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December 2006, Vol. 129, No. 12
Item replacement and quality change in apparel price indexes
Craig Brown and Anya Stockburger
A principal role of a Bureau of Labor Statistics (BLS) commodity analyst in the Consumer Price Index (CPI) program is that of data reviewer. In that role, commodity analysts are responsible primarily for monitoring the prices and characteristics of the goods and services tracked for the CPI market basket, verifying that the reported price movements of those goods and services meet the criteria for the collection of accurate consumer prices, and developing tools and procedures that aid in the careful collection and evaluation of the price and characteristic data used in producing the CPI.1 More broadly, the commodity analyst’s role is to ensure the accurate calculation of the CPI by eliminating the effects of inaccurate microlevel data.2
A commodity analyst’s microlevel data review consists largely of examining problematic observations (or price quotes) that meet one or more of the conditions for review defined in the CPI’s data-processing system. Commodity analysts must intervene and resolve the issues related to their assigned quotes before the price data from those quotes are used in computing the CPI. Two of the more common conditions prompting a review are an unusually large price change and the selection of a replacement item as a substitute for an original item that is no longer available. The latter of these conditions—the selection of replacement items—is the primary focus of this article.
The analysis to be presented assesses the impact of commodity analyst intervention on price indexes for apparel items. The definition of "commodity analyst intervention" is limited to "effort spent in the review and analysis of replacement items and changes in quality." Issues inherent in the calculation of apparel price indexes are discussed in order to identify the circumstances in which commodity analyst intervention is most critical. These issues are then further developed through the decomposition of the concept of commodity analyst intervention into two stages of microlevel data review. Following that development, experimental indexes that simulate the effects of removing commodity analyst intervention are calculated and compared with official apparel indexes.3 Finally, a brief summary of the findings and a few caveats regarding the analysis are offered.
This excerpt is from an article published in the December 2006 issue of the Monthly Labor Review. The full text of the article is available in Adobe Acrobat's Portable Document Format (PDF). See How to view a PDF file for more information.
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1 See Chapter 17 of the BLS Handbook of Methods (Bureau of Labor Statistics, 2006) for a complete discussion of the construction of the CPI and the role of commodity analysts.
2 The Bureau took a significant step forward in improving the quality of microlevel data used to compute the CPI when it began using computer-assisted data collection in 2002. Prior to that changeover, the collection, transmission, and transcription of data were subject to a large degree of human error. Now, automatic checks and reviews help improve the completeness and accuracy of CPI data.
3 The Bureau uses the term "experimental" in contrast to "official" to denote statistics that it produces outside of its regular production systems and, consequently, with less than full production quality. For security reasons, BLS researchers cannot produce experimental statistics until after the publication of the corresponding official statistics. To obtain experimental series referred to in this article, contact either of the authors.
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