it is never too late? evidence on increasing the retirement age in a transition economy

Increasing retirement age in transition

It is never too late?Evidence on increasing the retirement age in a transition economy

Pawel Strzelecki12 Joanna Tyrowicz31

1National Bank of Poland2Warsaw School of Economics

3University of Warsaw

IZA / World BankJune 2015


Motivation and insights from literature

Motivation I

Issues common to many (not only transition) countries

Longevity ...

... aggravated with (really!) early retirement, see Fox (1997)⇒ average female exit age in 2000 in PL: 52 years

Solutions:

introduce universal DC systems⇒ stronger link between contributions and benefitsPL in 1997-1999, but temporarily keep occupational privileges

gradually reduce the occupational privileges⇒ keep people in activity longerPL in 2004: extend occupational privileges and additional exceptionsPL in 2009: only medical criteria for early retirement



Motivation II



Motivation I

In about 2007 things start to change



Motivation II



Motivation III

In 2009 reform of early retirement

Eligibility for pension benefits

Prior to 2009 After 2009W born before 1954 Experience: 25, age: 55 Experience: 25, age 55W born after 1954 Experience: 25, age: 55 Experience: 25, age: 60*M born before 1949 Experience: 30, age: 60 Experience: 30, age: 65M born after 1949 Experience: 30, age: 60 Experience: 30, age: 65*

* selected occupations based on medical criteria

Bottom line: 85% of workers lost eligibility for early retirement



Earlier insights

For the US (or other advanced economies): Krueger and Pischke (1992);Jensen and Richter (2003); Snyder and Evans (2006); Liebman et al.(2009); Mastrobuoni (2009); Blau and Goodstein (2010); Behaghel andBlau (2012), summarized wonderfully by Manoli and Weber (2014)

For transition economies:Jensen and Richter (2003) for RussiaDanzer (2013) for Ukraine

Bottom line: “pass-through” is not complete, but people respond tochanges in incentives



Our objectives

Take the (huge!) Polish reform of 2009,

exploit the discontinuity

and inquire:

Reduction in pension benefits take-up

Increase in labor force participation

Reduction in outflows to inactivity



Table of contents

1 Motivation and insights from literature

2 Data

3 Results

4 Conclusions

5 References


Data

Our data - Labor Force Surveys (2007-2012)

Exploit the rotating panel

Compute the age on Jan 1st, 2009 (adequate up to 1 month)

Focus on transitions (earlier literature focuses on stocks)

Control for confounding factors (age, education, household structure)

Control for eligible/ineligible occupations


Data

Stocks - that everybody loves so much: pension take-up I


Data

Stocks - that everybody loves so much: pension take-up II


Data

Stocks - that everybody loves so much: exit age (women)


Data

Stocks - that everybody loves so much: exit age (men)


Data

Descriptives I

Before the reform After the reformeligible ineligible eligible ineligible

Number of individuals 68,788 562 2,083 38,535

Labor force participation rate (in %) 22.1 18.3 51.1 42.9Share of pension benefit recipients (in %) 52.7 12.6 39.4 19.3

Quarterly transition probabilities:remain active 0.95 0.75 0.94 0.96exit to early pension 0.05 0.03 0.06 0.03exit to inactivity (age) 0.05 0.25 0.06 0.04exit to inactivity (exp) 0.05 - 0.05 0.03


Data

Descriptives II


Individual characteristics (in %):Share of women 60.8 81.0 29.6 56.8

Tertiary education 12.5 3.9 11.5 13.2Secondary education 37.1 26.5 32.8 35.8Vocational 29.4 29.0 38.9 33.4Primary 20.9 40.6 16.8 17.6

Households with:other worker (in %) 44.1 45.6 49.4 50.9other pension (in %) 50.7 43.4 46.6 38.6other child (in %) 12.8 16.2 13.0 12.5


Data

Descriptives II


Individual characteristics (in %):Share of women 60.8 81.0 29.6 56.8Tertiary education 12.5 3.9 11.5 13.2

Secondary education 37.1 26.5 32.8 35.8Vocational 29.4 29.0 38.9 33.4Primary 20.9 40.6 16.8 17.6



Data

Descriptives II


Individual characteristics (in %):Share of women 60.8 81.0 29.6 56.8Tertiary education 12.5 3.9 11.5 13.2Secondary education 37.1 26.5 32.8 35.8Vocational 29.4 29.0 38.9 33.4Primary 20.9 40.6 16.8 17.6



Results

Aggregate results I

Please, remember, this was a HUGE reform (5 years, 85% affected)


Results

Aggregate results II

Model Coefficient (Std. Err.) z-statistic Significance level(a) transition to early retirement - 6%

