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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Vehicle Sales in the United States of America: A Statistical Analysis
NAMES REMOVED
University of South Alabama
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Abstract
This paper examines a number of variables and their impact on vehicle sales in the United States
(U.S.). It examines historic trends of the price of oil, U.S. Dollar and Euro exchange rates, the
U.S. Federal Fund Rate, and total vehicle sales. A series of hypotheses are presented and tested
utilizing the data collected for each variable. Statistical analyses, both descriptive and inferential,
were performed to determine any significant impact these variables have on each other and on
total vehicle sales in the U.S. Results of the analyses are presented in both table and graph forms.
A discussion of the results and analyses reveals any significant findings of the project as well as
reasons for further analyses and usage of the collected data with the subsequent analyses.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Vehicle Sales in the United States of America: A Statistical Analysis
In the United States you cannot go anywhere and not see a vehicle. According to I.
Wagner (2020), “In the fourth quarter of 2019, there were some 279.6 million vehicles operating
on the roads.” Vehicle sales in the United States occur daily—but to what extent do other factors
affect, or rather, not affect the total number of vehicle sales in the United States? This project
will discuss how oil prices, the Effective Federal Funds Rate, and the U.S. Dollar/Euro exchange
rate affect the total number of vehicle sales.
Background
While other forms of energy exist, most cars still use gasoline as fuel, so one variable that
may affect how many vehicles are sold in the United States is the price of oil per barrel. The first
null hypothesis discussed in this project is that oil prices do not predict the outcome of total
vehicle sales in the United States, with an alternative hypothesis stating that oil prices predict the
outcome of total vehicle sales in the United States. The null suggests that regardless of the price
of oil, total vehicle sales will not be impacted. Therefore, an increase in the price of oil per barrel
will not significantly increase or decrease the number of vehicles sold in the United States. We
predict that this will not be the case, and that oil prices can be used to predict the number of
vehicles sold in the U.S.
The Effective Federal Funds Rate determines the interest rate on money that is traded
between banks on a nightly basis to maintain a certain level of cash in their accounts (FRED,
2020). Because banks often give personal loans to people in order for them to purchase vehicles,
our second null hypothesis is that the Effective Federal Funds Rate does not predict the outcome
of total vehicle sales in the United States with an alternative hypothesis stating that the Effective
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Federal Funds Rate does predict the outcome of total vehicle sales in the United States. The null
for this hypothesis implies that changes in the Effective Federal Funds Rate do not significantly
change the number of vehicles sold in the United States. We believe that this is not the case and
that the Effective Federal Funds Rates will have an impact on the total number of vehicles sold.
When the European currency (Euro) is exchanged for the U.S. Dollar, the value of the
dollar increases or decreases depending on the current exchange rate. This exchange rate could
potentially be used to predict how vehicle sales will do in the United States, especially when the
number of vehicles imported from Europe is considered. The third null hypothesis discussed in
this paper is that U.S. Dollar/Euro exchange rates do not predict the outcome of the total vehicle
sales in the United States, with an alternative hypothesis that U.S. Dollar/Euro exchange rates do
predict the outcome of total vehicle sales in the United States. We believe that the U.S.
Dollar/Euro exchange rate will have a significant impact on the total number of vehicles sold in
the U.S.
As discussed previously, we believe that oil prices, the Effective Federal Funds Rate, and
the U.S. Dollar/Euro exchange rate all individually predict how many vehicles are sold in the
United States. We will now test the effect of all three variables on total vehicle sales
simultaneously to determine whether they significantly impact total vehicle sales when
combined. We believe this to be the case. Therefore, our null hypothesis is that oil prices, the
Effective Federal Funds Rate, and the U.S. Dollar/Euro exchange rate do not predict the outcome
to total vehicle sales. This leaves our final alternative hypothesis to be that oil prices, the
effective federal funds rate, and U.S. Dollar/Euro exchange rate do predict the outcome of total
vehicle sales.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Previously, we were interested in whether these variables had a significant impact on
total vehicle sales in the U.S. Now, however, we would like to determine whether a significant
relationship between monthly oil prices and total vehicle sales in the U.S. exists. Our null
hypothesis states there is no significant relationship between oil prices and total vehicle sales in
the U.S. Oppositely, our alternative hypothesis states that there is a significant relationship
between the two. We believe the alternative hypothesis to be true and that there is indeed a
significant relationship between oil prices and total vehicle sales in the U.S.
