### Chap009

```CHAPTER
9
The Health Care Market
McGraw-Hill/Irwin
U.S. Expenditures of Selected Goods and
Services as Share of GDP (1960-2007)
Source: US Bureau of the Census [2009, pp. 95, 425], and National Income and Product Accounts
9-2
Social Insurance
• Social insurance - government programs that
provide insurance to protect against adverse
events
• Examples
–
–
–
–
Medicaid
Medicare
Social Security
Unemployment Compensation
9-3
How Health Insurance Works
• Expected Value
– Expected value (EV) = probability of outcome 1) *
(Payout in outcome 1) + probability of outcome
2)*(Payout in outcome 2) + … + (probability of
outcome n)*(Payout in outcome n)
9-4
Expected Value Computation
Draw cards from deck of cards
Draw spade, diamond or club and lose \$4
Probability of drawing heart = 13/52 = ¼
Probability of drawing spade, diamond or club = 39/52 = ¾
EV = (1/4)(\$12) + (3/4)(-\$4) = \$0
9-5
(A)
Insurance
Options
Income
Probability
of Staying
Healthy
Probability
of Getting
Sick
Option 1: No
Insurance
\$50,000
9 in 10
Option 2: Full
Insurance
(\$3,000
cover \$30,000 in
losses
\$50,000
9 in 10
Income
if She
Stays
Healthy
(B)
(C)
Income if
She Gets
Sick
Expected
Value
1 in 10
Lost
Income if
She Gets
Sick
\$30,000
\$50,000
\$20,000
\$47,000
1 in 10
\$30,000
\$47,000
\$47,000
\$47,000
Actuarially Fair Insurance Policy
9-6
Utility
B
UB
UD
UC
D
C
• Expected
Utility
A
• Risk
Smoothing
UA
20,000
47,000 50,000
Income
9-7
• Risk Aversion
9-8
The Role of Risk Pooling
• Insurance in a small population
• Insurance in a large population
• Law of large numbers
9-9
Adverse Selection in the Health Insurance
Market
• Asymmetric information
9-10
(A)
(B)
(C)
(D)
(E)
(F)
Expected Benefit
Expected Benefit
Expected Benefit
Probability of
Lost Income
Expected
Getting Sick
if Sick
Lost Income
(Differential
Emily
1 in 5 (High Risk)
\$30,000
\$6,000
\$0
\$3,000
\$1,500
Jacob
1 in 5 (High Risk)
\$30,000
\$6,000
\$0
\$3,000
\$1,500
Emma
1 in 5 (High Risk)
\$30,000
\$6,000
\$0
\$3,000
\$1,500
Michael
1 in 5 (High Risk)
\$30,000
\$6,000
\$0
\$3,000
\$1,500
1 in 5 (High Risk)
\$30,000
\$6,000
\$0
\$3,000
\$1,500
Joshua
1 in 10 (Low Risk)
\$30,000
\$3,000
\$0
\$0
-\$1,500
Olivia
1 in 10 (Low Risk)
\$30,000
\$3,000
\$0
\$0
-\$1,500
Matthew
1 in 10 (Low Risk)
\$30,000
\$3,000
\$0
\$0
-\$1,500
Hannah
1 in 10 (Low Risk)
\$30,000
\$3,000
\$0
\$0
-\$1,500
Ethan
1 in 10 (Low Risk)
\$30,000
\$3,000
\$0
\$0
-\$1,500
\$0
-\$15,000
\$0
Insurer's Net Profits
9-11
Government Intervention?
• Experience rating
• Experience rating and equity
• Community rating
9-12
Insurance and Moral Hazard
•
•
•
•
Moral hazard
Deductible
Co-payment
Co-insurance
9-13
Price per unit
Moral Hazard
Flat-of-the-curve medicine
P0
a
b
h
.2P0
0
Sm
Dm
M0
M1
Medical services per year
9-14
• The Elasticity of Demand for Medical Services
• Does Moral Hazard Justify Government
Intervention?
– Third Party Payment
9-15
Other Market Failures in the Health Care Market
• Information Problems
• Externalities
9-16
Do We Want Efficient Provision of Health Care?
• Paternalism
• The Problem of the Uninsured
– Who are the uninsured?
– Does health insurance improve health?
9-17
High Health Care Costs
Source: Organization for Economic Cooperation and Development [2008a].
9-18
Causes of Health Care Cost
Inflation
•
•
•
•
The Graying of America
Income Growth
Improvements in Quality
Commodity Egalitarianism
9-19
```