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Using Online Prices for Measuring Real Consumption across Countries

Author

Listed:
  • Alberto Cavallo
  • W. Erwin Diewert
  • Robert C. Feenstra
  • Robert Inklaar
  • Marcel P. Timmer

Abstract

We show that online prices can be used to construct quarterly purchasing power parities (PPPs) with a closely matched set of goods and identical methodologies in a variety of developed and developing countries. Our results are close to those reported by the International Comparisons Program (ICP) in 2011 and the OECD in 2014, and can be used to obtain more up-to-date estimates of real consumption across countries without the need for consumer price index extrapolations. We discuss advantages and limitations associated with the use of online prices for PPs, including issues of representativeness and limited coverage of product categories and countries.

Suggested Citation

  • Alberto Cavallo & W. Erwin Diewert & Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2018. "Using Online Prices for Measuring Real Consumption across Countries," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 483-487, May.
    • Handle: RePEc:aea:apandp:v:108:y:2018:p:483-87
    Note: DOI: 10.1257/pandp.20181037
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    Cited by:

    1. Ilaria Benedetti & Tiziana Laureti & Luigi Palumbo & Brandon M. Rose, 2022. "Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques," Economies, MDPI, vol. 10(4), pages 1-20, April.
    2. Santiago E. Alvarez & Sarah M. Lein, 2020. "Tracking inflation on a daily basis," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-13, December.
    3. Apostolos Filippas & John J. Horton & Joseph M. Golden, 2019. "Reputation Inflation," NBER Working Papers 25857, National Bureau of Economic Research, Inc.
    4. David Argente & Chang-Tai Hsieh & Munseob Lee, 2020. "Measuring the Cost of Living in Mexico and the US," Working Papers 2020-123, Becker Friedman Institute for Research In Economics.
    5. Laureti Tiziana & Polidoro Federico, 2022. "Using Scanner Data for Computing Consumer Spatial Price Indexes at Regional Level: An Empirical Application for Grocery Products in Italy," Journal of Official Statistics, Sciendo, vol. 38(1), pages 23-56, March.
    6. Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
    7. Hai Long Vo & Duc Hong Vo, 2023. "The purchasing power parity and exchange‐rate economics half a century on," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 446-479, April.
    8. Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019. "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 373-402, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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