Estimating hydrogen demand function: a structural time series model

Mohammad Sharif Karimi, Saleh Ghavidel Doostkouei, Babak Naysary, Mir Hossein Mousavi

Research output: Contribution to journalArticleResearchpeer-review


This paper utilizes a Structural Time Series Model (STM) with an underlying component to estimate the global hydrogen demand function. This approach allows for the discernment of the ongoing impact of technology and the dynamic changes in consumer behavior that affect hydrogen demand over time. To estimate the hydrogen demand function, the analysis incorporates key variables, including hydrogen price, natural gas price, oil price, and GDP (Gross Domestic Product) per capita. The study utilizes quarterly global data from the first quarter of 2009 to the fourth quarter of 2021. In comparing the underlying components influencing hydrogen demand, the study suggests that advancements in production technology, organizational technology, and changes in consumer behavior collectively contribute to a gradual leftward shift in the global hydrogen demand curve over time. The study uncovered that, in the short term, global hydrogen demand demonstrates high inelasticity. Furthermore, the results reveal. a complementary relationship between natural gas and hydrogen, although this complementarity diminishes significantly over time. Additionally, the findings suggest that oil. can function as a substitute for hydrogen, with the substitution effect intensifying in the long term. Interestingly, hydrogen is initially perceived as a luxury commodity, yet over the long term, it transitions to behaving as a normal commodity.

Original languageEnglish
Article number142331
Number of pages14
JournalJournal of Cleaner Production
Publication statusPublished - 25 May 2024


  • Hydrogen demand
  • Natural gas price
  • Oil price
  • Structural time series model

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