IMF Working Papers

The Term Structure of Growth-at-Risk

By Tobias Adrian, Federico Grinberg, Nellie Liang, Sheheryar Malik

August 2, 2018

Download PDF

Preview Citation

Format: Chicago

Tobias Adrian, Federico Grinberg, Nellie Liang, and Sheheryar Malik. The Term Structure of Growth-at-Risk, (USA: International Monetary Fund, 2018) accessed December 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

Using panel quantile regressions for 11 advanced and 10 emerging market economies, we show that the conditional distribution of GDP growth depends on financial conditions, with growth-at-risk (GaR)—defined as growth at the lower 5th percentile—more responsive than the median or upper percentiles. In addition, the term structure of GaR features an intertemporal tradeoff: GaR is higher in the short run; but lower in the medium run when initial financial conditions are loose relative to typical levels, and the tradeoff is amplified by a credit boom. This shift in the growth distribution generally is not incorporated when solving dynamic stochastic general equilibrium models with macrofinancial linkages, which suggests downside risks to GDP growth are systematically underestimated.

Subject: Credit, Credit booms, Financial sector policy and analysis, Financial sector risk, Growth-at-risk assessment, Macrofinancial linkages, Money

Keywords: Coefficient estimate, Credit, Credit booms, Credit growth, Downside risk, Dummy variable, FCI decile group, FCI group, Financial sector risk, Financial stability, GaR decline, GaR estimate, GaR measure, Gaussian distribution, Global, Growth distribution, Growth-at-risk assessment, Macrofinancial linkages, Monetary policy, OLS panel estimation method, Projections estimation method, Quantile regression, Real GDP, Term structure, Time series, Volatility paradox, WP

Publication Details

  • Pages:

    40

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2018/180

  • Stock No:

    WPIEA2018180

  • ISBN:

    9781484372364

  • ISSN:

    1018-5941