Scenarios
What happens to the financial stress index after a climate shock? This page shows estimation results as they are, without re-estimation.
Estimation period: 1999-2025 (27 annual observations).
Shock simulator
Choose the rise in the climate risk index in a given year and the state of the financial system (quantile τ). The simulator shows the estimated effect on the financial stress index the following year, with its confidence interval.
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The default shock equals one standard deviation of the climate risk index (21.9 points). Effect = coefficient × shock size, over one year.
Coefficients by quantile
| Quantile | Coefficient | 95% CI | p |
|---|---|---|---|
| τ = 0.20 (low stress) | 0.667 | [-0.252 ; 1.288] | 0.180 |
| τ = 0.50 (median) | 0.687 | [-0.516 ; 1.369] | 0.358 |
| τ = 0.80 (high stress) | -0.027 | [-0.772 ; 1.719] | 0.922 |
| τ = 0.90 (maximum stress) | -0.233 | [-0.878 ; 1.922] | 0.860 |
| VAR (average) | 0.624 | [0.141 ; 1.108] | 0.007 |
At the quantiles, bootstrap confidence intervals include zero, and the test of equal coefficients across quantiles does not reject equality (p = 0.496). In the average VAR, the coefficient is significant. These results describe predictive precedence, not an established causal effect.
Response path over time
Horizontal axis: years after the shock. One-standard-deviation shock to the climate risk index (Cholesky decomposition). Only the one-year response is statistically significant at 5%.
Granger test: F = 6.75, p = 0.016. Toda-Yamamoto test (climate risk to financial stress): p = 0.012; reverse direction: p = 0.742.