Factors Influencing Natural Gas Prices: A Literature Review

Literature Review

Natural gas is a natural fuel that is utilized by humans for both commercial and household reasons. In the United States of America, it is mostly used for cooking and heating by the majority of families, while it is also utilized as a raw material in the industrial sector. Natural gas utilization has surged in recent years, with many individuals preferring it over alternative energy sources.

Since 2014, the decrease in gas prices has had a detrimental impact on the economies of exporting nations, putting further strains on financial earnings to fund the cost of the budget. My own nation responded to these changes in March 2015 by withholding employee pay and allowances, halting numerous projects, raising gasoline costs, and boosting the jobless rate. Since then, I’ve focused my study on the variables that cause gas prices to fluctuate and how governments may predict the volatility before it occurs.

The price of gas is an issue that dominates the daily economic news. It is a current issue that can have an impact on governments in general and people in particular. I picked this topic above others for two primary reasons. Second, I’ve seen the impact of fluctuating gas prices across two distinct companies since last year. This research study will look at the elements that have influenced gas prices during the previous 30 years, especially between 1985 and 2014. Many research on this issue have been undertaken throughout the previous four decades.

Jian Chai (2019) identifies the primary variables that drive gas prices to change from one day to the next. gas prices are affected by supply-demand dynamics on the worldwide market. Market demand and gas prices have a positive link, whereas market supply and gas prices have a negative association. The author begins his post by outlining the most essential elements that influence gas prices.

The debate about fluctuating gas prices began lately, owing to the detrimental consequences of these fluctuations on the economies of exporting and importing nations. It also began as a result of the impact on industrialized nations’ economy and people’s financial conditions. Because of the volatility of gas prices, several corporations have seen their projects lose money and have had to shut down their activities. one may claim that there is a tight association amid gas price variations and total productivity (TP) changes in a gas-exporting nation.” According to these researchers, most gas exporting nations enjoy increases in domestic investment, consumption, and subsidies.

Other variables that influence gas supply include global gas reserves, outputs, gas system choices made by the OPEC nations, gas production costs. Most factors have played significant roles in influencing market gas prices. Fluctuations can have a considerable impact on people’s and governments’ spending in importing nations like the United States.

Chai (2019) in “Are there truly bubbles in gas prices?” There are four distinct epochs. Two of the time periods are prior to 2000, while the other two are post-2000. The latter two periods are most likely the center of the post because the material is more useful and up to date to the reader. The essay describes the many causes of gas price booms and collapses throughout history, which might help answer my key question, “Factors impacting gas prices.”

Chai (2019)

It discusses the causes of the bubbles that occurred in 2008 and 2011. In general, the causes of these two bubbles include rising gas demand, changes in the US housing market, and changes in mortgage rates. Simultaneously, it provides a novel approach and formula for calculating these crashes and fluctuations in gas prices in the preceding years.

Several factors influence gas consumption, including the state of global economic development – changes in economic structure in certain wealthy nations. The 2008 financial crisis, dubbed the “Great Recession,” caused a shift in global economic structure, resulting in a dramatic drop in gas prices (Lin & Kuang, 2020).

The article proposes three models for assessing the variables influencing the price of gas. The first model is called “Path-Analysis,” and it is based on a simple correlation analysis. Its mechanism is dependent on 21 variables, including global economic growth, geopolitics, exchange rates, seasonal climate changes, alternative energy prices, inventory, production costs, the US dollar index, net gas imports to the US and Eurozone, global gas consumption, and other factors. gas prices are the dependent variable (Linn & Muehlenbachs, 2018).

The second model is known as the “Vector Auto Regression” (VAR) model, and it is very similar to the first model except that it may be used with selected variables rather than all of them. At the same time, this model has several flaws, such as the fact that it does not take into account economic theory. In addition, numerous critical parameters must be calculated (Liptáková et al., 2021).

