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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
https://ir.uitm.edu.my/id/eprint/61936/
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spelling my.uitm.ir.619362022-07-24T00:12:02Z https://ir.uitm.edu.my/id/eprint/61936/ Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin 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 NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/61936/1/61936.PDF Long-run dynamics of crude oil price and macroeconomic variables: a cointegration vector autoregressive analysis / Siti NurulAifa Mohd ZainulAbidin. (2018) Masters thesis, thesis, Universiti Teknologi MARA.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
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
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
publishDate 2018
url https://ir.uitm.edu.my/id/eprint/61936/1/61936.PDF
https://ir.uitm.edu.my/id/eprint/61936/
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score 13.211869

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