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Scanner Data, Time Aggregation and the Construction of Price Indexes

  • Diewert, Erwin
  • Fox, Kevin J.
  • Ivancic, Lorraine

The impact of weekly, monthly and quarterly time aggregation on estimates of price change is examined for nineteen different supermarket item categories over a fifteen month period using scanner data. We find that time aggregation choices (the choice of a weekly, monthly or quarterly unit value concept for prices) have a considerable impact on estimates of price change. When chained indexes are used, the difference in price change estimates can be huge, ranging from 0.28% to 29.73% for a superlative (Fisher) index and an incredible 14.88% to 46,463.71% for a non-superlative (Laspeyres) index. The results suggest that traditional index number theory breaks down when weekly data with severe price bouncing are used, even for superlative indexes. Monthly and (in some cases even) quarterly time aggregation were found to be insufficient to eliminate downward drift in superlative indexes. In order to eliminate chain drift, multilateral index number methods are adapted to provide drift free measures of price change.

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Paper provided by Vancouver School of Economics in its series Economics working papers with number erwin_diewert-2009-48.

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Length: 51 pages
Date of creation: 22 Sep 2009
Date of revision: 22 Sep 2009
Handle: RePEc:ubc:bricol:erwin_diewert-2009-48
Contact details of provider: Web page: http://www.economics.ubc.ca/

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  1. Robert C. Feenstra & Matthew D. Shapiro, 2003. "High-Frequency Substitution and the Measurement of Price Indexes," NBER Chapters, in: Scanner Data and Price Indexes, pages 123-150 National Bureau of Economic Research, Inc.
  2. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
  3. W. Erwin Diewert, 1995. "Axiomatic and Economic Approaches to Elementary Price Indexes," NBER Working Papers 5104, National Bureau of Economic Research, Inc.
  4. Reinsdorf, Marshall B, 1999. "Using Scanner Data to Construct CPI Basic Component Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 152-60, April.
  5. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
  6. William J. Hawkes & Frank W. Piotrowski, 2003. "Using Scanner Data to Improve the Quality of Measurement in the Consumer Price Index," NBER Chapters, in: Scanner Data and Price Indexes, pages 17-38 National Bureau of Economic Research, Inc.
  7. Drechsler, Laszlo, 1973. "Weighting of Index Numbers in Multilateral International Comparisons," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 19(1), pages 17-34, March.
  8. W. Erwin Diewert, 1996. "Axiomatic and Economic Approaches to International Comparisons," NBER Working Papers 5559, National Bureau of Economic Research, Inc.
  9. Diewert, W Erwin, 1978. "Superlative Index Numbers and Consistency in Aggregation," Econometrica, Econometric Society, vol. 46(4), pages 883-900, July.
  10. Kravis, Irving B, 1984. "Comparative Studies of National Incomes and Prices," Journal of Economic Literature, American Economic Association, vol. 22(1), pages 1-39, March.
  11. Hill, Robert J., 2006. "Superlative index numbers: not all of them are super," Journal of Econometrics, Elsevier, vol. 130(1), pages 25-43, January.
  12. Mary F. Kokoski & Brent R. Moulton & Kimberly D. Zieschang, 1999. "Interarea Price Comparisons for Heterogeneous Goods and Several Levels of Commodity Aggregation," NBER Chapters, in: International and Interarea Comparisons of Income, Output, and Prices, pages 123-169 National Bureau of Economic Research, Inc.
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