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ADJUSTING POVERTY THRESHOLDS 191 substitutions in housing production across cities. Moreover, the units that were priced and used in the BLS calculation might not be representative of units in a given community; also, there might be systematic differences across cities in the characteristics that were excluded. Hedonic Models Many analysts have taken another approach to estimating the price effects of various housing characteristics, including the price effect of geographic location. This approach is to develop a hedonic regression pricing model that relates observed market prices of housing to the implicit prices of the characteristics of the unit. In other words, hedonic models are used to isolate the contribution of individual housing characteristics to the price of housing. Examples of hedonic models include those developed by: â¢ Gillingham (1975), who analyzed microdata on individual housing units in 10 cities drawn from the 1960-1961 Comprehensive Housing Unit Survey conducted by BLS together with data on neighborhood characteristics from the 1960 decennial census; â¢ Blackley, Follain, and Lee (1986), who analyzed data from the 1975 and 1978 Annual Housing Survey to calculate housing cost indexes for 34 metropolitan areas; â¢ Thibodeau (1989), who created housing price indexes for 60 metropolitan areas using Annual Housing Survey data for 1974-1983; and â¢ Kokoski, Cardiff, and Moulton (1992, 1994), who produced interarea price indexes for consumer goods and services (including housing) as of 1989 for 44 areas (32 large metropolitan areas and 12 other region and city size classifications), using the CPI database (see also Moulton, 1992). Hedonic models are subject to a number of criticisms. Rosen (1978) objected that the choice of characteristics to include in any model is arbitrary. He also pointed out that the rank order of the indexes for cities or metropolitan areas usually depends on which city is used as the reference city (i.e., which city is assigned an index value of 1.0). Gillingham (1975) documented this phenomenon in his work. He and other analysts also estimated large standard errors for area-specific indexes; further, they found that the size of the standard error was affected by the specification of the bundle of characteristics included in the particular hedonic model. Kokoski, Cardiff, and Moulton (1992, 1994) attempted to correct for some of the problems with hedonic models in their analysis, which used the BLS CPI database for selected metropolitan areas matched with neighborhood characteristics data from the decennial census. This database has the advantage of relatively large sample sizes for the areas covered. The authors regressed the natural logarithm of the price of shelter on characteristic variables. (Their
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