Statutory Pension Age, (Pensions Wealth) Present and Future Retirement
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1 1 Statutory Pension Age, (Pensions Wealth) Present and Future Retirement Modelling Retirement with Preference Heterogenity, Microsimulation and Policy Analisys (work in progress)* Søren Arnberg 1), Anne-Line Koch Helsø 2) & Peter Stephensen 3) 1) Ministry of Finance, 2) University of Copenhagen and DREAM, 3) DREAM * This presentation presents prelimerary results that illustrates the joint work analyzing retirement by the authors. These results do not necessarily represent the collective view of the Ministry of Finance.
2 CONTENTS 1. Motivation 2. The Danish Settings 3. Retirement model 4. Microsimulation and predicting future retirement 5. Policy experiments 2
3 RESEARCH QUESTION 1 Recent Reforms of the Pension System (26 & 211) Indexation of Statutory Retirement Ages Mandatory Labour Market Pensions Expanded during the 199 ties Future generations will have large pension savings Will this result in earlier retirement and weaken fiscal sustainability? Pension Wealth divided by Labour Income 6 Years prior to OAP Men Pension Wealth divided by Labour Income 6 Years prior to OAP Women Unskilled Skilled Short higher education Bachelor Master Unskilled Skilled Short higher education Bachelor Master (OIM) (OIM) 3
4 2: FISCAL BURDEN OF AGING POPULATIONS Cutting Pension Benefit Levels (E.g. Germany, Sweden) Postponing statutory retirement ages (E.g. Denmark) Indexation of Early Retirement Age and Old Age Pension Age Year Year Old Age Pension Age Early Retirement Age Life Expectancy How will indexation affect the effetive retirement ages...(and fiscal sustainability)?
5 EARLY RETIREMENT SCHEME IS REDUCED Members of ERP-scheme (share of birth cohort) 5
6 APPROACH Recent Approaches Estimate Structural Model and Policy Experiments (e.g. French 25 & French & Jones 211) Evaluate reforms using dif in dif and similar (e.g. Cribb, Emmerson & Tetlow 216, Schaarup, Schultz & Søegaard 213) Using survey data (e.g. Maurer, Mitchell, Rogalla, Schimetschek 214) Our approach Estimate a Structural Model (using Danish Register Data) Microsimulation Model (MFI or SMILE): Future Income & Pension Saving Policy experiments: On older chohorts (with observed retirement) and future cohorts (unobserved retirement) Reforms used for model validation (increase in early retirement ages) 6
7 THE DANISH SETTINGS Old Age Pensions System From 65 and the rest of one s life (means tested) Weak economic incentive (OAP benefit level is increased with later retirement) Early retirement Scheme From 6-64 years, membership based (means testet) Strong economic incentives to postpone retirement until age 6 (62) Have to work until 6 to claim benefits Recent reforms / changes of economic incentives Increase in early retirement and old age pension ages Early retirement scheme reduced Labour market pensions scheme is maturing Healthy aging? 7
8 TRENDS IN DANISH RETIREMENT Departure from employment to voluntary retirement for cohorts Pct. 1 Pct (2) 1954(2) 8
9 RETIREMENT MODEL: - UTILITY SPECIFICATION 9
10 AGE RELATED PREFERENCES (ATTRITION) utility utility k 1 k 1 r r 1
11 COHORT TREND IN ATTRITION Utility Utility k 1 k 1 r r 11
12 DATA Danish register data, 33% of cohort employed at age 54 About 42. individueals First data year 1993, last data year 214 (215) We observe: Retirement age, Finansial Wealth, Pension Wealth, Salery, Benefit entitlements, spouses, housing etc. We simulate for hypothethical retirement ages: Counter-factual salaries Pensions (ERP, OAP, counterfactual private pension savings, housing benefits etc.) and taxes 12
13 ESTIMATION AND IDENTIFICATION Outer search routine evaluates log likelihood at parameter combination Given inner EM algorithm derives population distribution in leisure preferences Estimate functional form Assuming consistency between chosen retirement age and variation in economic incentives across retirement ages Validate model across pension reform: indexation ERP age 13
14 ESTIMATION RESULTS WITH SOCIAL DUMMY 14
15 ESTIMATION RESULTS WITH SOCIAL DUMMY - PREFERENCE DISTRIBUTION 15
16 MODEL FIT - MODEL WITHOUT SOCIAL NORM 16
17 MODEL FIT - MODEL WITH SOCIAL NORM 17
18 EKSTERNAL VALIDATATION - PREDICTION OF RETIREMENTS FOR YOUNGER COHORTS (NOT USED IN ESTIMATION OF ECONOMETRIC MODEL) 18
19 POLICY EXPERIMENT 1: INCREASE IN OAP AGE (MODELS WITHOUT ATTRITION TREND) 19
20 POLICY EXPERIMENT 1: INCREASE IN OAP AGE SMALL CHANGE IN ECONOMIC INCENTIVES Figure Average discounted wealth for skilled male workers at retirement age 68 (cohort 1958, non ERP-members) Figure Average discounted wealth for skilled female workers at retirement age 68 (cohort 1958, non ERP-members) Baseline Experiment -6-6 Baseline Experiment -6 Public Pensions Wages Taxes Public Pensions Wages Taxes Private Pensions Financial Wealth Private Pensions Financial Wealth 2
21 POLICY EXPERIMENT 1: INCREASE IN OAP AGE (MODELS WITH ATTRITION TREND) 21
22 POLICY EXPERIMENT 1: INCREASE IN OAP AGE (MODELS WITH ATTRITION TREND) 22
23 POLICY EXPERIMENT 1: INCREASE IN ERP AGE LARGE CHANGE IN ECONOMIC INCENTIVES Figur 1 Average discounted wealth for skilled male workers at retirement age 63 (cohort 1958, ERP-members) Figur 2 Average discounted wealth for skilled female workers at retirement age 63 (cohort 1958, ERP-members) Baseline Experiment -4-4 Baseline Experiment -4 Public Pensions Wages Taxes Public Pensions Wages Taxes Private Pensions Financial Wealth Private Pensions Financial Wealth 23
24 POLICY EXPERIMENT 1: INCREASE IN ERP AGE (MODELS WITHOUT ATTRITION TREND) 24
25 POLICY EXPERIMENT 1: INCREASE IN ERP AGE (MODELS WITH ATTRITION TREND) 25
26 POLICY EXPERIMENT 2: ABOLISHING ERP- SCHEME (EFFECT IN ABOUT 225 & 25) 26
27 POLICY EXPERIMENT 2: ABOLISHING OF ERP- SCHEME (ECON INCENTIVES IN 225) Table Average change in discounted effective wealth from abolishing ERP (ERP-members) Cohort 1958 at retirement age 63 Group 1., Men, Unskilled -42 Men, Skilled -4 Men, higher education (short) -3 Men, higher education (bachelor) -29 Men, higher education (master) -18 Women, Unskilled -47 Women, Skilled -47 Women, higher education (short) -42 Women, higher education (bachelor) -39 Women, higher education (master)
28 POLICY EXPERIMENT 2: ABOLISHING OF ERP- SCHEME (ECON INCENTIVES IN 225) Figure Average discounted wealth for skilled male workers at retirement age 63 (cohort 1958, ERP-members) Figure Average discounted wealth for skilled female workers at retirement age 63 (cohort 1958, ERP-members) With ERP Benefits Without ERP Benefits -4-4 With ERP Benefits Without ERP Benefits -4 Public Pensions Wages Taxes Public Pensions Wages Taxes Private Pensions Financial Wealth Private Pensions Financial Wealth 28
29 29 Thank You
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