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