Abstract
We analyse 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 much 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 |
|---|---|
| Place of Publication | Pretoria |
| Publisher | University of Pretoria |
| Number of pages | 13 |
| Publication status | Published - Mar 2024 |
| Series | Working Paper Series / Department of Economics. University of Pretoria |
|---|---|
| Number | 2024-10 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- Economic conditions
- Uncertainty
- Climate risks
- US states
- Linear and nonlinear local projections models
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