Estimating the Impact of Medication on Diabetics' Diet and Lifestyle Choices

from such trials. Large benefits are more likely if the company assumes that all the health
benefits possible from pharmaceuticals would be realized. Such a prediction would not allow for
the possibility that individuals might adjust to the possibility of using medicine. The prediction
would assume that individuals do not make themselves better off by modifying their diet and

∂B

lifestyle choices along with taking medicine, in effect----= 0.

∂M

To achieve the company’s forecasts requires FM to be identically zero. One could make
assumptions that make FM identically zero. For example, if utility were linear in health and
health were linear in medicine, U_H = k ⇒ U_HH = 0and H_M = l ⇒ H_MM = 0. Adding the

∂B

requirement that medicine is universally free, PM = 0, implies FM = 0 and thus---= 0. But

M         M        _∂M

giving up concavity and the notion that medicine might command a positive price are extreme
and unsupportable assumptions.

∂B    ∂B     ∂B

The overall change in behavior depends on the relative magnitudes of — and---. If ---is

∂η   ∂M   ∂M

∂B

relatively small compared to the absolute value of —, the overall response to bad health news

∂η

would be real attention to diet and exercise—a substantial change in diet and lifestyle. As the

∂B                                       ∂B

magnitude of---rises relative to the magnitude, in absolute value, of —, the sum of the two

∂M                                 ∂η

partials approaches zero, and diet and exercise concerns diminish. If the sum is zero, diet and
lifestyle return to the level chosen before the bad news arrived. In this case, the increased risk

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