Authors :
Tanvi Karwande; Dr. Sreelakshmi P.
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/yryhfzwt
Scribd :
https://tinyurl.com/3mv5fnfv
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR870
Abstract :
The interplay between macroeconomic indicators and oil prices has been a subject of intense scrutiny due to its far-
reaching implications for global economic stability. This research paper undertakes a thorough investigation into the
intricate relationship between various macroeconomic factors and the occurrence of oil price shocks. The study employs a
multidimensional approach, encompassing both empirical analysis and theoretical frameworks, to elucidate the complex
dynamics governing this interaction.
The research begins by establishing a robust theoretical foundation, delving into existing economic models that
elucidate the channels through which macroeconomic indicators influence oil prices. Recognising the intricate network of
supply and demand forces, the paper explores the impact of key macroeconomic factors, including GDP growth, inflation
rates, interest rates, and exchange rates, on the vulnerability of oil markets to price shocks.
Methodologically, the research leverages advanced econometric techniques to analyse extensive datasets spanning
multiple economies and time periods. A comprehensive panel data analysis is employed to capture the heterogeneity across
different regions and economies, thereby providing a nuanced understanding of the global nature of the phenomenon.
Additionally, time-series models are used to unravel the temporal dynamics of the relationship between macroeconomic
indicators and oil price shocks.
The findings of this research paper contribute significant insights to the existing body of knowledge. The empirical
results shed light on the varying degrees of sensitivity that different macroeconomic indicators exhibit concerning oil price
shocks. The study also uncovers potential feedback loops and non-linearities within the system, providing a more nuanced
understanding of the relationship.
Keywords :
Oil Price Shocks, Macroeconomic Relationship, Risk Factors, Non-Linear Relationship.
The interplay between macroeconomic indicators and oil prices has been a subject of intense scrutiny due to its far-
reaching implications for global economic stability. This research paper undertakes a thorough investigation into the
intricate relationship between various macroeconomic factors and the occurrence of oil price shocks. The study employs a
multidimensional approach, encompassing both empirical analysis and theoretical frameworks, to elucidate the complex
dynamics governing this interaction.
The research begins by establishing a robust theoretical foundation, delving into existing economic models that
elucidate the channels through which macroeconomic indicators influence oil prices. Recognising the intricate network of
supply and demand forces, the paper explores the impact of key macroeconomic factors, including GDP growth, inflation
rates, interest rates, and exchange rates, on the vulnerability of oil markets to price shocks.
Methodologically, the research leverages advanced econometric techniques to analyse extensive datasets spanning
multiple economies and time periods. A comprehensive panel data analysis is employed to capture the heterogeneity across
different regions and economies, thereby providing a nuanced understanding of the global nature of the phenomenon.
Additionally, time-series models are used to unravel the temporal dynamics of the relationship between macroeconomic
indicators and oil price shocks.
The findings of this research paper contribute significant insights to the existing body of knowledge. The empirical
results shed light on the varying degrees of sensitivity that different macroeconomic indicators exhibit concerning oil price
shocks. The study also uncovers potential feedback loops and non-linearities within the system, providing a more nuanced
understanding of the relationship.
Keywords :
Oil Price Shocks, Macroeconomic Relationship, Risk Factors, Non-Linear Relationship.
