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Learning by Doing as a Propagation Mechanism

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  • Yongsung Chang

    (University of Pennsylvania)

  • Joao Gomes

    (University of Pennsylvania)

  • Frank Schorfheide

    (University of Pennsylvania)

Abstract

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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Bibliographic Info

Paper provided by EconWPA in its series Macroeconomics with number 0204002.

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Date of creation: 01 May 2002
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Handle: RePEc:wpa:wuwpma:0204002

Note: Type of Document - pdf; prepared on IBM-PC; to print on HP;
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Web page: http://128.118.178.162

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Keywords: Learning by Doing; Propagation Mechanism; Business Cycles; Bayesian Analysis;

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