DISCUSSION PAPER SERIESIZA DP No. 15577

The Effect of Removing Early Retirement
on Mortality

Cristina Bellés-Obrero
Sergi Jiménez-Martín
Han YeSEPTEMBER 2022

DISCUSSION PAPER SERIESIZA DP No. 15577

The Effect of Removing Early Retirement
on Mortality

Cristina Bellés-Obrero

University of Mannheim and IZA

Sergi Jiménez-Martín

Universitat Pompeu Fabra, FEDEA and Barcelona School of Economics

Han YeUniversity of Mannheim, IZA and ZEW

SEPTEMBER 2022

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IZA DP No. 15577

SEPTEMBER 2022

ABSTRACTThe Effect of Removing Early Retirement
on Mortality*
This paper sheds new light on the mortality effect of delaying retirement by investigating
the impacts of the 1967 Spanish pension reform. This reform exogenously changed
the early retirement age, depending on the date individuals started contributing to theSocial Security system. Those contributing before 1 January 1967 maintained the right tovoluntarily retire early (at age 60), while individuals who started contributing after that date
could not voluntarily claim a pension until the age of 65. Using the Spanish administrative
Social Security data, we find that the reform delayed the individuals’ labour market exit
by around half a year and increased the probability that individuals take up disability
pensions, partial pensions, and no pensions. We show evidence that delaying exiting
employment increases the hazard of dying between the ages of 60 and 69, for almost allindividuals. Heterogeneous analysis indicates that the increase in mortality is stronger for
those employed in low-skilled, physically and psychosocially demanding jobs. Moreover, weshow that allowing for flexible retirement schemes, such as partial retirement, mitigates the
detrimental effect of delaying retirement on mortality.
JEL Classification:

I10, I12, J14, J26

Keywords:

delaying retirement, mortality, heterogeneity, flexible
retirement

Corresponding author:
Cristina Bellés-Obrero
University of Mannheim
Department of Economics
L7, 3-5, room 326
68161 Mannheim
Germany
E-mail: cbelleso@mail.uni-mannheim.de* We are thankful to seminar and conference participants at Pompeu Fabra University, University of Mannheim,
Boston University, University of Barcelona, University of Verona, the CRC annual meeting, ESPE2022, and Max
Planck/NBER workshop 2022 for their helpful insights and suggestions. We gratefully acknowledge funding from theGerman Research Foundation (DFG) through CRC TR 224 (Project A02 and C01) and the Spanish Ministry of Science,
Innovation, and Universities (MICINN) through PID2020-114231RB-I00. We thank the Social Security Administration
for giving us access to the data through the Barcelona Research Room. Sergi Jiménez also acknowledges financial
support from Spanish National Research Agency (AEI) through the Severo Ochoa Programme for Centres of
Excellence in R&D (Barcelona School of Economics CEX2019-000915-S). The views expressed here are solely those of
the authors. All errors are our own.

1

Introduction

Many countries have reformed their public pension systems to cope with their aging populations
and to maintain financial solvency. One of the main policy tools used is to restrict access to early
retirement schemes by increasing the minimum pension eligibility age. While there has been
an extensive literature studying the labour supply responses to such pension reforms,1 there are
relatively few studies about the impact of delaying retirement on mortality. Moreover, the existing
empirical evidence mostly draws lessons from policy experiments that allow for earlier retirement(Coe and Lindeboom, 2008; Hernaes et al., 2013; Hallberg et al., 2015; Bloemen et al., 2017; Kuhn
et al., 2020). Because the effects on mortality from preponing and postponing the retirement age
are not necessarily symmetric, these estimates might not generalize to today’s policy world, wheremost policymakers aim to incentivize prolonged working lives. Therefore, it is policy-relevant tounderstand the impact of delaying retirement on mortality, particularly the effect of closing theearly retirement options on mortality.
This paper provides novel empirical evidence on this important issue by investigating a Spanish
pension reform. This 1967 reform exogenously changed the early retirement age depending on thedate individuals started contributing to the Social Security system. Individuals who contributed tothe pension system before 1 January 1967 could voluntarily claim a pension as early as 60 yearsof age. On the other hand, individuals who started contributing after 1967 could only voluntarily
claim a pension at age 65.2
This reform has several advantages in answering our research question. First, the discontinuity
change in retirement age, based on the year the individuals started contributing to the Social Security system, allows us to credibly identify causal effects. Second, in contrast to most of the previous
literature, this reform creates a substantial increase (approximately four years) in the early retirement age and leads to a considerable delay in the exit time of the labour market. Third, the reform
affects a more general population compared to existing studies (see, e.g., Hallberg et al. (2015);
Bloemen et al. (2017); Hagen (2018), all of which study specific subsets of the population, such as
military personnel and civil servants). This feature allows us to capture the mortality responses in
the general population and examine the heterogeneous responses of subgroups. Lastly, the treatment was determined at the early stage of a worker’s career, which provides a long-term horizon
for the expected retirement age to impact mortality, if there are some anticipatory responses.
We use a novel version of the Spanish administrative Social Security panel data covering 10% of
1For example, see Coile and Gruber (2007), Garcı́a-Pérez et al. (2013), Atalay and Barrett (2015), Manoli andWeber (2016), Blundell et al. (2016) and Geyer and Welteke (2021) for recent evidence on the direct effects of raising
retirement ages.
2
Individuals of certain cohorts can retire at age 61 through involuntary early retirement under certain conditions.
See Section 2 for more details on the institutional setting.

1the cohort of individuals born between 1938 and 1949 who are registered with the Social Security
system at any point in time until 2020. We compare individuals who started contributing one year
before 1 January 1967 with those who started one year after that date. Using within-cohort firstdifference regression and controlling for a broad list of fixed effects, we find that the reform delays
the age at last employment by around half a year.3 Those who contributed in 1967 are also lesslikely to claim a regular pension and more likely to claim partial and disability pensions. This
indicates that individuals have utilized other ways to leave the labour market earlier when the early
retirement schemes are not available anymore. We also show that they have a higher probabilityof not claiming any pension, driven mainly by premature mortality. More specifically, individuals
who started contributing after 1 January 1967 are 2.5 percentage points more likely to die before
claiming any pension. To test the causality of our estimates, we use placebo cut-off dates and findno significant impacts on these placebo dates both before and after 1967.
To show the impact of delaying labour market exit on mortality, we instrument the age at last
employment using the year individuals started contributing to the Social Security system. We examine the impact of age at last employment on the hazard of dying between different age brackets.
We find that delaying labour market exit by one year increases the hazard of dying between theages of 60 to 69 by 4.2 percentage points (equivalent to a relative increase of 43%). When we look
more closely, we find that the mortality responses are the strongest between ages 60 and 64, when
individuals have no longer access to regular pensions. This result indicates that the negative effectof delaying retirement on mortality is driven mainly by the immediate effect of losing access toearly retirement schemes. Furthermore, we shed some light on the possible mechanisms behindthe detrimental effect of delaying retirement on mortality. In particular, we focus on the heterogeneous effects of delaying the labour market exit by the individuals’ labour market conditions prior
to retirement. As the parameters of most jobs are multi-dimensional, we examine four dimensionsof individuals’ labour environments: the physical burden, psychosocial burden, self-value at work,and occupational skill level.
First, using registered workplace accidents at the industry level as a proxy for physical burden,
we show that the increase in mortality is stronger for those who have worked in sectors witha very high number of workplace accidents. This finding is consistent with previous literatureestablishing that physically demanding occupations lead to adverse health effects. We also findthat the mortality effect is stronger for individuals in high psychosocial burden jobs (with a highlevel of mental and social stress). We measure the psychosocial exposure in a job following the Job
Exposure Matrices constructed by Kroll (2011). Delaying labour market exit by one year increases
the hazard of dying between the ages of 60 and 69 by 5.7 percentage points for individuals in
3

We show our results are robust using several robustness tests, including regression-based tests of the differencesin covariates, and using within-age start contributing fixed effects analysis. For more details see Section 4.3.

2

high psycho-socially demanding jobs, while this number is 2.8 percentage points for those in low
psychosocially burdensome jobs. Furthermore, we measure an individual’s sense of achievement
and recognition at their last job using the Occupational Information Network data (O*NET). We
show that only individuals who work in low self-value industries are more likely to die whenfacing a one-year delay in the labour market exit. This result indicates that individuals who ‘feelrecognized’ and have a sense of achievement in their work do not experience a negative mortality
effect due to a delay in the labour market exit. Lastly, similar to previous literature, we findthat delaying labour market exit by one year increases the hazard of dying by 5.4 percentage
points for blue-collar workers, while this number is 2.7 percentage points for other workers. The
heterogeneous results suggest that advocating for different ages to exit employment, depending on
the working conditions of each individual’s occupations, can mitigate the detrimental impacts ofdelaying retirement.
Our findings imply that losing access to early retirement can decrease life expectancy. One
proposal to incentivize individuals to stay longer in the labour force without having such a negative impact on their health is to allow them to gradually reduce their working time towards theend of their careers. In Spain, some workers can access partial retirement by working part-time
while claiming a partial pension. One of the eligible conditions is to have contributed to the Social
Security system for at least for 33 years. Comparing individuals with and without access to partial retirement, we find that individuals who have no access to partial pension experience higher
mortality rates when the retirement age is delayed. This finding highlights the importance of providing the opportunity for gradual retirement, which can smooth the adverse effects of delaying
retirement.
Apart from contributing to studies on the impact of pension reforms on retirement decisions (e.g.,
Mastrobuoni (2009); Garcı́a-Gómez et al. (2012); Manoli and Weber (2016); Geyer and Welteke(2021)), our paper relates to and completes papers studying the mortality effects of retirement. The
existing well-identified empirical literature finds mixed results, and explore three types of policy
experiments: allowing earlier retirement (Coe and Lindeboom, 2008; Hernaes et al., 2013; Hallberg et al., 2015; Bloemen et al., 2017; Kuhn et al., 2020), promoting later retirement (Zulkarnain
and Rutledge, 2018; Hagen, 2018; Bozio et al., 2021) and switching to retirement at the statutory
retirement age (Fitzpatrick and Moore, 2018).
The studies of earlier retirement overall find no significant or positive impacts on mortality. For
example, Hernaes et al. (2013) find that accessing a pension two to five years earlier has no effecton the probability of dying by the ages of 67, 70, 74, and 77 for the entire population of Norway.
Looking at some particular population groups, Hallberg et al. (2015) and Bloemen et al. (2017) finda positive impact of earlier retirement. Hallberg et al. (2015) show that a five-year early access toa retirement pension reduces the mortality of male army officers in Sweden. Bloemen et al. (2017)3

find that male civil servants in the Netherlands who are entitled to claim a pension around eight
years earlier have a lower mortality rate. The only paper that finds (earlier) access to a pension
increases mortality is Kuhn et al. (2020). Using Austrian register data, they estimate the (very)
short-term impact of a three-year early access to pension on mortality. Kuhn et al. (2020) find thatearly retirement increases male deaths before the age of 67.
Evidence on the impacts of later retirement is more scarce. Our paper directly contributes to thisliterature and is the first paper that provides a precisely estimated impact of later retirement inducedby the delay of early retirement age. To the best of our knowledge, only three papers study theeffect of delayed retirement. While Hagen (2018) studies the mortality effect of a two-year increasein the statutory retirement age, they find an imprecisely measured no effect on mortality by the ageof 69.4 Bozio et al. (2021) and Saporta-Eksten et al. (2021) show precisely estimated impacts on
mortality by exploring pension reforms that change early retirement financial incentives. Bozioet al. (2021) find that delaying retirement in France has a zero effect on the probability of dying
between the ages of 61 and 79. Saporta-Eksten et al. (2021) explore an exogenous decrease in
the implicit working tax in Israel and show the impact of work on longevity. They find that later
retirement increases mortality between the ages of 75 and 85 but that it has no impact on mortality
between the ages of 65 and 74. Our paper differs from Bozio et al. (2021) and Saporta-Eksten etal. (2021), as we expect the response to pension reforms that incentivize retirement via financial
incentives to be different from reforms that shut down early retirement schemes.
Our paper is the first one to provide empirical evidence that later retirement increases mortality.
When we look at the literature on the health impacts of delayed retirement, it is not surprising tofind a negative impact of delayed retirement. Many studies on the health impacts of retirementfind adverse health effects through increased social isolation and depression (Atalay and Barrett,2014; Eibich, 2015). Studies also find a positive impact of retirement on health outcomes due tothe adoption of a healthier lifestyle (Insler, 2014; Celidoni and Rebba, 2017; Gorry et al., 2018).
Therefore, it is reasonable to expect that later retirement might increase mortality rates.
Our findings have important policy implications. First, we show a large heterogeneity in theeffect of delayed retirement on mortality, depending on the characteristics of jobs that the individuals held before retirement. Going beyond distinguishing between blue- and white-collar jobs, weshow that other job dimensions (such as physical, psycho-social, and self-value) also matter. Thisfinding implies that policies that remove access to early retirement for the general population can
exacerbate the socio-economic disparities in life expectancy.
Second, we show the option of a gradual transition to retirement matters with regard to the4

Hagen (2018) studies the mortality effect of a two-year increase in the statutory retirement age of local government
female workers in Sweden and finds that the reform had no impact on mortality and/or health care utilization. See
Section 6.1 for a more detailed comparison with the existing literature.

4

impacts of retirement on mortality. Allowing older workers to gradually reduce their working
time at the end of their careers can mitigate the adverse effects on mortality. Such mitigating
effects can be made possible by promoting gradual retirement options. The results also speak to
the recent public discussions on flexible retirement. This insight is also relevant for public policy
and budgetary considerations, particularly when policymakers in many countries face long-term
solvency challenges in both the pension and public healthcare systems.
This article proceeds as follows: Section 2 presents a brief description of the institutional settingin Spain and the 1967 pension reform. Section 3 describes the data and the empirical strategy.
Section 4 and 5 present results on the labour supply responses, plus the instrumental variable
estimates of the impact of age at last employment on mortality. We also discuss the heterogeneityand potential mechanisms that may explain the impact on mortality. We provide a discussion of
the findings in Section 6. Section 7 concludes.

