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Using Investment Data to Assess the Importance of Price Mismeasurement


  • Comin, D.


This paper presents a new approach to assess the role of price mismeasurement in the productivity slowdown. I invert the firm's investment decision to identify the embodied and disembodied components of productivity growth. With a Cobb-Douglas production function, output price mismeasurement only should affect the latter. Contrary to the mismeasurement hypothesis, I find that in the Post-War period, disembodied productivity grew faster in the hard-to-measure than in the non-manufacturing easy-to-measure sectors, and that disembodied productivity slowed down less in the hard-to-measure than in the easy-to-measure sectors since the 70's. These results hold a fortiori when capital and labor are complements.

Suggested Citation

  • Comin, D., 2002. "Using Investment Data to Assess the Importance of Price Mismeasurement," Working Papers 02-08, C.V. Starr Center for Applied Economics, New York University.
  • Handle: RePEc:cvs:starer:02-08

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    References listed on IDEAS

    1. Zvi Griliches, 1998. "Productivity, R&D, and the Data Constraint," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 347-374 National Bureau of Economic Research, Inc.
    2. Martin Neil Baily & Robert J. Gordon, 1988. "The Productivity Slowdown, Measurement Issues, and the Explosion of Computer Power," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(2), pages 347-432.
    3. G. Christian Ehemann & Brent R. Moulton, 2001. "Balancing the GDP Account," BEA Papers 0014, Bureau of Economic Analysis.
    4. James Bessen, 2002. "Technology Adoption Costs and Productivity Growth: The Transition to Information Technology," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 443-469, April.
    5. Chong-en Bai & Shan Li, 2000. "Capital Structure and Product Market Strategy," Annals of Economics and Finance, Society for AEF, vol. 1(2), pages 381-400, November.
    6. Dora L. Costa, 2001. "Estimating Real Income in the United States from 1888 to 1994: Correcting CPI Bias Using Engel Curves," Journal of Political Economy, University of Chicago Press, vol. 109(6), pages 1288-1310, December.
    7. Bresnahan, Timothy F, 1986. "Measuring the Spillovers from Technical Advance: Mainframe Computers inFinancial Services," American Economic Review, American Economic Association, vol. 76(4), pages 742-755, September.
    8. Bruce W. Hamilton, 2001. "Using Engel's Law to Estimate CPI Bias," American Economic Review, American Economic Association, vol. 91(3), pages 619-630, June.
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    Cited by:

    1. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    2. Bruno Tissot & Les Skoczylas, 2005. "Revisiting recent productivity developments across OECD countries," BIS Working Papers 182, Bank for International Settlements.

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    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment

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