The third essay, “Analysis of the International gas Price Fluctuations and Its Influencing Causes,” authored by Liu & Lin, 2018), analyzes the factors that contribute to gas price fluctuation and how changes in gas prices might impact the economic conversation in each country. The author discussed several variables behind gas price variations in the paper, including the imbalance between supply and demand for international gas, changes in gas stockpiles, emergency situations, and the volatility of gas output by exporting nations. In addition, he offered an intriguing issue concerning crucial political choices and geopolitical instability in the globe, as well as how they affect variations in worldwide gas prices. All of these aspects were thoroughly discussed by the author, who also gave several instances from real-life scenarios.

In addition, he identified certain broad variables such as wars, political upheavals, terrorist attacks, and natural disasters. This article was discovered by doing an online search from a large number of accessible articles, reading them thoroughly, and then picking the one containing new factors. Furthermore, the author argues that predicting gas prices will grow increasingly difficult and erroneous due to the complexity of the elements that impact gas prices. Similarly, he advised that governments look for other energy alternatives to gas because it is a finite resource on the planet.

The other article, “Why do gas prices spike or fall?” by Nyga-?ukaszewska & Aruga, (2020), explores the theory of zigzag in gas prices and the way such prices react to competitive market circumstances. Market changes may happen in a split second, and there is ambiguity regarding the ramifications of political actions and facts that impact the media. The author paid more focus on earlier gas price changes as well as the latest one following the year 200He also notes that gas prices are being revised in response to the capacity usage of gas. He admits that the spike in gas prices is caused by the demand uncertainty and market’s demand shock and.

Contrastingly, he debates political motivations. He thoroughly discusses all of the reasons influencing gas price swings, as well as the ramifications of these changes. In addition, he employs several equations and models to investigate the historical growth of supply and demand. The author finds that the majority of prior changes in gas prices are tied to global political choices, but the latest one was unaffected since gas prices had already adjusted their levels based on earlier experiences. He insists that the current gas price swings are mostly due to economic concerns. Another source for my research was provided by Wang et al., (2019), who explained historical gas occurrences by noting, “World gas consumption climbed by more than 2% per year between 1994 and 1997.” Furthermore, if gas companies had properly predicted the increase in gas demand from newly industrialized nations.

Zhang et al., (2018) illustrates how the present fluctuations in gas prices are associated to the global economy. Between 2003 and 2008, he conducted research. He credits the variations in gas prices over the era to changes in gas market trading, a drop in gas supply, and robust worldwide economic development. In the majority of the paper, he goes over these three elements in greater detail, as well as the competitive interchangeable connection between all of them. Furthermore, he thinks that increased US gas output will lessen the impact of global price variations since increased production will reduce global gas demand, resulting in lower gas price volatility.

The basic empirical tests to examine whether gas prices are affected by a number of factors within a short time. It comprises of error correction model and estimating time-varying coefficients examining the conditional association of time varying parameters between gas prices and the independent variable factors.

1. Error correction model

Following the literature that investigates the determinant of gas prices, we developed a long-run association amid gas prices and the independent variable factors.

Where Y is the dependent variable, the world gas prices, P is the gas price and Pr is the gas production while t denotes week identifiers. It also involves several explanatory variables donating by Pr gas production per year in million, P for the gas prices in USD per thousand cubic feet.

The equation 1 can be written as an autoregressive-distributed lag model by considering long memory process in the market. The model (1) is equivalently written by using an error correction model (ECM) as shown below. Whereby delta shows the difference operator. This will mean that equation (2) is similar to the following ECM parametrization conditional on stationary assumption in the differenced data.

Where D is the dummy variable which captures the three war years.

 The statistical properties in equation 3 might be spurious without cointegration.

1. Time-Varying Parameters by using Kalman Filtering

Where  is the first difference of gas production rate observed rate at time t and time varying parameters vectors, and the are unobserved state variables are equivalent to the number of explanatory variables in ECM equation (3).

Where f_t|t-1 is the conditional variance of the prediction error and h_t|t-1 is the predictor.

1. The Data

The high frequency data must be used when determining the factors affecting of gas prices. We consider the yearly data from 1985 to 2014. 