2

Institutional Setting

The current old-pension system for the elderly in Spain is a pay-as-you-go system, with an averagereplacement rate of around 80% (one of the highest in the European Union). The key elementsof the existing Spanish pension system were established in 1967.5 Prior to 1967, a fixed-amountpension (SOVI) financed by employers and the state was available for low-income or disabledworkers. The SOVI pension, which was basic and insufficient, was complemented by the Mutualsocieties (Mutualidades Laborales), which were specific to each occupation/sector.
In 1967, the General Social Security Law (Ley General de Seguridad Social) unified the preexisting insurance systems into a single institution, called ‘Social Security’. In the new system,
further modified by the 1985, 1997, and the 2002 reforms,6 the statutory retirement age became
65 years of age. Initially, individuals needed a minimum of eight years of contributions to gain
access to the pension, which gradually increased to 15 years after the 1997 reform. The pension
benefits were calculated based on the average contributions during the 15 years preceding a claim.
In addition, full benefits are given to individuals with 35 contribution years. Finally, the penalty
for insufficient years of contributions is 2 percent per year.7
5

It was then further developed in the 1970s. In the last four decades, the system has experienced six importantreforms, in 1985, 1997, 2002, 2007, 2011, and 2013. See Boldrin et al. (1999), Boldrin et al. (2004) and Garcı́aGómez et al. (2012) for a detailed explanation of all the reforms of the old-age pension system in Spain.
6
Ley 24/1997, de 15 de julio, de Consolidación y Racionalización del Sistema de Seguridad Social, and Ley
35/2002, de medidas para el establecimiento de un sistema de jubilación gradual y flexible.
7
It is important to note that in many cases, the claim of a regular retirement pensions is preceded by a periodof unemployment that can last for a considerable time. To assist older workers in long unemployment spells, since
1989, those unemployed at age 52 or above who have exhausted their contributive benefits have been allowed toreceive unemployment assistance benefits until their pension-claiming age. The only prerequisite is to reach theminimum contribution years to become eligible for an old-age pension. This unemployment assistance paid 75% of

5The pension of all the individuals considered in our sample is regulated by the same pension law
and face a statutory retirement age of 65 years, with a minimum contribution period of eight years(further modified to 15 years after the 1997 reform). However, individuals from the selected cohort(1938 - 1949) who contributed before 1 January 1967,8 even by one day, maintained an indefinite
right to early retirement from the old-age pension system. These individuals could freely retire
early from age 60, though with some financial penalties.9 Around 13% of the individuals whostarted contributing in 1966 claimed a regular pension at the age of 60.
On the other hand, individuals from the selected cohorts (1938 - 1949) who contributed after
1 January 1967 faced a statutory retirement age of 65. They can now only retire early under the
involuntary early retirement scheme, set in the 2001 law, which allows individuals to retire as
early as age 61 (again with some financial penalties, between 6 and 8 percent, depending on theyears of contribution, per year of advancement) under certain conditions. These individuals needto have been unemployed (involuntarily) for at least six months and have contributed to the Social
Security system for at least 30 years. Due to these stringent requirements, a very small proportionof workers have taken up this involuntary early retirement option.
Because the law was published on 30 December 1966, there is little room left to manipulate thedate of the first social security contribution. This feature therefore allows us to compare individuals
who started contributing before and after 1 January 1967. As we can see in Figure 1, individuals
who contributed before 1967 (independently of their birth year) could voluntarily retire early at
the age of 60. For those who contributed after 1967, the only other way to receive early retirement
was to claim involuntary early retirement at the age of 61; otherwise, the earliest an individual canvoluntarily claim a pension is at the age of 65. Therefore, we expect that individuals who started
contributing after 1967 to increase their retirement age considerably.
In addition to the regular retirement pathway, there are two alternative pathways: permanent
disability and partial retirement pensions. Permanent disability benefits have been used extensively
in Spain as an early retirement mechanism (Boldrin et al., 1999; Garcı́a-Gómez et al., 2012). This
option has thus prompted several reforms since 1985 that have tightened the eligibility criteria inorder to maintain a steady level of applications into the disability system henceforth. Nevertheless,disability insurance is an important way by which to exit the labour market. Additionally, from2002, partial retirement options became available, allowing the combination of income from workwith old-age pension benefits. The partial retirement option enables individuals aged 60 years andthe minimum wage. Moreover, a reform in 2002 also created the possibility of combining unemployment insurance
claims with labour earnings. Older workers could receive 50% of their unemployment insurance entitlement and work
simultaneously, with the employer paying the remaining wages.
8
The January 1967 deadline was set at a later date for workers in specific sectors, such as construction, mining,fishing, and the railway. We control for these specific deadlines for workers in these sectors.
9
The penalty for early retirement is 8 percent per year of early claim. After the 2001 reform, the yearly penalty forearly retirement was reduced (up to 6 percent per year) as a function of the years contributed.

6

older, with at least 33 years of contribution and six years of tenure in the same company, to claim
85% pension while working 15% of the time (up to 75% of benefits after the 2011 reform). The
partial retirement option requires the firm’s agreement because the worker must be replaced witha new employee. In this paper, we investigate the impact of the reform on the age of the individual
when claiming disability, partial and regular retirement pensions, and the probabilities of choosing
these alternative exit routes from the labour market.

3

Data and Empirical Strategy

3.1

Data and Sample

This paper uses novel administrative data of an extended sample from the Continuous Sampleof Working Histories (Muestra Continua de Vidas Laborales (MCVL)) provided by the Spanish
Social Security system. The dataset contains a 10% random sample of individuals born between
1938 and 1949 who have registered with the Social Security (such as contributive workers andpensioners) at any point of their lives up until 2020.10
Therefore, we use a non-publicly available version of the MCVL provided by the Spanish Social
Security system, which allows us to observe contributive workers and pensioners prior to 2005 (thestarting time of the publicly available version). This data advantage makes it possible to explore
a representative sample of workers affiliated with the Spanish Social Security at any point in theirworking lives and examine their mortality responses.
The MCVL includes time-invariant information, such as gender, birth month, and birth year. It
also contains detailed labour market biographies from the date individuals started contributing to
the Social Security system, up until their death.11 Moreover, we observe their employment andunemployment spells, occupations, industry, and monthly contributions. The pension records from
the MCVL contain accurate information on an individual’s age at the time of claiming a pension,pension benefits, the type of pension they receive at each point in time, and the total number ofcontributive years before retirement. When individuals exit from the dataset due to death, weobserve the exact date of their death, which helps us measure mortality accurately.
Our sample covers Spanish individuals born between 1938 and 1949 who started contributing
to the Social Security system 12 months before and after 1 January 1967. We further restrict oursample to individuals still contributing at the age of 50, with at least eight years of contribution.
10Note the different sampling criteria our sample has with respect to the publicly available version of the MCVL
(see Garcia-Perez (2008)).
11
Note that the date that individuals started contributing to the Social Security system coincides with the date at
which they started their first formal job. It is important to emphasize that, for some individuals, this date does notcorrespond to the date they started working (for example, for those who switch from the informal sector to the formal
sector).

7

We drop 20% of observations with this restriction. In Table A1, we verify that our sample is notselected. First, we check if the reform has impacted the probability of not being in the main sample
due to either having stopped contributing to the Social Security system before the age of 50 or to
not having at least eight years of contribution. We find no significant differences. Moreover, we
also show no significant mortality differences among individuals not included in the main sample.
The final sample contains 25,903 individuals, of whom 27% are female.
To identify the treatment status, we need information about the exact date individuals started
contributing. One caveat of the dataset is that the exact date of the first contribution is poorly
recorded for some individuals, especially those who started contributing around 1967. We partiallycorrect this measure by using the number of contribution years, which are better documented, as
this information is used to calculate the pension benefit.12 Figure A1 in the Appendix shows
the distribution of years the individuals in our sample started contributing, before and after the
adjustment. This limitation is the reason we cannot use a Regression Discontinuity Design. In
Table A13 in the Appendix, we perform a robustness check for our main results using instead thereported date without making any correction and show that the results are similar.

3.2

Empirical Strategy

Estimating the causal effect of the retirement age on mortality is difficult because many unobserved factors can influence both retirement age and mortality. To deal with the endogeneity inretirement behaviour, we exploit an exogenous variation in retirement age provided by the 1967
Spanish pension reform. We first provide causal estimates of the reform on retirement outcomesusing a within-cohort OLS regression with a list of fixed effects and controls. We then use an
instrumental variable (IV) approach to estimate the causal impact of age at last employment on
mortality.
Within-cohort OLS Strategy
First, we estimate the following equation, where T reatedit is a dummy that takes the value of
one for individuals who started contributing to the Social Security system in 1967 and zero for
those that started contributing in 1966. The treated group can claim regular pensions voluntarily atage 65 (involuntarily at 61), while the control group can claim them as early as 60 years of age.
Ricmt =

0 +

1 c +

2 µm +

12

3 T reatedit +Xicmt + Uicmt(1)

To correct the reported date of the first contribution, we subtract the total number of years contributed from theyear they claim a regular pension. If the corrected year of starting contributions is before the reported date of the firstcontribution, we make this correction. This correction is only possible for individuals who have claimed a regularpension, as only for them is the total number of years contributed reported.

8

Ricmt represents the outcome variable of individual i born in year c and month m who started
contributing in year t (1966 or 1967). The outcome variables include the age at last employment,
the probability, and the age at which individuals claim the different pensions and pension benefits.
c is the year of birth, and µm is the month of birth fixed effects. 3 measures the average treatment
effect of the reform on the different outcomes.
Ximct includes a list of fixed effects, such as highest level of occupation and industry sector
between the ages of 30 and 40, and a list of other predetermined covariates, including individuals’
mean monthly contribution to the Social Security system, the fraction of days active and employed,
and the fraction of time self-employed between the ages of 30 and 40. We cluster the standard
errors at the birth year level and report the wild-bootstrap p-values in brackets in all tables.
The estimates from Equation 1 provide us with the reform’s reduced-form effects, plus the firststage estimates for the IV regression.
Instrumental Variable Strategy
The causal effect of age at last employment on mortality is estimated by the following equation,[
where age at last employment (Ricmt ) is replaced by the predicted value (Ricmt ) from Equation 1:[
Micmt = ↵0 + ↵1 c + ↵2 µm + ↵3 R
icmt + Xicmt + Uicmt(2)

Micmt represents the probability of dying of individual i born in year c and month m that started
contributing in the year t. We also include the same list of controls used in Equation 1 ( c , µm and
Xicmt ). Additionally, we control for the individuals’ proxy of their mean pension benefit.13 The
coefficient ↵3 captures the local average treatment effect of age at last employment on mortality
among individuals who delayed their retirement because they were not able to claim a regular pension at age 60 (compliers). In Section 5, we discuss who the compliers are in our estimation.
Assumptions
The critical assumption for the treatment status to be a valid instrument for access to early retirement is that the year individuals started contributing to the Social Security system is independentof unobserved characteristics that affect the age at last employment and mortality. The following
steps support the validity of our instrument.
First, we restrict our sample to those who started contributing in 1966 and 1967. The treated13

We do not have information on pension benefits for individuals who have never claimed a pension of any kind.
Therefore, for all individuals in our sample, we construct a proxy of the mean pension benefit using monthly contributions and years of contribution (or years of employment and unemployment) using the Social Security formula tocalculate pension benefits. The correlation between this proxy and the actual mean pension benefit is 0.93 for individuals who claim a regular pension, indicating that it is a good proxy. Moreover, in Table A9, we show the effect of thereform on this proxy.

9and control group individuals had similar labour market conditions when they began working:they were born in the same year and started working only one year apart. Second, we include
their highest occupation, industry, birth year, and month of birth fixed effects, which allows us toestimate variations within occupation, industry, and birth year.
Furthermore, we check whether the characteristics of the treated and control groups are similar
when they are between 30 and 40 years old.14 Table A2 shows the impact of the treatment on
a list of predetermined variables, including the fraction of time spent in employment, activity,and self-employment between the ages of 30 and 40; the probability of working in a blue-collar
occupation and industry sectors; and average monthly contributions between the ages of 30 and
40. The estimates are obtained from estimating Equation 1. Except for the fraction of time spent
in self-employment, there are no significant impacts.15 This suggests that there is no manipulationof the treatment status and that our control and treatment groups are very similar.
To further establish causality of the first stage estimates, we perform placebo tests using otheryears to define treatment status and a robustness test using age at first contribution fixed effectinstead of birth month fixed effects. These tests rule out the possibility that other confounding
factors drive our reduced-form estimates. For more details, see Section 4.
To fulfil the exclusion restriction, we need to ensure that the treatment status only affects mortality through its impact on age at last employment. The only possible alternative channels throughwhich the year individuals started contributing can affect mortality are changes in labour market
outcomes close to retirement and changes in pension benefits. We always control for the proxy ofthe mean of the pension base to wash out any possible income effect. In Table A16, we also showthat controlling for the labour market decisions before retirement (between 45 and 55 years of age)does not affect our IV estimates.
Finally, the monotonicity assumption requires that contributing to the Social Security system in1967 instead of 1966 would not lead to earlier retirement. The monotonicity assumption is alsosatisfied in our context because the treated individuals do not have the option to retire as early as
60 years of age.

14

Ideally, we would like to check whether the characteristics of individuals in the treatment and control groups differ
at the beginning of their career (before the age of 30). However, the data quality was not particularly good when our
individuals were that young so the labour market characteristics during the first years of their career might be wrongly
recorded for some individuals. We, therefore, look at their characteristics between the ages of 30 and 40.
15
In Table A12, we show that the effect of the reform on our main outcomes is robust to excluding from our sample
individuals in one of the self-employed pension regimes.

