distinction does not create clear-cut categories that imply specific corrective approaches. For instance, is a cell phone an improved wired phone or an entirely new product? What about a high-definition television, a fuel cell automobile, or on-line stock trading? The line between “new” and “improved” is inevitably arbitrary. The situation is brought into focus somewhat by thinking in slightly different terms, framed by consideration of how CPI product sampling and item identification actually work in real cases. Following Armknecht et al. (1997), three distinct cases can be delineated:
A new item replaces another that has been or soon will be discontinued and that will fall out of the CPI sample. Replacement goods may be substantively similar (in which case there may be no quality issue at all), or they may be improved (or possibly inferior) versions of the discontinued item. These goods replace old goods but fall into familiar CPI categories—e.g., 2001 Fords.
A new “supplemental” good appears that does not replace a specific outgoing good in the CPI, but that does fit appropriately into an existing item strata category—e.g., Honey Nut Cheerios.
A genuinely new item appears that does not fit into an established CPI item or strata—e.g., VCRs or wireless phones.
In some sense, all of the above situations involve new goods; however, the extent of the difference between an old and a new product ranges from close to zero, to run-of-the-mill quality changes that happen on a daily basis, all the way to the appearance of radically new products that reflect what Nordhaus (1998) calls “tectonic shifts in technology.”
Over time, BLS confronts situations on all points of this quality change spectrum. On the easy end, a commodity analyst may be forced to compare a 2-pound bag of rice with a 1-pound bag. Perhaps the previous 1-pound bag is out of stock or is not sold much anymore. Something like this happened with butter, which used to be sold in half-pound packets and now is more frequently sold in 1-pound packets. Most economists would simply work with per-pound prices in both cases. Of course, a 1-pound package is not identical to two half-pound packages, since the former requires longer storage, may be more likely to go bad, or may be sold with size discounts, and so on. But in many cases of this sort, per-unit prices seem likely to provide a very good approximation. The BLS apparently agrees. For instance, when the CPI went from pricing 16-ounce cans of tomato sauce to 14.5-ounce cans, all of the difference in price per ounce was attributed to pure price change (Kokoski et al., 2000:2).1
This is not to say that the nonlinear pricing issue is unimportant, particularly for large differences in package sizes. As a first step toward estimating its impact on the CPI, BLS could, in a straightforward manner, perform empirical research that examines how unit prices vary with package sizes. Of course, this only applies to products for which a range of sizes is typical.