variations are also significant across areas, and there are data and methods available with which to develop a reasonable index. Such an index should take account of differences by region and size of place.

For constructing housing cost index values for the purpose of adjusting the poverty thresholds for all families, not just urban families or families in selected areas, we conclude that it is almost a necessity to turn to the decennial census, despite its limited data content. Given a decision to use census data, the HUD methodology for developing fair market rents has appeal. This methodology is subject to criticism because of its use of a limited number of characteristics to define a ''standard" rental apartment unit for comparing rental costs across areas. But until more sophisticated methods are fully developed and, more important, improvements effected in the underlying database with which to apply these methods, the HUD methodology appears to offer a reasonable alternative that is easy to understand and straightforward to implement.

We implemented a modified version of the HUD approach with 1990 census data to determine whether we could develop interarea housing cost index values that accorded reasonably well with major findings in the literature.12 We obtained a copy of an extract of 1990 census data for every U.S. county (originally prepared for HUD). This extract provided the distribution of rents for two-bedroom apartments that had complete plumbing facilities, kitchen facilities, and electricity and in which the occupant had moved in within the last 5 years. (Units for which no cash rent was paid or for which the rent covered one or more meals were excluded.)

Using these data, we first produced index values (relative to 1.0 for the nation as a whole) for each of the 341 metropolitan areas in the country and for nonmetropolitan areas within each state. Compared to the 32 metropolitan areas for which Kokoski, Cardiff, and Moulton (1992) also computed index values by using hedonic techniques with the CPI database, our index showed similar patterns, although less variation. For these 32 areas, our index values ranged from 1.67 to 0.88; the Kokoski, Cardiff, and Moulton values ranged from 1.83 to 0.69.13 The rank-order correlation of our index values with those of Kokoski, Cardiff, and Moulton is very high (.897 computed using Spearman's r).

We next grouped the metropolitan areas into six population size categories within each of the nine census regions (divisions), aggregated the nonmetropolitan areas by region, and recomputed the index values. Following

12  

The modification was that, for reasons of feasibility and consistency of estimates across the nation, we used decennial census data exclusively rather than a combination of census, AHS, and random digit dialing survey data.

13  

One reason for the difference may be that our index values included utilities, which Kokoski, Cardiff, and Moulton found in a separate analysis varied somewhat less than shelter costs per se.



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