10

4

The Reform Effect on Retirement Outcomes

4.1

Descriptive Evidence

Table A3 provides summary statistics for the main outcomes used in our analysis. There are threedifferent pensions that individuals can claim. Table A3 shows that 47% of individuals claim aregular pension (old-age pension), while 33% claim a disability pension, and 4% of individuals
choose a partial pension. Some individuals in our sample never claim any pension due to reasons
such as a period of prolonged inactivity (⇠ 6%), dying before a claim can be made (⇠ 8%), andstill being active in the labour market in 2020 (⇠ 0.3%). Figure A2 compares the share of different
types of pensions by treatment status. Compared with those who started contributing in 1966
(control, light green bars), individuals who started contributing in 1967 (treated, darker green bars)
have a lower likelihood of claiming a regular pension and are more likely to claim a disability
pension, a partial pension, or claim no pension.
On average, individuals leave the labour market at 59.6 years old and claim regular pensions
at 63.6 years of age. Figure 2 shows the age distribution at last employment for individuals whostarted contributing in 1966 and 1967. As expected, we see a distinct difference. Figure 2 showsthat around 8% of individuals who started contributing in 1966 (control group, solid red line) leave
the labour market at the age of 60, while this percentage is almost zero for those individuals thatstarted contributing in 1967 (treated group, green dashed line). More than 22% of the treatedindividuals exit the labour market at the age of 65, while this number is only 17% for the control
group. We see the same pattern regarding the age of claiming a regular pension. Figure 3 a) showsthat 28% of individuals who started contributing in 1966 (control group, solid red line) claim aregular pension at the age of 60, and 32% of them claim at the age of 65. We also see someclaims at the ages of 61 to 64. However, for those individuals who started contributing in 1967
(treated group, green dashed line), almost no one claims a regular pension at any age other than 65
years, whilst almost 70% claim a regular pension at 65 years of age. These figures provide visualevidence that the reform is binding, and that individuals affected by it delayed their retirement.
In our sample, individuals, on average, claim a disability pension at the age of 57 and a partial
pension at 61 years of age. Figure 3 b) and Figure 3 c) show that the distribution of these ages bytreatment status. We observe that individuals who started contributing in 1967 (green dashed line)
claim more disability insurance between the ages of 60 and 65 than those who started contributing
in 1966. Moreover, individuals who started contributing in 1967 (green dashed line) claimed partial
pensions at slightly earlier ages.
Finally, regarding the mortality measure, conditional on being alive at the age of 50, 32% of
our sample died between the ages of 50 and 86. The hazard rate of dying between the ages of 50
and 59 years and the hazard rate of dying between the ages of 80 and 86 are low, at 7% and 2%,
11respectively. The highest mortality occurs between 60 and 79 years of age. The hazard of dying
between the ages of 60 and 69 is 11%, and the hazard of dying between the ages of 70 and 79 is
16%.

4.2

Regression Results

Table 1 examines the impact of the reform on the different types of pensions that individuals haveclaimed. We find that individuals who started contributing to the Social Security in 1967 are lesslikely to claim a regular pension by 10 percentage points (⇠ 19%), yet their probability of claiming a disability insurance increases by 5.8 percentage points (⇠ 19%). In Table A4, we further
show that the reform equally impacted the probability of claiming a severe or absolute disability
and a partial or professional disability pension (by a 3.1 and 2.7 percentage point increase, respectively).16 They are also 1.9 percentage points (⇠ 54 %) more likely to claim a partial pension.
These results indicate that individuals did not fully comply with the rise in statutory retirement
age and have utilized other ways to leave the labour market before claiming a regular pension, byeither claiming disability insurance or a partial pension.
We also observe that individuals contributing to the pension system in 1967 are 2.5 percentage
points (⇠ 18 %) more likely to leave the labour market without any pension. In Table A5 in the
Appendix, we further explore three reasons why individuals might not claim any pension: first,
they were still working in 2020; second, they became inactive; third, they died before claiming
any pension. Table A5 indicates that the reform has only a minimal impact (an increase of 0.2
percentage points) on the probability of continuing to work up until 2020 and has no impact at allon the probability of becoming inactive. Interestingly, individuals who started contributing in 1967
have a 1.6 percentage point (⇠ 22%) higher probability of dying before claiming any pension. Thisfinding implies that premature death is the main driver for not claiming any pension. We further
explore this effect in Section 5.
Table 2 examines the impact of the reform on the ages at which individuals leave the labour
market and claim different types of pensions. The 1967 reform resulted in the treated individuals
delaying their labour market exit by almost half a year17 and delaying claiming their first pension
16

There are four types of disability pensions. First, partial disability pensions are for individuals who have seen theirfunctional capacity reduced by at least 33 percent. These individuals can continue working, even in the same jobs they
had before applying for the pension. Second, professional disability is assigned to those workers who cannot resume
their work activity but could carry out a different occupation. Third, absolute pensions are thought for individuals who
cannot carry out any type of work due to physical or mental deterioration. Finally, severe disability occurs when theworker needs the support of another person to carry out their daily subsistence tasks.
17
Table A6 in the Appendix shows the reform’s effect on the probability of exiting the labour market in different
age brackets. The reform decreases the probability of leaving the labour market between the ages of 55 to 63. As
expected, the reform most significantly decreased the most the probability of exiting the labour market at 60 (by 4.1
percentage points or 37%). Individuals who started contributing in 1967 also have a higher probability of exiting the12(regardless of the type) by 0.28 years (four months). We find that early retirement is reduced by
1 year and four months for individuals who claim a regular pension.18 The ages at claiming adisability pension and a partial pension are also affected. Individuals who contributed after 1967
delay claiming disability by around four months but anticipate claiming a partial pension by around
two months. Table A8 in the Appendix shows that the reform significantly increased the probabilityof claiming a disability pension between the ages of 60 and 65 only. This result suggests that
individuals affected by the reform use disability pensions as an early retirement scheme between
the ages of 60 and 65, ages at which these individuals would have been able to retire with a regularpension if they had contributed in 1966. Moreover, it also indicates that the reform does not capture
differential ex-ante health conditions of individuals. If this were the case, the reform should havesignificantly increased disability pensions before the age of 60.
In Table 3, we examine the reform impact on the pension benefit amount. We expect the pension
benefits to be affected because the reform incentivizes individuals to work longer (as shown in Table 2), which increases the pension base and decreases the penalty for early retirement. Moreover,as more individuals claim disability insurance due to the reform, we expect the overall pension
benefits to be lower as disability pension benefits are typically less generous. We find that the total
pension benefit of individuals who started contributing in 1967 increased by 43e (⇠ 4%). The
increase in the pension benefit is driven by an increment in the base pension (without any financial
adjustments) of 19e (⇠ 1.6%) and an increase in the pension adjustment (due to later claiming) of
5 percentage points (⇠ 6%).19

4.3

Robustness and Placebo Tests

In this section, we perform several robustness checks on the reduced form effects of the reform.
Moreover, we test the causality of our estimates by using placebo cut-off dates from both before
and after 1967.
labour market after the age of 64. Again, the reform most significantly increased the probability of exiting the labour
market at the age of 65 (by 7 percentage points or 42%).
18
We observe in Table A7 that the reform decreased by 10 percentage points (⇠ 67 %) the probability of claiming
a regular pension at age 60 and between 2 and 3 percentage points (⇠ 48 % to 76%) the probability of claiming it
between the ages of 61 and 64. On the other hand, the reform increased the probability of claiming a regular pension
at age 65 by 9.5 percentage points (⇠ 50 %) and 3.6 percentage points after the age of 65 (⇠ 32 %).
19
It is important to note that the positive effects on pension benefits that we observe for all the sample whereindividuals claimed any pension is driven mainly by those individuals who claimed a regular pension, as Table A9shows. In particular, individuals who claimed a regular pension and started contributing in 1967 received, on average,
73e higher monthly pension benefit, which is driven by an increase of 31e of the pension base and an 8.5 percentage
point in the pension adjustments. We can also observe that the mean monthly pension benefit decreases by 26e for
affected individuals claiming a disability pension, while partial pension benefits are not significantly affected by thereform.

13

Within-Age at First Contribution Fixed Effects Model
The baseline analysis compares individuals born in the same year (along with their highest occupation level and industry sector fixed effects), who started contributing to the system one year apart(1966 vs. 1967). One potential confounding factor of this specification is the age at which individuals started contributing. These individuals were born in the same year but started contributing in
1966 and 1967 and were at different ages when they started contributing. One reason for startingat different ages could be differences in educational attainment. Unfortunately, we do not haveinformation on the education level of individuals in our database. Therefore, to test that the reform
is not capturing differences in educational attainment, we use age at first contribution fixed effectinstead of birth year fixed effects in Table A10. This robustness check estimates the impact oflosing access to early retirement for individuals who start working at the same age but were born
one year apart. These estimates should be similar to the main estimates unless the different startingage is a confounding factor. Compared with the baseline results in Tables 1 and 2, the magnitudesof the estimates in Table A10 are very similar.
Cohorts Born between 1941 and 1949
In the baseline sample, we consider individuals born between 1939 and 1949. A law in 2002
introduced the possibility of retiring early via the involuntary pathway. As a result, cohorts bornfrom 1938 to 1940 can claim a pension at the ages of 64, 63, and 62, respectively, while cohorts
born after 1941 can claim at the age of 61 (see Figure 1).
Therefore, we perform a robustness check, dropping the cohorts that were only partially affectedby the law of 2002. Table A11 reports the main reduced form results for the cohorts born between
1941 and 1949. If we compare them with the baseline results in Tables 1 and 2, we can see that themagnitude of the estimates is quite similar. These results demonstrate that our reduced form effects
are not driven by the older cohort of individuals with later access to involuntary early retirement.
Dropping Self-Employed Individuals
Table A2 shows the impact of the treatment on a list of labour market variables when the individuals
were between 30 and 40 years old. Except for the fraction of time spent in self-employment, we
do not find significant impacts, suggesting that there is no manipulation of the treatment status.
A potential reason for finding significant effects on individuals’ fraction of time spent in selfemployment is that self-employed individuals might have more flexibility in deciding when theywant to start contributing to the Social Security system. In this robustness check, we want to ensurethat our main baseline results are not driven by these individuals.
Therefore, we perform a robustness check dropping those individuals who received a pension
under the self-employed regime ( see Table A.14). If we compare them with the baseline results in
14

Tables 1 and 2, we can see that the magnitude of the estimates is quite similar, indicating that ourbaseline reduced form effects are not driven by those individuals who were self-employed.
No Correction for the Starting Year of Contribution
As mentioned earlier, one caveat of the Spanish administrative Social Security database that weare using is that the exact date of the first contribution is poorly recorded for some individuals,
especially those who started contributing around 1967. In fact, Figure A1 a) in the Appendix
shows that in the distribution of the start year of contribution, there is some bunching around
1965, 1966, and 1967. Fortunately, we have excellent information for many individuals about the
number of years of contribution and the exact date they claimed a pension. Therefore, we correct
the reported date of the first contribution by subtracting the total number of years of contribution
from the date they claimed a pension for those who reported having started contributing in 1965,
1966, and 1967. If the corrected year of starting contributions is before the reported date of thefirst contribution, we make this correction. Figure A1 b) shows how the distribution of the starting
year of contribution looks after we make this correction, and we see that the bunching has been
dramatically reduced.
In Table A13, we perform a robustness check for our main reduced form results using the reported date of starting contributions without making any correction. We show that, if anything,
the results are slightly stronger than in our main specification. First, individuals in the uncorrected
sample seem to react more to the reform by using different ways to leave the labour market before
claiming a regular pension. The reform increased by 7.5 percentage points (instead of 1.9) the
probability that the individuals claimed a partial pension, and by almost the same amount (7.4 percentage points instead of 5.8) the probability of claiming a disability pension. They also delayedleaving the labour market by 0.67 years instead of 0.4 years and by 1.43 years instead of 1.31 years
for individuals who claimed a regular pension.
Placebos
A concern for causality is that our results could be potentially biased by unobserved characteristics
that affect both the date of starting contributions and labour supply decisions. To test this possibility, we perform several placebo tests where we assign placebo treatment status to the individuals
using other dates at first contribution. Figure 4 plots the estimated coefficients of the different
placebos, where the treatment is defined as having started making contributions the year after the
one indicated in the y-axis (from 1959 to 1976).20 The placebo estimates are labelled in black,20

We do not perform the placebo test on years that are too close to the actual treatment years (1965, 1966, and 1968),
given that the start year of contribution is not well defined around that time, and we use the years of contribution tocorrect for it.

15while our baseline estimates are labelled in red. We can see that almost all placebo estimates areclose to zero. This suggests that the estimated changes in our baseline analysis result from theexogenous increase in early retirement age rather than from other confounding factors.

