The Term Structure of Growth-at-Risk
IMF Working Papers, August 2, 2018
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- The Term Structure of Growth-at-Risk
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Bibliographic details
- Authors: Tobias Adrian, Federico Grinberg, Nellie Liang, Sheheryar Malik
- Published: August 2, 2018
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781484372364.001
Overview and research question
- Using panel quantile regressions for 11 advanced and 10 emerging market economies, the paper examines how the conditional distribution of GDP growth depends on financial conditions.
- Growth-at-risk (GaR) is defined as growth at the lower 5th percentile.
- The analysis focuses on the term structure of GaR and how initial financial conditions and credit booms affect short- and medium-run downside risks to GDP growth.
Methodology
- Empirical approach: panel quantile regressions.
- Sample: 11 advanced and 10 emerging market economies.
- Key comparison: responsiveness of lower-tail (5th percentile) conditional GDP growth relative to the median and upper percentiles.
Key findings
- Growth-at-risk (GaR) is more responsive to financial conditions than the median or upper percentiles.
- The term structure of GaR features an intertemporal tradeoff:
- GaR is higher in the short run;
- GaR is lower in the medium run when initial financial conditions are loose relative to typical levels.
- The intertemporal tradeoff is amplified by a credit boom.
- Dynamic stochastic general equilibrium models with macrofinancial linkages generally do not incorporate this shift in the growth distribution, which suggests downside risks to GDP growth are systematically underestimated.
Implications for policy and modeling
- Financial conditions and credit booms materially affect the distribution of future GDP growth, especially downside risks captured by GaR.
- Risk assessments and policy frameworks that rely on models omitting this shift in the growth distribution may understate downside risks to GDP growth.
- Incorporating distributional shifts (particularly the term structure of GaR) into macrofinancial models could improve recognition of medium-run vulnerabilities following periods of loose financial conditions and credit expansion.
Content in this bundle
- The Term Structure of Growth-at-Risk, WP/18/180, August 2018