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Price bubbles in oil & gas markets and their transfer

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  • Wang, Zuyi
  • Kim, Man-Keun

Abstract

Research objective of the study is to examine if price bubbles can be transferred between the oil-gas markets. We also estimate the probability of bubble transfer and see if bubble transfer probability depends on the gas pricing mechanisms, for example, oil-indexation. We examine the bubble transfer as followings; i) identifying price bubbles in WTI, Brent, Henry Hub, EU gas, and Japan gas markets using Generalized Sup Augmented Dickey-Fuller (GSADF) test, ii) applying Granger causality test and Autoregressive Distributed Lag (ARDL) model to GSADF test statistics, not the energy prices, which is an innovative approach to understand price bubbles transfer, and iii) estimating probabilities of bubble transfers from the oil market to gas market using Logit models. Empirical results show that GSADF statistics for oil prices Granger cause GSADF statistics for gas prices implying that price bubbles in the oil market could transfer to the gas market. ARDL models with GSADF statistics indicate that the impact of oil GSADF on gas GSADF depends on gas pricing mechanisms. Japan gas market has the large impact and chance of transferring price bubbles from Brent while Henry Hub has the small impact and low chance of bubble transfer from WTI. This study contributes to existing literature by confirming that price bubbles in the oil market transferred to the gas market and the probabilities of transfer depend on gas pricing mechanism.

Suggested Citation

  • Wang, Zuyi & Kim, Man-Keun, 2022. "Price bubbles in oil & gas markets and their transfer," Resources Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:jrpoli:v:79:y:2022:i:c:s0301420722005025
    DOI: 10.1016/j.resourpol.2022.103059
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    More about this item

    Keywords

    Autoregressive distributed lag model; Crude oil prices; Generalized sup augmented dickey-fuller test; Granger causality; Natural gas prices; Price bubbles;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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