5

Right to Retire Early and Mortality

5.1

The Effect of Age at Last Employment on Mortality

In this section, we examine the impact of retiring later in life on mortality using the instrumental
variable method. Table 4 reports the effects of age at last employment on mortality at different
age brackets (conditional on having survived until that age). Panel 1 reports the simple OLS estimation where we regress age at last employment over mortality. For all our estimations, delaying
retirement is negatively and significantly correlated with mortality. This correlation likely captures
the fact that less healthy workers tend to retire early. Panel 2 shows the reduced form effect of
the reform on mortality. We find that individuals who contributed in 1967 have a 3 percentage
point (⇠ 10%) higher probability of dying between the ages of 50 and 86. When we examine thereform’s impact on mortality at different age brackets, we observe that the increase in mortality
is concentrated between the ages of 60 and 69. In particular, individuals who contributed in 1967
die between those ages (that is, ages 60 and 69) with a 2.1 percentage points higher probability(⇠ 22%). We also find a minor increase in mortality after 80 (0.4 percentage points). Figure 5
shows that all the placebo estimates for overall mortality after the age of 50 and between the agesof 60 and 69 are insignificant and close to zero. This confirms that our reduced-form estimates
result from the exogenous increase in early retirement age due to the reform rather than from otherconfounding factors.
The IV estimates in Panel 3 of Table 4 indicate that delaying the age at last employment by one
year increases the probability of dying between the ages of 50 and 86 by 7.4 percentage points (⇠24%), 4.2 percentage points (⇠ 43%) between the ages of 60 and 69, and 0.6 percentage points(⇠ 26%) after 80. In Table A14, we also report the effect of age at last employment on mortality
in five-year age brackets. We observe that the mortality responses are the strongest between ages
when public pensions are not accessible (between the ages of 60 and 64). Delaying leaving thelabour market by one year increases mortality in that age bracket by 3.8 percentage points (⇠67%). This result indicates that the negative effect of delaying retirement on mortality is driven
mainly by the short-term effect of losing access to early retirement schemes.
In Column 6 of Table 4, we also examine the effect of delaying retirement on age at death (inyears). This measure will capture both the extensive margin (the effect of delaying retirement on
premature death) and the intensive margin (the length of life). We censor the age of death at 71
16

years old for those individuals still alive at that age (as the younger cohort, born in 1949, are 71
years old at the end of our database in 2020). We find that delaying the age at last employment by
one year reduces individuals’ age at death by 0.75 years.
It is important to note that the F-statistic of the first stage regression for all our IV estimates inTable 4 are above the rule-of-thumb threshold of 10. Our instrument (the year individuals started
contributing) is relevant and correlated with the endogenous variable we are instrumenting (age atlast employment).
When we compare the OLS results with the IV estimates, we can see that the IV strategy does agood job controlling for the negative bias present in the correlation between age of last employment
and mortality. Moreover, compared with the reduced-form estimates, the IV results are more thandouble. This is consistent with the almost half a year increase in age at last employment (asestimated in Table 2). In addition, the IV estimates control for other effects of the reform that could
potentially impact mortality through different channels. In particular, in the IV strategy, we control
for the positive effect of the reform on pension income. As we do not have information about thepotential pension benefits for those individuals who never claimed any pension, we control for a
proxy of the monthly pension base. We constructed this proxy using the individual’s history ofmonthly contributions and the formula used by the Social Security system to calculate the pension
base.21 Another potential channel through which the reform could be affecting mortality is thelabour market outcomes of individuals before retirement (between the ages of 45 and 55).22 Table
A16 shows the IV estimates of the effect of age at last employment on mortality between the agesof 60 and 69 with different control variables. We observe that adding the labour market outcomesof individuals before retirement as controls in the IV estimation does not change the estimates toany great extent. Thus, our baseline IV estimations will only control for the proxy of the pension
base.
Finally, it is important to understand who the compliers are. In our specification, the compliers
are those individuals who, before the reform, when they had the chance, claimed a regular pension early at the age of 60. Table A17 compares the labour market conditions at the end of theworking careers of compliers and non-compliers.23 Not surprisingly, compliers have less attach21

The correlation between this proxy and the actual mean pension base is 0.9 for the whole sample and 0.93 forindividuals who claim a regular pension, indicating that it is a good proxy. Moreover, in Table 3, we show that thereform impacted this proxy similarly to the actual pension base.
22
Table A15 shows that the reform had an impact on the labour market outcomes of individuals between the agesof 45 and 55. We observe that individuals that started contributing in 1967 spent 1.85 percent more time employedduring these years, while they spent 0.67 percent less time self-employed. We also find that the individuals affectedby the reform have a 1.5 percentage point higher probability of having a blue-collar occupation. They also have a 1.9
percentage point lower probability of working in the trade or transportation sector, 2.7 percentage points of working in
the public, health, or education sectors, and 0.8 percentage points of working in the services, hotel, and housekeeping
sectors.
23
For this comparison, we only consider individuals who were not affected by the reform (who started contributing

17

ment to the labour market at the end of their working career (between the ages of 45 and 55),
have a lower probability of employment in a white-collar occupation, and work in industries withmore workplace accident incidences and higher psychosocially burdensome environment. This result suggests that, before the reform, those claiming retirement earlier worked in occupations andsectors with a higher health burden.

5.2

Mechanisms

This section attempts to shed light on some of the potential mechanisms explaining why losing
access to early retirement increases mortality. We focus on two types of heterogeneities: labour
market conditions before retirement and the possibility of flexible retirement.
Labour Market Conditions Prior to Retirement
Delaying retirement can have very different effects on an individual’s life expectancy, dependingon the working conditions experienced by the individuals during their last years of employment(Mazzonna and Peracchi, 2017).24 In this paper, we acknowledge that the burden of a job may
be multi-dimensional, and we examine four characteristics of the individuals’ labour environment
before retirement: first, physical burden; second, psychosocial burden; third, self-value at work;and last, the skill level of their last occupation before retirement. Table 5 reports the heterogeneity
results for the probability of dying between the ages of 60 and 69 (conditional on surviving toage 60)25 by all four measures. In the first panel, we report the reform’s effect on the age at last
employment for each subgroup, which will be the first stage of the IV estimation. In the second
and third panels, we report the effect of delaying retirement on mortality between the ages of 60
and 69. First, we report the reduced-form effect of the reform and then the IV estimates, which
capture the effect of delaying by one year the exit of the labour market on mortality.
to the Social Security in 1966). The difference between the two groups of individuals is estimated by running a
regression on a dummy variable for compliers while controlling for gender, month, and year of birth fixed effects.
24
One of the reasons we expect to see heterogeneity in mortality by labour market conditions is because harsher
working conditions are more likely to trigger mortality due to specific causes, which are predominant during the agesof 60 to 69. For instance, the medical literature has long established that circulatory system diseases can often becorrelated to work-related stress (Kivimäki et al., 2002). In fact, both Bloemen et al. (2017) and Hallberg et al. (2015)
report that retirement reduces the risk of heart-related mortality. For the cohort considered in our sample, circulatory
diseases are the second cause of mortality (after tumours) between the ages of 60 and 69. Moreover, the third cause of
mortality for our cohort of individuals is due to respiratory diseases. Important risks for respiratory conditions include
smoking and lack of physical activity (Godtfredsen et al., 2008; Lee et al., 1999). Both factors can be affected byworking status and, ultimately, retirement (Falba et al., 2005; Black et al., 2015; Evenson et al., 2002; Barnett et al.,2014). Fitzpatrick and Moore (2018) find that mortality due to two lung-related conditions (COPD and lung cancer)
statistically increases immediately after retirement at the age of 62.
25
As the reform has no impact on the probability of dying before age 60, the sample used in this regression is notselected.

18

Physical and Psychosocial Burden
Retirement enables individuals to enjoy more leisure time and eliminates work-related stressand exposure to job-specific accidents, potentially positively impacting individuals’ mental andphysical health, and their wellbeing. Thus, retirement may be particularly beneficial for those whowork in strenuous occupations, either physically or mentally. Indeed, labour unions have used thisargument heavily in their opposition to increases in the statutory retirement age. Therefore, we firstclassify individuals’ last industry depending on their physical and psychosocial burden in order toanalyse if the adverse effects of delaying retirement on mortality differ by these characteristics.
Previous literature has already established that physically demanding occupations lead to adverse
health effects (see Case et al. (2005) and Ravesteijn et al. (2013) for a summary). To measurephysical burden at work, we use the Spanish Register of Workplace Accidents between 2003 and2019, which has information on the total number of workplace accidents that individuals in our
sample (cohorts born between 1938 and 1949) experience in different industry sectors. Figure A3
shows the distribution of industry sectors depending on their incidence of workplace accidents.
We link individuals’ last industry to this aggregate industry-level data and divide our sample by
the median of the workplace incidence. After this division, the manufacturing, energy, water,
sanitation, and construction sectors are considered to have a high incidence of workplace accidents,
and the rest are included in the low incidence group.
Columns 1 and 2 of Table 5 show that the increase in mortality seems stronger for those individuals who worked in sectors with a higher incidence of workplace accidents before retirement.
Delaying the age at last employment by one year increases the probability of dying between theages of 60 and 69 by 6.8 percentage points (⇠ 57%) in sectors with a high incidence of workplace
accidents. At the same time, the effect is only 2.5 percentage points in sectors with a low incidenceof workplace accidents. However, the p-value of the difference between these two groups is 0.13.
We further divide our sample into three groups (see Table A18) and find that the impact of delaying
retirement is significantly different between the highest and lowest groups. In particular, we findno effect on mortality for individuals working in sectors with a very low incidence of workplace
accidents, while mortality increases by 6.8 percentage points for those in sectors with a very highincidence of workplace accidents. This heterogeneity confirms that individuals in more physicallydemanding jobs will benefit the most from having access to early retirement.
Next, we examine the heterogeneity effect of delaying retirement on mortality by the mental andsocial stress that individuals have experienced before retirement. Unfortunately, we do not havea good measure of occupations or industries by this measure for the Spanish context. Thus, wemeasure psycho-social exposure by adopting occupational indexes based on the Job Exposure Matrices constructed by Kroll (2011) using a large-scale representative survey of working conditionsof approximately 20,000 employees in Germany. In particular, we use their measure of ‘psycho19

social burden’, which is based on mental stress, social stress, and temporal loads. Figure A4 showsa distribution of industry sectors by this psychosocial exposure index. We link individuals’ lastindustry with this aggregate occupation-level data26 and divide our sample by the median of thisindex.
Columns 3 and 4 of Table 5 report that a delay of one year increases the probability of dying by
5.7 percentage points (⇠ 50%) for individuals with occupations in industries with a high psychosocial burden. In contrast, the increase is smaller (2.8 percentage points) for those with occupationsin industries with fewer psychosocial burderns. Again, in Table A18, we show that the impact on
the highest and lowest groups are statistically different. These results imply that losing the right toretire early can lead to the death of individuals who were not only in physically demanding jobs
but who also had a high exposure to psychosocial burdens in their workplace.
Self-value at Work
Previous literature has pointed out that retirement can negatively impact individuals’ wellbeing,as they often lose the social network of their co-workers and may feel less valuable to society(Szinovacz et al., 1992). Therefore, we want to test this hypothesis by looking at the heterogeneous
effect of delaying retirement on mortality based on how and whether individuals felt useful in theirjob before retirement.
As we do not have a good proxy of usefulness at work in the Spanish context, we utilize the
Occupational Information Network (O*NET) collected by the US Department of Labor. We use
the work value classification to measure self-value at the workplace, which includes two elements:
a sense of achievement and recognition within the workplace. Figure A5 shows the distribution ofindustry sectors by this self-value index. In our sample, we link individuals’ last industry with thisaggregate occupational-level data,27 and divide the sample by the index’s median.
In columns 5 and 6 of Table 5, we find strong evidence that the mortality effects between theages of 60 and 69 are driven by individuals working in low self-value industries. Delaying thelabour market exit by one year increases the probability of dying between the ages of 60 and 69
by 6.4 percentage points (⇠ 60%) for individuals working in these sectors, while the impact issmall and insignificant for individuals working in sectors with high self-value. The impacts onthese two subgroups are statistically different. Therefore, this result indicates that individuals who
26

The psychosocial burden occupational index elaborated by Kroll (2011) is linked to individuals’ last industry
following these steps. First, we group all the industries defined in CNAE09 into 21 different groups. Using the Labour
Force Survey of 2011, we observe which occupations (defined by CNO11) are most often performed in each of the 21
industries groups and with what frequency. Finally, we link the psychosocial index with each industry depending on
which occupations are usually performed within each industry, using the frequencies as weights to calculate the mean
psychosocial burden in each sector.
27
We link the occupational index of self-value with individuals’ last industry following the same steps as for thepsychosocial burden index.

20

feel a sense of achievement and recognition within their workplace do not experience a negative
mortality effect due to a delay in their exit from the labour market.
Skill Level
Finally, previous literature has relied heavily on heterogeneity differentiating between blue- andwhite-collar jobs, typically based on each occupation’s assumed skill level (Coe et al., 2012). Following this previous literature, we also look at the differential effect of age at last employment
on mortality for individuals working in white- and blue-collar occupations in columns 7 and 8 ofTable 5. Contrary to Mazzonna and Peracchi (2017), we find this heterogeneity very similar to thatbased on the physical burden. Delaying retirement by one year increases the probability of dying
between the ages of 60 and 69 by 5.4 percentage points (⇠ 68%) for individuals with a blue-collar
job, while it is 2.7 percentage points for the rest. Even though this difference in results is notstatistically different, it indicates that, in this context, skills capture differences in physical burden
across occupations.
Possibility of Gradual Retirement
Reducing the possibility of early retirement, as examined here, appears to be a good strategy tocope with an aging population, as it prolongs the working careers of older workers. However, wehave shown that this type of policy leads to serious adverse effects on individuals’ life expectancy.
A potential solution to incentivize workers to stay longer in the labour force without negatively
impacting their health is to allow these workers to gradually reduce their working time at the endof their careers.
As already explained in Section 2, from 2002, the Spanish pension system introduced the possibility of individuals partially retiring after the age of 60, allowing them to combine income fromwork with old-age pension benefits. They were allowed to claim up to 85% of their pension while
reducing employment time from 85% to 15% of the original contract. However, this option, whichis also subject to the agreement of the firm, was only available for workers with at least 33 yearsof contribution and six years of tenure in the same company.
In this section, we analyse whether having the option to claim a partial pension can mitigate thenegative impact of delaying the age at which individuals leave the labour market on mortality. As
we observe that the reform affected the probability of individuals claiming a partial pension, we
cannot simply directly look at the mortality effect of those individuals who chose this retirement
scheme. Therefore, we take advantage of the fact that only individuals with at least 33 years ofcontribution have access to this scheme.
Table 6 shows that an increase of one year in the age at last employment increases mortality
between the ages of 60 and 69 by 6.8 percentage points (⇠ 62%) for individuals with less than 33
21

years of contributions, who could not access to partial retirement. On the other hand, the effect ismuch smaller (2 percentage points or 23%) for individuals with more than 33 years of contributions
who could potentially access the partial retirement scheme. We also observe that the differential
impact of the reform on both subgroups is statistically different.
This result indicates that introducing the possibility of reducing the working time for older workers at the end of their careers can help mitigate the adverse effects on health of delaying retirement.

