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Vulnerable Growth

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  • Adrian, Tobias
  • Boyarchenko, Nina
  • Giannone, Domenico

Abstract

We study the conditional distribution of GDP growth as a function of economic and financial conditions. Deteriorating financial conditions are associated with an increase in conditional volatility and a decline in the conditional mean of GDP growth leading to a highly skewed distribution, with the lower quantiles of GDP growth exhibiting strong variation as a function of financial conditions and the upper quantiles stable over time. While measures of financial conditions significantly forecast downside vulnerability, measures of economic conditions have significant predictive power only for the median of the distribution. These findings are robust both in- and out-of-sample and to including different measures of financial conditions. We quantify GDP vulnerability as relative entropy between the empirical conditional and unconditional distribution. We show that this measure of vulnerability is highly asymmetric: the contribution to the total relative entropy of the probability mass below the median of the conditional distribution is larger and more volatile than the contribution of the probability mass above the median. The asymmetric response of the distribution of GDP growth to financial and economic conditions -- with adverse financial conditions increasing downside vulnerability of growth but not the median forecast -- is challenging for standard models of the macroeconomy. We argue that the inclusion of a financial sector is crucial for generating the observed dynamics of growth vulnerability.

Suggested Citation

  • Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2016. "Vulnerable Growth," CEPR Discussion Papers 11583, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11583
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    1. Possible pitfalls of a 1-in-X approach to financial stability
      by BankUnderground in Bank Underground on 2020-02-06 09:00:00

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    Cited by:

    1. Andrew Filardo & Marco Jacopo Lombardi & Marek Raczko, 2018. "Measuring financial cycle time," BIS Working Papers 755, Bank for International Settlements.
    2. Piergiorgio Alessandri & Antonio M. Conti & Fabrizio Venditti, 2016. "The Financial Stability Dark Side of Monetary Policy," BCAM Working Papers 1601, Birkbeck Centre for Applied Macroeconomics.
    3. Richard K. Crump & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Liberty Street Economics 20181004, Federal Reserve Bank of New York.
    4. Dominic Anene & Stefania D'Amico, 2017. "A Tale of Four Tails: Inflation, the Policy Rate, Longer-Term Rates, and Stock Prices," Working Paper Series WP-2017-26, Federal Reserve Bank of Chicago.
    5. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    6. Isabel Cairo & Jae Sim, 2017. "Income Inequality, Financial Crises and Monetary Policy," 2017 Meeting Papers 1433, Society for Economic Dynamics.
    7. Divya Kirti, 2018. "Lending Standards and Output Growth," IMF Working Papers 2018/023, International Monetary Fund.
    8. Thibaut Duprey, 2018. "Asymmetric Risks to the Economic Outlook Arising from Financial System Vulnerabilities," Staff Analytical Notes 2018-6, Bank of Canada.
    9. Claudio Borio & Piti Disyatat & Phurichai Rungcharoenkitkul, 2018. "What anchors for the natural rate of interest?," PIER Discussion Papers 98, Puey Ungphakorn Institute for Economic Research, revised Nov 2018.
    10. Aida Caldera Sánchez & Oliver Röhn, 2016. "How do policies influence GDP tail risks?," OECD Economics Department Working Papers 1339, OECD Publishing.
    11. Tatjana Dahlhaus & Tatevik Sekhposyan, 2018. "Monetary Policy Uncertainty: A Tale of Two Tails," Staff Working Papers 18-50, Bank of Canada.

    More about this item

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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