- sharp -0.0108 0.0066 1.637 0.102- fuzzy -0.0118 0.0072 -1.637 0.102

(b) remaining economically active - 94%- sharp 0.0270 0.0095 -2.836 0.005- fuzzy 0.0308 0.0109 2.835 0.005

(c) transition to inactivity (adequate age) - 6%- sharp -0.0269 0.0095 2.829 0.005- fuzzy -0.0308 0.0109 -2.828 0.005

(d) transition to inactivity (with sufficient tenure) - 5%- sharp -0.0221 0.0095 2.324 0.020- fuzzy -0.0252 0.0108 -2.324 0.020


Results

Aggregate results III


Results

Aggregate results IV

But don’t people always retire at retirement?


Results

Placebo tests - eyeballing I

Exit to retirement


Results

Placebo tests - eyeballing II

Remain active


Results

Placebo tests - eyeballing III

Exit to inactivity


Results

Confounding evidence I

Probit of likelihood to get a significant estimator

(1) (2) (3) (4)

Reform quarter 0.3310*** -0.3311*** 0.3309*** 0.3312***(0.048) (0.048) (0.048) (0.048)

Treatment 0.0000 0.0000 -0.0000 0.0000(0.016) (0.016) (0.016) (0.016)

Other retired in hh -0.0437(0.028)

Other worker in hh -0.0331(0.029)

Kid in hh -0.0647**(0.027)

Female -0.0229(0.029)

FE for outcome variables Yes Yes Yes YesObservations 2,576 2,576 2,576 2,576


Results

Confounding evidence II

Probit of likelihood to get a significant estimator

(1) (2) (3) (4)

Reform quarter 0.3310*** -0.3311*** 0.3309*** 0.3312***(0.048) (0.048) (0.048) (0.048)

Treatment 0.0000 0.0000 -0.0000 0.0000(0.016) (0.016) (0.016) (0.016)

Primary -0.0637** -0.0628** -0.0619** -0.0657**(0.027) (0.027) (0.027) (0.027)

Gymnasium -0.0374 -0.0363 -0.0354 -0.0395(0.029) (0.029) (0.029) (0.029)

Vocational -0.0784*** -0.0775*** -0.0767*** -0.0802***(0.026) (0.026) (0.026) (0.026)

Tertiary -0.0361 -0.0350 -0.0341 -0.0383(0.029) (0.029) (0.029) (0.029)

FE for outcome variables Yes Yes Yes YesObservations 2,576 2,576 2,576 2,576


Conclusions

Conclusions

Discontinuity from the reform: small relative to the scope of the reform

Almost no heterogeneity

Would have happened even without the reform?


Conclusions

Questions or suggestions?

Thank you!


References

References

Behaghel, L. and Blau, D. (2012). Framing social security reform: behavioral responses to changesin the full retirement age. American Economic Journal: Economic Policy, 4:41–67.

Blau, D. and Goodstein, R. (2010). Can social security explain trends in labor force participationof older men in the United States? Journal of Human Resources, 45:328–363.

Danzer, A. (2013). Benefit generosity and the income effect on labour supply: quasi-experimentalevidence. Economic Journal, 123:1059–1084.

Fox, L. (1997). Pension reform in the post-communist transition economies. In Nelson, J. M.,Tilly, C., and Walker, L., editors, Transforming Post-Communist Political Economies. NationalAcademy Press, Washington, D.C.

Jensen, R. and Richter, K. (2003). The health implications of social security failure: evidence fromthe Russian pensions. Journal of Public Economics, 88:209–236.

Krueger, A. and Pischke, J.-S. (1992). The effect of social security on labor supply: a cohortanalysis of the notch generation. Journal of Labor Economics, 10:4120–4437.

Liebman, J., Luttmer, E., and Seif, D. (2009). Labor supply responsens to marginal Social Securitybenefits: Evidence from discontinuities. Journal of Public Economics, 93:1224–1233.

Manoli, D. and Weber, A. (2014). Intertemporal substitution in labor force participation: evidencefrom policy discontinuities. CESifo Working Paper Series 4619, CESifo.

Mastrobuoni, G. (2009). Labor supply effects of the recent social security benefit cuts: Empiricalestimates using cohort discontinuities. Journal of Public Economics, 93(11):1224–1233.

Snyder, S. and Evans, W. (2006). The effect of income on mortality: evidence from social securitynotch. Review of Economics and Statistics, 88:482–495.

it is never too late? evidence on increasing the retirement age in a transition economy

Economy & Finance

increasing retirement

transition motivation

literature motivation

confounding factors

transition economies

literature earlier insights

transition data stocks

transition countries