6

Discussion

6.1

Comparison with Existing Studies

We find that individuals who contributed in 1967 (a delay of five years in statutory retirementage) have a 2-percentage point higher probability of dying between the ages of 60 and 69 (22%increase). The IV estimates indicate that delaying the age at last employment by one year increases
the probability of dying between the ages of 60 and 69 by 4.2 percentage points ( 43%). This
may seem quite a large effect; however, our estimates are comparable in magnitude with studies
showing that early retirement reduces mortality (Hallberg et al., 2015; Bloemen et al., 2017).
Hallberg et al. (2015) find that by offering a five-year reduction of the statutory retirement age
from the age of 65 to 60 reduces the probability of dying by the age of 70 by 26 percent. Using thesame measure of mortality, we find that a five-year increase in the statutory retirement age fromthe age of 60 to 65 increases the probability of dying before age 70 by 3 percentage points, whichis equivalent to a 17 percent increase. Additionally, Hallberg et al. (2015) show that the mortality
effects are driven by those who are more exposed to workplace hazards; that is, those with low
pre-retirement incomes and those without a college education. Their finding is consistent with ourheterogeneous results. Bloemen et al. (2017) also find estimates of a similar magnitude. They findthat retirement induced by a temporary decrease in the retirement eligibility age (from the age of
65 to 61 or 62) for male Dutch civil servants decreased the probability of dying within five years by
47 percent (2.6 percentage points).28 Although our prior is that the effect of delaying retirement is
not necessarily symmetric with the impact of early retirement, our estimates suggest that the effecton mortality has a similar magnitude when the nature of the reform and affected age ranges arecomparable.
Our paper is the first to find that retirement reduces mortality by exploring quasi-experimentsthat delay retirement. Existing papers find no effect of delaying retirement on mortality. Bozio et28

Although Hallberg et al. (2015) study male military officers in Sweden and Bloemen et al. (2017) focus on Dutch
male civil servants, both papers point out that the working environment of these subgroups of males is not moredemanding than that for the general population.

22

al. (2021) and Saporta-Eksten et al. (2021) are the only two papers we know of that have the statistical power to conclusively estimate the mortality impacts, and they find precisely zero effects
of delaying retirement.29 One common feature of these two papers is that they explore reforms
that increase the financial incentives to delay retirement while keeping the statutory retirement age
unchanged. Bozio et al. (2021) find a precisely zero impact of delaying retirement on the probability of dying between the ages of 61 and 79 for private-sector workers in France. Saporta-Eksten
et al. (2021) find no effect of delaying retirement on mortality between the ages of 65 and 74 by
exploring a reform that reduced the implied tax of working for married males in Israel.30 One possible reason that we find an adverse impact of delayed retirement (while their study find no effect)is that the groups of compliers differ. Those who retire later as a response to a pension reform
incentivizing later retirement via financial incentives differ from those who retire later because theearly retirement possibility is not available. Therefore, it is reasonable to expect a more harmful
impact on mortality when the early retirement option is removed than when early retirement isfinancially less attractive. Moreover, we find that workers entitled to gradual retirement suffer lessfrom the reform (see Table 6). This finding indicates that delaying retirement is less harmful when
pension reform provides a flexible choice, rather than a paternalistic policy that prohibits workers
from retiring earlier.

6.2

Policy Discussion

The heterogeneous mortality impacts of delayed retirement suggest important distributional consequences of raising the statutory retirement age. In particular, the socio-economic disparities
in lifespans are large and have increased in recent decades (OECD, 2016).31 One possible contributing factor might be the heterogeneous mortality responses to pension reforms, which could
exacerbate the disparity. Moreover, individuals who survive longer receive more years of pen29

Hagen (2018) explores a reform that increases the statutory retirement age from the age of 63 to 65 for Swedish
public sector workers born since 1938. They find an imprecisely measured no effect on mortality by the age of 69.
Their IV estimates show that a one-year increase in retirement age results in a 0.34% increase in morality by the ageof 69 (insignificant).
30
It is important to note that Saporta-Eksten et al. (2021) show a decline in the probability of survival of the affected
men between the ages of 75 and 85 due to later retirement. Overall, they find that one additional year of employment
decreases longevity by 9 to 12 months. Our result is in line with this finding.
31
We acknowledge that life expectancy also differs largely by gender. In Spain, in 2021, men live on average
until age 80.2, while women live on average until age 85.8 (Spanish National Institute of Statistics). In Table A19,
we examine if the reform had differential effects across gender. We show that a year delaying retirement increases
mortality more for men than women. In particular, a one-year delay in the age at which men exit the labour market
increases by 7.7 percentage points (⇠ 59%) the probability of dying between the ages of 60 and 69. The same delay
for women increases mortality by 1.9 percentage points (⇠ 48%). Factors influencing gender differences in mortality
include biological factors (genetics and hormones) and behavioural and environmental factors. One behavioural factor
that explains part of the mortality gender gap is that women and men select different occupations. Therefore, thedifferential effect of delaying retirement on mortality by gender may be partly driven by men and women selecting
occupations and sectors with different degrees of health burden (DeLeire and Levy, 2001).

23

sion. The resulting gaps in life expectancy will affect the actuarial fairness and progressivity of
public pension systems (Sanchez-Romero et al., 2020). Specifically, individuals from lower socioeconomic groups (typically those who are more exposed to workplace hazards) spend fewer years
in retirement than the rest of the population due to the pension reform.
A reduction in the duration of claiming a pension is composed of two factors: delayed claiming apension and earlier death. While the welfare impact of delayed labour market exit can be positive,
earlier death is harmful. Table 5 shows that individuals with strenuous employment (both physically and psychosocially), low-self-value and who work in blue-collar jobs experience a greater
increase in mortality between the ages of 60 and 69 due to the reform. In comparison, the reform
impact on the individual’s age at last employment is relatively similar between the different subgroups. If anything, individuals with better jobs delay their exit from the workplace for a longer
period. This comparison implies that the mortality impact plays an important role in explaining
the shortened pension claiming duration for workers with worse working conditions. One possible
policy recommendation would be to consider reforms that link retirement age to changes in life
expectancy. It might be worthwhile to consider a target retirement age based on the years a person
is expected to claim a pension rather than a uniform nationwide retirement age.

7

Conclusion

This paper studies the effect of delaying retirement on mortality. We exploit the 1967 Spanishreform that removed access to voluntary early retirement for individuals who had not contributed
since that year. Individuals who started contributing to the pension system before 1 January 1967
maintained the right to retire early at the age of 60. However, individuals who have not contributedby that date can only retire voluntarily at the statutory retirement age of 65 (although, under certain
circumstances, some individuals can involuntarily retire early at the age of 61).
Focusing on cohorts born between 1938 and 1949, we use Spanish administrative Social Security
data and compare individuals who started contributing 12 months before and after 1 January 1967.
We first show the reform effect on labour supply outcomes using a within-cohort OLS regression
controlling for gender and individuals’ employment history between the ages of 30 and 40. We
find that individuals who started contributing after 1967 delayed their labour market exit by almost
half a year. The reform not only modified the age at last employment but also changed the ageof claiming a pension and the types of pensions claimed. We find a decrease in the probability ofclaiming a regular pension by 19%, an increase in the probability of claiming a partial pension by
54%, and an increase in the probability of claiming disability insurance by 19%. This indicatesthat individuals did not fully comply with the rise in the statutory retirement age and utilized otherways to leave the labour market before claiming a regular pension. Moreover, the results suggest
24that treated individuals are more likely to claim no pension, driven mainly by premature death.
Furthermore, we estimate the effect of age at last employment on mortality using the instrumental
variable method. We find that delaying labour market exit by one year increases the hazard of dying
between the ages of 60 and 69 by 4.2 percentage points (43%). The mortality responses are thestrongest between the ages of 60 and 64 (67%), when public pensions are no longer accessible forindividuals who started contributing after 1967. This suggests that the effect of delaying retirement
on mortality is driven mainly by the immediate effect of losing access to early retirement schemes.
We explore several mechanisms to explain the detrimental effects of delaying retirement on
health. First, we show that individuals’ workplace conditions before retirement are an essential
factor. Moreover, we show that allowing workers to gradually reduce their working time towards
the end of their career and making partial retirement an option can incentivize workers to staylonger in the labour force without negatively affecting their health.
The applicability and relevance of our findings extend further than the Spanish setting. Delaying
statutory retirement and closing early retirement options is a pertinent policy agenda in many
countries. However, the existing empirical evidence on the mortality effects of retirement rests
almost exclusively on the estimates of policy experiments that have allowed for earlier retirement.
Given that it is unclear if there is a symmetry impact of advancing or delaying retirement age, ourfindings on the mortality effect of delaying retirement are particularly relevant.
Additionally, the heterogeneous mortality impacts of delaying retirement raise discussions on
the distributional consequences of raising the statutory retirement age. We find that individuals
who have high physically and/or psychosocially burdensome jobs are those who suffer the mostfrom a delay in retirement. Furthermore, the reform has a more substantial effect on individuals injobs where they feel they have achieved less and received less recognition for their contributions.
Combining the results on partial retirement, our findings suggest that it is crucial to provide options
for gradual and flexible retirement while raising the age of statutory retirement.

25

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28

8Figures and Tables
Figure 1: Retirement Age by First Year of Contribution and Cohort

Source: Authors’ own construction according to the pension laws.
Notes: This figure plots the statutory retirement age and the earliest possible early retirement age for individuals
that contributed before and after 1 January 1967 as a function of their birth year. The blue line shows that
individuals who start contributing before 1 January 1967 can voluntarily retire after age 60, independently of theirbirth year. The orange line shows that those who start contributing after 1967 can only involuntary retire after 64
to 61, depending on their birth year. The grey line shows that the statutory retirement age remains at age 65 forall cohorts independently from the moment they started contributing.

29





3HUFHQWDJH

Figure 2: Densityof Age at Last Employment by Treatment Status'HQVLW\RI$JHDW/DVW(PSOR\PHQW                 $JHDW/DVW(PSOR\PHQW&RQWULEXWHGLQ
&RQWULEXWHGLQ
Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the percentage of individuals by the age at which they finished their last employment.
The solid red line shows the density for individuals who started contributing in 1966, while the green dashed line
shows those who started contributing in 1967.

30

Figure 3: Density of Pension Ages by Treatment Status(a) Age at Regular Pension(b) Age at Disability Pension(c) Age at Partial Pension

Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the percentage of individuals by the age at claiming regular pension (Graph a), age atclaiming disability pension (Graph b), and age at claiming partial pension (Graph c). The solid red lines show
the density for individuals who started contributing in 1966, while the green dashed lines show those who started
contributing in 1967.

31

Figure 4: Placebo Tests: Using Other Cutoffs(a) Age at last employment(b) Age at claiming regular pension(c) Probability of claiming regular pension(d) Probability of claiming disability pension(e) Probability of claiming partial pension(f) Probability of not claiming any pension

Source: MCVL, cohorts 1938-1949.
Notes: This figure shows the estimates and the 95 percent confidence intervals of a list of placebos, estimating regression 1 using the yearsof the y-axis as the cutoff. The red estimate corresponds to the estimation of the regression 1 on the real cutoff: 1967. The outcomesconsidered are displayed on top of each figure.

32

Figure 5: Placebo Tests for Mortality: Using Other Cutoffs(a) Dying between 60 and 69 years old(b) Dying between 50 and 86 years old

Source: MCVL, cohorts 1938-1949.
Notes: This figure shows the estimates and the 95 percent confidence intervals of a list of placebos, estimating
regression 1 using the years of the y-axis as the cutoff. The red estimate corresponds to the estimation of theregression 1 on the real cutoff: 1967. The outcomes considered are displayed on top of each figure.

33

Table 1: Impact of the Reform on the Type of Pension
First Pension Claimed
Regular Pension

Partial Pension Disability Pension

No Pension

Contributed in 1967

-0.102***(0.032)[0.006]0.019***(0.005)[0.002]0.058**(0.024)[0.029]0.025***(0.007)[0.003]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.140
0.398
0.533

X
X
X
25,903
0.067
0.048
0.035

X
X
X
25,903
0.091
0.387
0.296

X
X
X
25,903
0.054
0.167
0.137

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market through regularpension (Column 1), partial pension (Column 2), disability pension (Column 3), and not claiming any pension(Column 4), obtained from the estimation of regression 1. The estimation sample includes individuals that started
contributing 12 months before and after January 1st, 1967. All specifications control for gender, year of birth, andmonth of birth fixed effects. Each regression also includes the following controls measured when the individuals
were between 30 and 40 years old: average monthly contribution, fraction of time employed, fraction of time
active, fraction of time in self-employment, and highest occupation and industry sector fixed effects. All standard
errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

34

Table 2: Impact of the Reform on the Age at Claiming Pension
Age of the Individual at
Last
Employment

First
PensionRegularPensionDisability
PensionPartialPensionContributed in 1967

0.405***(0.073)[0.003]0.279**(0.107)[0.041]1.310***(0.207)[0.001]0.288**(0.067)[0.023]-0.153***(0.054)[0.005]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,9030.083
59.85859.401

X
X
X
22,0400.106
61.04960.889X
X
X
12,3670.220
64.64163.036

X
X
X
8,633
0.035
57.35256.986

X
X
X
1,040
0.245
61.10161.134

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the age at last employment (Column 1), atclaiming first pension (any type) (Column 2), regular pension (Column 3), disability pension (Column4), and partial pension (Column 5), obtained from the estimation of regression 1. The estimation
sample includes individuals that started contributing 12 months before and after January 1st, 1967.
All specifications control for gender, year of birth, and month of birth fixed effects. Each regression
also includes the following controls measured when the individuals were between 30 and 40 years
old: average monthly contribution, fraction of time employed, fraction of time active, fraction of timein self-employment, and highest occupation and industry sector fixed effects. All standard errors are
clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

35

Table 3: Impact of the Reform on Pension Benefit
Pension Benefit

Base Pension

Percent of Base Pension

Contributed in 1967

43.777***(10.913)[0.003]19.112**(6.570)[0.015]5.039***(1.014)[0.001]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
22,0400.377
1177.066
1089.755

X
X
X
22,0400.410
1203.640
1150.027

X
X
X
22,0390.155
86.09978.796

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on monthly pension benefit (Column 1), pension base (Column 2), and pension adjustment factor (Column 3), obtained from the estimation ofregression 1 for those individuals in our sample that claim any pension. The estimation sample
includes individuals that started contributing 12 months before and after January 1st, 1967. All
specifications control for gender, year of birth, and month of birth fixed effects. Each regression also
includes the following controls measured when the individuals were between 30 and 40 years old:
average monthly contribution, fraction of time employed, fraction of time active, fraction of time inself-employment, and highest occupation and industry sector fixed effects. All standard errors are
clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

