Age and Choice in Health Insurance: Evidence from Switzerland Peter Zweifel Dept. of Economics, University of Zurich peter.zweifel@econ.uzh.ch SAAN ACT.

Age and Choice in Health Insurance:Evidence from Switzerland

Peter Zweifel

Dept. of Economics, University of Zurich

peter.zweifel@econ.uzh.ch

SAAN ACT Launch Canberra, 29 November 2011

Socioeconomic InstituteUniversity of Zürich

Motivation

• Rising health care expenditure due to more ample coverage in compulsory health insurance since 1996 in Switzerland

higher premiums for health insurance• 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 InstituteUniversity of Zürich

Age and Choice Behavior 3 Hypotheses

H1: increased variance in asset "health" caused by health problems demand for comprehensive coverage increases with age (Arrow, 1971)

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 temporarily

Socioeconomic InstituteUniversity of Zürich

Discrete Choice Experiments (1)

• Allow 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 InstituteUniversity of Zürich

Discrete Choice Experiments (2)

• Comparison of utility values determined by indirect utility function (i=individual, j=product alternative)

• Choice between alternatives j and

}], , s y,, bp[ v], , s y,, bp[ vPr{ P iliilllijiijjjij

),s,y;b,p(vV ijiijjjij

• Decomposition into a stochastic and a deterministic part

]}, s, y, bp[w], s y,, bp[wPr P iillliijjjijilij {

Socioeconomic InstituteUniversity of Zürich

Setup of the Study (1)

• Sample of 1000 Swiss residents (older than 24)• Telephone survey (two contacts, in 2004)

– questions on utilization of the health care 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 InstituteUniversity of Zürich

Setup of the Study (2)

Which of these contracts would you choose?

premium reduction - CHF 50premium: CHF 290/month

This alternative contract My current contract

access to innovative treatments with delay of 3 years

innovation (status quo)

status quogenerics (status quo)

fewer treatments are coveredalternative medicine (status quo)

copayment: 10%copayment: 10%

deductible: CHF 1500 deductible: CHF 230

alternative contractstatus quo insurance contract

Example of a choice card

Socioeconomic InstituteUniversity of Zürich

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 InstituteUniversity of Zürich

Results

• Derive marginal willingness-to-pay (WTP) for Model 1

marginal WTP (in CHF)

standard errors (bootstrapped)

deductible -0.03205 0.01099

copayment -18.91 3.30448

alt.med (more coverage)

12.36 3.01507

generics -13.77 3.14571

innovation -38.39 3.36486

ji

ji

premium/v

b/v:MWTP

Socioeconomic InstituteUniversity of Zürich

2.970.001830.00543prem*a63+

-0.810.13653-0.10998rich

0.170.057810.00957hhsize

-1.490.12322-0.18403notreat

0.280.209560.05966poor

-2.630.17655-0.46353a63+

0.980.133520.13103a2539

-0.420.13744-0.05830sex

1.530.001410.00215prem*french

-2.290.00141-0.00322prem*a2539

zvalue s.e.  coefficient

Table 1c: Random-effects Probit estimation results (selected interactions)

Socioeconomic InstituteUniversity of Zürich

WTP for age groups (all interaction terms)- evaluated at the median individual of each subgroup

marg. WTP 25-39 marg. WTP 40-62 marg. WTP 63+

deduct -0.06(0.04)

deduct -0.05(0.02)

deduct -0.03(0.01)

copay -16.64(16.00)

copay -30.36(12.31)

copay -8.24(6.96)

alt.med(+) 67.51(44.88)

alt.med(+) 19.95(10.60)

alt.med(+) 0.77(6.38)

generics -31.77(22.00)

generics -13.81(9.57)

generics -8.91(6.90)

innov. -54.12(35.41)

innov. -25.50(11.57)

innov. -14.10(8.34)

Socioeconomic InstituteUniversity of Zürich

Age-specific results

Compensation demanded for a 20% copayment

(status quo 10%)

Compensation demanded for delayed access to innovations (3 yrs)

Socioeconomic InstituteUniversity of Zürich

Conclusion (1)

3 Hypotheses with respect to age

H1: increased asset variance 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 InstituteUniversity of Zürich

Conclusion (2)

• Estimation results for socioeconomic groups indicate preference heterogeneity Uniform health insurance contracts cause a

welfare loss

• Contracts with certain restrictions but lower premiums might be attractive also for the elderly, affording them a utility gain

Socioeconomic InstituteUniversity of Zürich

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 InstituteUniversity of Zürich

References (2)

• McFadden (2000), Economic Choices, AER, 91(3): 351-378.• Ryan, M. and K. Gerard (2003), Using discrete choice

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.