It has previously been discussed that we predict that the U.S. Dollar/Euro exchange rate
does indeed impact the total number of vehicle sales in the U.S. We additionally would like to
explore whether there a significant relationship exists between the two. We believe that there is a
significant relationship between the U.S. Dollar/Euro Exchange Rate and total vehicle sales. As
such, our null hypothesis is that a significant relationship does not exist between the U.S.
Dollar/Euro exchange rate and total vehicle sales in the United States. The alternative hypothesis
is that a significant relationship does exist between the U.S. Dollar/Euro exchange rate and the
total number of vehicles sold in the United States.
Method
The project utilizes the Federal Reserve Economic Data (FRED) website in order to
gather information about chosen variables. FRED compiles data from numerous sources and
allows users to quickly and easily view trendlines of the chosen variable. This website is
extremely valuable when attempting to compare economic data as it allows the user to
manipulate the frequency, period, and units that the data set uses. This is useful in order to ensure
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
all variables compared in the project were collected over the same time period and with the
frequency.
This project compares monthly values from 01/01/2003-12/01/2019 for the following
variables: oil prices per barrel, total vehicle sales (in millions), Effective Federal Funds Rate, and
U.S. Dollar/Euro exchange rate. Using these values over a 17-year span, the data set includes
204 values for each of the five variables. This brings the total number of observations to 1,020.
To better understand the data, the source and collection method need to be given. First,
the oil price per barrel was based on the “West Texas Intermediate (WTI) - Cushing, Oklahoma”
model. This is the preferred measure and pricing model in the United States according to the
U.S. Energy Information Administration. FRED collected this data from the U.S. Energy
Information Administration. Second, the total vehicle sales data was collected from the U.S.
Bureau of Economic Analysis. Next, the Effective Federal Funds Rate is calculated as a
“volume-weighted median of overnight federal funds transactions” (FRED, 2020), which FRED
collected from the Federal Reserve Bank of New York. Lastly, the U.S. Dollar/Euro exchange
rate is the noon buying rates in New York City for cable transfers payable in foreign currencies.
FRED compiled this data from the Board of Governors of the Federal Reserve System.
Initial Results
Since the data level for all variables in question is in ratio, mean and median are used to
describe the initial results and standard deviation is used as a measure of variability, as seen
below in Table 1.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Table 1
Mean, Median and Standard Deviation per Variable
Mean, Median and Standard Deviation per Variable
Variable
Mean
Median
Standard Deviation
Total Vehicle Sales
15.89
16.89
2.36
Oil Prices
67.81
63.58
23.60
Effective Federal
Funds Rate
1.41
0.91
1.63
U.S. Dollar/Euro
Exchange Rate
1.26
1.27
0.12
From an evaluation of the values computed for total vehicle sales, it is observed that the
mean is located to the left of the median, which is an indication that the distribution is skewed.
The skewed distribution can be observed on the following histogram in Graph 1
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Graph 1
Histogram for Total Vehicle Sales
Performing the same analysis of the mean and median for oil prices and Effective Federal
Funds Rate, as seen in Graphs 2 and 3, it is observed that the mean is located to the right of the
median, therefore an indication that the distribution is rightly skewed.
Graphs 2 and 3
Histograms for Oil Prices and Effective Federal Funds Rate
The histogram for oil prices shows a slightly rightly skewed distribution while the
respective for Effective Federal Funds Rate is highly skewed to the same direction.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
From an analysis of the U.S. Dollar/Euro exchange rate, it is observed that the mean and
median are relatively equal, an indication of a normal distribution. The histogram in Graph 4,
however, shows that the distribution is rightly skewed.
