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

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Author Info
Jens J. Krüger () (University of Jena, Faculty of Economics)

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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.

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Paper provided by Friedrich-Schiller-Universität Jena, Wirtschaftswissenschaftliche Fakultät in its series Jenaer Schriften zur Wirtschaftswissenschaft with number 09/2003.

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Date of creation: May 2003
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Handle: RePEc:jen:jenasw:2003-09

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Related research
Keywords: productivity; persistence; quantile regression;

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Find related papers by JEL classification:
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - 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; Growth and Fluctuations - - - General, International, or Comparative
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Panos Fousekis, 2007. "Growth determinants, intra-distribution mobility, and convergence of state-level agricultural productivity in the USA," International Review of Economics, Springer, vol. 54(1), pages 129-147, March. [Downloadable!] (restricted)
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