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Learning, Capital-Embodied Technology and Aggregate Fluctuations

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  • Christoph Görtz
  • John Tsoukalas

Abstract

Recent evidence suggests that agents’ expectations may have played a role in several cycli¬cal episodes such as the U.S. "new economy" boom in the late 1990s, the real estate boom in Japan in the 1980s and the real estate boom in the U.S. which ended in 2008. One chal¬lenge in the expectations driven view of fluctuations has been to develop simple one sector models that can give rise to such fluctuations without a compromise on other dimensions. In this paper we propose a simple generalization of the Greenwood et al. (1988) one sec¬tor model and show it can generate fluctuations that arise as a result of agents difficulty to forecast productivity embodied in new capital. The two key assumptions in the model are: (1) the vintage view of capital productivity, whereby each successive vintage has (po¬tentially) different productivity and (2) agents’ imperfect information and learning about this productivity. The model is consistent with second and third moments from U.S. data. Simulations of the model suggest that, (a) noise amplifies fluctuations and (b) pure noise can trigger recessions that mimic in magnitude, duration and depth the typical post WW II U.S. recession.

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  • Christoph Görtz & John Tsoukalas, 2011. "Learning, Capital-Embodied Technology and Aggregate Fluctuations," Discussion Papers 11/06, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  • Handle: RePEc:not:notcfc:11/06
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    Cited by:

    1. Saijo, Hikaru, 2017. "The uncertainty multiplier and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 1-25.
    2. Christoph Görtz & John D. Tsoukalas, 2013. "Sector Specific News Shocks in Aggregate and Sectoral Fluctuations," CESifo Working Paper Series 4269, CESifo.
    3. repec:pra:mprapa:38985 is not listed on IDEAS
    4. Görtz, Christoph & Tsoukalas, John, 2011. "News and financial intermediation in aggregate and sectoral fluctuations," MPRA Paper 38986, University Library of Munich, Germany, revised Mar 2012.
    5. Görtz, Christoph & Yeromonahos, Mallory, 2022. "Asymmetries in risk premia, macroeconomic uncertainty and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    6. Christopher M. Gunn, 2018. "Overaccumulation, Interest, and Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 479-511, March.
    7. Christoph Görtz & John D. Tsoukalas, 2017. "News and Financial Intermediation in Aggregate Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 514-530, July.
    8. Domenico Ferraro, 2018. "The Asymmetric Cyclical Behavior of the U.S. Labor Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 30, pages 145-162, October.
    9. Ma, Xiaohan & Samaniego, Roberto, 2022. "Business cycle dynamics when neutral and investment-specific technology shocks are imperfectly observable," Journal of Mathematical Economics, Elsevier, vol. 101(C).
    10. Domenico Ferraro, 2018. "The Asymmetric Cyclical Behavior of the U.S. Labor Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 30, pages 145-162, October.

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    More about this item

    Keywords

    News shocks; expectations; growth asymmetry; Bayesian learning; business cy¬cles.;
    All these keywords.

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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