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Is equipment price deflation a statistical artifact?

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  • Bart Hobijn

Abstract

I argue that equipment price deflation might be overstated because the methods used to measure it rely on the erroneous assumption of perfectly competitive markets. The main intuition behind this argument is that what these price indices might actually capture not a price decrease but the erosion of the market power of existing vintages of machines. To illustrate my argument, I introduce an endogenous growth model in which heterogeneous final goods producers can choose the technology they will use. The various technologies are supplied by monopolistically competing machine suppliers. This market structure implies that the best machines are marketed to the best workers and are sold at the highest markup. In my model economy, the endogenously determined markups are such that standard methods will tend to find equipment price deflation, even though the model does not exhibit any equipment price deflation.

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  • Bart Hobijn, 2001. "Is equipment price deflation a statistical artifact?," Staff Reports 139, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:139
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    References listed on IDEAS

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    Cited by:

    1. Jason G. Cummins & Giovanni L. Violante, 2002. "Investment-Specific Technical Change in the US (1947-2000): Measurement and Macroeconomic Consequences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 243-284, April.
    2. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2006. "Projecting Productivity Growth: Lessons from the US Growth Resurgence," Chapters, in: Dennis W. Jansen (ed.), The New Economy and Beyond, chapter 2, Edward Elgar Publishing.
    3. Comin, D. & Hobijn, B., 2004. "Cross-country technology adoption: making the theories face the facts," Journal of Monetary Economics, Elsevier, vol. 51(1), pages 39-83, January.
    4. Peter N. Ireland, 2009. "On the Welfare Cost of Inflation and the Recent Behavior of Money Demand," American Economic Review, American Economic Association, vol. 99(3), pages 1040-1052, June.
    5. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    6. Hyunbae Chun & M. Ishaq Nadiri, 2008. "Decomposing Productivity Growth in the U.S. Computer Industry," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 174-180, February.
    7. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    8. Boyan Jovanovic, 2002. "EconomicDynamics Interviews Boyan Jovanovic on Technology Adoption," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 4(1), November.
    9. Cozzi, Guido & Impullitti, Giammario, 2006. "Technological policy and wage inequality," MPRA Paper 10140, University Library of Munich, Germany.
    10. Lawless, Martina, 2006. "Measurement Issues and Int. Comparisons of Output and Productivity Growth," Quarterly Bulletin Articles, Central Bank of Ireland, pages 108-120, April.
    11. Henning Ahnert & Geoff Kenny, 2004. "Quality adjustment of European price statistics and the role for hedonics," Occasional Paper Series 15, European Central Bank.
    12. Wojciech Szewczyk & Anna Sabadash, 2013. "Macroeconomic Modelling of Public Expenditures on Research and Development in Information and Communication Technologies," JRC Research Reports JRC82943, Joint Research Centre (Seville site).
    13. Lawless, Martina, 2006. "Measurement Issues and International Comparisons of Output and Productivity Growth," MPRA Paper 10007, University Library of Munich, Germany.
    14. Bart Hobijn, 2002. "On both sides of the quality bias in price indexes," Staff Reports 157, Federal Reserve Bank of New York.

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