Influence of oil price fluctuations on inflation uncertainty

Date07 January 2025
Pages44-85
DOIhttps://doi.org/10.1108/JCEFTS-06-2024-0045
Published date07 January 2025
AuthorJassim Aladwani
Inuence of oil price uctuations on
ination uncertainty
Jassim Aladwani
Business Department, Box Hill College of Kuwait, Abh Halifa, Kuwait
Abstract
Purpose The purpose of this study is to achieve a comprehensive understanding of how the intricate
interconnections between oil price uctuations, supply chain disruptions and shifting demand patterns
collectively shape ination dynamicswithin the Chinese economy, especially during critical periods suchas
the Covid-19 pandemic and geopoliticalevents like the RussiaUkraine conict. The importance of assessing
the impact of oil price volatility on Chinasination becomes particularly pronounced amidst these
challengingcircumstances.
Design/methodology/approach This study uses the Markov Regime-Switching generalized autoregressive
conditional heteroskedasticity (MRS-GARCH) family of models under students t-distributions to measure the
uncertainty of oil prices and the ination rate during the periodspanning from 1994 to 2023 in China.
Findings The results indicate thatthe MRS-GJR-GARCH-in-mean (MRS-GARCH-M) models, when used
under students t-distributions, exhibit superior performancein modeling the volatility of both oil prices and
the ination rate. This nding underscores the effectiveness of these models in capturing the intricacies of
volatility dynamics in the contextof oil prices and ination. The study has identied compelling evidence of
regime-switching behavior within the oil price market. Subsequently, the author conducted an analysisby
Declaration of generative AI and AI-assisted technologies in the writing process: The author hereby
declares that the author has used the services of ChatGPT solely for the purpose of verifying the
grammar in hispaper. The assistance providedby ChatGPT was limitedto ensuring theaccuracy of
his writing, particularly in terms of grammar, punctuation and coherence. The author did not seek any
content-related suggestions from the model; its role was solely conned to checking the grammatical
aspects of his paper. The author bears full responsibility for the overall content, ideas and arguments
presented in his research, and the author has not relied solely on the suggestions provided by
ChatGPT.
Funding: This research was conducted without external funding.
Ethical approval: This article does not contain any studies with human or animal participants
performed by any of the authors.
Availability of data and materials: Based on the reviewersand editors request.
Competing Interests: As the author of this research, I declare that there are no competing interests
related to this study.
Informed consent: This article does not contain any studies with human or animal participants
performed by any of the authors.
Authorscontributions: The author conceived the research topic, inuencing the oil price
uctuations on ination uncertainty in China by using Markov Regime Switching GARCH Family
Models. An extensive literature review was conducted to gather relevant information on oil price
uctuations and ination dynamics. In addition, the author collected and analyzed data related to oil
price and data on ination volatility. Based on the research ndings and insights gathered, the author
took the lead in drafting the essay, ensuring clarity, coherence and depth of analysis. Critical review
and revision of the initial draft were conducted by the author, incorporating constructive feedback to
enhance the quality of the essay. After nalizing the revisions, the author reviewed the nal version of
the essay and provided approval for submission. Serving as the corresponding author, the author was
responsible for communication with the journal editor and overseeing the submission process.
JCEFTS
18,1
44
Received13 June 2024
Revised27 September 2024
Accepted4 November2024
Journalof Chinese Economic and
ForeignTrade Studies
Vol.18 No. 1, 2025
pp. 44-85
© Emerald Publishing Limited
1754-4408
DOI 10.1108/JCEFTS-06-2024-0045
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1754-4408.htm
extracting the forecastable component, which represents the expected variation,from the best-tted models.
This allowed us to isolatethe time series of oil price uncertainty, representingthe unforecastable component.
With this unforecastable component in hand, the author proceeded to estimate the impact of oil price
uctuations on the ination rate. Toaccomplish this, the author used an autoregressive distributed lag model,
which enables usto explore the dynamic relationships and lags betweenthese crucial economic variables. The
study further revealsthat uctuations in oil prices exert a noteworthyand discernible inuence on the ination
rate, with distinct patterns observed across different economic regimes. The ndings indicate a consistent
positive impact of oil prices on ination rate uncertainty, particularly withinexport-oriented and import-
oriented industries,under both of these economic regimes.
Originality/value This study offers originalvalue by analyzing the impact of crude oil price volatility on
ination in China. It provides unique insights into the relationship between energy market uctuations and
macroeconomicstability in one of the worlds largesteconomies. By focusing on crude oil a critical but often
overlooked component this research enhances understanding of how energy price dynamics inuence
inationary trends. The ndings can inform policymakers and stakeholders about the signicance of energy
market stabilityfor maintaining economic stability andguiding ination control measures in China.
