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Learning by Doing as a Propagation Mechanism

Listed author(s):
  • Yongsung Chang

    (University of Pennsylvania)

  • Joao Gomes

    (University of Pennsylvania)

  • Frank Schorfheide

    (University of Pennsylvania)

This paper suggests that skill accumulation through past work experience, or ``learning-by-doing'' (LBD), can provide an important propagation mechanism in a dynamic stochastic general equilibrium model, as the current labor supply affects future productivity. Our econometric analysis uses a Bayesian approach to combine micro-level panel data with aggregate time series. Formal model evaluation shows that the introduction of the LBD mechanism improves the model's ability to fit the dynamics of aggregate output and hours.

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File URL: http://econwpa.repec.org/eps/mac/papers/0204/0204002.pdf
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Paper provided by EconWPA in its series Macroeconomics with number 0204002.

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Date of creation: 01 May 2002
Handle: RePEc:wpa:wuwpma:0204002
Note: Type of Document - pdf; prepared on IBM-PC; to print on HP;
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Learning-by-Doing as a Propagation Mechanism (AER 2002) in ReplicationWiki
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