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Oil price fluctuations have an effect on the global economy because most countries depend on oil as their main source of resources. It is widely acknowledged that low oil prices are advantageous, especially for the US economy, but the cost of low prices affects other countries as well. Low rates have a major impact on the supply side. However, the results vary greatly among various producers whose goal is to increase demand in order to increase revenue gained. Analyzing demand supply fluctuations as a diverse driver reveals that price shifts have an episodic effect on oil markets, ranging from high to low oil prices. In this paper, quantitative analysis is done and show the relationship of various dependent variables on price and oil economy in general. We confirm that there is non-linearity between output and exchange rate. The quantitative analysis looks at the relationship between domestic real output against the real exchange rate in currency per one US dollar. Further analysis focus on foreign real output against the nominal price oil per barrel in US dollars. The four variables are also addressed in consideration to the domestic oil exports in thousands of barrels per day. An exact prediction is evidenced by closeness to zero value in the residual plot. poil, xoil and ys predictions are correct since the value of residuals is close to the zero value. That is, the values are clustered around the lower digit of zero.
Key words: Supply, Demand, Regression, Analysis, Fluctuation, Economy.
THE MAJOR OIL EXPORTER'S ECONOMY CHALLENGES
Oil has been considered as a primary commodity in fueling the worlds’ economy. It is a crucial export commodity for oil suppliers in the world and a crucial input for consumer countries. Any country depend on oil at some level of supply chain, being either the supplier or the consumer. Any change in price of oil affects the whole world’s economy. However, the extent of oil price fluctuations depends on factors such as whether the country is an international trade supplier or consumer or whether the economy is climate dependent. The oil market dynamics have tendency to change due to political and changes in technological aspects of the market.
Real prices of oil have fluctuated between 145$ and 15$ between 2015 and 2016 (Baumeister, & Kilian, 2016). The fall in oil prices since June 2014 became enormous and the oil changes for the global economy in terms of real input and output have been addressed. Initial impacts of oil prices affects the globe with oil importers benefiting from reduced oil prices while oil exporters count losses for the low selling prices. As with the law of demand and supply, low prices show up in high oil demand by importers including United States.
America receives most of its oil from the international market. As a dependent of oil, they cannot afford any interruption in trade. By producing domestically, the US lessens the influence of foreign nations. Even including crude oil that is refined domestically, America receives over 50% of its oil from the international market. America gets its oil from Canada at 15.1% of total oil, Saudi Arabia at 12.9%, Mexico at 7.5%, Venezuela at 5.9%, and from Africa mainly in Nigeria at 5.2%. It is also observed that Nigeria’s exports declined as oil production was disrupted by civil unrest in the country.
The quantitative analysis looks at the relationship between domestic real output against the real exchange rate in currency per one US dollar. Further analysis focusses on foreign real output against the nominal price oil per barrel in US dollars. The four variables are also addressed in consideration to the domestic oil exports in thousands of barrels per day. Which aspect of the supply chain is more affected, the exporter or the importer? By the end of this paper, it will be clear what affects the major oil Exporter’s economy change. Nearly all the oil imported in the US comes from Canada, it will be an easier analysis by comparing oil prices in the two main countries.
The descriptive statistics for each variable is as follows:
The mean shows the average value for the selected variable. The variables are;
ep is the logarithm of the real exchange rate (number of domestic currency per US dollar)
ys is the log of foreign real output
poil is the log of the nominal price of oil per barrel in US dollars.
xoil is the log of domestic oil exports in thousands of barrels per day.
Mean foreign real output is lower at 4.364674 compared to domestic oil exports at 6.896393. Difference in output and oil exports shows a variation in the market as experienced by oil exporters who depend on oil as source of income. The costs incurred in export are included in the low output. Standard deviation shows how the statistic deviates from the average value used in the analysis. For example, a large deviation from the mean is experienced from the real exchange rate as compared to only a 0.3 deviation by the other variables in question. The level of confidence shows how much one can rely on the statistics and data analysis. A confidence level of 95% is reported in all cases.
