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Productivity Dynamics Beyond-the-Mean in U.S. Manufacturing Industries

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  • Jens J. Krüger

    () (University of Jena, Faculty of Economics)

Abstract

The approach of quantile regression is used to explore the fine details of the relation of current period and lagged productivity levels. Productivity is calculated as total factor productivity by a nonparametric approach using data for U.S. manufacturing industries on the three- and four-digit levels. Bootstrap-based confidence intervals and specification tests are reported. The results point to a first-order Markov process as a valid description of productivity transitions. Further conditioning variables show up insignificant in the majority of cases considered. The most notable exception is the variability of the growth process which increases explanatory power substantially.

Suggested Citation

  • Jens J. Krüger, 2003. "Productivity Dynamics Beyond-the-Mean in U.S. Manufacturing Industries," Jenaer Schriften zur Wirtschaftswissenschaft (Expired!) 09/2003, Friedrich-Schiller-Universität Jena, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:jen:jenasw:2003-09
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    References listed on IDEAS

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    1. repec:cup:etheor:v:11:y:1995:i:1:p:105-21 is not listed on IDEAS
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    4. Quah, Danny T, 1996. "Twin Peaks: Growth and Convergence in Models of Distribution Dynamics," Economic Journal, Royal Economic Society, vol. 106(437), pages 1045-1055, July.
    5. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    6. Entorf, Horst, 1997. "Random walks with drifts: Nonsense regression and spurious fixed-effect estimation," Journal of Econometrics, Elsevier, vol. 80(2), pages 287-296, October.
    7. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
    9. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    10. Harberger, Arnold C, 1998. "A Vision of the Growth Process," American Economic Review, American Economic Association, vol. 88(1), pages 1-32, March.
    11. Danny Quah, 1996. "Twin Peaks: Growth and Convergence in Models of Distribution Dynamics," CEP Discussion Papers dp0280, Centre for Economic Performance, LSE.
    12. Bronwyn H. Hall & Zvi Griliches & Jerry A. Hausman, 1984. "Patents and R&D: Is There A Lag?," NBER Working Papers 1454, National Bureau of Economic Research, Inc.
    13. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
    14. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    15. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    16. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
    17. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    18. Bernd Fitzenberger & Roger Koenker & JosÊ A. F. Machado, 2001. "Introduction," Empirical Economics, Springer, vol. 26(1), pages 1-5.
    19. Hahn, Jinyong, 1995. "Bootstrapping Quantile Regression Estimators," Econometric Theory, Cambridge University Press, vol. 11(01), pages 105-121, February.
    20. Flaig, Gebhard & Stadler, Manfred, 1994. "Success Breeds Success. The Dynamics of the Innovation Process," Empirical Economics, Springer, vol. 19(1), pages 55-68.
    21. repec:fth:harver:1487 is not listed on IDEAS
    22. Gort, Michael & Klepper, Steven, 1982. "Time Paths in the Diffusion of Product Innovations," Economic Journal, Royal Economic Society, vol. 92(367), pages 630-653, September.
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    Cited by:

    1. Panos Fousekis, 2007. "Growth determinants, intra-distribution mobility, and convergence of state-level agricultural productivity in the USA," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 54(1), pages 129-147, March.

    More about this item

    Keywords

    productivity; persistence; quantile regression;

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • N10 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - General, International, or Comparative
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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