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Financial uncertainty and real activity: The good, the bad, and the ugly

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  • Giovanni Caggiano
  • Efrem Castelnuovo
  • Richard Kima
  • Silvia Delrio

Abstract

This paper quantifies the finance uncertainty multiplier (i.e., the magnifying effect of the real impact of uncertainty shocks due to financial frictions) by relying on two historical events related to the US economy, i.e., the large jump in financial uncertainty occurred in October 1987 (which was not accompanied by a deterioration of the credit supply conditions), and the comparable jump in financial uncertainty in September 2008 (which went hand-in-hand with an increase in financial stress). Working with a VAR framework and a set-identification strategy which focuses on - but it is not limited to - restrictions related to these two dates, we estimate the finance uncertainty multiplier to be equal to 2, i.e., credit supply disruptions are found to double the negative output response to an uncertainty shock. We then employ our model to estimate the overall economic cost of the COVID-19-induced uncertainty shock under different scenarios. Our results point to the possibility of a cumulative yearly loss of industrial production as large as 31% if credit supply gets disrupted. Liquidity interventions that keep credit conditions as healthy as they were before the COVID-19 uncertainty shock are found to substantially reduce such loss.

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  • Giovanni Caggiano & Efrem Castelnuovo & Richard Kima & Silvia Delrio, 2020. "Financial uncertainty and real activity: The good, the bad, and the ugly," CAMA Working Papers 2020-67, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2020-67
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    Cited by:

    1. Caggiano, Giovanni & Castelnuovo, Efrem & Delrio, Silvia & Kima, Richard, 2021. "Financial uncertainty and real activity: The good, the bad, and the ugly," European Economic Review, Elsevier, vol. 136(C).
    2. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Research Discussion Papers 5/2020, Bank of Finland.
    3. Brianti, Marco, 2021. "Financial Shocks, Uncertainty Shocks, and Monetary Policy Trade-Offs," Working Papers 2021-5, University of Alberta, Department of Economics.
    4. Caggiano, Giovanni & Castelnuovo, Efrem, 2021. "Global Uncertainty," Research Discussion Papers 1/2021, Bank of Finland.
    5. Balduzzi, Pierluigi & Brancati, Emanuele & Brianti, Marco & Schiantarelli, Fabio, 2020. "The Economic Effects of COVID-19 and Credit Constraints: Evidence from Italian Firms' Expectations and Plans," IZA Discussion Papers 13629, Institute of Labor Economics (IZA).
    6. Breitenlechner, Max & Geiger, Martin & Scharler, Johann, 2022. "Bank liquidity and the propagation of uncertainty in the U.S," Finance Research Letters, Elsevier, vol. 46(PB).
    7. Afees A. Salisu & Rangan Gupta & Idris A. Adediran, 2021. "The Effect of US Uncertainty Shock on International Equity Markets: The Role of the Global Financial Cycle," Working Papers 202136, University of Pretoria, Department of Economics.
    8. Choi, Sangyup & Furceri, Davide & Loungani, Prakash & Shim, Myungkyu, 2022. "Inflation anchoring and growth: The role of credit constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    9. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    10. Luca Fanelli & Antonio Marsi, 2021. "Unconventional Monetary Policy in the Euro Area: A Tale of Three Shocks," Working Papers wp1164, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.

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    More about this item

    Keywords

    Uncertainty shocks; finance-uncertainty multiplier; set-identification; VAR; financial frictions; COVID-19;
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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