Climate Risk Transmissions to Commodity Markets: Evidence From a Mixed-Frequency Spillover Approach

The relationship between climate risks and commodity markets remains insufficiently explored, especially when analyzed through the lens of high-frequency data. This study seeks to address this gap by investigating the spillover effects of global climate risks, both physical and transitional, on key commodity markets and employs a novel analytical framework. By utilizing newly developed climate risk indices alongside the innovative mixed-frequency spillover measure, this research combines high-frequency climate risk data with the responses of low-frequency commodity prices. Our results highlight notable spillover effects, demonstrating that climate risks serve as the primary drivers of spillovers to commodity markets in a mixed-frequency data context, whereas such effects are not observed within a common-frequency data environment. These findings have important implications for policy-makers and investors, indicating that current market analyses may not capture the influence of climate risk adequately.

Authors

Institutions

Publication Details

Journal
Evaluation Review
Published
2025-10-29
DOI
https://doi.org/10.1177/0193841x251391891
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climate Risk Transmissions to Commodity Markets: Evidence From a Mixed-Frequency Spillover Approach

Ye Chen, Chunyan Zhou, Yu Wei
Evaluation Review
Market Dynamics and Volatility
article

Climate Risk Transmissions to Commodity Markets: Evidence From a Mixed-Frequency Spillover Approach

Ye Chen, Chunyan Zhou, Yu Wei
article en

Abstract

The relationship between climate risks and commodity markets remains insufficiently explored, especially when analyzed through the lens of high-frequency data. This study seeks to address this gap by investigating the spillover effects of global climate risks, both physical and transitional, on key commodity markets and employs a novel analytical framework. By utilizing newly developed climate risk indices alongside the innovative mixed-frequency spillover measure, this research combines high-frequency climate risk data with the responses of low-frequency commodity prices. Our results highlight notable spillover effects, demonstrating that climate risks serve as the primary drivers of spillovers to commodity markets in a mixed-frequency data context, whereas such effects are not observed within a common-frequency data environment. These findings have important implications for policy-makers and investors, indicating that current market analyses may not capture the influence of climate risk adequately.

Evaluation Review
China West Normal University (CN), University of Finance and Economics (MN), Honghe University (CN), Yunnan University of Finance And Economics (CN)
Openalex Percentile: Top 60%
Market Dynamics and Volatility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.