Functional Causality between Oil Prices and GDP Based on Big Data

This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil...

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Bibliographic Details
Published in:Computers, materials & continua materials & continua, 2020-01, Vol.63 (2), p.593
Main Authors: Ibrahim Mufrah Almanjahie, Zouaoui Chikr Elmezouar, Laksaci, Ali
Format: Article
Language:English
Subjects:
Causality
Computer simulation
Crude oil
Crude oil prices
Pricing
Online Access:Get full text
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Summary:This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil price affects the GDP of KSA. Based on a new technique, we treat this data in its continuous path. Precisely, we analyze the causality between these two variables, i.e., oil prices and GDP, by using their yearly curves observed in the four quarters of each year. We discuss the causality in the sense of Granger, which requires the stationarity of the data. Thus, in the first Step, we test the stationarity by using the Monte Carlo test of a functional time series stationarity. Our main goal is treated in the second step, where we use the functional causality idea to model the co-variability between these variables. We show that the two series are not integrated; there is one causality between these two variables. All the statistical analyzes were performed using R software.
ISSN:1546-2218
1546-2226
DOI:10.32604/cmc.2020.08901