Utility and Health

1. 2 Utility and Health

2. Learning Goals • Master the model of health as a durable good and asset that produces happiness (“utility”). • Learn how lifestyle choices affect health, including both direct effects on health and indirect effects on earnings. • Discover how education affects health outcomes both directly and indirectly.

3. 2.1 How to Think About Health and Health Care Health as a Durable Good • Consumer demand is based on goods and services that create utility. • In this case, health creates happiness, rather than the actual services that add to health. • The demand for health care is a derived from the underlying demand for health itself. • Health can be considered to be a durable good. • Each person has an inherent “stock” of health. • Utility = U(X, H), where X is a bundle of other goods, and H is the (unobservable) stock of health. • Assume that more health is better.

4. 2.1 How to Think About Health and Health Care • Figure 2.1 shows different levels of utility, holding the amount of the alternative good constant. • Increasing the stock of health increases the utility received from other goods. • Increasing the bundle of other goods increases the utility derived from health.

5. 2.1 How to Think About Health and Health Care • Equivalently, Figure 2.2 shows indifference curves. • Different combinations of health and other goods that give the same amount of utility

6. 2.2 The Production of Health • A production function shows the transformation of inputs into outputs. • H = g(m), where m is medical care. • Assume that the marginal productivity of medical care is positive but diminishing. • Health outcomes also depend on disease (D). • H = g(m, D) • Diseases are affected differently by application of medical care.

7. 2.2 The Production of Health • In Figure 2.3, there are different responses to medical care. • For Disease I, there is little effect on health, and medical care offers some help, but plateaus. • For Disease II, the initial effect on health is worse, and care restores much of the stock of health quickly (high productivity of medical care) • For Disease III, the person is not very sick, and care does not help much (low productivity of medical care)

8. 2.2 The Production of Health • For every possible medical intervention, there is some point where the marginal productivity of medical care will become very low or negative. • Important to distinguish between average and marginal effects • It is overly simplistic to think of a single medical care production function. • Some medical interventions do not change the eventual level of health of the person, but can speed up the process of a “cure.” • A cut will heal on its own, but will heal faster with bandages and antibiotic ointment. • Lifestyle and other factors also have effects on the productivity of medical intervention.

9. 2.3 Health Through the Life Cycle • Our stock of health wears out over time (depreciation). • A typical person’s health stock might look like Figure 2.4, increasing during childhood, gradually declining with age, and punctuated by random events. • Path also depends on medical technology, as events that might have caused death in earlier periods. • At HMIN, stock of health care is so low that the person dies.

10. 2.3 Health Through the Life Cycle • Table 2.1 shows aggregate mortality rates, showing the dramatic decrease in health stock associated with aging. • Medical technology has reduced death rates for some groups over time. • Other societal changes are also factors. • TABLE 2.1 HERE

11. 2.4 A Model of Consumption and Health

12. 2.4 A Model of Consumption and Health

13. 2.4 A Model of Consumption and Health • McGinnis and Foege (1993) calculated deaths for various age groups associated with various identifiable sources, summing the effects of the “actual cause” across diseases. • 2004 study (Mokdad et al., 2004) repeated the study. • Around half of all deaths attributable to only a few “actual causes”, and almost all have to do with lifestyle choices.

14. 2.4 A Model of Consumption and Health Obesity • Climbing obesity rates • Likely to overtake tobacco as leading cause of death • Possible result of technological change that increases inactivity combined with falling food prices • Increased value of time causes shifts to fast food. • Increase portion sizes in packaged food and restaurant meals • Increase in number of restaurants • Also related to transportation choices • Working farther from home encourages driving rather than walking • Low gas prices encourage driving

15. 2.4 A Model of Consumption and Health • Obesity is strongly linked to mortality rates • Figures show relationship between mortality and BMI. • Vertical lines show relative risk (log) • Horizontal bars show 95% confidence interval around the mean values • A male with a BMI of 40 has a relative risk of dying that is more than 2.5 times greater than the lowest risk group. • Calle et al., 1999 • Replicated in many studies • Also associated with other diseases (diabetes, heart disease, etc.) • Estimates suggest that obese people spend 40% more on health care and account for 10% of all health spending.

16. 2.4 A Model of Consumption and Health Tobacco and Health • Tobacco use long linked to health problems • But consumers maximize utility, not longevity • Information may play a role • Smoking shows an inverse relationship with educational attainment • In 2009, 20.6% of U.S. adults smoked. • Less than high school education: 26.5% • High school diploma: 25.1% • Some college: 23.3% • Bachelor’s degree: 11.1% • Graduate degree: 5.6% • Dube et al, 2010

17. 2.4 A Model of Consumption and Health Alcohol and Health • Complicated effects • Pattern and intensity matters, even holding quantity constant • Heavy drinking worse than light; binge drinking has separate and distinct negative effects. • Relates to liver cirrhosis, some cancers, heart disease • Drinking and driving increases risk of vehicle fatalities • Type of alcohol matters • Groenbaek et al., 2000: relative risk of cancer death is double for heavy drinkers of distilled spirits • Wine reduces risk of heart disease for moderate users • Relationship with lifetime earnings also mixed • Moderate drinking may be associated with improvements in earning; heavy drinking lowers lifetime earnings, largely from reduced labor force participation

18. 2.4 A Model of Consumption and Health Alcohol and Health • Relationship between alcohol and education • Education affects drink of preference as well as frequency of use • Wine drinkers more highly educated; spirit drinkers less educated • Increased education correlated with more drinkers, but fewer heavy or binge drinkers

19. 2.4 A Model of Consumption and Health Education and Health • Many studies show associations between education and health outcomes • However, difficult to determine causality • Fuchs (1982) relates investments in education and health may be related to rates of time preference • Education increases earnings, and higher earnings allow people to live in safer communities and buy things that improve health • Higher earnings could also mean purchases of less healthy goods • Health also affects earning power