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Noise-Ridden Lending Cycles

Author

Listed:
  • Jochen Guentner

    (Johannes Kepler University Linz)

  • Elena Afanasyeva

    (Goethe University Frankfurt)

Abstract

In this paper, we use a neoclassical investment model to study the effects of imperfect information on the lending behaviour of financial intermediaries. We start by developing intuition in partial equilibrium. We model a rational financial intermediary with limited knowledge of the current state of the economy. In response to a noise shock, the intermediary lowers the interest rates on risky loans and extends relatively more credit, both of which are unaffected under perfect information. This credit boom is driven by informational rather than financial frictions and accompanied by higher aggregate default and decrease in credit spreads. We further show that these noise-ridden credit booms also survive in the general equilibrium version of the model.

Suggested Citation

  • Jochen Guentner & Elena Afanasyeva, 2017. "Noise-Ridden Lending Cycles," 2017 Meeting Papers 1211, Society for Economic Dynamics.
  • Handle: RePEc:red:sed017:1211
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    References listed on IDEAS

    as
    1. Hikaru Saijo & Cosmin Ilut, 2015. "Learning, Confidence, and Business Cycles," 2015 Meeting Papers 917, Society for Economic Dynamics.
    2. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2018. "Diagnostic Expectations and Credit Cycles," Journal of Finance, American Finance Association, vol. 73(1), pages 199-227, February.
    3. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    4. De Grauwe, Paul & Macchiarelli, Corrado, 2015. "Animal spirits and credit cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 95-117.
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