It is a well-known fact that when oil and gas prices increase, the impact it has in terms of stock pricing and economic opportunity affects the way people and corporations spend money. How and when people purchase goods, travel, and even the means in which goods are produced then shipped are all influenced one way or another by fluctuations in oil and gas prices. To better understand this phenomenon and definitively prove or dis-prove a correlation between both commodities exists, we will start by looking over prior research and historical price observations between crude oil (a specific type of oil that can be used as an overall benchmark for world oil pricing) and natural gas. The topic and scope of the paper is to either positively or negatively identify a correlation between oil prices and gas prices using the value of r (-1and +1) to calculate and measure the strength of the linear relation between both x (oil stocks) and y (gas prices) variables. In doing so, we will be able to determine, using the correlation coefficient, the strength if any there is between the two and whether or not they are casually related.
There are many factors contributing to the simultaneous rise and fall of oil and gas prices, this in effect has caused much speculation as to whether or not both commodities are correlated with one another. It would seem that logic points to a positive correlation between the two commodities seeing that (natural) gas is the byproduct of drilling for crude oil however there are substantial differences between the two in regards to basic markets forces each commodity falls within. Furthermore there is also statistical analysis indicating periods of strong correlation between the two assets followed by periods of limited to no correlation at all. Economic theory expresses indirectly that natural gas prices and crude oil prices should be dependent on one another because natural gas and crude oil are substitutes in consumption and also complements, as well as rivals, in production (Villar & Joutz, 2006, pg. 2). To prove whether or not this is the case, research articles pertaining to the issue will be examined to gain a deeper understanding of the relationship between crude oil prices and gas prices.
The statistical methodology used to identify and determine the nature of the relationship between these two variables x (oil stocks) and y (gas prices) will be a measure of linear relation using the correlation coefficient. The correlation coefficient, denoted by r is a measure of strength of the linear relation between the x and y variables (Johnson & Bhattacharyya, 2014, 3.4). The first article titled “The Relationship between Crude Oil and Natural Gas Prices” examines the relationship of crude oil prices and natural gas prices using the Henry Hub gas price and the West Texas Intermediate crude oil price on a histogram chart. The focus of the article is to develop an understanding of the principle characteristics of the statistical relationship between oil and gas prices. Beginning with a time period of January 1989 to December 2005, the analysis identifies the economic factors suggesting how crude oil and natural gas prices are related, and assesses the statistical significance of the relationship between the two over time.
Using a histogram chart (Figure 1) as a reference, this article uses data points from fifteen years of historical price observations as represented on the graph with oil prices denoted as (x) and natural gas prices denoted as (y) variables. Calculating the correlation coefficient using x, y variables at intervals of five years shows a positive but not strong correlation between the two of r = 0.507 however, research suggests that the analysis supports the presence of a cointegrating relationship between the crude oil and natural gas price time series, providing significant statistical evidence that WTI crude oil and Henry Hub natural gas prices have a long-run cointegrating relationship.
The second article titled “Oil and Natural Gas: Are the Prices Linked?” describes a study that examines the casual relationship between the two variables using a histogram chart during a 16 month time period. The primary focus of the article is to shown instances throughout 16 months of pricing when the two commodities were identified to be positively correlated as well as times where they were shown to have a negative correlation. The main question observers had regarding the relationship of oil and gas pricing was the degree and extent to which natural gas and oil prices are linked. In the study, researchers were able identify a mean correlation coefficient of 0.40 that showed a positive relationship between the two commodities. The article states:
“Overall this is rather consistent with historical data which shows a mean positive correlation between the two. However, a correlation coefficient of less than 0.40 means that changes in oil price account for less than 40% of the changes in the price of natural gas. The conclusion is that oil prices influence gas prices, but there are other important drivers, too” (Oil and Natural Gas: Are the Prices Linked, 2014).
Another article of interest centering on the same question “is there a correlation between oil and gas prices?” details a study aimed at determining the short and long run relationship between crude oil and natural gas in the U.S. and European commodity markets. Titled “Crucial Relationship Among Energy Commodity Prices”, this research article focuses on utilizing daily price data during a period of eight years (2001-2009) to perform a correlation analysis on the short run relationship between the two variables and a cointegration analysis to determine the long run relationship if any. Among the questions asked by researchers aside from how these two commodities are linked to one another is how they can be used as tools in risk management to measure and set the pricing of derivatives in contracts, spread options and so forth. Economic theory suggests the existence of a relationship between natural gas and oil prices being competitive substitutes and complements in the electricity generation and in the industrial production (Bencivenga, & Sargenti, 2010).
Statistical analysis in this article concludes that an overall correlation between oil and gas prices during 2001-2009 was equal to 0.677. The overall correlation coefficient was expected to be positive between the two commodities as stated in the article’s introduction, hypothesis and research questions aimed to prove a definitive relationship between gas and oil prices as well as the strength of the relationship by determining both short run and long run correlations through a correlation and cointegration analysis. Using a correlation analysis to determine the correlation coefficient from historical price data in each article helped confirm the hypothesis that gas and oil prices have a strong linear relationship with one another. Our text states “the magnitude of r indicates the strength of a linear relation, whereas its sign indicates the direction (Johnson & Bhattacharyya, 2014, 3.4). In each article, it can be determined using the correlation coefficient that we find statistical evidence suggesting the presence of a linear relationship with a mean of .528 between the three coefficients.
The role statistics play in research can be utilized in many ways. Statistical methods such as determining the correlation coefficient, or probabilities are often and most commonly used to summarize a collection of data in support of not only communicating any findings but also in support of hypothesis. In short, statistics give a level of credibility to the methodology used and any conclusions derived from such techniques. Limitations of statistics vary, because statistics deal with a collection of data it is impossible to draw a conclusion from isolated or qualitative measurements. The greatest limitation of statistics is the one that needs to be stressed least, because it is obvious. It is that so much knowledge is either unique or the quantitative aspects are not sufficiently great to be called statistical (Ogburn, 1934, pg 15). It is also important to note that the way data is interpreted has an effect on any conclusions. Therefore it is vital to use honesty and consider all conditions of a situation before making any inferences in regards to any data that is obtained.
In conclusion, statistics has wide spread application as it is often used to help understand or in some cases describe phenomena in a way that is informative and credible. Using gas prices and oil prices as variables, this paper sought to identify the relationship between the two commodities using the value r to measure the linear strength of the correlation coefficient in three separate research articles. A common theme among the articles was the question “are oil and gas prices correlated?” After reviewing the articles and supporting literature, it can be concluded that identifying a correlation coefficient can help answer the question by giving us reference as to the strength of the relationship. The closer the coefficient is to the value r=1, gives us a positive and strong relationship between the two variables. The statistical method used in this paper confirmed the hypothesis and proved there is a strong correlation of the two variables and that they are influenced by one another.