Abstract
We analyze the impact of uncertainty on the Economic Conditions Index (ECI) of the 50 US states in a panel data set-up, over the weekly period of the 3rd week of April 1987 to the 4th week of March 2023. Using impulse response functions (IRFs) from a linear local projections (LP) model, we show that uncertainty, as captured by the stochastic volatility (SV) of the ECIs, negatively impacts ECI in a statistically significant manner. More importantly, using a nonlinear LP model, the IRFs reveal that the adverse effect of uncertainty is significantly stronger under the high-regime of climate risks when compared to the low-regime of the same. Understandably, our results have important policy implications.
| Original language | English |
|---|---|
| Journal | Scottish Journal of Political Economy |
| Number of pages | 8 |
| ISSN | 0036-9292 |
| DOIs | |
| Publication status | Published - 24 Oct 2025 |
Bibliographical note
Epub ahead of print. Published online: 24 October 2025.UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- Climate risks
- Economic conditions
- Extreme weather risks
- Linear and nonlinear local projections models
- Uncertainty
- US states
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