IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/42730.html
   My bibliography  Save this paper

Notes on GEKS and RGEKS indices

Author

Listed:
  • von der Lippe, Peter

Abstract

The paper criticizes the translation of the so called GEKS (Gini - Eltetö - Köves - Szulc) method to make consistent (transitive, or "drift free") international comparisons of price indices (parities), into the intertemporal framework. It shows that transitivity appears to be "over-ambitious" and too restrictive in this context, where chain indices possibly may suffice. Formulas of GEKS indices are complicated geometric averages of many (2m-3) direct Fisher indices relating to m periods in time. They are therefore much more difficult to compile in praxis than both, chained and direct Fisher indices. They are only transitive for a given m, but as we are free to choose different m's there is no unique, "drift free" index to compare any two periods, s and t. Instead there are many indices Pst depending on m. Moreover with new periods, t+1, t+2, … the method requires an updating (as m increases) and a re-computing of all previously compiled indices Pst. With chain indices the update is much easier and there is no need for a re-computing. To avoid such problems a "rolling" variant (RGEKS), a kind of moving average methodology, has been proposed. With RGEKS (of which chain indices are the limiting case of m = 2), however, desirable properties of (standard) GEKS, such as transitivity and proportionality get lost, and with a cyclical movement in the prices we can well generate a trend in the indices which is absent in the underlying price data.

Suggested Citation

  • von der Lippe, Peter, 2012. "Notes on GEKS and RGEKS indices," MPRA Paper 42730, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:42730
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/42730/1/MPRA_paper_42730.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivancic, Lorraine & Erwin Diewert, W. & Fox, Kevin J., 2011. "Scanner data, time aggregation and the construction of price indexes," Journal of Econometrics, Elsevier, vol. 161(1), pages 24-35, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marie Leclair & Isabelle Léonard & Guillaume Rateau & Patrick Sillard & Gaëtan Varlet & Pierre Vernédal, 2019. "Scanner Data: Advances in Methodology and New Challenges for Computing Consumer Price," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 509, pages 13-29.

    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. W. Erwin Diewert & Robert C. Feenstra, 2021. "Estimating the Benefits of New Products," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 437-473, National Bureau of Economic Research, Inc.
    2. Diewert, Erwin & Shimizu, Chihiro, 2015. "Residential Property Price Indices For Tokyo," Macroeconomic Dynamics, Cambridge University Press, vol. 19(8), pages 1659-1714, December.
    3. Diewert, W. Erwin & Fox, Kevin J., 2017. "Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data," Microeconomics.ca working papers erwin_diewert-2017-3, Vancouver School of Economics, revised 23 Mar 2017.
    4. Tsutomu Watanabe & Tomoyoshi Yabu, 2018. "The Demand for Money at the Zero Interest Rate Bound," CARF F-Series CARF-F-444, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
    6. Irz, Xavier & Mazzocchi, Mario & Réquillart, Vincent & Soler, Louis-Georges, 2015. "Research in Food Economics: past trends and new challenges," Revue d'Etudes en Agriculture et Environnement, Editions NecPlus, vol. 96(01), pages 187-237, March.
    7. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    8. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2021. "Household Inventory, Temporary Sales, and Price Indices," CARF F-Series CARF-F-520, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. Mauro Caselli & Arpita Chatterjee & Shengyu Li, 2023. "Productivity and Quality of Multi-product Firms," Discussion Papers 2023-10, School of Economics, The University of New South Wales.
    10. Jaravel, Xavier & O'Connell, Martin, 2020. "Real-time price indices: Inflation spike and falling product variety during the Great Lockdown," Journal of Public Economics, Elsevier, vol. 191(C).
    11. Cakir, Metin & Beatty, Timothy & Boland, Michael A. & Park, Timothy A. & Wang, Yanghao, 2017. "Spatial and Temporal Variation in Price Premiums for Organic Fresh Fruits and Vegetables," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259141, Agricultural and Applied Economics Association.
    12. Bentley Alan, 2022. "Rentals for Housing: A Property Fixed-Effects Estimator of Inflation from Administrative Data," Journal of Official Statistics, Sciendo, vol. 38(1), pages 187-211, March.
    13. Ivancic, Lorraine & Erwin Diewert, W. & Fox, Kevin J., 2011. "Scanner data, time aggregation and the construction of price indexes," Journal of Econometrics, Elsevier, vol. 161(1), pages 24-35, March.
    14. Conner Mullally & Jayson L Lusk, 2018. "The Impact of Farm Animal Housing Restrictions on Egg Prices, Consumer Welfare, and Production in California," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(3), pages 649-669.
    15. Delajara Marcelo & Murillo Garza José Antonio, 2012. "Weekday with Low Prices: Evidence on Daily Seasonality of Foods, Beverages and Tobacco Prices," Working Papers 2012-09, Banco de México.
    16. Li-Chun Zhang & Ingvild Johansen & Ragnhild Nygaard, 2019. "Evaluating multilateral price indices in a dynamic item universe," Discussion Papers 914, Statistics Norway, Research Department.
    17. Jacek Białek, 2023. "Improving quality of the scanner CPI: proposition of new multilateral methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2893-2921, June.
    18. Kota Watanabe & Tsutomu Watanabe, 2014. "Estimating Daily Inflation Using Scanner Data: A Progress Report," UTokyo Price Project Working Paper Series 020, University of Tokyo, Graduate School of Economics.
    19. Consuelo Nava & Maria Grazia Zoia, 2019. "An econometric analysis of the Italian cultural supply," Papers 1910.00073, arXiv.org, revised May 2020.
    20. Qingxiao Li & Metin Çakır, 2024. "Estimating SNAP purchasing power and its effect on participation," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 779-804, March.

    More about this item

    Keywords

    international comparison of price indices; intertemporal comparison; transitive price indices; chain indices; chain drift;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology

    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:pra:mprapa:42730. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.