Age and Choice in Health Insurance: Evidence from Switzerland

1. Age and Choice in Health Insurance:Evidence from Switzerland Karolin Becker und Peter Zweifel Socioeconomic Institute, University of Zurich pzweifel@soi.unizh.ch ARIA Annual Meeting Washington DC, 6-9 August, 2006

2. Motivation • Rising health care expenditure due to more ample coverage in compulsory health insurance  higher premiums for health insurance • Expansion of benefits in1996  increasing welfare loss due to uniformity in the presence of preference heterogeneity (Cutler and Zeckhauser, 1997) • Political debate focuses on the cost side. • Here, issues relate to the benefit side: ...what is the compensation asked by Swiss consumers for accepting more stingy contracts? ... Will such new options not be rejected by the elderly in particular? Socioeconomic Institute University of Zürich

3. Age and Choice Behavior 3 Hypotheses H1:increased variance in asset"health" caused by health problems  demand for comprehensive coverage increases with age (Arrow, 1973) H2: demand for health insurance follows the value of life over the life cycle  demand for coverage decreases beyond the age of ca. 40 (Shepard and Zeckhauser, 1984) H3: transition to retirement causes transitory reduction in variance of "health" and in value of life  demand for coverage decreases Socioeconomic Institute University of Zürich

4. Discrete Choice Experiments (1) • Allows individuals to express preferences for non-marketed goods • Is based on the Random Utility Model (Luce, 1959; Manski and Lerman 1977; McFadden, 1973 and 2001) • individuals choose alternative with the highest utility (hypothetical choice) • choices are deterministic, but the researcher cannot observe all determinants of utility Socioeconomic Institute University of Zürich

5. Discrete Choice Experiments (2) • Comparison of utility values determined by indirect utility function (i=individual, j=product alternative) • choice between alternatives j and  • decomposition into a stochastic and a deterministic part Socioeconomic Institute University of Zürich

6. Setup of the Study (1) • Sample of 1000 Swiss residents (older than 24) • Telephone survey (two contacts) • questions on utilization of the health system and socioeconomic variables • DCE: 10 choices per individual (status quo vs hypothetical alternative) • Attributes considered: • annual deductible (deduct) • copayment rate (copay) • alternative treatment methods (altmed) • list of medications (generics) • restricted access to innovations (innovation) • monthly premium per capita (premium) Socioeconomic Institute University of Zürich

7. status quo insurance contract alternative contract deductible: CHF 230 ($177) deductible: CHF 1500 ($1155) copayment: 10% copayment: 10% alternative medicine (status quo) fewer treatments are covered generics (status quo) status quo innovation (status quo) access to innovative treatments with delay of 2 years premium: CHF 290/month premium reduction - CHF 50 Which of these contracts would you choose? My current contract  This alternative contract  Setup of the Study (2) example of a choice card Socioeconomic Institute University of Zürich

8. Estimation strategy • Random-effects Probit specification • Model 1: Serves to check for the relevance of attributes • Model 2: Designed to capture age-specific effects simple model, only product attributes included controlling for all relevant socioeconomic variables (interaction terms) Socioeconomic Institute University of Zürich

9. Results • Derive marginal willingness-to-pay (WTP) for Model 1 Socioeconomic Institute University of Zürich

10. Socioeconomic Institute University of Zürich

11. Table 1b: Random-effects Probit estimation results (selected interactions)  coefficient s.e.  zvalue  deduct*sexm 0.00015 0.00006 2.34 deduct*a63+ 0.00020 0.00010 1.93 deduct*rich 0.00028 0.00009 3.07 deduct*poor -0.00027 0.00011 -2.54 deduct2*hhsize -1.63e-08 7.51e-09 -2.16 copay*a63+ 0.26306 0.13380 1.97 copay*notreat 0.29779 0.09277 3.21 altmed*sexm -0.16156 0.08891 -1.82 innov*a2539 -0.23113 0.11262 -2.05 innov*french 0.24711 0.11308 2.19 Socioeconomic Institute University of Zürich

12. Table 1c: Random-effects Probit estimation results (selected interactions)  coefficient s.e.  zvalue  prem*a2539 -0.00322 0.00141 -2.29 prem*a63+ 0.00543 0.00183 2.97 prem*french 0.00215 0.00141 1.53 sex -0.05830 0.13744 -0.42 a2539 0.13103 0.13352 0.98 a63+ -0.46353 0.17655 -2.63 rich -0.10998 0.13653 -0.81 poor 0.05966 0.20956 0.28 hhsize 0.00957 0.05781 0.17 notreat -0.18403 0.12322 -1.49 Socioeconomic Institute University of Zürich

13. WTP for age groups (all interaction terms)- evaluated at the median individual of each subgroup Socioeconomic Institute University of Zürich

14. Compensation demanded for a 20% copayment (status quo 10%) Compensation demanded for delayed access to innovations (3 yrs) Age-specific results Socioeconomic Institute University of Zürich

15. Conclusion (1) 3 Hypotheses with respect to age H1: increased assetvariance demand for coverage increases with age H2: demand follows the value of life  demand for coverage decreases with age H3: transition to retirement  demand for coverage temporarily decreases with age • H1 cannot be confirmed (contrary to popular belief) • H2 and H3 tend to be confirmed for the median individual Socioeconomic Institute University of Zürich

16. Conclusion (2) • Estimation results for socioeconomic groups indicate preference heterogeneity • Uniform insurance contracts cause a welfare loss • Contracts with certain restrictions and lower premiums might be attractive also for the elderly, affording them a utility gain Socioeconomic Institute University of Zürich

17. Links • SOI-Working Paper: http://www.soi.unizh.ch/research/wp/wp0410.pdf • Study Report (German): http://www.soi.unizh.ch/staff/becker/becker-zweifel_summary.pdf Socioeconomic Institute University of Zürich

18. References (1) • Arrow, K. (1971), Alternative approaches to the theory of choice in risk-taking situations, in: Arrow, K., Essays in the Theory of Risk-bearing, Amsterdam: North-Holland, 1-44. • Ben-Akiva, M. and S.R. Lerman (1985), Discrete Choice Analysis, Cambridge: The MIT Press. • Felder, S. (1997), Costs of dying: alternatives to rationing, Health Policy, 39: 167-176. • Louvière, J.L., Hensher, D.A. and J.D. Swait (2000), Stated Choice Methods. Analysis and Applications, Cambridge: University Press. • Luce, D. R. (1959), Individual Choice Behaviour, New York: Wiley and Sons. • Manski, C. and S.R. Lerman(1977), The estimation of choice probabilities from choice based samples, Econometrica, 45(8): 1977-88. Socioeconomic Institute University of Zürich

19. References (2) • McFadden (2000), Economic Choices, AER, 91(3): 351-378. • Ryan, M. and K. Gerard (2003), Using discrete choices experiments to value health care programmes: current practice and future reflections, Applied Health Economics and Health Policy, 2(1): 55-64. • Samuelson, W. and R.J. Zeckhauser (1988), Status quo bias in decision making, Journal of Risk and Uncertainty, 1: 7-59. • Shepard, D.S. and R.J. Zeckhauser (1984), Survival and consumption, Management Science, 30(4): 423-439. • Telser H. et al. (2004), Was leistet unser Gesundheitswesen?, Schlussbericht, Bern. Socioeconomic Institute University of Zürich