Quantile and Time–Frequency Risk Spillover Between Climate Policy Uncertainty and Grains Commodity Markets

Abstract

This paper aims to study the dynamic risk connection between the Climate Policy Uncertainty Index (CPU) of the United States and the grain commodity market. Our findings denote that (a) quantile spillover is stronger at extreme than median levels, underscoring the value of systematic risk spillovers in extreme market conditions. (b) Wavelet coherence analysis proposes that the structure of the CPU connection with the grain commodity market is heterogeneous at time–frequency scales. (c) Under conditions of market stability, CPU's capability to predict risks in the most segmented grain commodity markets was not as pronounced as in extreme market scenarios. (d) The spillovers between CPU and major grain commodities under diverse quantile states were significantly influenced by climate change. Results from this paper have practical implications for investors managing climate-related risk exposures and will also assist policymakers in developing countries to develop a sensible policy package.