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Hedonic Price Indexes with Unobserved Product Characteristics, and Application to PC's

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  • C. Lanier Benkard
  • Patrick Bajari
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    Abstract

    We show that hedonic price indexes may be biased when not all product characteristics are observed. We derive two primary sources of bias. The first is a classical selection problem that arises due to changes over time in the values of unobserved characteristics. The second comes from changes in the implicit prices of unobserved characteristics. Next, we show that the bias can be corrected for under fairly general assumptions using extensions of factor analysis methods. We test our methods empirically using a new comprehensive monthly data set for desktop personal computer systems. For this data we find that the standard hedonic index has a slight upward bias of approximately 1.4\% per year. We also find that omitting an important characteristic (CPU benchmark) causes a large bias in the index with standard methods, but that this bias is essentially eliminated when the proposed correction is applied.

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    Bibliographic Info

    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 9980.

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    Date of creation: Sep 2003
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    Publication status: published as Benkard, C. Lenair and Patrick Bajari. "Hedonic Price Indexes With Unobserved Product Characteristics," Journal of Business and Economic Statistics, 2005, v23(1,Jan), 61-75.
    Handle: RePEc:nbr:nberwo:9980

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
    2. Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
    3. Iain M. Cockburn & Aslam H. Anis, 1998. "Hedonic Analysis of Arthritis Drugs," NBER Working Papers 6574, National Bureau of Economic Research, Inc.
    4. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
    5. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, 09.
    6. Ohta, Makoto & Griliches, Zvi, 1986. "Automobile Prices and Quality: Did the Gasoline Price Increases Change Consumer Tastes in the U.S.?," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(2), pages 187-98, April.
    7. Makoto Ohta, 1983. "Automobile Prices and Quality: Did the Gasoline Price Increase Change Consumer Tastes in the U.S.?," NBER Working Papers 1211, National Bureau of Economic Research, Inc.
    8. G. Christian Ehemann & Brent R. Moulton, 2001. "Balancing the GDP Account," BEA Papers 0014, Bureau of Economic Analysis.
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    Cited by:
    1. Robert C. Feenstra & Christopher R. Knittel, 2009. "Re-Assessing the U.S. Quality Adjustment to Computer Prices: The Role of Durability and Changing Software," NBER Chapters, in: Price Index Concepts and Measurement, pages 129-160 National Bureau of Economic Research, Inc.
    2. C. Lanier Benkard & Patrick Bajari, 2004. "Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach," NBER Working Papers 10278, National Bureau of Economic Research, Inc.

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