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Learning-by-Doing or Habit Formation?

Author

Listed:
  • Takashi Kano
  • Hafedh Bouakez

    (Economics HEC Montreal)

Abstract

In a recent paper, Chang, Gomes, and Schorfheide (2002) extend the standard real business cycle (RBC) model to allow for a learning-by-doing (LBD) mechanism whereby current labour supply affects future productivity. They show that this feature magnifies the propagation of shocks and improves the matching performance of the standard RBC model. In this paper, the authors show that the LBD model is nearly observationally equivalent to an RBC model with habit formation in labour (or, equivalently, in leisure). Under the same calibration of the parameters, the two models share the same equilibrium paths of output, consumption, and investment, but have different implications for hours worked. Using Bayesian techniques, the authors investigate which of the LBD and habit models fits the U.S. data best. Their results suggest that the habit specification is more strongly supported by the data.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Takashi Kano & Hafedh Bouakez, 2005. "Learning-by-Doing or Habit Formation?," 2005 Meeting Papers 513, Society for Economic Dynamics.
    • Handle: RePEc:red:sed005:513
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    References listed on IDEAS

    as
    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. repec:wop:calsdi:97-23 is not listed on IDEAS
    3. Hall, Robert E, 1997. "Macroeconomic Fluctuations and the Allocation of Time," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 223-250, January.
    4. Cooper, Russell & Johri, Alok, 2002. "Learning-by-doing and aggregate fluctuations," Journal of Monetary Economics, Elsevier, vol. 49(8), pages 1539-1566, November.
    5. Rouwenhorst, K. Geert, 1991. "Time to build and aggregate fluctuations : A reconsideration," Journal of Monetary Economics, Elsevier, vol. 27(2), pages 241-254, April.
    6. Nakajima, Tomoyuki, 2005. "A business cycle model with variable capacity utilization and demand disturbances," European Economic Review, Elsevier, vol. 49(5), pages 1331-1360, July.
    7. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
    8. Andreas Beyer & Roger E. A. Farmer, 2004. "On the Indeterminacy of New-Keynesian Economics," Computing in Economics and Finance 2004 152, Society for Computational Economics.
    9. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    10. Garey Ramey & Wouter J. den Haan & Joel Watson, 2000. "Job Destruction and Propagation of Shocks," American Economic Review, American Economic Association, vol. 90(3), pages 482-498, June.
    11. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    12. 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.
    13. Johri, Alok & Letendre, Marc-Andre, 2007. "What do `residuals' from first-order conditions reveal about DGE models?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2744-2773, August.
    14. John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
    15. Burnside, Craig & Eichenbaum, Martin, 1996. "Factor-Hoarding and the Propagation of Business-Cycle Shocks," American Economic Review, American Economic Association, vol. 86(5), pages 1154-1174, December.
    16. Martin S. Eichenbaum & Lars Peter Hansen & Kenneth J. Singleton, 1988. "A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice Under Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 103(1), pages 51-78.
    17. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Business Cycle Accounting," Econometrica, Econometric Society, vol. 75(3), pages 781-836, May.
    18. Yun, Tack, 1996. "Nominal price rigidity, money supply endogeneity, and business cycles," Journal of Monetary Economics, Elsevier, vol. 37(2-3), pages 345-370, April.
    19. Hotz, V Joseph & Kydland, Finn E & Sedlacek, Guilherme L, 1988. "Intertemporal Preferences and Labor Supply," Econometrica, Econometric Society, vol. 56(2), pages 335-360, March.
    20. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    21. Yongsung Chang & Sun-Bin Kim, 2004. "Heterogeneity and aggregation in the labor market : implications for aggregate preference shifts," Working Paper 03-17, Federal Reserve Bank of Richmond.
    22. repec:dgr:kubcen:199554 is not listed on IDEAS
    23. Bover, Olympia, 1991. "Relaxing Intertemporal Separability: A Rational Habits Model of Labor Supply Estimated from Panel Data," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 85-100, January.
    24. Martin Lettau & Harald Uhlig, 2000. "Can Habit Formation be Reconciled with Business Cycle Facts?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(1), pages 79-99, January.
    25. Andolfatto, David, 1996. "Business Cycles and Labor-Market Search," American Economic Review, American Economic Association, vol. 86(1), pages 112-132, March.
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    More about this item

    Keywords

    Learning-by-doing; Habit formation; Bayesian analysis;
    All these keywords.

    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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