ment over not adjusting the poverty thresholds at all for geographic price difference—to adjust the thresholds for differences in the cost of housing.
Overall, using BLS price data for the period July 1988-June 1989, Kokoski, Cardiff, and Moulton (1992) found little variation in prices by geographic area for many components of the CPI. For example, the index values for food at home (which accounts for 10% of the CPI market basket) ranged from 93 to 107 (with the geometric mean of all areas in the sample equal to 100). This range of values excludes Anchorage and Honolulu, for which the food at home index values were 126 and 139, respectively. However, for some categories of expenditures, Anchorage and Honolulu did not have higher costs than other areas. Index values for the category of private transportation commodities, which account for 16 percent of the CPI market basket (and include new and used vehicles, gasoline and oil, coolant and fluids, and automobile parts and equipment), ranged from 91 to 105. Greater variation was observed for clothing (index values of 67 to 154) and professional medical services (index values of 62 to 147), but these items account for relatively small proportions of the CPI market basket (6% and 3%, respectively). The component with the largest variation was shelter, with index values from 52 to 183. Utilities also showed considerable variation, with index values from 57 to 152. Together, these two components account for 33 percent of the CPI market basket (25% for shelter and 8% for utilities).
The 1976 Poverty Studies Task Force (Economic Research Service, 1976) reported the same finding as in the BLS research—that interarea price differences are greater for housing (including utilities) than for other commodities.10 These results, coupled with the fact that housing is such a large component of spending, led us to look for a methodology that could provide a reasonable basis for adjusting the poverty thresholds for interarea housing cost differences. We found that considerable analytical effort has been expended to develop estimates of geographic differences in housing costs; the chief methodological challenge has been to devise methods that estimate differences in prices per se and not differences in the characteristics or quality of the housing being priced.
Several methodologies have been used to estimate geographic housing cost differences, including:
the methods used by the U.S. Department of Housing and Urban Development (HUD) to calculate fair market rents for metropolitan areas and nonmetropolitan counties;