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Imputation and Price Indexes: Theory and Evidence from the International Price Program

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  • Robert C. Feenstra
  • Erwin W. Diewert

Abstract

The goal of this paper is to theoretically and empirically demonstrate the consequences of different imputation methods, using recent data from the International Price Program. We suppose that prices are missing due to random or erratic reporting. We consider three different imputation methods: carry-forward, which just assumes that the missing price is the same as in the previous period; cell-mean, which imputes the missing price using either the short-term or long-term index for related commodities; and linear interpolation, which uses the last and next observations for the item to linearly interpolate. Certain hybrid techniques, combining either carry-forward or cell-mean with linear interpolation, are also considered. Our conclusions are: (1) Some imputation is better than no imputation; (2) the short term cell-mean introduces some “noise” into the price index: (3) linear interpolation results in less fluctuation of prices than the true series: (4) combining either carry-forward or cell-mean with linear interpolation gives similar results.

Suggested Citation

  • Robert C. Feenstra & Erwin W. Diewert, "undated". "Imputation and Price Indexes: Theory and Evidence from the International Price Program," Department of Economics 00-12, California Davis - Department of Economics.
    • Handle: RePEc:fth:caldec:00-12
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    File URL: http://www.econ.ucdavis.edu/working_papers/00-12.pdf
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    References listed on IDEAS

    as
    1. Diewert, W. Erwin, 1998. "High Inflation, Seasonal Commodities, And Annual Index Numbers," Macroeconomic Dynamics, Cambridge University Press, vol. 2(4), pages 456-471, December.
    2. Diewert, Erwin, 2007. "Index Numbers," Economics working papers diewert-07-01-03-08-17-23, Vancouver School of Economics, revised 31 Jan 2007.
    3. 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.
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    5. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219, National Bureau of Economic Research, Inc.
    6. repec:cup:macdyn:v:3:y:1999:i:1:p:48-68 is not listed on IDEAS
    7. Michael F. Bryan & Stephen G. Cecchetti, 1993. "The consumer price index as a measure of inflation," Economic Review, Federal Reserve Bank of Cleveland, vol. 29(Q IV), pages 15-24.
    8. Clements, Kenneth W & Izan, H Y, 1987. "The Measurement of Inflation: A Stochastic Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(3), pages 339-350, July.
    9. Stephen G. Cecchetti, 1997. "Measuring short-run inflation for central bankers," Review, Federal Reserve Bank of St. Louis, issue May, pages 143-155.
    10. Diewert, W. Erwin, 1999. "Index Number Approaches To Seasonal Adjustment," Macroeconomic Dynamics, Cambridge University Press, vol. 3(1), pages 48-68, March.
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    Cited by:

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    2. 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.

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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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