[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/ags/aaea06/21227.html
   My bibliography  Save this paper

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

Author

Listed:
  • Leibtag, Ephraim S.
Abstract
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.

Suggested Citation

  • Leibtag, Ephraim S., 2006. "The Impact of Changing Retail Services on the Grocery Store Producer Price Index," 2006 Annual meeting, July 23-26, Long Beach, CA 21227, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea06:21227
    DOI: 10.22004/ag.econ.21227
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/21227/files/sp06le02.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.21227?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Mr. Paul A Armknecht Jr. & Fenella Maitland-Smith, 1999. "Price Imputation and Other Techniques for Dealing with Missing Observations, Seasonality and Quality Change in Price Indices," IMF Working Papers 1999/078, International Monetary Fund.
    3. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mick Silver & Saeed Heravi, 2003. "The Measurement of Quality-Adjusted Price Changes," NBER Chapters, in: Scanner Data and Price Indexes, pages 277-316, National Bureau of Economic Research, Inc.
    2. Libor Dusek & Lubomir Lizal (ed.), 2011. "CERGE-EI Tackles Transition," CERGE-EI Books, The Center for Economic Research and Graduate Education - Economics Institute, Prague, edition 1, number b05, May.
    3. Hanousek, Jan & Filer, Randall K, 2004. "Consumers' Opinion of Inflation Bias Due to Quality Improvements," Economic Development and Cultural Change, University of Chicago Press, vol. 53(1), pages 235-254, October.
    4. Robert C. Feenstra & Christopher R. Knittel, 2009. "Reassessing the US Quality Adjustment to Computer Prices: The Role of Durability and Changing Software," NBER Chapters, in: Price Index Concepts and Measurement, pages 129-160, National Bureau of Economic Research, Inc.
    5. Leonard I. Nakamura, 2010. "Intangible Assets And National Income Accounting," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(s1), pages 135-155, June.
    6. Silver, Mick & Heravi, Saeed, 2005. "A Failure in the Measurement of Inflation: Results From a Hedonic and Matched Experiment Using Scanner Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 269-281, July.
    7. Christos Ioannidis & Mick Silver, 1999. "Estimating exact hedonic indexes: An application to UK television sets," Journal of Economics, Springer, vol. 69(1), pages 71-94, February.
    8. Jan van Dalen & Ben Bode, 2004. "Quality-corrected price indices: the case of the Dutch new passenger car market, 1990-1999," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1169-1197.
    9. Hoffmann, Johannes, 1998. "Problems of inflation measurement in Germany," Discussion Paper Series 1: Economic Studies 1998,01e, Deutsche Bundesbank.
    10. W. Erwin Diewert, 2003. "Hedonic Regressions. A Consumer Theory Approach," NBER Chapters, in: Scanner Data and Price Indexes, pages 317-348, National Bureau of Economic Research, Inc.
    11. Christos Ioannidis & Mick Silver, 2003. "Chained, exact and superlative hedonic price changes: estimates from microdata," Applied Economics, Taylor & Francis Journals, vol. 35(9), pages 1005-1014.
    12. Adam Gorajek, 2018. "Econometric Perspectives on Economic Measurement," RBA Research Discussion Papers rdp2018-08, Reserve Bank of Australia.
    13. Bradley, Ralph, 2013. "Feasible methods to estimate disease based price indexes," Journal of Health Economics, Elsevier, vol. 32(3), pages 504-514.
    14. Robert J. Hill & Alice O. Nakamura, 2010. "Improving Inflation And Related Performance Measures For Nations: An Introduction," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(s1), pages 1-10, June.
    15. Edgar Caicedo, 2000. "Problemas en la medición del IPC, el Caso Colombiano," Borradores de Economia 152, Banco de la Republica de Colombia.
    16. Mick Silver, 2016. "How to Better Measure Hedonic Residential Property Price Indexes," IMF Working Papers 2016/213, International Monetary Fund.
    17. Edgar caicedo, 2000. "Problemas En La Medición Del Ipc, El Caso Colombiano," Borradores de Economia 3381, Banco de la Republica.
    18. Jonathan Murray & Nicholas Sarantis, 1999. "Price-Quality Relations and Hedonic Price Indexes for Cars in the United Kingdom," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 6(1), pages 5-27.
    19. Leonard I. Nakamura, 2009. "Intangible assets and national income accounting: measuring a scientific revolution," Working Papers 09-11, Federal Reserve Bank of Philadelphia.
    20. Mick Silver & Saeed Heravi, 2004. "Hedonic Price Indexes and the Matched Models Approach," Manchester School, University of Manchester, vol. 72(1), pages 24-49, January.

    More about this item

    Keywords

    Demand and Price Analysis;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea06:21227. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.