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

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Title: Climate Risk Transmissions to Commodity Markets: Evidence from a Mixed-Frequency Spillover Approach
Language: English
Authors: Ye Chen, Yu Wei (ORCID 0000-0003-3809-1449), Chunyan Zhou (ORCID 0009-0007-0256-8539)
Source: Evaluation Review. 2026 50(3):346-383.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 38
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Climate, Risk, Business, Statistical Analysis
DOI: 10.1177/0193841X251391891
ISSN: 0193-841X
1552-3926
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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1501591
Database: ERIC
FullText Text:
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  Data: Climate Risk Transmissions to Commodity Markets: Evidence from a Mixed-Frequency Spillover Approach
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Ye+Chen%22">Ye Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Yu+Wei%22">Yu Wei</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3809-1449">0000-0003-3809-1449</externalLink>)<br /><searchLink fieldCode="AR" term="%22Chunyan+Zhou%22">Chunyan Zhou</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0007-0256-8539">0009-0007-0256-8539</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Evaluation+Review%22"><i>Evaluation Review</i></searchLink>. 2026 50(3):346-383.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 38
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  Data: 2026
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Climate%22">Climate</searchLink><br /><searchLink fieldCode="DE" term="%22Risk%22">Risk</searchLink><br /><searchLink fieldCode="DE" term="%22Business%22">Business</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Analysis%22">Statistical Analysis</searchLink>
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  Data: 10.1177/0193841X251391891
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  Data: 0193-841X<br />1552-3926
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  Label: Abstract
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  Data: 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.
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  Data: 2026
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