Keywords Oil prices, Volatility, Ination, GARCH-type family, MRS-GARCH-type models,
ARDL model
Paper type Research paper
List of abbreviations
MRS- GARCH = Markov regime-switching GARCH;
ARDL= Autoregressive distributed lag;
COVID-19= Coronavirus disease 2019;
PBoC= People's Bank of China;
CPI= consumer price index;
FRED= Federal reserve economic data;
BRENT= Shell UK exploration and production;
WTI= West Texasintermediate;
OPEC= Organization of the Petroleum Exporting Countries;
ARCH= Autoregressive conditional heteroskedasticity;
DF= DickyFuller test;
PP= PhillipsPerron test;
KPSS= KwiatkowskiPhillipsSchmidtShin test;
GARCH= Generalized autoregressive conditional heteroskedasticity;
AIC= Akaike information criterion; and
SC= Schwarz information criterion.
1. Introduction
Oil price volatility remains a signicant global economic concern, affecting economies
across the world, including China. As the largest oil importer on the planet, China relies
heavily on oil to power its rapideconomic expansion and sustain various sectors. Therefore,
uctuations in oil prices can yield substantial consequences for Chinasination rate. Oil
price volatility represents a substantial factor with far-reaching implications for the Chinese
economy, particularly regarding its inuence on ination. Fluctuations in oil prices can
impact the overall price level within an economy, thereby exerting inuence on inationary
pressures. Comprehending the relationship between oil price volatility and ination holds
pivotal signicance for policymakers, economists and businesses as they navigate the
complexities and opportunitiespresented by an increasingly interconnected global economy.
Oil is a pivotal commodity, functioning as a crucial input in various sectors such as energy
Journal of
Chinese
Economic and
Foreign Trade
Studies
45
production, manufacturing and transportation. As a result, changes in oilprices can exert a
widespread inuence on production costs and consumer prices across the entire supply
chain. Substantial uctuations in oil prices can consequently give rise to signicant
repercussions for the dynamics of inationwithin an economy. For instance, when oil prices
rise, this can result in elevated productioncosts for businesses in China. Subsequently, these
escalated production costscan betransferredto consumers in the form of increased prices for
goods and services. Such a chain of events can culminateinan elevation of the overall price
level within the economy,a phenomenon recognized as ination. Beyond the direct inuence
of oil price volatility on ination,it can give rise to a range of indirect effects. For instance, it
has the potential to trigger a reductionin economic growth, a decline in consumer condence
and a devaluation of the Chinese yuan. These indirect consequences can amplify the
repercussions of oil pricevolatility on ination within China.
The inuence of oil price volatility on Chinasination, particularly during critical
periods such as the COVID-19 pandemic and geopolitical events like the RussiaUkraine
conict, carries substantial signicance. Fluctuations in oil prices possess the potential to
exert signicant impacts on Chinasinationary environment, thereby inuencing
macroeconomic outcomes. Recognized as a fundamental determinant of ination, oil prices
play a pervasive role indetermining production and distribution costs for goodsand services.
Amid crisis periods like the COVID-19 pandemic,disruptions in supply chains, shifts in
demand patterns and overarching economic uncertainty can magnify the inuence of oil
price volatility on ination. Furthermore, the COVID-19 pandemic served to highlight the
intricate relationship between oil price dynamics and ination within China. As economic
activities slowed down and demand patterns shifted, the sharp declinein oilprices gave rise
to a complex interplay of deationary and inationary pressures. This intricate relationship
underscores the necessityfor a comprehensive analysis of the impact of oilprice volatility on
Chinasination during crisis periods. The Asian Development Bank has examinedhow the
COVID-19 pandemic and the subsequent oil price volatility have affected the Chinese
economy. The report indicates that the pandemic has resulted in a decrease in oil demand,
exerting downwardpressure on oil prices. However, the reporthighlights that the volatility in
oil prices has posed challenges for businesses in terms of future planning, consequently
fostering uncertainty and curtailing investment. As a result, this situation has adversely
affected economic growthin China. Geopolitical events such as the RussiaUkraine conict
can introduce additional uncertainty and supplydisruptions to the global oil market, thereby
intensifying the potential consequences for Chinasination dynamics. A study conducted
by Mohanty and Klau (2004) revealed that oil price shocks have signicant and enduring
effects on ination across numerous Asian economies, including China. Likewise, research
conducted by Lee et al. (2017) highlighted the interdependence between oil price volatility
and ination in Asian economies,emphasizing the potential channels through which changes
in oil prices can propagateto consumer price levels.
The objective of this study is to achieve a comprehensive understanding of how the
intricate interconnections between oil price uctuations, supply chain disruptions and
shifting demand patternscollectively shape ination dynamics within the Chinese economy,
especially during critical periods such as the COVID-19 pandemic and geopolitical events
like the RussiaUkraine conict. The importance of assessing the impact of oil price
volatility on Chinasination becomes particularly pronounced amidst these challenging
circumstances. In this analysis, the implementation of Markov Regime-Switching-GARCH
(MRS-GARCH) familymodels stands out as a robust choice for modeling oil price volatility.
This choice is grounded in their aptitude for capturing intricate dynamics, including
persistent memory and discernible asymmetric effects commonly observed in oil price data
JCEFTS
18,1
46

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