Graph 4
Histogram for U.S. Dollar/Euro Foreign Exchange Rate
Although it is important to analyze how the data is distributed, the main purpose of this
research is to learn the impact of oil prices, U.S. Effective Federal Funds rates, and the U.S.
Dollar/Euro exchange rate on total vehicle sales. Based on that, the following Graphs were
computed. Graph 5 shows the distribution of Total Vehicle Sales and Oil Prices. Graph 6 shows
the distribution of Total Vehicle Sales and the Effective Federal Funds Rate and Graph 7 shows
the distribution of Total Vehicle Sales and the U.S. Dollar/Euro Exchange Rate.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Graph 5
Total Vehicle Sales vs Oil Price 2003-2019
Graph 6
Total Vehicle Sales and Effective Federal Funds Rate 2013-2019
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Graph 7
Total Vehicle Sales vs U.S. Dollar/Euro Exchange Rate 2003-2019
From the graphs presented above, it is possible to observe an indication of a relationship
between the variables and the vehicle sales, more specifically an indication of an indirect
relationship. As the value of total vehicle sales increases over time, the oil price, Effective
Federal Funds Rate, and U.S. Dollar/Euro exchange rate decreases; and as total vehicle sales
decrease, the other variables increase. Graph 5 can be explained as the price of oil increases, the
less affordable it would be for most people to purchase a vehicle; therefore, the sales of vehicles
would decrease. Similarly, the lower the price of oil, the more affordable it would be to have and
maintain a vehicle. Therefore, the total vehicles sales increases. Graph 6 would follow the same
stream of thought. As most people use personal loans from banks to purchase a vehicle,
consequently a higher Effective Federal Funds Rate would result in a decrease of vehicle sales.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Lastly, it is possible that the exchange rate between the U.S. Dollar and Euro could affect
the sale price of European vehicles. The higher the exchange rate, the higher the price of the
vehicle in the U.S. would be and could result in a decrease of vehicle sales.
Even though, by observing the graphs, we have an indication of all the mentioned
relationships, it is inaccurate to conclude those as significant without further analysis. Therefore,
the statistical analyses on the possibility of oil prices, Effective Federal Funds Rates, and U.S.
Dollar/Euro Foreign exchange rates impacting total vehicle sales are presented in the following
sections.
Results
We will be using a type of inferential statistics called linear regression to identify whether
there is a linear relationship between the predictor variables and outcome variable. Our
predictors are oil prices, Effective Federal Funds Rates, and U.S. Dollar/Euro foreign exchange
rates and our outcome is total vehicle sales in the U.S. Regression can also identify the
“relatedness of one or many predictor variables with a single outcome” (Howard, 2020). For the
purpose of this paper, we will be conducting regression analysis to test the following alternative
hypotheses and their respective null hypotheses:
HA1: Oil prices predict the outcome of total vehicle sales in the U.S. (Testing 1).
HA2: Effective Federal Funds Rates predict the outcome of total vehicle sales in the U.S. (Testing
2)
HA3: U.S. Dollar/Euro foreign exchange rates predict the outcome of total vehicle sales in the
U.S. (Testing 3)
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Additionally, we will be examining each of the aforementioned relationships while
controlling for the other predictors by utilizing multiple regression. Lastly, this paper will look at
the following hypotheses tested by conducting the correlation analyses:
HA4: A significant relationship exists between oil prices and total vehicle sales in the U.S.
(Testing 4)
HA5: A significant relationship exists between the U.S. Dollar/Euro foreign exchange rates and
total vehicle sales in the U.S. (Testing 5)
It is to be noted that correlation analysis is similar to regression analysis; however, they
differ in that correlation measures the degree of a relationship between two variables, whereas
regression typically measures how one variable, the predictor, affects the outcome variable.
