caa a22 4500 467896054 CHVBK 20180406152804.0 cr unu---uuuuu 170328e20060301xx s 000 0 eng 10.1007/s00181-005-0020-y doi (NATIONALLICENCE)springer-10.1007/s00181-005-0020-y Krüger Jens Department of Economics, Friedrich-Schiller-University Jena, Carl-Zeiss Strasse 3, D-07743, Jena, Germany aut Productivity dynamics beyond-the-mean in U.S. manufacturing industries: An application of quantile regression [Elektronische Daten] [Jens Krüger] In this paper quantile regression is used to explore the relation of current and lagged productivity levels of U.S. manufacturing industries. Productivity is calculated in the form of total factor productivity by a non-parametric approach. Bootstrap-based confidence intervals and specification tests are reported. Key findings are that a first-order Markov process provides a valid description of productivity transitions and that persistence is larger in the range of higher productivity levels. This is reinforced by the widespread insignificance of additional conditioning variables. A notable exception is the variability of the growth path which increases explanatory power substantially. Springer-Verlag, 2005 Productivity nationallicence Persistence nationallicence Quantile regression nationallicence Empirical Economics Springer-Verlag 31/1(2006-03-01), 95-111 0377-7332 31:1<95 2006 31 181 https://doi.org/10.1007/s00181-005-0020-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00181-005-0020-y text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Krüger Jens Department of Economics, Friedrich-Schiller-University Jena, Carl-Zeiss Strasse 3, D-07743, Jena, Germany aut NATIONALLICENCE 773 0- Empirical Economics Springer-Verlag 31/1(2006-03-01), 95-111 0377-7332 31:1<95 2006 31 181 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer