Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin

Oil plays an essential factor in Malaysia's economic growth. Malaysia is the second largest oil producer in South East Asia and has the 24th largest crude oil reserves. Considering that oil is a depleting and a highly demanded global commodity, fluctuations in its prices may cause an impact on...

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Main Author:	Mohd ZainulAbidin, Siti NurulAifa
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Commodities Commercial products Generic products
Online Access:	https://ir.uitm.edu.my/id/eprint/61936/1/61936.PDF
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id	my-uitm-ir.61936
record_format	uketd_dc
spelling	my-uitm-ir.619362022-07-24T00:12:02Z Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin 2018-01 Mohd ZainulAbidin, Siti NurulAifa Commodities. Commercial products. Generic products Oil plays an essential factor in Malaysia's economic growth. Malaysia is the second largest oil producer in South East Asia and has the 24th largest crude oil reserves. Considering that oil is a depleting and a highly demanded global commodity, fluctuations in its prices may cause an impact on several macroeconomic variables such as gross domestic product (GDP), inflation rates and the production. It is essential to know the relationship between crude oil price and the macroeconomic variables to determine the economic interdependence. The main purpose of this study is to identify the causal relationship between crude oil price and the macroeconomic variables using vector autoregressive (VAR) model approach. This study utilized data from the year 2006 to2016 on a monthly basis. The result of a VAR model approach indicates that GDP and inflation are the significant variables that will affect crude oil price. In addition, the study made a forecast to all the four variables by using geometric Brownian motion (GBM)model. Hence, the crucial part in this study is to determine which method is more reliable in forecasting crude oil price. This is done by comparing the mean absolute percentage error (MAPE) of VAR model approach and GBM. The lowest MAPE value indicates the highest accuracy of the forecast values. In this study, for both methods MAPE were below twenty percent, however, MAPE for VAR model approach is the lowest, which is3.84 compared with 20.48. Thus, the VAR model approach is used to forecast crude oil price for the year 2018 on a monthly basis. 2018-01 Thesis https://ir.uitm.edu.my/id/eprint/61936/ https://ir.uitm.edu.my/id/eprint/61936/1/61936.PDF text en public masters Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Yusof, Hasnah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Yusof, Hasnah
topic	Commodities Commercial products Generic products
spellingShingle	Commodities Commercial products Generic products Mohd ZainulAbidin, Siti NurulAifa Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
description	Oil plays an essential factor in Malaysia's economic growth. Malaysia is the second largest oil producer in South East Asia and has the 24th largest crude oil reserves. Considering that oil is a depleting and a highly demanded global commodity, fluctuations in its prices may cause an impact on several macroeconomic variables such as gross domestic product (GDP), inflation rates and the production. It is essential to know the relationship between crude oil price and the macroeconomic variables to determine the economic interdependence. The main purpose of this study is to identify the causal relationship between crude oil price and the macroeconomic variables using vector autoregressive (VAR) model approach. This study utilized data from the year 2006 to2016 on a monthly basis. The result of a VAR model approach indicates that GDP and inflation are the significant variables that will affect crude oil price. In addition, the study made a forecast to all the four variables by using geometric Brownian motion (GBM)model. Hence, the crucial part in this study is to determine which method is more reliable in forecasting crude oil price. This is done by comparing the mean absolute percentage error (MAPE) of VAR model approach and GBM. The lowest MAPE value indicates the highest accuracy of the forecast values. In this study, for both methods MAPE were below twenty percent, however, MAPE for VAR model approach is the lowest, which is3.84 compared with 20.48. Thus, the VAR model approach is used to forecast crude oil price for the year 2018 on a monthly basis.
format	Thesis
qualification_level	Master's degree
author	Mohd ZainulAbidin, Siti NurulAifa
author_facet	Mohd ZainulAbidin, Siti NurulAifa
author_sort	Mohd ZainulAbidin, Siti NurulAifa
title	Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
title_short	Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
title_full	Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
title_fullStr	Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
title_full_unstemmed	Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin
title_sort	long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / siti nurulaifa mohd zainulabidin
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/61936/1/61936.PDF
_version_	1783735241042558976

Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin

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