Testing 1:
HA1: Oil prices predict the outcome of total vehicle sales in the U.S.
H01: Oil prices do not predict the outcome of total vehicle sales in the U.S.
Based on Graph 8, one can conclude that there is an implication that oil prices play a role
in predicting total vehicle sales in the U.S. However, just by looking at the graph without
analyzing the equation at all, the direction of the trendline shows there is a weak and negative
relationship between oil prices and total vehicle sales. Looking closer at the equation itself, the
slope is -0.381, which is indeed closer to 0 and signals a flatter trendline.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Graph 8
Total Vehicle Sales 2003-2019
Our R2 of 0.145 confirms this weak link between the independent variable predicting our
outcome. Our p-value of less than 0.05 helps us determine that we should reject our null
hypothesis H01. We can also determine that the relationship is statistically significant and
conclude that oil prices predict the outcome of total vehicle sales in the U.S. as seen in below
Tables 2 and 3.
Table 2
Model Fit Measures
R
R2
0.381
0.145
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Table 3
Model Coefficients - Total Vehicle Sales (Millions on Units)
Predictor
Estimate
p
Intercept
18.472
< 0.001
Oil Prices (Dollars per
Barrel)
-0.038
< 0.001
Testing 2:
HA2: Effective Federal Funds Rates predict the outcome of total vehicle sales in the U.S.
H02: Effective Federal Funds Rates do not predict the outcome of total vehicle sales in the U.S.
The second regression analysis gives us a result that describes how well the Effective
Federal Funds Rate predict the outcome of total vehicle sales in the U.S. With our slope being
0.479, we can conclude that there is a positive, but relatively flat regression. Our R2 value of
0.109 also helps confirm this. Like the first hypothesis testing above, a p-value of less than 0.05
in this caseallows us to reject the null hypothesis and determine that it is statistically significant.
We can therefore conclude that Effective Federal Funds Rates significantly predict the outcome
of vehicle sales in the U.S.as seen below in Tables 4 and 5.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Table 4
Model Fit Measures
R
R2
0.330
0.109
Table 5
Model Coefficients - Total Vehicle Sales (millions of units)
Predictor
Estimate
p
Intercept
15.215
< 0.001
Effective federal fund
rates
0.479
< 0.001
Testing 3:
HA3: U.S. Dollar/Euro foreign exchange rates predict the outcome of total vehicle sales in the
U.S.
H03: U.S. Dollar/Euro foreign exchange rates do not predict the outcome of total vehicle sales in
the U.S.
The last linear regression analysis gives us a result that describes how well the U.S.
Dollar/Euro foreign exchange rates predict the outcome of total vehicle sales in the U.S. With
our slope being -11.8, we can conclude that this regression is a negative and rather steep. Our R2
value of 0.372 tells us that U.S. Dollar/Euro foreign exchange rates have a medium effect on the
outcome of total vehicle sales in the U.S. A p-value of less than 0.05 in this case means that it is
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
statistically significant and signals us to again reject the null hypothesis. We conclude that U.S.
Dollar/Euro foreign exchange rates predict the outcome of vehicle sales in the U.S. as seen
below in Tables 6 and 7.
Table 6
Model Fit Measures
R
R2
0.610
0.372
Table 7
Model Coefficients - Total Vehicle Sales (millions of units)
Predictor
Estimate
p
Intercept
30.80
< 0.001
U.S. Dollar/Euro Foreign
Exchange Rate
-11.8
< 0.001
All three hypothesis tests above have looked at how each predictor variable individually
affects the total vehicle sales in the U.S. Multiple regression will assess how all of the predictor
variables affect our only outcome, which is total vehicle sales in the U.S., while controlling for
the other predictors. We can see that all three predictor variables are statistically significant in
terms of predicting the outcome of total vehicle sales in the U.S. while controlling for the others,
meaning that they all contribute to predicting the outcome variable. An R2 of 0.541 of the
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
multiple regression shows that the effect is moderate and greater than each individual R2 value of
all the previous analyses. We can state that when accounting for the effect of all the predictors at
the same time, we get a stronger predicting effect on the outcome as seen below in Tables 8 and
9.
Table 8
Multiple Regression - Model Fit Measures
R
R2
0.735
0.541
Table 9
Model Coefficients - Total Vehicle Sales (millions of units)
Predictor
Estimate
p
Intercept
35.9859
< 0.001
Oil prices
0.0334
< 0.001
Effective Federal
Funds Rates
48.0875
< 0.001
U.S. Dollar/Euro
exchange rates
-1749.5607
< 0.001
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Testing 4 & Testing 5:
HA4: A significant relationship exists between oil prices and total vehicle sales in the U.S.
H04: A significant relationship does not exist between oil prices and total vehicle sales in the U.S.
HA5: A significant relationship exists between the U.S. Dollar/Euro foreign exchange rates and
total vehicle sales in the U.S.
H05: A significant relationship does not exist between the U.S. Dollar/Euro foreign exchange
rates and total vehicle sales in the U.S.
Table 10
Correlation Matrix Oil Prices and U.S. Dollar/Euro Exchange Rates
Total vehicle
sales
Pearson’s r
p
Oil prices
U.S./Euro exchange
rates
-0.381
<0.001
-0.610
<0.001
Based on the above correlation matrix in Table 10, total vehicle sales in the U.S. and oil
prices have a correlation of -0.381 that is statistically significant with a p-value of less than 0.05.
We can therefore reject the null hypothesis H04 and conclude that there is a significant
relationship between total vehicle sales in the U.S. and oil prices.
Likewise, total vehicle sales in the U.S. and U.S. Dollar/Euro exchange rates have a
correlation of -0.610 and the relationship is also statistically significant with a p-value of less
than 0.05. We can therefore reject the null hypothesis H05 and conclude that there is a significant
relationship between total vehicle sales in the U.S. and U.S. Dollar/Euro exchange rates.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
Discussion
In Graph 1, we see a visual representation of the impact that oil prices have on total
vehicle sales in the United States. There is only a slight, negative slope that can be seen when the
data is plotted. Without doing any further analyses, it appears as though oil prices would not be a
very good predictor of vehicle sales. In running a regression analysis on this same data, the
impact of oil prices on vehicle sales was found to be statistically significant. This allows us to
reject the null hypothesis and find that oil prices do have a significant impact on vehicle sales.
Additionally, our slope was found to be -0.381 which confirms the negative impact oil prices
have on vehicle sales. These analyses are important for two reasons. The first being that though a
predictor’s impact may look weak visually, it does not mean said impact is insignificant—and
vice versa. This is also important because experts/managers in the vehicle industry will most
likely need methods of estimating sales volumes for the following financial period. Because we
can show that oil prices are, statistically speaking, indeed a trustworthy predictor of vehicle
sales, one could follow the trends in oil prices to forecast vehicle sales.
For the following two tests, two and three, we follow similar logic. In Test 2, we ran a
regression analysis to determine whether Effective Federal Funds Rates had a significant impact
on total vehicle sales in the U.S. In this case, our slope was positive at 0.479 which tells us that
as the Effective Federal Funds Rate increases, total vehicle sales should go up as well. Similar to
oil prices, the R2 value in Test 2 was only 0.109—indicating that Effective Federal Funds Rate
may not be a considerable predictor of vehicle sales in the U.S. However, the p-value of this test
was found to be less than 0.001 and thus, we can determine the impact of Effective Federal
Funds Rate on total vehicle sales is significant. This may be another variable managers and
experts utilize when they are looking to forecast vehicle sales. Test 3 was used to determine
whether U.S. Dollar/Euro foreign exchange rates are a statistically significant predictor of total
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
vehicle sales in the United States. The R2 value for this test was 0.372 and the slope was -11.8.