36

Table 4: Impact of Age at Last Employment on Mortality
Probability of Dying between the Ages

OLS:
Impact of Age at Last Employment

Reduced Form:
Contributed in 1967

IV:
Impact of Age at Last Employment

Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS

50-86

50-59

60-69

70-79

80-86

Age at Death
Censored 71-0.013***(0.001)[0.001]-0.012***(0.001)[0.001]-0.004***(0.000)[0.001]-0.003***(0.000)[0.001]-0.000(0.000)[0.622]0.207***(0.015)[0.001]0.030***(0.009)[0.002]0.010(0.006)[0.115]0.021***(0.004)[0.001]0.001(0.007)[0.840]0.004*(0.002)[0.059]-0.305***(0.092)[0.001]0.074**(0.031)[0.019]0.025(0.015)[0.147]0.042***(0.010)[0.003]0.003(0.012)[0.834]0.006**(0.003)[0.036]-0.757**(0.278)[0.012]

X
X
X
25,9030.369
0.297
35.762

X
X
X
25,9030.085
0.066
35.762

X
X
X
23,9870.131
0.098
59.364

X
X
X
21,0090.184
0.154
56.135

X
X
X
17,5160.036
0.023
68.987

X
X
X
25,90368.85969.38435.762

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between the ages of 50-86 (Column 1), 5059 (Column 2), 60-69 (Column 3), 70-79 (Column 4), and 80-86 (Column 5). Column 6 reports the impact of age at last employment
on age at death censored at 71 years old. The first panel reports the correlation of age at last employment on mortality (OLS), and thesecond panel shows the effect of the reform on mortality (reduced form effect using regression 1). The IV estimates, obtained fromthe estimation of regression 2, are reported in the third panel. The estimation sample includes individuals that started contributing 12months before and after January 1st, 1967. All specifications control for gender, year of birth, and month of birth fixed effects. Eachregression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly
contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation andindustry sector fixed effects. The IV estimation also controls for a proxy of the pension base. All standard errors are clustered at theyear of birth, and wild-bootstrap p-values are reported in brackets.

37

Table 5: Impact on Mortality by Labour Market Conditions Before Retirement
Last Industry
Workplace Accidents
High

Low

Psychosocial Exposure
High

Low

Last Occupation
Self-valueHigh

Blue-collar

Low

No

Yes

0.420***(0.092)[0.001]0.613***(0.070)[0.001]0.437***(0.102)[0.005]Age at Last Employment
First Stage:
Contributed in 1967

0.435***(0.116)[0.006]0.682***(0.108)[0.001]0.472***(0.104)[0.001]0.671***(0.127)[0.002]0.962***(0.216)[0.001]

Probability of Dying between 60 and 69
Reduced Form:
Contributed in 1967

0.029***(0.008)[0.016]0.017***(0.005)[0.007]0.027***(0.006)[0.002]0.018**(0.007)[0.028]0.011(0.008)[0.150]0.027***(0.006)[0.003]0.016**(0.007)[0.040]0.024***(0.005)[0.001]

IV:
Impact of Age at Last Employment

0.068**(0.028)[0.043]0.025***(0.007)[0.000]0.057***(0.016)[0.001]0.028**(0.011)[0.023]0.012(0.009)[0.181]

0.064***(0.019)[0.007]0.027**(0.011)[0.036]

0.054***(0.017)[0.007]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS
P-value Difference (IV Est.)

X
X
X
X
X
X
7,941
12,991
0.158
0.122
0.117
0.094
15.84846.6880.136

X
X
X
10,5800.148
0.105
22.664

X
X
X
10,3520.126
0.100
24.433
0.131

X
X
X
X
X
X
6,025
14,9070.112
0.146 )
0.095
0.106
18.25323.120
0.016

X
X
X
X
X
X
8,058
15,929
0.129
0.133
0.102
0.096
72.88220.4570.197

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between the ages of 60-and 69 by the labour market conditions
experienced by the individual just before retirement. Individual’s last industry is classified depending on their workplace accident incidence for our cohorts
between 2003 and 2019 (Columns 1 and 2), by the psychosocial exposure (mental stress, social stress, and temporal load) following Kroll (2011) (Columns 3
and 4), and by their self-value index (sense of achievement and recognition) constructed using O*NET (Columns 5 and 6). We also differentiate if individuals’
last occupation pertains to a white or a blue-collar occupation (Columns 7 and 8). The first panel reports the first stage of the IV estimation (the reform’s effecton the age at last employment, using 1). The second panel shows the second stage; the effect on the probability of dying between 60 and 69 years old. First, wereport the reduced form effect of the reform on mortality using regression 1. After that, we report the IV estimates obtained from the estimation of regression
2. The estimation sample includes individuals that started contributing 12 months before and after January 1st, 1967. All specifications control for gender,
year of birth, and month of birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40
years old: average monthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation andindustry sector fixed effects. The IV estimation also controls for a proxy of the pension base. At the bottom, we report the First Stage F-statistic and thep-value of the differences between groups in the IV estimation. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported
in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

38

Table 6: Impact on Mortality by Availability of Flexible Retirement
More 33
Less 33
Years of Contribution Years of Contribution
Age at Last Employment
First Stage:
Contributed in 1967

0.825***(0.155)[0.002]0.316***(0.079)[0.005]

Probability of Dying between 60 and 69
Reduced Form:
Contributed in 1967

0.016**(0.007)[0.019]0.022***(0.004)[0.005]

IV:
Impact of Age at Last Employment

0.020***(0.007)[0.010]0.068**(0.022)[0.013]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS
P-value Difference (IV Est.)

X
X
X
11,7820.108
0.087
27.534

X
X
X
12,2050.155
0.109
15.8880.050

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between
the ages of 60-and 69 for individuals with less (Column 1) or more than 33 years of contribution(Column 2). Only individuals with more than 33 years of contribution when claiming a pension canaccess the partial retirement scheme. The first panel reports the first stage of the IV estimation (thereform’s effect on the age at last employment, using 1). The second panel shows the second stage;
the effect on the probability of dying between 60 and 69 years old. First, we report the reduced
form effect of the reform on mortality using regression 1. After that, we report the IV estimatesobtained from the estimation of regression 2. The estimation sample includes individuals that started
contributing 12 months before and after January 1st, 1967. All specifications control for gender,
year of birth, and month of birth fixed effects. Each regression also includes the following controls
measured when the individuals were between 30 and 40 years old: average monthly contribution,
fraction of time employed, fraction of time active, fraction of time in self-employment, and highest
occupation and industry sector fixed effects. The IV estimation also controls for a proxy of thepension base. At the bottom, we report the First Stage F-statistic and the p-value of the differences
between groups in the IV estimation. All standard errors are clustered at the year of birth, andwild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

39Online Appendix
The Effect of Removing Early Retirement on Mortality
Cristina Bellés-Obrero

Sergi Jiménez-Martı́n

Han YeUniversity of Mannheim,

Universitat Pompeu Fabra,

University of Mannheim,

IZA

FEDEA

IZA, ZEW

List of Figures
1
2
3
4
5
A1
A2
A3
A4
A5

Retirement Age by First Year of Contribution and Cohort . . . . . . . . . . . . . .
Density of Age at Last Employment by Treatment Status . . . . . . . . . . . . . .
Density of Pension Ages by Treatment Status . . . . . . . . . . . . . . . . . . . .
Placebo Tests: Using Other Cutoffs . . . . . . . . . . . . . . . . . . . . . . . . .
Placebo Tests for Mortality: Using Other Cutoffs . . . . . . . . . . . . . . . . . .
Correction of Year Started Contributing . . . . . . . . . . . . . . . . . . . . . . .
Types of Pension by Treatment Status . . . . . . . . . . . . . . . . . . . . . . . .
Classification of Industries by Incidence of Workplace Accidents . . . . . . . . . .
Classification of Industries by Psychosocial Exposure . . . . . . . . . . . . . . . .
Classification of Industries by Self-value Index . . . . . . . . . . . . . . . . . . .

29
30
31
32
33
3
4
5
6
7

List of Tables
1
Impact of the Reform on the Type of Pension . . . . . . . . . . . . . . . . . . . .
2Impact of the Reform on the Age at Claiming Pension . . . . . . . . . . . . . . . .
3Impact of the Reform on Pension Benefit . . . . . . . . . . . . . . . . . . . . . . .
4Impact of Age at Last Employment on Mortality . . . . . . . . . . . . . . . . . . .
5Impact on Mortality by Labour Market Conditions Before Retirement . . . . . . .
6Impact on Mortality by Availability of Flexible Retirement . . . . . . . . . . . . .
A1 Sample Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A2 Smoothness of the Covariates . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A3 Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A4 Impact of the Reform on the Type of Disability . . . . . . . . . . . . . . . . . . .
A5 Impact of the Reform on Reason for No Pension . . . . . . . . . . . . . . . . . . .
A6 Impact of the Reform on Age at Last Employment (in Brackets) . . . . . . . . . .
A7 Impact of the Reform on Age at Regular Pension (in Brackets) . . . . . . . . . . .
A8 Impact of the Reform on Age at Disability Pension (in Brackets) . . . . . . . . . .
A9 Impact of the Reform on Pension Benefit by Type of Pension . . . . . . . . . . . .
A10 Robustness: Age Start FE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1

34
35
36
37
38
39
8
9
10
11
12
13
14
15
16
17

A11 Robustness: Cohorts 1941 to 1949 . . . . . . . . . . . . . . . . . . . . . . . . . .
A12 Robustness: No Selfemployed . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A13 Robustness: No Correction of the Year Start Contributing . . . . . . . . . . . . . .
A14 Impact of Age at Last Employment on Mortality at Five-year Intervals . . . . . . .
A15 Impact of the Reform on Labour Market Outcomes between the Ages of 45 and 55
A16 Impact of Age at Last Employment on Mortality with Different Controls . . . . . .
A17 Descriptive Statistics of Compliers . . . . . . . . . . . . . . . . . . . . . . . . . .
A18 Impact on Mortality by Labour Market Conditions Before Retirement: Division by
3 Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A19 Impact on Mortality by Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

18
19
20
21
22
23
24
25
26

A

Appendix Tables and Figures
Figure A1: Correction of Year Started Contributing.1
Density
.05
0

0

.05

Density.1.15(b) With Correction.15(a) Without Correction

1950

1960

1970
1980
Year starts contribution

1990

2000

1950

1960

1970
1980
Year starts contribution

1990

Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the density of date started contributing without correction (Graph a) and with correction(Graph b). The correction uses the number of years of contribution and the date starting a regular or partial pension(years of contribution are not available for individuals that claim a disability pension) to correct for the date ofstarting contributing for those whose year of started contributing was between 1965 and 1967.

3

2000









Figure A2: Types of Pension by Treatment Status

5HJXODU3HQVLRQ'LVDELOLW\

3DUWLDO3HQVLRQ&RQWULEXWHGLQ

1R3HQVLRQ&RQWULEXWHGLQ

Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the percentage of individuals by the different types of pension claimed (regular pension,
disability insurance, partial pension, or no pension). The light green bars show the density for individuals thatstarted contributing in 1966, while the dark green bars show the density for those who started contributing in
1967.

4

Manufacturing Industry

Energy, Water and Sanitation Sector

Construction

Wholesale and retail trade

Administrative Activities

Hostelry

Health Sector

Public Administration and Defense

Agriculture

Transport

Other Services

Artistic Sector

Education

Extractive Industry

Scientific and Technical Activitiess

Financial Sector

Information and Comunications

Domestic Sector

0

5
500

1,000

1,500

2,000

Thousands of workplace accidents

Figure A3: Classification of Industries by Incidence of Workplace Accidents

Source: Register of Workplace Accidents 2003-2019, cohorts 1938-1949.
Notes: This figure plots the total number of workplace accidents between 2003 and 2019 for workers born between 1938 and 1949 in the industry sector theworkers were working at the moment of the accident.

Transport

Public Administration and Defense

Administrative Activities

Artistic Sector

Wholesale and retail trade

Extractive Industry

Manufacturing Industry

Health Sector

Energy, Water and Sanitation Sector

Education

Scientific and Technical Activitiess

Administrative Activities

Construction

Agriculture

Hostelry

Construction

Information and Comunications

Financial Sector

0

6
2

4

6

8

Overall Psychosocial Exposure Index

Figure A4: Classification of Industries by Psychosocial Exposure

Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the different industry sectors classified by the degree of psychosocial pressure (mental, social stress, and temporal load) individuals
working in these sectors are exposed to. We follow Kroll (2011) for the definition of psychosocial exposure.

7
Education

Information and Comunications

Scientific and Technical Activitiess

Health Sector

Financial Sector

Public Administration and Defense

Artistic Sector

Other Services

Agriculture

Manufacturing Industry

Construction

Extractive Industry

Energy, Water and Sanitation Sector

Wholesale and retail trade

Administrative Activities

Transport

Domestic Sector

Hostelry

0

.2

.4

.6

.8

Self-Value (Achievement and Recognition)

Figure A5: Classification of Industries by Self-value Index

Source: MCVL, cohorts 1938-1949.
Notes: This figure plots the different industry sectors classified by the degree of self-value (sense of achievement and recognition) that individuals working inthese sectors are exposed to. We follow the O*NET for the definition of the self-value index.

Table A1: Sample Selection
Sample Selection
Mortality
Observations
droppedDropped Obs
Contributed in 1967

-0.021(0.012)[0.100]0.016(0.013)[0.246]

Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
30,888
0.030
0.189
0.220

X
X
X
6,385
0.203
0.393
0.313

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of not being in the main sample due to having stopped
contributing to the Social Security system before age 50 or nothaving at least 8 years of contribution (Column1). Column 2reports the effect of the reform on mortality for the sample ofindividuals dropped from the main sample, obtained from theestimation of regression 1. The estimation sample includes individuals that started contributing 12 months before and after 1
January 1967. All specifications control for gender, year of birth,and month of birth fixed effects. All standard errors are clusteredat the birth year level, and wild-bootstrap p-values are reported
in brackets.

