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Learning-by-Doing as a Propagation Mechanism

Author

Listed:
  • Yongsung Chang
  • Joao F. Gomes
  • Frank Schorfheide

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.

Suggested Citation

  • Yongsung Chang & Joao F. Gomes & Frank Schorfheide, 2002. "Learning-by-Doing as a Propagation Mechanism," American Economic Review, American Economic Association, vol. 92(5), pages 1498-1520, December.
  • Handle: RePEc:aea:aecrev:v:92:y:2002:i:5:p:1498-1520
    Note: DOI: 10.1257/000282802762024601
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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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