place comparisons are needed; for example, the State Department needs to make cost-of-living adjustments for employees living in foreign countries or when an employer wants to adjust salaries for the cost of living in different U.S. cities. A cost-of-living index that compares Phoenix with San Francisco would surely recognize that homes in Phoenix require more air-conditioning than homes in San Francisco. It is hard to see the purpose of a conditional cost of living computed under the assumption that Phoenix has San Francisco’s climate, or vice versa. Yet it is precisely this assumption that is needed to prevent a COLI from changing with climate fluctuations over time.
A conditional COLI can also limit our ability to handle quality change. Most people would probably agree that general increases in life expectancy that are not caused by changes in medical care or other market goods should not reduce the CPI, but a conditional COLI should take account of changes in life expectancy due to improvements in the quality of medical care, such as better treatment of heart attacks. Yet it is not clear where to draw the line between general increases in life expectancy and more specific quality improvements, for example, in the treatment of depression or heart attacks or in cataract surgery. When new drugs make it easier to ameliorate an episode of depression or when new techniques reduce the cost of cataract surgery, most would probably want the change to be reflected in a cost-of-living index, and perhaps even in the price index. Some help comes from an appropriate redefinition of commodities, for example as the treatment for an illness, rather than the drugs and medical services themselves. But if quality improvement comes through new technology and if a conditional COLI treats technology as an environmental variable to be held constant, the contribution of quality change to effective price reduction may be ignored or at least understated. Indeed, if one thinks of a conditional COLI as designed to prevent changes in the index level when prices are constant, then it would seem to rule out quality adjustments to price. To capture the contribution of technological change to effective price reduction in the price index, one must remove technology from the conditioning variables in a conditional COLI. Yet as the example of life expectancy shows, such “unconditioning” must be selective; one must hold some technologies constant while others are allowed to change (see “Technical Note” for a more formal discussion of this point). The difficulty of deciding on what to condition is further aggravated by the difficulty in practice of separating changes in technology from changes in tastes, as when the BLS counted as a quality improvement not only the switch from cotton to synthetic shirts but also the subsequent switch in the opposite direction.
One more example is worth thinking about. The availability of a new drug like Viagra certainly makes many people better off. There is no obvious way of redefining one or more commodities so that this shows up as a price decrease. Indeed, many people—including most members of the panel—are quite uncomfortable with the idea that the introduction of Viagra should reduce the CPI. (Here we are considering specifically the “new goods” effect. If, hypothetically, there had been a CPI stratum “treatment for impotence” and the introduction of Viagra