Name File Type Size Last Modified
  Replication_and_Outputs 09/08/2021 03:51:PM

Project Citation: 

Adrian, Tobias, Grinberg, Federico, Liang, Nellie, Malik, Sheherya, and Yu, Jie. Data and Code for: The Term Structure of Growth-at-Risk. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-06-24. https://doi.org/10.3886/E129441V1

Project Description

Summary:  View help for Summary We show that the conditional distribution of forecasted GDP growth depends on financial conditions in a panel of 11 advanced economies.  Financial conditions have a larger effect on the lower 5th percentile of conditional growth—which we call growth-at-risk (GaR)—than the median.  In addition, the term structure of GaR reflects that when initial financial conditions are loose, downside risks are lower in the near-term but increase in later quarters.  This intertemporal tradeoff for loose financial conditions is amplified when credit-to-GDP growth is rapid.  Using granular instrumental variables, we also provide evidence that the relationship from loose financial conditions to future downside risks is causal.  Our results suggest that models of macrofinancial linkages should incorporate the endogeneity of higher-order moments to systematically account for downside risks to growth in the medium run.

Scope of Project

Subject Terms:  View help for Subject Terms macroeconomics; financial economics; macroeconomics; financial economics; macro-financial; macroeconomics
JEL Classification:  View help for JEL Classification
      E10 General Aggregative Models: General
      F44 International Business Cycles
      G10 General Financial Markets: General (includes Measurement and Data)
Geographic Coverage:  View help for Geographic Coverage Canada, Sweden, United States, Japan, United Kingdom, Italy, Australia, France, Switzerland, Germany, Spain
Time Period(s):  View help for Time Period(s) 1973 – 2017


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