The study paper will look at the link between gas prices and other factors from 1985 to 2014. In this article, five independent variables will be examined. The first variable is gas production (x1), which will be denoted in STATA as (Oprod). The level of gas production has a significant impact on pricing since it affects the fundamental ideas of supply and demand and how they have influenced gas prices in the past. The second variable is the gas price (x2), which will be referred to in STATA as (Gprice). It discusses how variations in gas prices affect gas demand and supply.

Empirical Results

1. ECM Model

Table 1 shows the estimates of equation 3 obtained from a general-to-specific specification upon all the diagnostic tests. Autocorrelation consistent covariance and heteroskedasticity was estimated, it is consistent in the presence of both autocorrelation and heteroskedasticity of the unknown. The third column in table 1 shows the Newey-west t-values. Every test statistic is evaluated at the 5% significance level. We found f-value to be 1.36 from this regression. As we compare with the f-critical value of 2.46, we have failed to reject the null hypotheses, since the value is lower compared to the f-critical values. This shows that there is no heteroskedasticity. 

Table 1: shows estimation of ECM (source self-generated)

We used CUSUMSQ to observe the stability of the effect of gas price and three-year war. It can be clearly seen that results were not stable over the entire period.

Figure 2: shows CUSUMSQ 

 Table 2: shows empirical results 1 

Time-varying regression coefficients generated by using the Kalman filter method is shown in figure 2. As shown in the figure, the time-varying coefficients on the three-war period have a positive over the sample period. The results are consistent with the results in ECM estimation.

Figure 2: shows TVP coefficients

Non-linearity

This procedure involves examining the connection amidst the dependent and independent variables to determine whether or not they are linearly connected. 

The dependent variable is then regressed against all of the basic independent factors and the newly formed independent variables. Finally, the t-test or f-test are used to examine the null and alternative hypotheses. 

The t-critical values are 2.094 with 31 observations together with 5 percent significant level, while the t-absolute value are less than this value. The result shows that we have failed to reject the null hypotheses, indicating linearity in this case. Such independent variables are associated to the dependent variable in a linear fashion. 

Conclusion

Changes in gas prices are one of the most contentious issues in modern economics. Gas price changes can be influenced by a variety of factors. The first model has no nonlinearity issues. Nevertheless, several of the independent variables showed multicollinearity. To address this issue, the gas proven reserves were removed from the initial empirical results since they are a nearly set number every year with very minor variations from one year to the next. 

References

Chai, J., Wei, Z., Hu, Y., Su, S., & Zhang, Z. G. (2019). Is China’s natural gas market globally connected?. Energy Policy, 132, 940-949.

Guo, M., Bu, Y., Cheng, J., & Jiang, Z. (2018). Natural gas security in China: A simulation of evolutionary trajectory and obstacle degree analysis. Sustainability, 11(1), 96.

Lin, B., & Kuang, Y. (2020). Natural gas subsidies in the industrial sector in China: National and regional perspectives. Applied Energy, 260, 114329.

Linn, J., & Muehlenbachs, L. (2018). The heterogeneous impacts of low natural gas prices on consumers and the environment. Journal of Environmental Economics and Management, 89, 1-28.

Liptáková, E., Rimár, M., Kizek, J., & Šef?íková, Z. (2021). The Evolution of Natural Gas Prices in EU Countries and their Impact on the Country’s Macroeconomic Indicators. Civil and Environmental Engineering Reports, 31(2).

Liu, C., & Lin, B. (2018). Analysis of the changes in the scale of natural gas subsidy in China and its decomposition factors. Energy Economics, 70, 37-44.

Nyga-?ukaszewska, H., & Aruga, K. (2020). Energy prices and COVID-immunity: The case of  gas and natural gas prices in the US and Japan. Energies, 13(23), 6300.

Wang, T., Zhang, D., & Broadstock, D. C. (2019). Financialization, fundamentals, and the time-varying determinants of US natural gas prices. Energy Economics, 80, 707-719.

Zhang, D., Shi, M., & Shi, X. (2018). Gas indexation, market fundamentals, and natural gas prices: An investigation of the Asian premium in natural gas trade. Energy Economics, 69, 33-41.

Order an Essay Now & Get These Features For Free:

Turnitin Report

Formatting

Title Page

Citation

Outline

Place an Order