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The Product Life Cycle and Sample Representativity Bias in Price Indexes

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Listed:
  • Daniel Melser

    () (RMIT University)

  • Iqbal A. Syed

    () (School of Economics and CAER, UNSW Business School, UNSW)

Abstract

Official price indexes are usually calculated using matched samples of products. If products exhibit systematic price trends at different points in their life cycle then matched sample methods may introduce bias if the life cycle movement in the sample does not adequately reflect that in the population. This article explores the extent of these life cycle pricing effects and then examines the bias it can introduce in measured inflation. A large US supermarket scanner data set for 6 cities and 6 products over 12 years is used. Using hedonic methods we find that the life cycle component of price change is important across a range of products and cities. To explore the bias introduced by these movements we use simulations which construct indexes with different sample update frequency. For indexes which are never completely resampled we find an annual bias of 0.88 and 0.59 percentage points depending upon whether we use the actual prices or prices imputed from our hedonic model. This compares with absolute biases of 0.24 and 0.08 percentage points for the corresponding cases for samples which are re-selected annually. Thus our results provide strong support for more frequently updating index samples.

Suggested Citation

  • Daniel Melser & Iqbal A. Syed, 2016. "The Product Life Cycle and Sample Representativity Bias in Price Indexes," Discussion Papers 2016-07, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2016-07
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2016-07.pdf
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    References listed on IDEAS

    as
    1. Daniel Melser & Iqbal A. Syed, 2016. "Life Cycle Price Trends and Product Replacement: Implications for the Measurement of Inflation," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 509-533, September.
    2. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    3. 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.
    4. Erwin Diewert, 2005. "Weighted Country Product Dummy Variable Regressions And Index Number Formulae," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(4), pages 561-570, December.
    5. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    6. Ariel Pakes, 2003. "A Reconsideration of Hedonic Price Indexes with an Application to PC's," American Economic Review, American Economic Association, vol. 93(5), pages 1578-1596, December.
    7. W. Erwin Diewert, 1995. "Axiomatic and Economic Approaches to Elementary Price Indexes," NBER Working Papers 5104, National Bureau of Economic Research, Inc.
    8. Michael Landsberger & Isaac Meilijson, 1985. "Intertemporal Price Discrimination and Sales Strategy under Incomplete Information," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 424-430, Autumn.
    9. Ana Aizcorbe, 2005. "Moore's Law, Competition, and Intel's Productivity in the Mid-1990s," American Economic Review, American Economic Association, vol. 95(2), pages 305-308, May.
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    More about this item

    Keywords

    Consumer price index (CPI); lifecycle pricing; hedonic regression; survey sampling;

    JEL classification:

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

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