. "4 Evolving Market Baskets: Adjusting Indexes to Account for Quality Change." At What Price?: Conceptualizing and Measuring Cost-of-Living and Price Indexes. Washington, DC: The National Academies Press, 2002.
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At What Price?: Conceptualizing and Measuring Cost-of-Living and Price Indexes
yield an insufficient number of models to permit reliable estimation of realistically complex hedonic functions. The initiative specifically provided funding to collect additional price observations from current CPI outlets (2,500 quotes distributed among eight items). For some experiments, BLS field agents are also collecting observations from added outlets (as is the case for camcorders); for others (audio products), market data have been purchased from vendors such as A.C. Nielsen or NPD.26 It is important that BLS continue to examine the implications of using non-uniform data for estimating hedonic regressions and for index construction generally.
The CPI Hedonics Model
Most of the recent BLS work uses the indirect adjustment method. Price adjustments are calculated with an equation in which the (logarithm of) price is estimated as a function of product characteristics. The portion of the observed price difference between a replaced item and a substitute item assigned to differences in quality is determined by the differences in characteristics variables and the associated coefficient values. The process of specifying the model typically involves researching consumer magazines and manufacturer and industry information to develop a sense about which characteristics are related to price. Several specifications may be experimented with prior to final model selection. In the case of VCRs, BLS’s final specification consisted of all dummy variables on the right-hand side, each indicating the presence of a particular feature (number of video heads, auto rewind, hi-fi stereo, etc.). Liegey and Shepler (1999:27) write: “The specification for the final VCR regression model was deemed satisfactory, primarily because the magnitude and direction of the parameter estimates matched a priori expectations. The high R-squared value further validates the model.” For several of the applications, the dependent variable is the list price, not the transaction price. When the model is estimated using retail list price as the dependent variable, a dummy variable indicating that the item was sold at a sale price is included in the model to capture the (negative) effect on actual price in the data.27
In addition to tangible characteristics, brand dummies are often included as explanatory variables. Inclusion of brand names in the equations has been de-
The audio project, which relies on purchased point-of-sale data, and the video project, which relies on conventional in-house surveys, may provide useful contrasts. The audio data include price and units sold but have limited information about attributes, which forces BLS to supplement the data with manufacturer specifications. Typically, collecting vendor data is more expensive than collecting a sample internally, but the data are available with greater frequency.
This is often done because of data constraints. Earlier studies, such as Liegey and Shepler (1999) on VCRs, used Consumer Reports and not CPI price data. Mary Kokoski has questioned this practice commenting that, “since no one really pays full prices, do they (the results) really reflect the equilibrium assumptions that underlie the hedonic method?” (Liegey and Shepler, 1999:32). The panel shares Kokoski’s concerns.