Residual plot shows the residuals on the vertical axis against the independent variable. The residuals areas a result of difference between estimated values and real values. Randomly dispersed points of residual graph indicate that regression model can be used for data analysis. . With the residual plots, we can determine the predicted value from observed value.
Figure 1: Graph 1
Figure 2: Graph 2
Figure 3: Graph 3
Figure 4: Graph 4
Graphs 1-4 show the residual plots of various variables. Positive values for the residuals, plotted on y axis, mean the prediction was too low and negative variables show that the prediction was too high. An exact prediction is evidenced by closeness to zero value in the residual plot. poil, xoil and ys predictions are correct since the value of residuals is close to the zero value. That is, the values are clustered around the lower digit of zero. X2 residual plot indicates outliers that are x-axis unbalanced. The model can be improved by assessing outlying data point that is legitimate. Also, transformation of variable affects the distribution of points in the graph. Variable with asymmetrical distribution is preferred to symmetrical or bell-shaped since it allows variable transformation.
When conducting residual analysis, it is important that fit plots are analyzed as well. Fit plots are scatterplot in which residuals are used as the dependent variables against the independent variables. The plot will be used to check the linearity, error variances and outliers. For example, log of domestic rate output vs. log of exchange rate to US currency. The plot shows non-linearity between output and exchange rate. However, the graph shows variation around the estimated regression line which is constant around the regression line suggesting that assumption of reasonable equal errors. The corresponding fit plots for the data sets are shown in graph 5- 8.
Figure 5: Graph 5
Figure 6: Graph 6
Figure 7: Graph 7
Figure 8: Graph 8
Regression analysis helps one to determine the typical value in case the dependent variable changes. In other words, when the independent variable is changed, the dependent variable changes in the same scale. In the analysis, regression analysis will be used to estimate conditional expectation of dependent variable as given by independent variable. From the graph shown below,
Figure 9: Graph 9
In the fitted lines, the slope coefficient is zero and expected domestic rate output does not change no matter how exchange rate increases or decreases. Graph 9 provides a key understanding of the coefficients. The graph has three case scenarios. In the linear relationship, an increase in domestic real output results to a decrease in exchange rate to US currency. The other two scenarios show a change in exchange rate at constant domestic real output. The values show that the two scenarios are outlier data and cannot be used in regression analysis.
To determine whether a regression is in good shape, or in other words healthy, assumptions are used. There are multiple assumptions that are used to determine different things. The plots from the fit plots and residuals show unhealthy relationship. A linear relationship provides healthy relationship of the variables. Within the normal probability plot, the points do fall within a straight line. Polynomial terms are used in interpreting of data results by changing the predictor variable. Predictor in most cases is known to change depending on value of independent variable. Further interaction shows variation between one predictor and the other.
Model selection involves the task of selecting statistical model from candidate models. When the actual true model is one of the models under consideration and has a small number of nonzero parameters, then exchange rate to US currency is best. It provides consistent model selection as the sample size goes to infinity and domestic real output does not. When the actual true model is not one of the models under consideration or has a large number of nonzero parameters, then domestic real output is best. The consistent estimation property of exchange rate to US currency is meaningless in this context. Moreover, Exchange rate to US currency tends to pick models that are too small.
Conclusion and future works
As with all markets, demand and supply law holds for the oil market. Lower price of oil increase demand and lower the supply. There has been known benefits especially to importing countries like USA. The benefits are facilitated by high oil demand while the exporters regret low revenue generated from the oil business. Nevertheless, the exporting side is prone to experiencing adverse effects of low oil prices which are facilitated by US reduced importation and Canada increased production. Future work should address other factors that affect oil market such as climate and political situations. In the study also, researcher should determine if buying from unstable regimes makes us supportive of human rights violations and leaderships that otherwise we would argue against in the international community. For instance, US has imposed sanctions on Iran. The effects of Iranian oil also affects the US oil market indirectly making oil market a global affair.
Baumeister, C., & Kilian, L. (2016). Lower Oil Prices and the U.S. Economy: Is This Time Different?. Brookings Papers On Economic Activity, 2016(2), 287-357. http://dx.doi.org/10.1353/eca.2016.0029
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