the elderly, one must review the BLS index construction method. For the CPI-E, BLS identifies expenditure patterns for the sample of elderly from CEX data. The standard modified Laspeyres index is calculated using a reweighted consumption basket that reflects those patterns. However, as Amble and Stewart (1994:141) report: “The experimental price index for older consumers is a weighted average of price changes for the same set of item strata and [is] collected from the same sample of urban areas used in calculating the CPI-U and CPI-W.” Thus, the selection of outlets, as well as the selection of specific item categories to price, may not be representative of those used by the urban population age 62 and over.19

The BLS reports also note that, relative to the CPI-U, the CPI-E has a higher sampling error since it is constructed from a smaller sample. Also, the CPI-E does not capture the effect of nonfixed percentage senior citizen price discounts. Nor does it account for higher rates of home ownership among the elderly. Boskin et al. (1998) argue that, because of the rental equivalency indexing method, homeowners are, in effect, getting compensated for capital gains on their homes.

Out-of-pocket medical care expenses account for the majority of the growth rate differences between the CPI-E and the CPI-U; and many economists believe that the medical care component is among the most biased item categories (if the goal is a cost-of-living indicator), due to omitted quality effects and output definition problems. The Boskin commission argued that widespread and systematic quality improvements in the health care sector are not captured by the CPI, creating a significant upward bias in the medical care component—about 3 percent per year when weighted by out-of-pocket expenditures. In short, though the CPI-E has risen more rapidly than the CPI-U, one still cannot estimate relative cost-of-living trends.

To summarize, BLS research shows that the CPI-E series rose slightly faster than the general CPI. However, the CPI-E is computed using a comparatively small CEX sample, and the differences are generally not statistically significant. Also, the growth differential between the CPI-E and CPI-U is attributable to increased weighting of a few item categories, most notably medical services, an item category economists agree has poorly captured improved quality and new item effects.

The non-BLS literature generally concludes that there is a lack of measurable divergence between elderly and general population price inflation trends. Using the reweighted Laspeyres index approach, Boskin and Hurd (1985) found little difference in the cost of living faced by the elderly and the general population during the early 1980s. Jorgenson and Slesnick (1983) arrived at a similar conclu-


Of course, this says nothing of the more general problem that, to the extent that price changes faced by the rural elderly are different than those faced by the urban elderly, inaccuracies are compounded.

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement