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Informed Intermediation over the Cycle

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  • Vanasco, Victoria

    (Stanford University)

  • Asriyan, Vladimir

Abstract

We construct a dynamic model of financial intermediation in which changes in the information held by financial intermediaries generate asymmetric credit cycles as the ones documented by Reinhart and Reinhart (2010). We model financial intermediaries as "expert" agents who have a unique ability to acquire information about firm fundamentals. While the level of "expertize" in the economy grows in tandem with information that the "experts" possess, the gains from intermediation are hindered by informational asymmetries. We find the optimal financial contracts and show that the economy inherits not only the dynamic nature of information flow, but also the interaction of information with the contractual setting. We introduce a cyclical component to information by supposing that the fundamentals about which experts acquire information are stochastic. While persistence of fundamentals is essential for information to be valuable, their randomness acts as an opposing force and diminishes the value of expert learning. Our setting then features economic fluctuations due to waves of "confidence" in the intermediaries' ability to allocate funds profitably.

Suggested Citation

  • Vanasco, Victoria & Asriyan, Vladimir, 2014. "Informed Intermediation over the Cycle," Research Papers 3235, Stanford University, Graduate School of Business.
  • Handle: RePEc:ecl:stabus:3235
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    File URL: http://www.gsb.stanford.edu/faculty-research/working-papers/informed-intermediation-over-cycle-0
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    Cited by:

    1. Farboodi, Maryam & Kondor, Péter, 2023. "Cleansing by tight credit: Rational cycles and endogenous lending standards," Journal of Financial Economics, Elsevier, vol. 150(1), pages 46-67.
    2. Jianxing Wei & Tong Xu, 2018. "A Model of Bank Credit Cycles," 2018 Meeting Papers 610, Society for Economic Dynamics.
    3. Maryam Farboodi & Laura Veldkamp, 2017. "Long Run Growth of Financial Technology," NBER Working Papers 23457, National Bureau of Economic Research, Inc.
    4. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," NBER Working Papers 24550, National Bureau of Economic Research, Inc.
    5. Veldkamp, Laura & Farboodi, Maryam, 2018. "Long Run Growth of Financial Data Technology," CEPR Discussion Papers 13278, C.E.P.R. Discussion Papers.
    6. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," Working Papers 18-08, New York University, Leonard N. Stern School of Business, Department of Economics.
    7. Juliane Begenau & Laura Veldkamp & Maryam Farboodi, 2018. "Big Data in Finance and the Growth of Large Firms," 2018 Meeting Papers 155, Society for Economic Dynamics.
    8. Begenau, Juliane & Farboodi, Maryam & Veldkamp, Laura, 2018. "Big data in finance and the growth of large firms," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 71-87.
    9. Maryam Farboodi & Laura Veldkamp, 2018. "Long Run Growth of Financial Data Technology," Working Papers 18-09, New York University, Leonard N. Stern School of Business, Department of Economics.

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