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The Impact of Changing Retail Services on the Grocery Store Producer Price Index

Listed author(s):
  • Leibtag, Ephraim S.

This article focuses on quality adjustment of the U.S. Producer Price Index (PPI) for retail food stores. Within the retail trade sector, food stores make up 15.4% of the revenue generated in the sector. This article outlines methods of quality adjustment and applies a direct adjustment technique to the PPI for grocery stores. This subset of the PPI is unique in that it is one of the first indices for retail goods to use the retail margin (retail price - wholesale price) as a measure of the price of the products sold in a store. This measure provides an estimate of the prices of the services provided by the retailers. In this study I find that the Producer Price Index for food stores would be biased upward between 0.06 and 1.74 index points if a change in store characteristics was not adjusted for in the index calculation. This bias would be larger if store characteristics were to change over time without any adjustment made for them. Given the ever-expanding services available in grocery stores and the recent increase in nontraditional retailers selling a greater share of consumer food products , this is likely to occur. An up-to-date measure of store and product characteristics will be needed to construct an unbiased (or at least less biased) index. The use of PPI indices in labor contracts and cost estimate adjustments makes accurate measures of producer price inflation crucial. For example, since food service companies use the PPI to adjust their cost estimates, the upward bias in the PPI causes prices to rise artificially in response to a higher than actual inflation estimate. The more information that is available in terms of store and product characteristics, the more accurate an adjustment that can be made. The potential bias that would occur without these adjustments underlies the importance of proper data collection and frequent updates of any changing characteristics in order to construct a more accurate measure of price change in an industry, sector, or market where the price that is observed encompasses more than the physical product that is sold. This adjustment method can and should be applied to retail and service sector indices whenever possible.

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Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2006 Annual meeting, July 23-26, Long Beach, CA with number 21227.

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Date of creation: 2006
Handle: RePEc:ags:aaea06:21227
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  1. Feenstra, Robert C, 1995. "Exact Hedonic Price Indexes," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 634-653, November.
  2. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
  3. Paul A. Armknecht & Fenella Maitland-Smith, 1999. "Price Imputation and Other Techniques for Dealing with Missing Observations, Seasonality and Quality Change in Price Indices," IMF Working Papers 99/78, International Monetary Fund.
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