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Dynamic risks from climate policy uncertainty: A case study for the natural gas market

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  • Liu, Guangqiang
  • Zeng, Qing
  • Lei, Juan

Abstract

A series of policies proposed to deal with climate change has affected the development of the natural gas market. This study aims to investigate whether climate policy uncertainty (CPU) affects natural gas from a dynamic perspective. First, we employ the time-varying Granger causality test to test the impact of CPU on natural gas over time. The results show that events related to climate policy can lead to changes in this impact. Then, we detect the long-, mid-, and short-run changes in this impact by using the frequency-domain Granger causality test. We find that the CPU only holds a significant long-run effect on natural gas. However, considering that raised CPU and declined CPU may have different effects on natural gas, we further apply the asymmetric frequency-domain test, and the results verify that this unidirectional risk transmission has asymmetry. Particularly, we find that increased CPU may lead to a decline in natural gas in the medium run, and this impact lasts until the end of the sample. Thus, market participants invested in natural gas markets should pay attention to the events related to climate policies and the long-run impact of CPU, especially of increased CPU shocks.

Suggested Citation

  • Liu, Guangqiang & Zeng, Qing & Lei, Juan, 2022. "Dynamic risks from climate policy uncertainty: A case study for the natural gas market," Resources Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:jrpoli:v:79:y:2022:i:c:s0301420722004573
    DOI: 10.1016/j.resourpol.2022.103014
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    Cited by:

    1. Ke Mao & Junxin Huang, 2022. "How Does Climate Policy Uncertainty Affect Green Innovation? Evidence from China," IJERPH, MDPI, vol. 19(23), pages 1-14, November.
    2. Su, Chi Wei & Qin, Meng & Chang, Hsu-Ling & Țăran, Alexandra-Mădălina, 2023. "Which risks drive European natural gas bubbles? Novel evidence from geopolitics and climate," Resources Policy, Elsevier, vol. 81(C).
    3. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    4. Zhang, Hongwei & Hong, Huojun & Ding, Shijie, 2023. "The role of climate policy uncertainty on the long-term correlation between crude oil and clean energy," Energy, Elsevier, vol. 284(C).
    5. Guo, Kun & Liu, Fengqi & Sun, Xiaolei & Zhang, Dayong & Ji, Qiang, 2023. "Predicting natural gas futures’ volatility using climate risks," Finance Research Letters, Elsevier, vol. 55(PA).

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    More about this item

    Keywords

    Climate policy uncertainty; Natural gas markets; Time-varying; Asymmetric; Granger causality;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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