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ARE FIXED EFFECTS FIXED? Persistence in Plant Level Productivity

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  • Douglas W Dwyer

Abstract

Estimates of production functions suffer from an omitted variable problem; plant quality is an omitted variable that is likely to be correlated with variable inputs. One approach is to capture differences in plant qualities through plant specific intercepts, i.e., to estimate a fixed effects model. For this technique to work, it is necessary that differences in plant quality are more or less fixed; if the "fixed effects" erode over time, such a procedure becomes problematic, especially when working with long panels. In this paper, a standard fixed effects model, extended to allow for serial correlation in the error term, is applied to a 16-year panel of textile plants. This parametric approach strongly accepts the hypothesis of fixed effects. They account for about one-third of the variation in productivity. A simple non-parametric approach, however, concludes that differences in plant qualities erode over time, that is plant qualities f-mix. Monte Carlo results demonstrate that this discrepancy comes from the parametric approach imposing an overly restrictive functional form on the data; if there were fixed effects of the magnitude measured, one would reject the hypothesis of f-mixing. For textiles, at least, the functional form of a fixed effects model appears to generate misleading conclusions. A more flexible functional form is estimated. The "fixed" effects actually have a half life of approximately 10 to 20 years, and they account for about one-half the variation in productivity.

Suggested Citation

  • Douglas W Dwyer, 1996. "ARE FIXED EFFECTS FIXED? Persistence in Plant Level Productivity," Working Papers 96-3, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:96-3
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    File URL: https://www2.census.gov/ces/wp/1996/CES-WP-96-03.pdf
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    Cited by:

    1. Nathan Musick, 1998. "Heroic Plants: Persistently Rapid Job Creators in the Longitudinal Research Database - Their Distinguishing Characteristics and Contribution to Employment Growth," Industrial Organization 9811001, EconWPA.
    2. Douglas W Dwyer, 1997. "Productivity Races I: Are Some Productivuty Measures Better Than Others?," Working Papers 97-2, Center for Economic Studies, U.S. Census Bureau.
    3. Douglas W Dwyer, 1996. "Whittling Away At Productivity Dispersion Futher Notes: Persistent Dispersion or Measurement Error?," Working Papers 96-11, Center for Economic Studies, U.S. Census Bureau.
    4. Kirk White & Arpad Abraham, 2004. "The Dynamics of Plant-level Productivity in U.S. Manufacturing," Computing in Economics and Finance 2004 332, Society for Computational Economics.
    5. Douglas W Dwyer, 1997. "Productivity Races II: The Issue of Capital Measurement," Working Papers 97-3, Center for Economic Studies, U.S. Census Bureau.

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    Keywords

    CES; economic; research; micro; data; microdata; chief; economist;

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