supported by anecdotes. It is not the purpose of this panel to provide new estimates of bias or a detailed technical assessment of BLS procedures. However, the panel has identified several broad issues relating to quality adjustment that deserve attention. First, how can the BLS best assure that the process whereby it identifies and measures quality changes is as objective as possible is not driven by highly subjective assessments of where the problems are likely to be and pays appropriate attention to areas where quality deterioration may have occurred? Second, while adjusting for quality change can in some cases be relatively straightforward, it usually involves product characteristics that are difficult to quantify. Airline deregulation, for example, led to generally lower airfares, but the low fares produced more crowded planes, more cancellations, and more frequent and longer delays (quality deterioration from the standpoint of travelers), as well as an increase in the frequency of flights between many pairs of cities (a quality improvement). How can these serious measurement problems be addressed so that the value of these kinds of quality changes is reflected in the CPI?

Many of the quality change examples used in recent critiques that find an upward bias in the CPI strongly suggest that quality improvements are overlooked. But many of the examples have been chosen from visible product classes presumed to bias the CPI upward. Furthermore, it is difficult to know where BLS should draw the line between adjustments that are sufficiently replicable to be used for producing a publishable index and adjustments that ought to be part of an ongoing research program but are not yet (and may never be) suitable for publication by a federal statistical agency.

HEDONIC REGRESSION METHODS

Hedonics currently offers the most promising technique for explicitly adjusting observed prices to account for changing product quality.14 Hedonic regressions are used to estimate the value of specific bundles of individual characteristics that, when packaged together, form goods. The principle underlying hedonics is that, if consumers face observable relationships between goods’ characteristics and their prices, one should be able to use these relationships to disentangle pure price changes from quality changes. Hedonics essentially replaces the price of goods with the price of bundles of characteristics.15

14  

This sentiment dates back as far as the Stigler commission report (1961), and is reflected in recent work by Triplett (1990), Kokoski (1993), Boskin et al. (1996), Fixler et al. (1999), and many others.

15  

This basic idea is useful in a variety of other contexts. Particularly when considering product design, marketers routinely treat products as bundles of characteristics; see Green and Krieger (1985). And hedonic regression is routinely used in real estate appraisal and assessment: equations relating sales prices to the characteristics of properties sold during a particular period are widely used to predict the “missing” sales prices of properties that did not change hands; see, e.g., Kang and Reichert (1991).



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