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Measuring Aggregate Productivity Growth Using Plant-Level Data

  • Amil Petrin
  • James Levinsohn

We define aggregate productivity growth as the change in aggregate final demand minus the change in the aggregate cost of primary inputs. We show how to aggregate plant-level data to this measure and how to use plant-level data to decompose our measure into technical efficiency and reallocation components. This requires us to confront the "non-neoclassical" features that impact plant-level data including plant-level heterogeneity, the entry and exit of goods, adjustment costs, fixed and sunk costs, and market power. We compare our measure of aggregate productivity growth to several competing variants that are based only on a single plant-level factor of technical efficiency. We show that theory suggests our measure may differ substantially from these measures of aggregate productivity growth. We illustrate this using panel data from manufacturing industries in Chile. We find that our measure does differ substantially from other widely used measures with especially marked differences in the fraction of productivity growth attributed to reallocation.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11887.

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Date of creation: Dec 2005
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Publication status: published as Amil Petrin & James Levinsohn, 2012. "Measuring aggregate productivity growth using plant-level data," The RAND Journal of Economics, vol 43(4), pages 705-725.
Handle: RePEc:nbr:nberwo:11887
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