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Learning and Asymmetric Business Cycles

Author

Listed:
  • Martin Chalkley

    (University of Southampton)

  • In Ho Lee

    (University of Southampton)

Abstract

It is known that a variety of economic time series exhibit asymmetry in the sense that the arrival of a recession is prompt, while the recovery from a recession appears protracted. This paper provides an explanation for the asymmetric movement of economic time series over business cycles by considering learning and information aggregation, given risk aversion on the part of economic agents. A model is constructed in which the underlying state of nature changes according to a symmetric first-order Markov process. Risk-averse agents make capital utilization choices which partially reveal their private information on the underlying state of nature. Risk aversion prevents them from acting promptly on receiving good news, while it encourages them to act quickly on receiving bad news. When this cautious response at the individual level is combined with aggregate noise, an economy-wide asymmetric time series is generated. A numerical simulation is carried out to derive the empirical distribution of movements of such a time series. (Copyright: Elsevier)

Suggested Citation

  • Martin Chalkley & In Ho Lee, 1998. "Learning and Asymmetric Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(3), pages 623-645, July.
  • Handle: RePEc:red:issued:v:1:y:1998:i:3:p:623-645
    DOI: 10.1006/redy.1998.0024
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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