940
.04
.04
.06
.06
.08
.08
.1
.1
.12
Probability of retirement x years apart Women 1935
-4
-2
0
diff_year
diff_scale
diff_r1_scale
2
-4
4
-2
0
diff_year
diff_scale
diff_r1_scale
diff_r0_scale
diff_r3_scale
4
diff_r0_scale
diff_r3_scale
Probability of retirement x years apart Men 1940
.04
.04
.05
.06
.06
.07
.08
.08
.09
.1
Probability of retirement x years apart Men 1935
2
-4
-2
0
diff_year
diff_scale
diff_r1_scale
2
diff_r0_scale
diff_r3_scale
4
-4
-2
0
diff_year
diff_scale
diff_r1_scale
2
diff_r0_scale
diff_r3_scale
4
Difference in difference estimation of
reform effect (change in own pension
incentives) on retirement probability
(treatment= birth year>1937, post= year>2000)
Females
Males
(1)
(2)
(3)
(4)
1930-1950
1934-1941
1930-1950
1934-1941
Cohorts
-.276***
-.065***
-.195***
-.064***
Treatment*Post
(.001)
(.001)
(.001)
(.001)
-.286***
-.134***
-.367***
-.158***
Treatment
(.001)
(.001)
(.001)
(.001)
1.035***
1.020***
1.050***
1.044***
Post
( .001)
( .002)
(.001)
(.001)
2
0.30
0.46
0.39
0.51
R
6,518,815
2,659,022
6,539,423
2,860,731
Observations
Standard errors clustered at individual level. All estimations control for a full set of year dummies
plus all relevant direct effects and double interaction effects. *** denotes significance at one
percent level, ** at five percent level and * at ten percent level.
Difference in difference estimation
of reform effect on pension
probability
(birth year*post interactions, reference year = 1930)
0
-.1
-.2
-.2
-.1
0
Estimated coefficient
.1
.1
.2
Females
.2
Males:
1931
1933
1935
1937
F( 13,350562) = 4608.31
Prob > F =
0.0000
1939 1941
Birth year
1943
1945
1947
1949
1931
1933
1935
1937
1939 1941
Birth year
F( 13,350107) = 4701.79
Prob > F =
0.0000
1943
1945
1947
1949
Triple difference estimation of
direct reform effect on retirement
Females
Males
(1)
(2)
(3)
(4)
1930-1950
1934-1941
1930-1950
1934-1941
Cohorts
-.144***
-.074***
-. 101***
-. 077***
Treatment*Post*Public
(.002)
(.003)
(.003)
(.004)
-. 212***
-. 033***
-. 180***
-. 052***
Treatment*Post
(.002)
(.003)
(.001)
(.002)
2
0.31
0.47
0.39
0.51
R
6,518,815
2,659,022
6,539,423
2,860,731
Observations
Standard errors clustered at individual level. All estimations control for a full set of year dummies
plus all relevant direct effects and double interaction effects. *** denotes significance at one
percent level, ** at five percent level and * at ten percent level.
Triple difference estimation of
reform effect
(birth year*local public sector*post)
-.05
-.1
-.2
-.15
-.15
-.1
-.05
Estimated coefficient
0
0
.05
Females:
.05
Males:
1931
1933
1935
1937
1939 1941
Birth year
F( 13,350562) = 91.59
Prob > F =
0.0000
1943
1945
1947
1949
1931
1933
1935
1937
1939 1941
Birth year
F( 13,350107) = 208.89
Prob > F =
0.0000
1943
1945
1947
1949
OLS Estimation of Spousal Retirement
on Individual Retirement
Female
Spousal
Retirement
(1)
1930-1950
.176***
(.005)
Male
(2)
1934-1941
.147***
(.007)
(3)
1930-1950
.163***
(.005)
(4)
1934-1941
.130***
(.006)
0.38
0.49
0.45
0.52
R2
6,518,815
2,659,022
6,539,423
2,860,731
Observations
440
168
440
168
Clusters
Standard errors clustered on cohort*spousal cohort. All estimates control for cohort, spousal
cohort, direct reform effects, sector, spousal sector and year dummies. *** denotes significance at
the one percent level.