8

Table A2: Smoothness of the Covariates
Labor Market between the Ages of 30 and 40
Fraction Fraction Blue-collar Av. monthly
Fraction
active employedocc
contribution selfempoyed
Contributed in 1967

0.108
(0.362)[0.754]0.581(0.519)[0.344]-0.007(0.009)[0.493]30.190*(16.300)[0.098]2.602***(0.537)[0.002]Month-Year Birth FE
Observations
R2

X
25,9030.170

X25,9030.193

X25,9030.063

X25,9030.243

X25,9030.006

Industry between the Ages of 30 and 40
9Agriculture
MineryConstruction

Services
PublicHostelry
Science
Trade
HealthManufacturing Transportation Education Administrative Housekeeping

Contributed in 1967

0.002
(0.007)[0.769]-0.004(0.002)[0.128]-0.002(0.002)[0.382]-0.006(0.007)[0.374]-0.000(0.001)[0.847]0.000(0.003)[0.912]Month-Year Birth FE
Observations
R2

X
25,9030.045

X25,9030.012

X25,9030.008

X25,9030.044

X25,9030.004

X25,9030.004

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on a list of predetermined variables: fraction of time spent active (Column 1), the fraction oftime spent employed (Column 2), probability of having been employed in a blue-collar occupation (Column 3), average monthly contribution(Column 4), the fraction of time self-employed (Column 5), and probability of being employed in the agriculture, minery or construction
sectors (Column 6), manufacturing sector (Column 7), trade or transportation sectors (Column 8), public, health or educational sectors(Column 9), scientific or administrative sectors (Column 10), or services, hostelry or housekeeping sectors (Column 11). The estimation
sample includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender, yearof birth, and month of birth fixed effects. All standard errors are clustered at the birth year level, and wild-bootstrap p-values are reported inbrackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A3: Descriptive Statistics
Dependent Variables

N

Mean

SD

Min

Max

Regular Pension
Partial Pension
Disability Pension
No Pension
Age Last Employment
Age First Pension
Age Regular Pension
Age Disability Pension
Age Partial Pension
Dying 50-86 y.o.
Dying 50-59 y.o.
Dying 60-69 y.o.
Dying 70-79 y.o.
Dying 80-86 y.o.

25,90325,90325,90325,90325,90322,04012,3678,633
1,040
25,90325,90323,98721,00917,516

0.47
0.04
0.33
0.14
59.58
60.95
63.58
57.16
61.11
0.32
0.07
0.11
0.16
0.02

0.49
0.19
0.47
0.35
5.43
4.25
2.29
3.76
1.33
0.46
0.26
0.31
0.37
0.16

0
0
0
0
18.75
50
60
50
60
0
0
0
0
0

1
1
1
1
82.91
79.41
74
79.41
70.08
1
1
1
1
1

Source: MCVL, cohorts 1938-1949.
Notes: This table reports summary statistics for the main outcome variables.
The sample corresponds to individuals born between 1938 and 1949, registered in the Social Security (contributive workers and pensioners) at any
point of their lives till 2020. We further restrict the same to individuals
contributing to the Social Security system at age 50 with at least 8 years of
employment.

10

Table A4: Impact of the Reform on the Type of Disability
Type of Disability
Severe or Absolute

Partial or Professional

Contributed in 1967

0.031**(0.012)[0.013]0.027*(0.013)[0.066]

Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.040
0.180
0.133

X
X
X
25,903
0.051
0.207
0.162

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of claiming absolute or severe disability (Column 1) and partial or professional disability(Column 2), obtained from the estimation of regression 1. The estimation sample
includes individuals that started contributing 12 months before and after 1 January
1967. All specifications control for gender, year of birth, and month of birth fixed
effects. Each regression also includes the following controls measured when theindividuals were between 30 and 40 years old: average monthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment,
and highest occupation and industry sector fixed effects. All standard errors are
clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

11

Table A5: Impact of the Reform on Reason for No Pension
Reason for No Pension
No Pension

Still Working

Became Inactive

Died before Pension

Contributed in 1967

0.025***(0.007)[0.003]0.002*(0.001)[0.091]0.007(0.005)[0.141]0.016***(0.005)[0.007]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.054
0.167
0.137

X
X
X
25,903
0.007
0.004
0.003

X
X
X
25,903
0.080
0.065
0.064

X
X
X
25,903
0.031
0.098
0.070

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market without claiming any pension (Column 1), continuing working (Column 2), becoming inactive (Column 3), and dying before
claiming a pension (Column 4), obtained from the estimation of regression 1. The estimation sample includes
individuals that started contributing 12 months before and after 1 January 1967. All specifications control forgender, year of birth, and month of birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly contribution, fraction of time
employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector
fixed effects. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported inbrackets.
*** p<0.01, ** p<0.05, * p<0.1.

12

Table A6: Impact of the Reform on Age at Last Employment (in Brackets)
Last Employment at Age
50-54

55-59

60

61

62

63

64

65

After 65

Contributed in 1967

0.011
(0.008)[0.222]-0.011*(0.005)[0.068]-0.041***(0.013)[0.009]-0.011**(0.005)[0.026]-0.011**(0.004)[0.011]-0.011***(0.003)[0.005]0.006**(0.002)[0.023]0.070***(0.012)[0.001]0.016***(0.004)[0.004]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.033
0.198
0.176

X
X
X
25,903
0.041
0.247
0.253

X
X
X
25,903
0.020
0.059
0.109

X
X
X
25,903
0.007
0.047
0.060

X
X
X
25,903
0.007
0.041
0.054

X
X
X
25,903
0.012
0.046
0.060

X
X
X
25,903
0.009
0.054
0.049

X
X
X
25,903
0.076
0.240
0.166

X
X
X
25,903
0.049
0.086
0.066

13

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market between the ages of 50-54 (Column 1), 55-59(Column 2), at 60 (Column 3), at 61 (Column 4), at 62 (Column 5), at 63 (Column 6), at 64 (Column 7), at 65 (Column 8), and after age 65 (Column9), obtained from the estimation of regression 1. The estimation sample includes individuals that started contributing 12 months before and after 1
January 1967. All specifications control for gender, year of birth, and month of birth fixed effects. Each regression also includes the following controls
measured when the individuals were between 30 and 40 years old: average monthly contribution, fraction of time employed, fraction of time active,
fraction of time in self-employment, and highest occupation and industry sector fixed effects. All standard errors are clustered at the year of birth, andwild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A7: Impact of the Reform on Age at Regular Pension (in Brackets)
Regular Pension at Age
60

61

62

63

64

65

After 65

Contributed in 1967

-0.100***(0.024)[0.001]-0.020***(0.005)[0.005]-0.032***(0.005)[0.001]-0.032***(0.006)[0.001]-0.020***(0.005)[0.001]

0.095***(0.014)[0.001]0.036***(0.008)[0.003]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.088
0.030
0.149

X
X
X
25,903
0.029
0.014
0.041

X
X
X
25,903
0.023
0.007
0.042

X
X
X
25,903
0.028
0.009
0.045

X
X
X
25,903
0.019
0.020
0.043

X
X
X
25,903
0.107
0.284
0.188

X
X
X
25,903
0.139
0.159
0.112

14

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of claiming a regular pension between the ages of 50-54(Column 1), 55-59 (Column 2), at 60 (Column 3), at 61 (Column 4), at 62 (Column 5), at 63 (Column 6), at 64 (Column 7), at 65(Column 8), and after age 65 (Column 9), obtained from the estimation of regression 1. The estimation sample includes individuals
that started contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, and monthof birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40
years old: average monthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment,
and highest occupation and industry sector fixed effects. All standard errors are clustered at the year of birth, and wild-bootstrap
p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A8: Impact of the Reform on Age at Disability
Pension (in Brackets)
Disability at Age
50-54

55-59

60-65

After 65

Contributed in 1967

0.012
(0.009)[0.170]0.017(0.012)[0.176]0.028***(0.005)[0.001]0.000*(0.000)[0.092]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.026
0.113
0.091

X
X
X
25,903
0.045
0.167
0.136

X
X
X
25,903
0.017
0.106
0.068

X
X
X
25,903
0.006
0.001
0.001

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of claiming a disability pension between the ages of 50-54 (Column 1), 55-59 (Column2), 60-56 (Column 3), and after age 65 (Column 4), obtained from the estimation of regression 1. The estimation sample includes individuals that started
contributing 12 months before and after 1 January 1967. All specifications
control for gender, year of birth, and month of birth fixed effects. Each regression also includes the following controls measured when the individuals
were between 30 and 40 years old: average monthly contribution, fraction oftime employed, fraction of time active, fraction of time in self-employment,
and highest occupation and industry sector fixed effects. All standard errors
are clustered at the year of birth, and wild-bootstrap p-values are reported inbrackets.
*** p<0.01, ** p<0.05, * p<0.1.

15

Table A9: Impact of the Reform on Pension Benefit by Type of Pension
Regular Pensions

Disability Pensions

Partial Pensions

No Pension

Mean
Benefit

Base
Benefit

Perc
Base

Proxy
Base

Mean
Benefit

Base
Benefit

Perc
Base

Proxy
Base

Mean
Benefit

Base
Benefit

Perc
Base

Proxy
Base

Proxy
Base

Contributed in 1967

73.70***(11.75)[0.00]

31.30**(11.10)[0.02]

8.54***(1.59)[0.00]

46.192***(12.283)[0.012]-26.28**(8.81)[0.02]-5.04(23.93)[0.81]

0.97(0.61)[0.13]-31.222**(13.182)[0.063]-6.67(22.20)[0.74]-5.04(23.93)[0.81]-0.10(0.31)[0.76]-40.421(22.529)[0.112]-41.402(25.196)[0.159]Month-Year Birth FE
Controls
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
12,0070.373
1026.6937.0

XX
12,0070.397
1041.361014.31X
X
12,007
0.358
88.30
75.5

X
X
12,3670.355
1089.888
1028.816

X
X
8,434
0.397
1252.71279.64

X
X
1,038
0.501
1852.11
1856.49

X
X
8,434
0.051
84.03
84.01

X
X
8,633
0.467
1235.633
1277.667

X
X
1,038
0.482
1545.391544.27

1,038
0.501
1852.11
1856.49

1,038
0.288
81.72
81.19

1,040
0.386
1684.707
1715.096

3,863
0.485
1231.647
1186.478

16

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on monthly pension benefit (Columns 1, 5, and 9), pension base (Column 2, 6, and 10), the pension adjustment factor (Column 3, 7 and 11), and theproxy of the pension base (calculated using years of contribution for those individuals that claimed regular pension and total years of activity for the rest) by type of pension claimed by the individual,
obtained from the estimation of regression 1. The estimation sample includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender,
year of birth, and month of birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly contribution,
fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector fixed effects. All standard errors are clustered at the year of birth,and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A10: Robustness: Age Start FE
Type of Pension

Age at17

RegularPensionPartialPensionDisability
Last
Pension No Pension Employment

RegularPensionDisability
PensionPartialPensionContributed in 1967

-0.097***(0.032)[0.014]0.025***(0.006)[0.005]0.051**(0.021)[0.024]0.020**(0.009)[0.039]0.529***(0.165)[0.021]1.362***(0.154)[0.001]0.329***(0.109)[0.040]-0.241**(0.103)[0.048]Age Start Contributing FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.136
0.398
0.533

X
X
X
25,903
0.069
0.048
0.035

X
X
X
25,903
0.086
0.387
0.296

X
X
X
25,903
0.054
0.167
0.137

X
X
X
25,9030.081
59.85859.401

X
X
X
12,3670.219
64.64163.036

X
X
X
8,633
0.033
57.35256.986

X
X
X
1,040
0.228
61.10161.134

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market through regular pension (Column 1), partial pension(Column 2), disability pension (Column 3), not claiming any pension (Column 4), age at last employment (Column 5), age at claiming regular pension(Column 6), age at claiming disability pension (Column 7), and age at claiming partial pension (Column 8), using age at first contribution fixed effects.
This robustness check estimates the impact of losing access to early retirement for people that start working at the same age. The estimation sample
includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender and age at first contribution
fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly
contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector fixed
effects. All standard errors are clustered at the age of the first contribution, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A11: Robustness: Cohorts 1941 to 1949
Type of Pension

Age at18

RegularPensionPartialPensionDisability
PensionNo
Pension

Last
Employment

RegularPensionDisability
PensionPartialPensionContributed in 1967

-0.156***(0.022)[0.002]0.025***(0.006)[0.002]

0.095***(0.016)[0.000]0.035***(0.006)[0.004]0.395***(0.130)[0.006]

1.666***(0.060)[0.000]0.187*(0.095)[0.262]-0.163**(0.054)[0.035]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
18,288
0.130
0.408
0.601

X
X
X
18,288
0.061
0.068
0.046

X
X
X
18,288
0.087
0.371
0.241

X
X
X
18,288
0.063
0.153
0.113

X
X
X
18,2880.074
60.08059.591

X
X
X
9,605
0.269
64.83262.860

X
X
X
5,340
0.042
57.30757.056

X
X
X
995
0.200
61.01461.097

Source: MCVL, cohorts 1941-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market through regular pension (Column 1), partial
pension (Column 2), disability pension (Column 3), not claiming any pension (Column 4), age at last employment (Column 5), age at claiming
regular pension (Column 6), age at claiming disability pension (Column 7), and age at claiming partial pension (Column 8), obtained from theestimation of regression 1 restringing the sample to cohorts born between 1941 and 1949. The estimation sample includes individuals that started
contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, and month of birth fixed effects. Eachregression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly contribution,
fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector fixed effects.
All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A12: Robustness: No SelfemployedType of Pension

Age at19

RegularPensionPartialPensionDisability
PensionNo
Pension

Last
Employment

RegularPensionDisability
PensionPartialPensionContributed in 1967

-0.110***(0.030)[0.002]0.024***(0.006)[0.000]0.049**(0.021)[0.034]0.037***(0.007)[0.000]0.470***(0.098)[0.004]1.563***(0.169)[0.000]0.314***(0.077)[0.026]-0.152**(0.053)[0.045]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
21,468
0.160
0.338
0.499

