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Learning Efficiency Shocks, Knowledge Capital and the Business Cycle: A Bayesian Evaluation

Alok Johri () and Muhebullah Karimzada ()

Department of Economics Working Papers from McMaster University

Abstract: We incorporate shocks to the efficiency with which firms learn from production activity and accumulate knowledge into an otherwise standard real DSGE model with imperfect competition. Using real aggregate data and Bayesian inference techniques, we find that learning efficiency shocks are an important source of observed variation in the growth rate of aggregate output, investment, consumption and especially hours worked in post-war US data. The estimated shock processes suggest much less exogenous variation in preferences and total factor productivity are needed by our model to account for the joint dynamics of consumption and hours. This occurs because learning efficiency shocks induce shifts in labour demand uncorrelated with current TFP, a role usually played by preference shocks. At the same time, knowledge capital acts like an endogenous source of productivity variation in the model. Measures of model fit prefer the specification with learning efficiency shocks. Independent evidence on learning efficiency shocks are provided using sign-restriction based structural vector auto-regressions.

Keywords: Business Cycles; Learning-by-Doing; Learning Efficiency Shocks; Knowledge Capital (search for similar items in EconPapers)
JEL-codes: E32 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2018-12
New Economics Papers: this item is included in nep-dge, nep-knm and nep-mac
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Related works:
Working Paper: Learning Efficiency Shocks, Knowledge Capital and the Business Cycle: A Bayesian Evaluation (2016) Downloads
Working Paper: Learning Efficiency Shocks, Knowledge Capital and the Business Cycle: A Bayesian Evaluation (2015) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:mcm:deptwp:2018-18

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