The study is an attempt to build a univariate Time Series Model to forecast monthly petroleum prices for 2010/2011, from January 1990 to September 2010, since national petroleum agency (NPA) is failing to plan for fluctuation of petroleum prices. The data was source from the website of Bank of Ghana. The study employs Box-Jenkins methodology of building Seasonal Autoregressive Integrated Moving Average (SARIMA) model to achieve various objectives. Different selected models were tested by Residual plots of Autocorrelation and Partial Autocorrelation and Ljung Box Q statistic to ensure adequacy of results. The results reveal that demand and supply, crudel oil prices, gasoline, natural disasters and government regulations are some of factors that can influence fuel prices and ARIMA(1,1,5)×(1,0,1)11 is the best model for forecast. The future values expose that during the months to come; petroleum prices are going to experience an insignificant increase. In light of the forecast, I know Ghana will ascertain a healthy state of economy.
Table of Contents
Chapter 1: Introduction
1.1 Background of the Study
1.2 Statement of Problem
1.3 Objectives of the Study
1.4 Research Questions
1.5 Significance of the Study
1.6 Scope of the Study
Chapter 2: Related Review of Literature
2.1 Introduction
2.2 Theoritical Framework
2.2.1 The Economics Importance of Oil
2.2.2 History of Oil and Gas Exploration
2.2.3 Ghanaian Policy Subsidy
2.2.4 Supply Side Channel
2.2.5 Demand Side Channel
2.2.6 Economic Policy Relations
2.3 Empirical Framework
2.3.1 Forecasting
Chapter 3: Review of Basic Theory and Methods
3.1 Introduction
3.2 Research Design
3.3 Source of Data
3.4 Statistical Analysis Procedure
3.4.1 Box-Jenkins Methodology
Chapter 4: Preliminary and Further Analysis
4.1 Introduction
4.2 Preliminary analysis
4.3 Further analysis
Chapter 5: Results and Discussion
5.1 Introduction
5.2 Discussion of Result
5.2.1 Stationarity
5.2.2 Model Identification
5.2.3 Model Estimations
5.2.4 Model Verification or Diagnostic Checking
5.2.5 Forecasting Stage
Chapter 6: Conclusion and Recommendation
6.1 Conclusions
6.2 Recommendations
Objectives and Topics of the Study
The primary objective of this study is to develop a univariate time series model to forecast monthly petroleum prices in Ghana for the period of 2010 to 2011, addressing the lack of adequate planning by the national petroleum agency regarding price fluctuations. The study investigates the impact of global oil price trends on the Ghanaian economy and utilizes statistical modeling to mitigate the uncertainties associated with fuel pricing.
- Application of the Box-Jenkins methodology for time series analysis
- Development of Seasonal Autoregressive Integrated Moving Average (SARIMA) models
- Evaluation of stationarity and seasonal variation in petroleum price data
- Statistical validation of models using Residual plots, Autocorrelation, and Ljung-Box statistics
- Forecasting of future petroleum price trends to support national economic decision-making
Excerpt from the Book
1.1 BACKGROUND OF THE STUDY
The significance of oil as an input into the macro economy, and its ability to predict future growth in economic variables, suggests that the oil price is an important variable to consider in the context of consumption.
Petroleum (from Greek: petra (rock) plus Latin: oleum (oil)) or crude oil is a naturally occurring, flammable liquid consisting of a complex mixture of hydrocarbons of various molecular weights and other liquid organic compounds, that are found in geologic formations beneath the Earth's surface Wikipedia, (2012). Petroleum is also called fossil fuel. It is called a fossil fuel because it was formed from the remains of tiny sea plants and animals that died millions of years ago. When the plants and animals died, they sank to the bottom of the oceans. Here, they were buried by thousands of feet of sand and sediment, which turned into sedimentary rock. As the layers increased, they pressed harder and harder on the decayed remains at the bottom. The heat and pressure changed the remains and, eventually, petroleum was formed. Petroleum deposits are locked in porous rocks almost like water is trapped in a wet sponge. When crude oil comes out of the ground, it can be as thin as water or as thick as tar. Petroleum is called a nonrenewable energy source because it takes millions of years to form, (www.NEED.org., 2012).
Summary of Chapters
Chapter 1: Introduction: This chapter provides the foundation for the research by defining the scope, problem statement, and objectives regarding the forecasting of petroleum prices in Ghana.
Chapter 2: Related Review of Literature: This section reviews theoretical frameworks, the history of oil exploration in Ghana, and economic channels through which oil prices affect the macroeconomy.
Chapter 3: Review of Basic Theory and Methods: This chapter outlines the research design and the statistical procedures, specifically the Box-Jenkins methodology, used for the analysis.
Chapter 4: Preliminary and Further Analysis: This chapter presents the initial descriptive analysis of the data and performs the necessary trend and stationarity testing required for model building.
Chapter 5: Results and Discussion: This chapter discusses the model identification, estimation, and verification processes to determine the optimal forecasting model.
Chapter 6: Conclusion and Recommendation: This chapter summarizes the findings and provides recommendations for using the identified model in petroleum pricing decisions.
Keywords
Petroleum Prices, Forecasting, Ghana, SARIMA, Box-Jenkins Methodology, Time Series Analysis, Stationarity, Macroeconomy, Autocorrelation, Model Identification, Fuel Subsidies, Oil Exploration, Statistical Modeling, Residual Analysis, Economic Growth
Frequently Asked Questions
What is the core purpose of this research?
The research aims to create a reliable univariate time series model to forecast monthly petroleum prices in Ghana, helping the national petroleum agency better manage price fluctuations.
Which thematic areas does the study cover?
The study covers the economics of oil, the history of petroleum exploration in Ghana, price subsidy policies, supply and demand side economic channels, and time series forecasting techniques.
What is the primary research objective?
The primary goal is to generate accurate forecasts for monthly petroleum prices for the period 2010 to 2011 to aid economic planning and policy response.
Which scientific methodology is employed?
The study employs the Box-Jenkins methodology for building Seasonal Autoregressive Integrated Moving Average (SARIMA) models to perform time series analysis.
What are the key components of the main body?
The main body covers a literature review of economic frameworks, a detailed methodology section describing the Box-Jenkins approach, preliminary data analysis, and the identification and verification of optimal models.
Which keywords best characterize this work?
Key terms include Petroleum Prices, Forecasting, SARIMA, Box-Jenkins Methodology, Ghana, Time Series Analysis, and Economic Policy.
How was the model adequacy determined?
Model adequacy was checked using Residual plots of Autocorrelation and Partial Autocorrelation, as well as the Ljung-Box Q statistic to ensure the residuals were random and normally distributed.
What was the conclusion regarding the best model?
The study concluded that the ARIMA(1,1,5)×(1,0,1)11 model was the most suitable for forecasting future monthly petroleum prices in Ghana.
- Quote paper
- Francis Okyere (Author), 2012, Modelling and forecasting monthly petroleum prices of Ghana using subset ARIMA models, Munich, GRIN Verlag, https://www.grin.com/document/215463
