Understanding Health, Ageing and Retirement in Europe Prof. Axel Börsch-Supan, Ph.D.

1. Understanding Health, Ageing and Retirement in Europe Prof. Axel Börsch-Supan, Ph.D. Director, Mannheim Research Institute for the Economics of Aging (mea) University of Mannheim, Germany

2. Contents 1.Gaps of knowledge: • Reforms and professional policy design • Five examples and key policy questions: Why links among health and economics are so important to understand aging in Europe 2. SHARE: • Data needed for professional policy design

3. Conditions for active and healthy ageing Income security and personal wealth  Public policy dynamic longitudinal Kinship and social networks, living arrangements Physical and mental health, disability, mortality

4. Example 1: Pension Systems and Labor Force Participation

5. Key Policy Questions: Early retirement costs 25-33% of pension budget • Why is retirement so early in some European countries? • How important are economic reasons (incentives, generosity) versus non-economic determinants (health, work place conditions, macroeconomics)? • Where are incentives particularly strong, and how can they be changed to become more fair? • How true are the productivity myths? How to make work places more attractive for older workers?

6. Example 2: Economic and Epidemiological Disability

7. Key Policy Questions: If old-age pensions (or unemployment benefits) become less generous, disability may pick up • Why is disability prevalence in Europe so different? • What is the „true“ prevalence of disability? (Indicators needed for method of open policy coordination) • How to avoid type-I (healthy people get disability pensions) and type-II (truly disabled persons are denied disability benefits) errors?

8. Example 3: Savings and Pension Reforms

9. Key Policy Questions: Pension reform will substitute private savings for reduced state support • Will people voluntarily fill the emerging gaps by their own own provision? • If not, what kinds of incentives are required? • If people save more for retirement and health care, where does it come from? Other savings? Consumption? Bequests? • Need indicators based on micro data to build „early warning system“

10. Example 4: Health care reformCosts, efficiency, insurance

11. Key Policy Questions: Health care reform is cutting costs and enforces managed care models • Will people pick up uninsured health care by own expenses? • Who get‘s left out if public health care is reduced? • How regionally diverse is health care quality? • Do managed-care systems produce similar health outcomes at lower costs?

12. Example 5: Mortality and economic status

13. Key Policy Questions: • How different is mortality/morbidity by socio-economic status? What are the causes? Which direction goes the causality? • How fast does mortality, morbidity (disability) change? What are the implications for health care costs? • How different is health care utilisation by socio-economic status? • How large will demand for long-term care be? How widespread is family care? How will it change?

14. Why is this of particular interest for Europe? • Sustainability of pension and health care insurance:The aging process is particularly pronounced in Europe • Incentive effects of public policies: Labor force disincentives and health market distortions particularly large in Europe -- aggravating the problems of sustainability • Cross country comparisons: To learn from experiences (and institutional differences) in other countries, one needs comparable data. The EU represents an ideal laboratory to observe (still) many different policy approaches (from Northern and Southern welfare states to UK liberal society).

15. 2. The SHARE Survey Data collection for professional policy design • Inter-disciplinary:Health-Economics-Sociology • Cross-national:Currently 13 countries involved:Denmark, France, Germany, Greece, Italy, Netherlands, Spain, Sweden, + Austria, Belgium, Switzerland, + United Kindom, United States • Longitudinal: Ageing is a process, not a state

16. What data will be collected? (1) • 1. Health variables: Self-reported health, physical functioning (ADLs, IADLs, walking speed, grip strength), mental health and cognition, health behaviors and health service utilization, insurance coverage. In the longer run: bio-medical data. • 2. Economic Variables: Current work activity and job characteristics (job demands, flexibility, hours worked, opportunities to work post-retirement age), employment history, pension rights, sources and composition of current income, wealth and consumption.

17. What data will be collected? (2) • 3. Family and Social Network: Family structure, assistance within families, intergenerational transfers of assets, money and time, social networks, proximity to relatives and activities (shopping, amusement), time use after retirement, volunteer activities. • Psychological data: Expectations, preferences, risk aversion, time horizon • Demographic data: Basics (age, gender, marital status...), housing, education • Data Links: Where available: administrative earnings, social security, employer provided information.

18. Prototype Survey • English pilot: September 2002 • Full pilot: June 2003 • Full pretest: January-February 2004 (n=750) • Main prototype survey: April-Sept. 2004 (1500 HHs in 11 countries, n=22.000) • Evaluation: AMANDA (5. Framework Program) • Bi-annual panel: 6. Framework Program