Retirement Patterns in Europe: the Effect of Health

Agar BrugiaviniEnrica Croda

Franco Peracchi

2

Motivation

Europe is aging faster than other parts of the world: – the highest proportion of population aged 65 or

over (about 15%) – The old-age dependency ratio is expected to

increase from about 27% in 2000 to 39% in 2025, and to 53% in 2050

Reforms throughout Europe

Need to know more about retirement behavior

3

This paper

This paper uses SHARE (Survey of Health Ageing and Retirement in Europe) to investigate the retirement decisions of older Europeans

In particular: – retirement (and labor force participation)

decisions may depend on a number of factors, including health

– individual factors matter, but we also hypothesize that institutions matter as well

4

Theoretical Framework Following Grossman (1972a, 1972b, 1999) and

Currie and Madrian (1999), assume individuals derive utility from consumption, leisure and also, directly from health, i.e. have the following the period utility function:

Health is valued by individuals both for its own sake and because being sick is assumed to take time away from market and non-market activities

),;,,( tttttt XLCHUU

5

Theoretical Framework Individuals maximize intertemporal Utility function:

subject to the following constraints:

t

tT

1t

Uδ1

1max

tttt

ttttt

tttttt

tttttt

STHTWL

YrATWwI

YAAMpC

VTHMHHH

)(

),;,,(

1

1

6

Theoretical Framework

The model yields a conditional labor supply function depending on (endogenous) health, and more generally a demand function for health

Empirically, health must be treated as an endogenous choice

Note that:– both equations are intrinsically dynamic– causality between health outcomes and labor

force participation can go both ways (alternative use of time)

*AT

SE

DKDE

CH

FR

SP IT

GR

BENL PL

Israel

USA (HRS)

First wave 2004/05: 28.000 individuals

Korea

Japan

China

UK (ELSA)

*PL

IR

*CZ

Data: SHARE

8

Distribution of Economically Active IndividualsMen

0.2

.4.6

.81

SE DK DE NL BE FR CH AT ES IT GR

Men working

50-54 55-59 60-64 65+

9

Economic Activity and Physical Health

0.2

.4.6

SE DK DE NL BE FR CH AT ES IT GR

Economic activity of 'functioning' respondents

worker retired but work retired allother

10

Generosity of Pension Systems

Measure of Social Security and Pension Wealth (SSW): – SSW defined as present discounted value of

expected future benefits from social security and pensions, discounted by both a given interest rate and the conditional survival probability

– In the absence of longitudinal data, one cannot measure dynamic incentives of the welfare system

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Distribution of Social Security Wealth Median - by age and gender

120

140

160

180

200

med

ian

SS

W (

'00

0s)

50 52 54 56 58 60 62 64 66 68 70age of respondent

men women

by age and genderSocial Security Wealth

12

Social Security Wealth and Household IncomeMedian

50,0

0010

0000

1500

0020

0000

SE DK DE BE FR CH AT ES IT GR

by countrySocial Security Wealth and Household Income

median SSW median hhld income

13

Social Security WealthMedian - by activity status

050

,000

1000

0015

0000

2000

00

SE DK DE BE FR CH AT ES IT GR

by country and activity status Median Social Security Wealth

pensioners workers

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Econometric Evidence

Probability [being Retired] Dependent variable: – Retired indicator = 1 if (self-reported as) currently

retired

0 otherwise– Sample: Workers and Pensioners - aged 50-70

about 13,000 observations

IV-probit

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Econometric Evidence

Basic regressors common to both models– indicators for gender, marital status, indicators for age 60

and age 65, age, age squared, years of schooling– With country dummies (Germany dummy omitted)

Measure of Social Security and Pension Wealth: SSWREL: SSW/total household income

IADL-Index for health: cumulative number of failures in

instrumental activities and activities of daily living

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Econometric Evidence

Instrumental variables

– Social Security Wealth (SSW)

Instrumented with occupational indicators

– IADL – index

Retrospective questions (“ever smoked”, “ever been depressed”, age of parents at death or if parent survived a target age), material inputs for health (vigorous physical activity) plus subjective survival probability

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Table 8. Probit Estimates - Marginal Effects (1) (2)

Respondent is male -0.138 -0.150(0.014) (0.016)

Respondent is married 0.172 0.171(0.021) (0.021)

Years of schooling -0.002 -0.002(0.001) (0.001)

(Age/10) -3.038(0.414)

(Age/10) squared 0.336(0.035)

Respondent is 60 0.019 0.475(0.024) (0.022)

Respondent is 65 0.151 0.551(0.037) (0.012)

SSWrel 0.062 0.070(0.002) (0.003)

IADL-index 0.016 0.018(0.002) (0.002)

age dummies yesinteraction dummies

(country*age) yes

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Table 8. Probit Estimates - Marginal Effects , cont (1) (2)

(0.027) (0.069)DK 0.078 0.231

(0.028) (0.053)NL -0.172 -0.162

(0.030) (0.071)BE 0.086 0.143

(0.034) (0.073)FR 0.102 0.104

(0.024) (0.056)CH -0.169 -0.175

(0.041) (0.103)AT 0.292 0.366

(0.016) (0.036)ES -0.080 0.017

(0.041) (0.089)IT 0.217 0.246

(0.020) (0.051)GR 0.192 0.355

(0.023) (0.040)age dummies yesinteraction dummies

(country*age) yes

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Table 9. Instrumental Variable Estimates - IV Probit

Coeff. M.E.

Respondent is male -0.256 -0.097(0.087)

Respondent is married 0.761 0.291(0.200)

Years of schooling 0.002 0.001 '(.003)

(Age/10) -11.049 -4.178( 2.137)

(Age/10) squared 1.074 0.406(0.189)

Respondent is 60 0.120 0.045(0.141)

Respondent is 65 0.074 0.028(0.186)

SSWrel 0.254 0.096(0.061)

IADL-index 0.087 0.033(0.026)

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Table 9. Instrumental Variable Estimates - IV Probit cont

Coeff. M.E.SE -0.268 -0.104

(0.129)DK 0.443 0.154

(0.164)NL -0.362 -0.141

(0.149)BE -0.071 -0.027

(0.188)FR 0.221 0.081

(0.136)CH -0.054 -0.021

(0.188)AT 0.573 0.192

(0.222)ES -0.262 -0.102

(0.195)IT 0.253 0.092

(0.171)GR 0.276 0.099

(0.231)

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Conclusions

Social Security Wealth and health still relevant after including a whole battery of dummies; still of the expected sign with IV estimate

Institutions matter, even after controlling for other factors

Future plans: model labor supply (hours of work) and labor demand