Triple difference estimation of
SPOUSAL reform effect on retirement
probabilities (given own reform effect)
Females
Males
(1)
(2)
(3)
(4)
1930-1950 1934-1941 1930-1950 1934-1941
Cohorts
-.028
-.018
-.029
-.016
Spouse_Treatment*Post*Spouse_Public
(.019)
(.016)
(.021)
(.013)
-.104***
-.024***
.025
.009
Spouse_Treatment*Post
(.007)
(.005)
(.016)
(.009)
2
0.33
0.47
0.40
0.51
R
6,518,815
2,659,022 6,539,423 2,860,731
Observations
1693
653
1688
670
Clusters
Standard errors clustered on cohort*sector*spousal cohort*spousal sector. All estimations control
for a full set of year dummies plus all relevant direct effects and double interaction effects (own
and spouses). *** denotes significance at one percent level, ** at five percent level and * at ten
percent level.
Triple difference estimation of
SPOUSAL reform effect on
retirement probabilities
(spouse birth year*spouse local public sector*post)
Female
-.02
-.04
-.08
-.04
-.06
-.02
0
Estimated coefficient
0
.02
.02
.04
Male
1931
1933
F( 13, 1687) =
1937 1939 1941 1943
Spouse's Birth year
1935
3.87
Prob > F =
0.0000
1945
1947
1949
1931
1933
1935
F( 13, 1692) =
Prob > F =
1937 1939 1941 1943
Spouse's Birth year
2.06
0.0136
1945
1947
1949
-.02
-.04
-.06
Estimated coefficient
0
.02
Effects of 'SPOUSAL birth year'-'post reform'-'SPOUSAL local public sector' interactions on retirement probabilities, males
1931
1933
1935
1937 1939 1941 1943
Spouse's Birth year
1945
1947
1949
0
-.02
-.04
-.06
Estimated coefficient
.02
.04
Effects of 'SPOUSAL birth year'-'post reform'-'SPOUSAL local public sector' interactions on retirement probabilities, females
1931
1933
1935
1937 1939 1941 1943
Spouse's Birth year
1945
1947
1949
If we want to use reform as an instrument for spousal retirement, need to
drop those directly affected by the reform (cohorts born after 1937)
Distribution of spouses by birth year:
Birth year:
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
Observations
Spouses to Females
14.19
14.63
14.56
13.00
11.76
9.89
7.59
5.24
3.26
2.00
1.25
0.77
0.51
0.46
0.32
0.22
0.14
0.10
0.06
0.03
0.02
1,785,064
Spouses to Males
3.22
4.68
6.10
7.15
8.42
9.28
10.22
10.23
9.67
8.37
6.49
4.84
3.74
2.66
1.76
1.15
0.79
0.51
0.34
0.22
0.15
2,762,234
Smaller proportion of spouses to females born after 1937 (these male spouses are older than their
wives).
Triple difference estimation of SPOUSAL
reform effect on retirement probabilities,
Individuals born on or before 1937 only:
0
-.2
-.1
-.4
-.05
0
Estimated coefficient
.2
.05
.4
Female
.1
Male
1931
1933
F( 13, 670) =
1937 1939 1941 1943
Spouse's Birth year
1935
0.90
Prob > F =
0.5554
1945
1947
1949
1931
1933
F( 13, 602) =
1935
1937 1939 1941 1943
Spouse's Birth year
1.40
Prob > F =
0.1520
1945
1947
1949
Original idea was to quantify the
effect of spousal retirement on own
retirement by IV
”If you can’t see the the causal relation of interest
in the reduced form, it’s probably not there”
-Angrist and Krueger (2001)
IV estimation of spousal
retirement:
• There is a first stage effect of reform on spousal
retirement (corr (retirement_s, reform_s)>0)
– Female spouses affected by the reform (triple
difference) decrease retirement probabilities by
approx. 5.0 percentage points in comparison to
female spouses not affected by the reform
– Likewise reform effect on male spouses is - 8.0 pp.
• No reduced form effect of spousal reform on own
retirement probabilities
(corr (retirement_i, reform_s)=0)
– Spousal (local public sector reform effect of female
(male) spouses on male (female) retirement is -0.4
(0.9) percentage points and not signficant.
Conclusions
• Are there spillover effects of the reform on own
retirement due to changes in spousal retirement
incentives?
– Yes, something seems to be happening for those
with spouses born after 1940
• Spill-over effect of reform is likely to work via spousal
retirement but...
– can’t as of now use the reform as an instrument to
quantify the causal effect of spousal retirement on
own retirement.