Retirement Choice Modelling in Dynamic Microsimulation

1. Retirement Choice Modelling in Dynamic Microsimulation Jinjing Li NATSEM, Australia Cathal O’Donghue Teagasc, Ireland 18 May 2012

2. Why retirement behaviour modelling in Microsimulation • Ageing pressure • Evaluate current pension system • Reform projection • Microsimulation as a tool Retirement Behaviour Modelling in Microsimulation

3. Social Economic Variable Matching • Discrete, non-Behavioural model • It uses a range of personal characteristics to explain the retirement • Easy to estimate • Difficulties in policy simulation, not even “status quo” • Missing link between incentives and outcomes Current Retirement Models in Microsimulation

4. Structural Model • Option Value Approach from Stock & Wise (1990) • Typically Individual based • Put monetary incentive directly in utility optimizing process • Dynamic Programming Model from Rust (1987) • More theoretical correct functions • Complex algorithm, approximation needed • Other Models • Replacement rate based (e.g. 2/3 rules) • Hazard Model Alternative Approach

5. Policy independent (Structural Model) • Reflect policy changes to the finest details • Use only variables that are able to simulate • Adaptive to the existing data • Good predictive power • Reasonable computation time What we need in a retirement choice simulation model

6. Behaviour Modelling for Simulation

7. Define the attributes • Incorporate lifetime information into the options • Income Stream: Lifetime income (Actual and Simulated using DMM) • Leisure Stream: Free time (Actual and Simulated using DMM) • Complementary leisure for spouses • Control for Other Household/Personal Characteristics (Age and Health) • Simple ML Function: Conditional Logit Estimation

8. Overview of the modelling process Interactions with Tax Benefit System Capture the Dynamics of Pension Reforms and Complex Career Trajectory

9. LII Ireland Dataset • Observed Retirement instead of Reported Retirement Data

10. Policy Background

11. Estimation Result

12. Positive marginal effect for household income stream and leisure streams • People enjoy leisure more as they get older • Positive complementary leisure • Dual career households are very different from single worker household • Females seem to have put higher value on leisure • Health Not Significant Estimation Result

13. More than 50% households have an maximum error of less than 2 years Predictive Power – Difference between Real and Simulated Retirement Age

14. Postponing minimum age for state pension from 65 to 70 A Simulation Exercise

15. This Retirement Model • Lifetime framework • Capture the dynamics of pensions system • Household based, sensitive to policy change • Uses existing microsimulation framework • Static Microsimulation (Tax benefit system) • Dynamic Microsimulation (for earning trajectory prediction) • Using estimation result as the basis for further simulation • Compared with traditional approach where Iifetime earnings are very roughly approximated • Improve the relevancy in policy debate as more policies are reflected in the model • Takes into account the heterogeneities in career trajectories Summary

16. Thank you