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The Econometric Foundations of Hedonic Elementary Price Indices

Hedonic methods are currently considered state-of-the-art for handling quality changes when compiling consumer price indices. The present article proposes first a mathematical description of characteristics and of elementary aggregates. In a following step, a hedonic econometric model is formulated and hedonic elementary population indices are defined. These indices extend from simple indices based on some average quality to universal formulae that incorporate the full quality spectrum of the respective elementary aggregate. We emphasise that population indices are unobservable economic parameters that need to be estimated by suitable sample indices. It is shown that most of the hedonic elementary index formulae used in practice are sample versions of particular hedonic elementary population indices.

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Paper provided by Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland in its series DQE Working Papers with number 12.

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Length: 19 pages
Date of creation: 24 Apr 2009
Date of revision:
Handle: RePEc:fri:dqewps:wp0012
Note: Room document at the 11th Ottawa Group meeting (Neuchâtel 2009)
Contact details of provider: Postal: Bd de Pérolles 90, CH-1700 Fribourg
Phone: +41 26 300 8200
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  1. Jack Triplett, 2004. "Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products," OECD Science, Technology and Industry Working Papers 2004/9, OECD Publishing.
  2. Silver, Mick & Heravi, Saeed, 2007. "Why elementary price index number formulas differ: Evidence on price dispersion," Journal of Econometrics, Elsevier, vol. 140(2), pages 874-883, October.
  3. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
  4. Mark Dickie & Charles Delorme & Jeffrey Humphreys, 1997. "Hedonic prices, goods-specific effects and functional form: inferences from cross-section time series data," Applied Economics, Taylor & Francis Journals, vol. 29(2), pages 239-249.
  5. Erwin Diewert & Saeed Heravi & Mick Silver, 2008. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Working Papers 14018, National Bureau of Economic Research, Inc.
  6. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Scanner Data and Price Indexes," NBER Books, National Bureau of Economic Research, Inc, number feen03-1, May.
  7. 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.
  8. Brachinger, Hans Wolfgang, 2002. "Statistical Theory of Hedonic Price Indices," DQE Working Papers 1, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised Aug 2003.
  9. Beer, Michael, 2005. "Bootstrapping a Hedonic Price Index: Experience from Used Cars Data," DQE Working Papers 4, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 20 Jan 2007.
  10. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132.
  11. Bruce Curry & Peter Morgan & Mick Silver, 2001. "Hedonic regressions: mis-specification and neural networks," Applied Economics, Taylor & Francis Journals, vol. 33(5), pages 659-671.
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