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Productivity Races I: Are Some Productivuty Measures Better Than Others?

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  • Douglas W Dwyer
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    Abstract

    In this study we construct twelve different measures of productivity at the plant level and test which measures of productivity are most closely associated with direct measures of economic performance. We first examine how closely correlated these measures are with various measures of profits. We then evaluate the extent to which each productivity measure is associated with lower rates of plant closure and faster plant growth (growth in employment, output, and capital). All measures of productivity considered are credible in the sense that highly productive plants, regardless of measure, are clearly more profitable, less likely to close, and grow faster. Nevertheless, labor productivity and measures of total factor productivity that are based on regression estimates of production functions are better predictors of plant growth and survival than factor share-based measures of total factor productivity (TFP). Measures of productivity that are based on several years of data appear to outperform measures of productivity that are based solely on data from the most recent year.

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    File URL: ftp://ftp2.census.gov/ces/wp/1997/CES-WP-97-02.pdf
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    Bibliographic Info

    Paper provided by Center for Economic Studies, U.S. Census Bureau in its series Working Papers with number 97-2.

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    Date of creation: Jan 1997
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    Handle: RePEc:cen:wpaper:97-2

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

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," Harvard Institute of Economic Research Working Papers 1719, Harvard - Institute of Economic Research.
    2. 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.
    3. Douglas W Dwyer, 1995. "Technology Locks, Creative Destruction And Non-Convergence In Productivity Levels," Working Papers 95-6, Center for Economic Studies, U.S. Census Bureau.
    4. Douglas W Dwyer, 1995. "Whittling Away At Productivity Dispersion," Working Papers 95-5, Center for Economic Studies, U.S. Census Bureau.
    5. Robert H Mcguckin & George A Pascoe, 1988. "The Longitudinal Research Database (LRD): Status And Research Possibilities," Working Papers 88-2, Center for Economic Studies, U.S. Census Bureau.
    6. 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.
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    Cited by:
    1. C.J. Krizan & John Haltiwanger & Lucia Foster, 2002. "The Link Between Aggregate and Micro Productivity Growth: Evidence from Retail Trade," Working Papers 02-18, Center for Economic Studies, U.S. Census Bureau.
    2. 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.

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