X
X
X
21,468
0.067
0.060
0.041

X
X
X
21,468
0.113
0.394
0.299

X
X
X
21,468
0.068
0.208
0.161

X
X
X
21,4680.057
59.14158.797

X
X
X
9,337
0.185
64.33462.618

X
X
X
7,231
0.032
57.14156.792

X
X
X
1,037
0.245
61.09961.131

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market through regular pension (Column 1), partial
pension (Column 2), disability pension (Column 3), not claiming any pension (Column 4), age at last employment (Column 5), age at claiming
regular pension (Column 6), age at claiming disability pension (Column 7), and age at claiming partial pension (Column 8), obtained from theestimation of regression 1 restringing the sample to individuals that are not in one of the self-employed pension regimes. The estimation sample
includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, andmonth of birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years
old: average monthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupationand industry sector fixed effects. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A13: Robustness: No Correction of the Year Start Contributing
Type of Pension

Age at20

RegularPensionPartialPensionDisability
PensionNo
Pension

Last
Employment

RegularPensionDisability
PensionPartialPensionContributed in 1967

-0.177***(0.028)[0.000]0.075***(0.013)[0.000]0.074***(0.012)[0.000]0.029***(0.005)[0.001]0.676***(0.201)[0.007]1.432***(0.269)[0.002]0.256**(0.108)[0.040]-0.323***(0.069)[0.001]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
54,692
0.061
0.600
0.759

X
X
X
54,692
0.075
0.097
0.043

X
X
X
54,692
0.028
0.214
0.137

X
X
X
54,692
0.038
0.088
0.060

X
X
X
54,6920.058
61.14960.437

X
X
X
38,2960.172
64.00062.534

X
X
X
9,069
0.029
57.49657.189

X
X
X
3,464
0.207
61.20761.400Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on the probability of leaving the labour market through regular pension (Column 1), partial
pension (Column 2), disability pension (Column 3), not claiming any pension (Column 4), age at last employment (Column 5), age at claiming
regular pension (Column 6), age at claiming disability pension (Column 7), and age at claiming partial pension (Column 8), obtained from theestimation of regression 1 without correcting for the year of starting contributing reported in the affiliation data. The estimation sample includes
individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, and month ofbirth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years old: averagemonthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry
sector fixed effects. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A14: Impact of Age at Last Employment on Mortality at Five-year Intervals
Probability of Dying between the Ages
OLS:
Impact of Age at Last Employment

Reduced Form:
Contributed in 1967

21

IV:
Impact of Age at Last Employment

Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS

50-86

50-54

55-59

60-64

65-69

70-74

75-79

80-86

-0.013***(0.001)[0.001]-0.007***(0.001)[0.001]-0.006***(0.001)[0.001]-0.002***(0.000)[0.001]-0.002***(0.000)[0.001]-0.002***(0.000)[0.001]-0.002***(0.000)[0.001]-0.000(0.000)[0.622]0.030***(0.009)[0.002]0.003(0.002)[0.155]0.007(0.005)[0.187]0.018***(0.004)[0.004]0.007**(0.002)[0.011]0.001(0.006)[0.901]0.001(0.005)[0.897]0.004*(0.002)[0.059]0.074**(0.031)[0.019]0.008(0.006)[0.190]0.015(0.011)[0.204]0.038***(0.009)[0.004]0.013**(0.006)[0.048]0.001(0.010)[0.902]0.001(0.008)[0.898]0.006**(0.003)[0.036]25,9030.369
0.297
35.76225,9030.030
0.023
35.762

25,2230.057
0.044
42.75323,9870.082
0.056
59.364

22,3830.069
0.056
55.27521,0090.095
0.083
56.135

19,1740.099
0.078
65.193

17,5160.036
0.023
68.987

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between the ages of 50-86 (Column 1), 50-54 (Column 2), 55-59(Column 3),60-64 (Column 4), 65-69 (Column 5), 70-74 (Column 6), 75-79 (Column 7), and 80-86 (Column 8). The first panel reports the correlation of age atlast employment on mortality (OLS), and the second panel shows the effect of the reform on mortality (reduced form effect using regression 1). The IV estimates,
obtained from the estimation of regression 2, are reported in the third panel. The estimation sample includes individuals that started contributing 12 months
before and after 1 January 1967. All specifications control for gender, year of birth, and month of birth fixed effects. Each regression also includes the following
controls measured when the individuals were between 30 and 40 years old: average monthly contribution, fraction of time employed, fraction of time active,
fraction of time in self-employment, and highest occupation and industry sector fixed effects. The IV estimation also controls for the proxy of the pension base.
All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A15: Impact of the Reform on Labour Market Outcomes between the Ages of 45 and 55
Labor Market between the Ages of 45 and 55
Fraction Fraction
active employed

Fraction
Blue-collar Av. monthly
occ
contribution selfempoyed

Contributed in 1967

0.410
(0.230)[0.108]1.858**(0.647)[0.010]0.015***(0.004)[0.009]5.109(13.201)[0.710]-0.676*(0.364)[0.093]

Year Birth FE
Contributed 1966-1967
Controls
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,9030.116
95.65692.975

X
X
X
25,9030.128
86.53781.659X
X
X
25,903
0.411
0.469
0.436

X
X
X
25,9030.432
1165.975
1099.951

X
X
X
25,9030.304
17.62315.984

Industry between the Ages of 45 and 55

22

Agriculture
MineryConstruction

Services
PublicHostelry
Science
Trade
HealthManufacturing Transportation Education Administrative Housekeeping

Contributed in 1967

0.001
(0.005)[0.823]0.001(0.004)[0.885]-0.019***(0.004)[0.002]-0.027**(0.008)[0.019]-0.006(0.003)[0.102]-0.008**(0.003)[0.027]Month-Year Birth FE
Contributed 1966-1967
Controls
Observations
R2
Mean Dep. (Treated)
Mean Dep. (Control)

X
X
X
25,903
0.249
0.135
0.123

X
X
X
25,903
0.078
0.141
0.136

X
X
X
25,903
0.046
0.088
0.110

X
X
X
25,903
0.094
0.314
0.344

X
X
X
25,903
0.042
0.058
0.077

X
X
X
25,903
0.068
0.030
0.044

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of the reform on a list of labour market outcomes when the individual is between 45 and 55 years
old: fraction of time spent active (Column 1), the fraction of time spent employed (Column 2), probability of having been employed in ablue-collar occupation (Column 3), average monthly contribution (Column 4), the fraction of time self-employed (Column 5), and probabilityof being employed in the agriculture, minery or construction sectors (Column 6), manufacturing sector (Column 7), trade or transportation
sectors (Column 8), public, health or educational sectors (Column 9), scientific or administrative sectors (Column 10), or services, hostelryor housekeeping sectors (Column 11), obtained from the estimation of regression 1. The estimation sample includes individuals that started
contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, and month of birth fixed effects.
Each regression also includes the following controls measured when the individuals were between 30 and 40 years old: average monthly
contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector
fixed effects. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A16: Impact of Age at Last Employment on Mortality with Different
Controls
Probability of dying between the ages 60 and 69
IV:
Impact of Age at Last Employment
Month-Year Birth FE
Controls
Contributed 1966-1967
Proxy Pension BaseLM Controls 45-55
Observations
Mean Dep. Variable (Treated)
Mean Dep. Variable (Control)
F-stat FS

(1)

(2)

(3)

0.042***(0.010)[0.001]

0.042***(0.010)[0.003]0.049***(0.014)[0.009]

X
X
X

X
X
X
X

23,9870.131
0.098
50.211

23,9870.131
0.098
59.364X
X
X
X
X
23,9870.131
0.098
33.854

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between theages of 60 and 69 with no controls (Column 1), controlling for the proxy of the base of the pension benefit (Column 2), and also controlling for the labour market outcomes when the individuals were between
45 and 55 years old (Column 3), obtained from the estimation of regression 2. The estimation sample
includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender, year of birth, and month of birth fixed effects. Each regression also includes thefollowing controls measured when the individuals were between 30 and 40 years old: average monthly
contribution, fraction of time employed, fraction of time active, fraction of time in self-employment,
and highest occupation and industry sector fixed effects. All standard errors are clustered at the year ofbirth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

23

Table A17: Descriptive Statistics of Compliers
Compliers
Mean

Non-compliers
Mean

Difference[P-value]

Frac. Active 45-55

89.78

93.00

Frac. Employed 45-55

62.66

84.43

Frac. Self-employed 45-55

11.43

17.28

Mean Contribution 45-55

819.941127.45

Last Industry with High Workplace Accidents

0.33

0.37

Last Industry with High Psychosocial Exposure

0.49

0.51

Last Industry with High Self-value

0.33

0.28

Last Blue-collar Occupation

0.34

0.35

More than 33 Years of Contribution

0.45

0.48

2.169**[0.021]-16.047***[0.000]-4.609***[0.003]-189.401***[0.000]0.031*[0.075]-0.033*[0.079]0.001[0.957]-0.036**[0.034]-0.002[0.892]

Observations

2,272

11,968

Variables

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the summary statistics for individuals that are considered compliers and non-compliers.
We define as compliers as those individuals that started contributing in 1966 and claimed a regular pension before
age 61, while non-compliers are those that also started contributing in 1966 but did not claim a regular pension
before 61. The third column shows the coefficient and wild-bootstrap p-value from the regression of all thevariables on the dummy variable indicating if the individual is a complier. In this regression we also control forgender, year of birth, and month of birth fixed effects.
*** p<0.01, ** p<0.05, * p<0.1.

24

Table A18: Impact on Mortality by Labour Market Conditions Before Retirement: Division by 3 Groups
Probability of Dying between 60 and 69
Workplace Accidents
High
Reduced Form:
Contributed in 1967

IV:
Impact of Age at Last Employment

25

Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS
P-value Diff High-Low

MediumLow

Psychosocial ExposureHigh

MediumLow

Self-value
High

MediumLow

0.029***(0.008)[0.016]0.025*** 0.013(0.008) (0.007)[0.012] [0.076]

0.027***(0.006)[0.003]0.030*** 0.004
0.014(0.007) (0.010) (0.009)[0.003] [0.755] [0.089]

0.031***(0.009)[0.016]0.020***(0.006)[0.012]0.068**(0.028)[0.043]0.050**(0.022)[0.026]0.016(0.011)[0.139]0.062***(0.019)[0.002]0.040*** 0.008
0.016(0.010) (0.020) (0.010)[0.000] [0.731] [0.110]

0.061**(0.030)[0.059]0.049***(0.017)[0.010]

X
X
X
7,941
0.158
0.117
15.848

X
X
X
5,133
0.131
0.090
13.012
0.086

X
X
X
7,858
0.117
0.097
26.495

X
X
X
9,756
0.149
0.105
17.207

X
X
X
6,736
0.129
0.092
24.195
0.060

X
X
X
5,993
0.153
0.108
10.935
0.155

X
X
X
9,787
0.135
0.102
11.446

X
X
X
4,440
0.121
0.113
14.418

X
X
X
5,152
0.121
0.097
17.007

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between the ages of 60-and 69 by the labour market conditions
experienced by the individual just before retirement. Individual’s last industry is classified depending on their workplace accident incidence for our cohorts
between 2003 and 2019 (Columns 1, 2 and 3), by the psychosocial exposure (mental stress, social stress, and temporal load) following Kroll (2011) (Columns 4,
5 and 6), and by their self-value index (sense of achievement and recognition) constructed using O*NET (Columns 7, 8 and 9). The first panel reports the effectof the reform on mortality (reduced form effect using regression 1). The IV estimates, obtained from the estimation of regression 2, are reported in the second
panel. The estimation sample includes individuals that started contributing 12 months before and after 1 January 1967. All specifications control for gender, yearof birth, and month of birth fixed effects. Each regression also includes the following controls measured when the individuals were between 30 and 40 years old:
average monthly contribution, fraction of time employed, fraction of time active, fraction of time in self-employment, and highest occupation and industry sector
fixed effects. The IV estimation also controls for a proxy of the pension base. At the bottom, we report the First Stage F-statistic and the p-value of the differences
between the high and the low groups in the IV estimation. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

Table A19: Impact on Mortality by Gender
Age at Last Employment
First Stage
Contributed in 1967

Men

Women

0.285**(0.106)[0.037]1.041***(0.108)[0.001]

Probability of Dying between 60 and 69
Reduced Form:
Contributed in 1967

0.022***(0.005)[0.003]0.019***(0.005)[0.007]

IV:
Impact of Age at Last Employment

0.077***(0.029)[0.005]0.019**(0.006)[0.017]Month-Year Birth FE
Controls
Contributed 1966-1967
Observations
Mean Dep. (Treated)
Mean Dep. (Control)
F-stat FS
P-value Difference (IV Est.)

X
X
X
17,180
0.150
0.129
8.412

X
X
X
6,807
0.057
0.039
102.086
0.036

Source: MCVL, cohorts 1938-1949.
Notes: This table reports the impact of age at last employment on the probability of dying between theages of 60-and 69 for men (Column 1) and women (Column 2). The first panel reports the first stageof the IV estimation (the reform’s effect on the age at last employment, using 1). The second panel
shows the second stage; the effect on the probability of dying between 60 and 69 years old. First, wereport the reduced form effect of the reform on mortality using regression 1. After that, we report the IV
estimates obtained from the estimation of regression 2. The estimation sample includes individuals thatstarted contributing 12 months before and after 1 January 1967. All specifications control for gender,
year of birth, and month of birth fixed effects. Each regression also includes the following controls
measured when the individuals were between 30 and 40 years old: average monthly contribution, fractionof time employed, fraction of time active, fraction of time in self-employment, and highest occupationand industry sector fixed effects. The IV estimation also controls for a proxy of the pension base. At thebottom, we report the First Stage F-statistic and the p-value of the differences between groups in the IV
estimation. All standard errors are clustered at the year of birth, and wild-bootstrap p-values are reported
in brackets.
*** p<0.01, ** p<0.05, * p<0.1.

26