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The Impact of Plant-level Resource Reallocations and Technical Progress on U.S. Macroeconomic Growth

  • Amil Petrin

    (University of Minnesota)

  • Jerome Reiter

    (Duke University)

  • Kirk White

    (U.S. Department of Agriculture)

We build up from the plant level an aggregate(d) Solow residual by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. Our framework uses the Petrin and Levinsohn (2010) definition of aggregate productivity growth, which aggregates plant-level changes to changes in aggregate final demand in the presence of imperfect competition and other distortions and frictions. We decompose these contributions into plant-level resource reallocations and plant-level technical efficiency changes while allowing in the estimation for 459 different production technologies, one for each 4-digit SIC code. On average we find positive aggregate productivity growth of 2.2% in this sector during this period of declining share in U.S. GDP. We find that aggregate reallocation made a larger contribution to growth than aggregate technical efficiency. Our estimates of the contribution of reallocation range from 1.7% to 2.1% per year, while our estimates of the average contribution of aggregate technical efficiency growth range from 0.2% to 0.6% per year. In terms of cyclicality, the aggregate technical efficiency component has a standard deviation that is roughly 50% to 100% larger than that of aggregate total reallocation, pointing to an important role for technical efficiency in macroeconomic fluctuations. Aggregate reallocation is negative in only 3 of the 20 years of our sample, suggesting that the movement of inputs to more highly valued activities on average plays a stabilizing role in manufacturing growth. Our results have implications for both the theoretical literature on growth and alternative indexes of aggregate productivity growth based only on technical efficiency. (Copyright: Elsevier)

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File URL: http://dx.doi.org/10.1016/j.red.2010.09.004
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Article provided by Elsevier for the Society for Economic Dynamics in its journal Review of Economic Dynamics.

Volume (Year): 14 (2011)
Issue (Month): 1 (January)
Pages: 3-26

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Handle: RePEc:red:issued:09-247
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  1. Chang-Tai Hsieh & Peter J. Klenow, 2007. "Misallocation and Manufacturing TFP in China and India," NBER Working Papers 13290, National Bureau of Economic Research, Inc.
  2. Basu, Susanto & Fernald, John G., 2002. "Aggregate productivity and aggregate technology," European Economic Review, Elsevier, vol. 46(6), pages 963-991, June.
  3. Ron S Jarmin & Javier Miranda, 2002. "The Longitudinal Business Database," Working Papers 02-17, Center for Economic Studies, U.S. Census Bureau.
  4. Hulten, Charles R, 1978. "Growth Accounting with Intermediate Inputs," Review of Economic Studies, Wiley Blackwell, vol. 45(3), pages 511-18, October.
  5. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Wiley Blackwell, vol. 70(2), pages 317-341, 04.
  6. Marc J. Melitz, 2003. "The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity," Econometrica, Econometric Society, vol. 71(6), pages 1695-1725, November.
  7. George S Olley & Ariel Pakes, 1992. "The Dynamics Of Productivity In The Telecommunications Equipment Industry," Working Papers 92-2, Center for Economic Studies, U.S. Census Bureau.
  8. Lucia Foster & John C. Haltiwanger & C. J. Krizan, 2001. "Aggregate Productivity Growth. Lessons from Microeconomic Evidence," NBER Chapters, in: New Developments in Productivity Analysis, pages 303-372 National Bureau of Economic Research, Inc.
  9. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
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