
Macroeconomists seeking to construct conditional forecasts often face a choice between taking a stand on the details of a fully-specified structural model or relying on empirical correlations from vector autoregressions and remain silent about the underlying causal mechanisms. This paper develops tools for constructing ``structural scenarios'' that can be given an economic interpretation using identified structural VARs. We provide a unified and transparent treatment of conditional forecasting and structural scenario analysis and relate our approach to entropic forecast tilting. We advocate for a careful treatment of uncertainty, making the methods suitable for density forecasting and risk assessment. We also propose a metric to assess and compare the plausibility of alternative scenarios. We illustrate our methods with two applications: assessing the power of forward guidance about future interest rate policies and stress testing the reaction of bank profitability to an economic recession.\ud
HC, HB, HA, HG
HC, HB, HA, HG
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 62 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
