Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We analyse the impact of climate risks (temperature growth and its volatility) on the coincident indicator of the 50 US states in a panel data set-up, over the monthly period of March, 1984 to December, 2019. Using impulse response functions (IRFs) from a linear local projections (LPs) model, we show that climate risks negatively impact economic activity to a similar degree, irrespective of whether such risks are due to changes in temperature growth or its volatility. More importantly, using a nonlinear LPs model, the IRFs reveal that the adverse effect of climate risks is contingent on the regimes of economic and policy-related uncertainty of the states, with the impact being significantly much stronger under relatively higher values of uncertainty, rather than lower values of the same. In addition to this, temperature growth volatility is found to contract economic activity nearly five times more compared to when temperature growth increases by a similar magnitude in the higher uncertainty-based regime of the nonlinear model. Understandably, our results have important policy implications.