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Multimodality in Macro-Financial Dynamics

Author

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  • Tobias Adrian
  • Nina Boyarchenko
  • Domenico Giannone

Abstract

We estimate the evolution of the conditional joint distribution of economic and financial conditions. While the joint distribution is approximately Gaussian during normal periods, sharp tightenings of financial conditions lead to the emergence of additional modes. The U.S. economy has historically resolved quickly to the “good” mode, but we conjecture that poor policy choices could lead to prolonged periods of multimodality. We argue that multimodality arises naturally in a macro-financial intermediary model with occasionally binding intermediary constraints.

Suggested Citation

  • Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Multimodality in Macro-Financial Dynamics," Staff Reports 903, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:903
    Note: Revised December 2020.
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    References listed on IDEAS

    as
    1. Tobias Adrian & Fernando M. Duarte, 2016. "Financial vulnerability and monetary policy," Staff Reports 804, Federal Reserve Bank of New York.
    2. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2020. "Economic Policy Uncertainty Spillovers in Booms and Busts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 125-155, February.
    3. Aruoba, S. Borağan & Bocola, Luigi & Schorfheide, Frank, 2017. "Assessing DSGE model nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 83(C), pages 34-54.
    4. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    5. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.
    6. Roger Koenker & Samantha Leorato & Franco Peracchi, 2013. "Distributional vs. Quantile Regression," CEIS Research Paper 300, Tor Vergata University, CEIS, revised 17 Dec 2013.
    7. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    8. Sims, Christopher A., 2000. "Using a likelihood perspective to sharpen econometric discourse: Three examples," Journal of Econometrics, Elsevier, vol. 95(2), pages 443-462, April.
    9. Gertler, M. & Kiyotaki, N. & Prestipino, A., 2016. "Wholesale Banking and Bank Runs in Macroeconomic Modeling of Financial Crises," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.),Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1345-1425, Elsevier.
    10. Norets, Andriy & Pati, Debdeep, 2017. "Adaptive Bayesian Estimation Of Conditional Densities," Econometric Theory, Cambridge University Press, vol. 33(4), pages 980-1012, August.
    11. Diamond, Peter A, 1982. "Aggregate Demand Management in Search Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 90(5), pages 881-894, October.
    12. Jesus Fernandez-Villaverde & Samuel Hurtado & Galo Nuno, 2019. "Financial Frictions and the Wealth Distribution," PIER Working Paper Archive 19-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. John Bryant, 1983. "A Simple Rational Expectations Keynes-type Model," The Quarterly Journal of Economics, Oxford University Press, vol. 98(3), pages 525-528.
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    Cited by:

    1. Mark Gertler & Nobuhiro Kiyotaki & Andrea Prestipino, 2020. "Credit Booms, Financial Crises, and Macroprudential Policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 8-33, August.

    More about this item

    Keywords

    nonparametric density estimator; density impulse response; multimodality;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises

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