Can effects of weather variation predict future economic downturn? Evidence from systemic risk in Indian financial markets

We examine how weather variation influences economic activity through its impact on systemic risk in financial markets, an underexplored channel for a developing economy like India. Using a semi-parametric generalized additive model, we analyze weather effects on monthly systemic risk data from 898 listed Indian firms from January 2005 to November 2022. Our findings confirm that weather variation significantly impacts Indian systemic risk. However, we observe that these effects are reliably estimated when we consider decomposed weather- expected and anomaly-instead of aggregate weather variables. We find that a rise in temperature (precipitation) increases (decreases) systemic risk. Unlike existing studies, this paper highlights that the impact is more pronounced when we observe a rise in weather anomaly compared to its expected counterpart. Moreover, these weather effects vary across seasons and broad industry clusters. Supply chain disruptions, energy demand shifts, and credit supply constraints emerge as key mechanisms linking weather fluctuations to systemic risk. Finally, we show that weather-related systemic risk can predict future economic downturns, offering early warning signs for climate risk management.