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Quantitative Implications Of The Credit Constraint In The Kiyotaki-Moore (1997) Setup

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  • Andrés Arias

Abstract

The Kiyotaki-Moore (1997) framework is a prominent macro model that features credit constraints as an important factor that propagates and magnifies the effects of shocks. However, the quantitative importance of these constraints in this setup remains an open question. This paper introduces the Kiyotaki-Moore (1997) setup into an otherwise standard dynamic general equilibrium model to explore the quantitative properties of credit constraints. I take a Hansen (1985)- type RBC model and introduce a banking sector that intermediates savings and investment. After calibrating the model to post-1959 U.S. data, I evaluate the propagation and magnification effects of a standard TFP shock to the aggregate economy. I find that the quantitative importance is very small. I then ask if the propagation and magnification effects are stronger if the shock originates in the banking sector. I therefore introduce TFP shocks into financial intermediation. I find that the constraints are also quantitatively unimportant. I conclude that the quantitative significance of the credit constraint in the Kiyotaki-Moore setup is small. The reason underlying this result has to do, theoretically, with asset market dynamics and, empirically, with the low participation of loans in economic activity in the U.S.

Suggested Citation

  • Andrés Arias, 2003. "Quantitative Implications Of The Credit Constraint In The Kiyotaki-Moore (1997) Setup," Documentos CEDE 3412, Universidad de los Andes, Facultad de Economía, CEDE.
    • Handle: RePEc:col:000089:003412
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    References listed on IDEAS

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    Cited by:

    1. Ctirad Slavik, 2011. "Asset Prices and Business Cycles with Financial Frictions," 2011 Meeting Papers 587, Society for Economic Dynamics.

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    More about this item

    Keywords

    Credit constraint;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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