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2 Utility and Health 17 January 2019.

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1 2 Utility and Health 17 January 2019

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. 17 January 2019

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. 17 January 2019

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. 17 January 2019

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 17 January 2019

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. 17 January 2019

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) 17 January 2019

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. 17 January 2019

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. 17 January 2019

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 17 January 2019

11 2.4 A Model of Consumption and Health
17 January 2019

12 2.4 A Model of Consumption and Health
17 January 2019

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. 17 January 2019

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 17 January 2019

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. 17 January 2019

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 January 2019

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 17 January 2019

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 17 January 2019

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 17 January 2019


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