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Life Cycle Pricing and the Measurement of Inflation

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  • Melser, Daniel
  • Syed, Iqbal

Abstract

This paper explores the extent to which goods follow systematic pricing patterns over their life cycle. The theoretical literature, and anecdotal evidence, often suggests that new products are often introduced at high prices which decline as the good ages while, older goods exit the market at a discount. We outline and apply a smoothing-spline approach to the estimation of life cycle price effects using data on two different types of goods (desktop and laptop computers, and personal digital assistants). We interpret these results within a simple conceptual framework and find evidence for the existence of significant life cycle pricing effects. This implies that hedonic pricing functions that exclude age are misspecified. Furthermore, in order to eliminate biases in price indexes, samples must be constructed carefully. Using a simulation we show that the bias introduced by the traditional match-model method may be non-trivial.

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File URL: http://mpra.ub.uni-muenchen.de/16722/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 16722.

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Date of creation: 26 Aug 2007
Date of revision: 07 Jul 2008
Handle: RePEc:pra:mprapa:16722

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Related research

Keywords: Product life cycle; Hedonic regression; Price index; Spline smoothing; Scanner data;

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References

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  1. Helen X.H. Bao & Alan T.K. Wan, 2004. "On the Use of Spline Smoothing in Estimating Hedonic Housing Price Models: Empirical Evidence Using Hong Kong Data," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(3), pages 487-507, 09.
  2. Winston T.H. Koh, 2005. "The Micro-foundations of Intertemporal Price Discrimination," Working Papers 04-2005, Singapore Management University, School of Economics.
  3. Robert J. Hill & Daniel Melser, 2007. "Comparing House Prices Across Regions and Time: An Hedonic Approach," Discussion Papers 2007-33, School of Economics, The University of New South Wales.
  4. Varian, Hal R., 1989. "Price discrimination," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 1, chapter 10, pages 597-654 Elsevier.
  5. Hausman, Jerry, 1999. "Cellular Telephone, New Products, and the CPI," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 188-94, April.
  6. Gordon, Robert J & Griliches, Zvi, 1997. "Quality Change and New Products," American Economic Review, American Economic Association, vol. 87(2), pages 84-88, May.
  7. Stokey, Nancy L, 1979. "Intertemporal Price Discrimination," The Quarterly Journal of Economics, MIT Press, vol. 93(3), pages 355-71, August.
  8. Hardle, W., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
  9. 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.
  10. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Scanner Data and Price Indexes," NBER Books, National Bureau of Economic Research, Inc, number feen03-1, May.
  11. Daniel Melser, 2006. "Accounting For The Effects Of New And Disappearing Goods Using Scanner Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(4), pages 547-568, December.
  12. Ernst R. Berndt & Margaret Kyle & Davina Ling, 2003. "The Long Shadow of Patent Expiration. Generic Entry and Rx-to-OTC Switches," NBER Chapters, in: Scanner Data and Price Indexes, pages 229-274 National Bureau of Economic Research, Inc.
  13. Kees Jan Van Garderen & Chandra Shah, 2002. "Exact interpretation of dummy variables in semilogarithmic equations," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 149-159, June.
  14. 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.
  15. W. Erwin Diewert, 2003. "Hedonic Regressions. A Consumer Theory Approach," NBER Chapters, in: Scanner Data and Price Indexes, pages 317-348 National Bureau of Economic Research, Inc.
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