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December
2004, Vol. 127, No.12
Hedonic regression models using in-house and out-of-house data
Craig Brown
T he research leading up to the publication of this article was conducted under the CPI initiative to expand the scope of developing hedonic regression models for quality adjustment purposes to more items within the CPI market basket. The primary focus of the article is to provide a detailed analysis of the hedonic modeling process and to illustrate the characteristics of two data sources the Bureau of Labor Statistics has chosen to utilize in its ongoing research on hedonic-based quality adjustment methods.
Early research by BLS personnel and a significant portion of the current research done by the CPI staff in this area rely upon the existing sample of CPI data for the creation of hedonic regression models.1 When it was recommended that the Bureau expand its use of hedonic models for quality adjustment purposes to more items within the CPI, situations arose in which the existing sample size of the items chosen were deemed insufficient to support the creation of hedonic models. To alleviate this problem, supplemental samples were designed and collected exclusively for hedonic modeling purposes.2 Despite the Bureau抯 having full control over this type of sample data, such an "in-house" prescription was not seen as a cure-all, because designing and collecting these data exhausts many BLS resources. Accordingly, the Bureau was led to investigate the use of hedonic models created with market data purchased from private firms that specialize in collecting point-of-sale observational data.3 Purchased, or out-of-house, data offer many enhancements over in-house data, but are costly and have their own sets of limitations.
With home-based telephones (corded or cordless), the Bureau has an opportunity to compare the process and results of using both in-house and out-of-house data in the creation of hedonic regression models. This article discusses the issues of data quality, the specification of a model, and the application of hedonic quality adjustments to substitutions in the CPI sample. Empirical evidence and quantitative data support the topics addressed. The next section examines the characteristics of the data. Following that section, the results of the models are presented, and a discussion illustrates how they could have been used in quality-adjusting substitutions in the CPI. The final section is a follow-up of what has changed with the data and presents a brief conclusion.
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Footnotes
1 Most notably, the hedonic models
for items of apparel and their continual upkeep. (For more information on early
work with hedonic models for apparel items in the CPI, see P. Liegey,
"Adjusting Apparel Indexes in the Consumer Price Index for Quality
Differences," in Price Measurements and Their Uses, National Bureau
of Economic Research Studies in Income and Wealth, 57 (Chicago, University of
Chicago Press, 1993), pp. 209�, and "Apparel price indexes: effects of
hedonic adjustment," Monthly Labor Review, May 1994, pp. 38�;
and N. Shepler "Analysis of Hedonic Regression: Applied to Women抯
Apparel in the Consumer Price Index," manuscript (Bureau of Labor
Statistics, 1994).
2 Between April and September in each of 1999 and 2000, supplemental research samples were collected for motor vehicle painting, film processing, refrigerators, microwave ovens, videocassette recorders (VCR抯), digital video disk (DVD) players, camcorders, telephones, and dental restorations.
3 See M. Kokoski, K. Waehrer, and P. Rozaklis, "Using Hedonic Methods for Quality Adjustment in the CPI: The Consumer Audio Products Component," BLS working paper (Bureau of Labor Statistics, 2000), for an example of research conducted with this type of data.
Related Monthly Labor Review articles
Adjusting VCR
prices for quality change. � Sep.
1999.
Apparel price indexes: effects of hedonic adjustment�a href="/opub/mlr/1994/05/contents.htm">May
1994.
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