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Technology Locks, Creative Destruction And Non-Convergence In Productivity Levels

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  • Douglas W Dwyer
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    Abstract

    This paper presents a simple solution to a new model that seeks to explain the distribution of plants across productivity levels within an industry, and empirically confirms some key predictions using the U.S. textile industry. In the model, plants are locked into a given productivity level, until they exit or retool. Convex costs of adjustment captures the fact that more productive plants expand faster. Provided there is technical change, productivity levels do not converge; the model achieves persistent dispersion in productivity levels within the context of a distortion free competitive equilibrium. The equilibrium, however, is rather turbulent; plants continually come on line with the cutting edge technology, gradually expand and finally exit or retool when they cease to recover their variable costs. The more productive plants create jobs, while the less productive destroy them. The model establishes a close link between productivity growth and dispersion in productivity levels; more rapid productivity growth leads to more widespread dispersion. This prediction is empirically confirmed. Additionally, the model provides an explanation for S-shaped diffusion.

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    File URL: ftp://ftp2.census.gov/ces/wp/1995/CES-WP-95-06.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 95-6.

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    Date of creation: Apr 1995
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    Handle: RePEc:cen:wpaper:95-6

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

    References

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    1. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-97, November.
    2. Jovanovic, B. & MacDonald, G.M., 1991. "Competitive Diffusion," Papers 92-08, Rochester, Business - Financial Research and Policy Studies.
    3. Phoebus J Dhrymes, 1991. "The Structure Of Production Technology Productivity And Aggregation Effects," Working Papers 91-5, Center for Economic Studies, U.S. Census Bureau.
    4. Saul Lach & Rafael Rob, 1995. "R&D, investment and industry dynamics," Finance and Economics Discussion Series 95-47, Board of Governors of the Federal Reserve System (U.S.).
    5. Bernard, A.B. & Jones, C.I., 1993. "Productivity Across Industries and Countries: Time Series Theory and Evidence," Working papers 93-17, Massachusetts Institute of Technology (MIT), Department of Economics.
    6. Alwyn Young, 1991. "Learning by Doing and the Dynamic Effects of International Trade," NBER Working Papers 3577, National Bureau of Economic Research, Inc.
    7. Robert E. Lucas Jr., 1978. "On the Size Distribution of Business Firms," Bell Journal of Economics, The RAND Corporation, vol. 9(2), pages 508-523, Autumn.
    8. Segerstrom, Paul S, 1991. "Innovation, Imitation, and Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 99(4), pages 807-27, August.
    9. Steve J. Davis & John Haltiwanger, 1991. "Gross Job Creation, Gross Job Destruction and Employment Reallocation," NBER Working Papers 3728, National Bureau of Economic Research, Inc.
    10. Dunne, Timothy & Roberts, Mark J & Samuelson, Larry, 1989. "The Growth and Failure of U.S. Manufacturing Plants," The Quarterly Journal of Economics, MIT Press, vol. 104(4), pages 671-98, November.
    11. Ariel Pakes, 1987. "Mueller's Profits in the Long Run," RAND Journal of Economics, The RAND Corporation, vol. 18(2), pages 319-332, Summer.
    12. Jovanovic, Boyan & Lach, Saul, 1989. "Entry, Exit, and Diffusion with Learning by Doing," American Economic Review, American Economic Association, vol. 79(4), pages 690-99, September.
    13. Steven Klepper & Elizabeth Graddy, 1990. "The Evolution of New Industries and the Determinants of Market Structure," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 27-44, Spring.
    14. Nelson, Richard R, 1981. "Research on Productivity Growth and Productivity Differences: Dead Ends and New Departures," Journal of Economic Literature, American Economic Association, vol. 19(3), pages 1029-64, September.
    15. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-70, May.
    16. Young, Alwyn, 1991. "Learning by Doing and the Dynamic Effects of International Trade," The Quarterly Journal of Economics, MIT Press, vol. 106(2), pages 369-405, May.
    17. Calvo, Guillermo A & Wellisz, Stanislaw, 1978. "Supervision, Loss of Control, and the Optimum Size of the Firm," Journal of Political Economy, University of Chicago Press, vol. 86(5), pages 943-52, October.
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    Cited by:
    1. 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.
    2. Lucia Foster & John Haltiwanger & C.J. Krizan, 1998. "Aggregate Productivity Growth: Lessons from Microeconomic Evidence," NBER Working Papers 6803, National Bureau of Economic Research, Inc.
    3. Douglas W Dwyer, 1997. "Productivity Races II: The Issue of Capital Measurement," Working Papers 97-3, Center for Economic Studies, U.S. Census Bureau.
    4. Stuart Kauffman & Jose Lobo & William G. Macready, 1998. "Optimal Search on a Technology Landscape," Research in Economics 98-10-091e, Santa Fe Institute.

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