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Growth-at-Risk is Investment-at-Risk

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Abstract

We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role. We show that leverage plays a key role in determining both consumption- and investment-at-risk, which provides support to the financial accelerator mechanism proposed by Bernanke et al. (1999).

Suggested Citation

  • Aaron Amburgey & Michael W. McCracken, 2023. "Growth-at-Risk is Investment-at-Risk," Working Papers 2023-020, Federal Reserve Bank of St. Louis, revised 16 Aug 2024.
    • Handle: RePEc:fip:fedlwp:96594
    DOI: 10.20955/wp.2023.020
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    References listed on IDEAS

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    1. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    2. Edward E. Leamer, 2007. "Housing is the business cycle," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 149-233.
    3. Tony Chernis & Patrick J. Coe & Shaun P. Vahey, 2023. "Reassessing the dependence between economic growth and financial conditions since 1973," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 260-267, March.
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    Cited by:

    1. Zhou, Yang, 2024. "Benefits and costs: The impact of capital control on growth-at-risk in China," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    growth-at-risk; real-time data; quantiles; expected shortfall;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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