Both values indicate that U.S. Dollar/Euro foreign exchange rates are a very good predictor of
total vehicle sales—though it is a negative relationship. The p-value supports this finding as well,
being that it is less than .001. Professionals in the vehicle industry may use this variable to
estimate vehicle sales.
In the previous section, we ran individual regression analyses on the effect that oil prices,
the Effective Federal Funds Rate and U.S. Dollar/Euro foreign exchange rates had on total
vehicle sales in the United States. We found that all three predictors were significant predictors
for vehicle sales with varying R2 values. These values explain what percent of variance in total
vehicle sales our predictor variable is responsible for. In this section, we wanted to know how
much of the variance in total vehicle sales was determined by all three of our predictor variables.
In order to do so, we ran a Multiple Regression analysis in which all three variables (oil prices,
the Effective Federal Funds Rate and U.S. Dollar/Euro foreign exchange rates) were our
predictors, and total vehicle sales was the outcome variable. We found that all three variables
had p-values of less than .001, meaning that they are all significant predictors of total vehicle
sales once again. The R2 value came out to be 0.541 which tells us that these three variables can
explain approximately 54% of the variance in total vehicle sales. This is a considerable amount
of variance in the outcome explained and supports our alternative hypotheses that these three
variables do significantly impact total vehicle sales.
The last two analyses we ran on this data were for correlations that may exist within the
variables. Our first correlation hypothesis states that a significant relationship exists between oil
prices and total vehicle sales in the U.S. Our analysis found a correlation of -0.381 between the
two. This relationship can be described as a negative, moderate relationship—similar to our
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
findings when running a regression analysis. This would mean that as oil prices increase, total
vehicle sales will fall, and vice versa. Our p-value for this analysis was less than .001, meaning
that a significant relationship does exist between oil prices and total vehicle sales. Though this
correlation does not prove any causation, this inverse relationship is very logical if we relate it to
real-world contexts. The cheaper oil is, the cheaper it will be to make, transport and fuel vehicles
in the U.S. A lower Cost of Goods Sold should result in a lower price tag for the vehicles, and a
higher purchasing power for end users. Thus, a decrease in oil prices should increase vehicle
sales for the United States.
The second correlation we tested was whether a significant relationship exists between
the U.S./Euro foreign exchange rates and total vehicle sales. Similar to oil prices, the exchange
rates and vehicle sales had a negative correlation at -0.610. Though both correlations are
negative, the correlation between U.S. Dollar/Euro foreign exchange rates is far stronger. This
would suggest a more direct relationship between the variables, meaning U.S. Dollar/Euro
exchange rate activity more explicitly affects vehicle sales in the United States. This could
possibly be due to the fact that the higher the exchange rate is, the more a vehicle will cost in the
U.S. This will obviously have a negative effect on the number of vehicles being sold. Strong
relationships like these are important for management personnel or experts in this field to
consider when making decisions.
It should be noted that these analyses are based on only one sample of data. In order to
further support these findings, more samples of similar data should be collected and tested. The
more analyses we can run on samples of relevant data, the further we can test the above
hypotheses. If similar results were found after many more sets of data are compiled and
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
analyzed, these variables could reasonably be used to make forecasts about future vehicle sales
in the United States.
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VEHICLE SALES IN THE UNITED STATES OF AMERICA: A STATISTICAL ANALYSIS
References
Board of Governors of the Federal Reserve System (US), Effective Federal Funds Rate
[FEDFUNDS], retrieved from FRED, Federal Reserve Bank of St. Louis;
https://fred.stlouisfed.org/series/FEDFUNDS, October 4, 2020
Federal Reserve Economic Data: FRED: St. Louis Fed. (n.d.). Retrieved October 06, 2020, from
https://fred.stlouisfed.org/
Howard, M. (n.d.). Dr. Matt C. Howard. Retrieved October 06, 2020, from
https://mattchoward.com/
U.S. Energy Information Administration - EIA - Independent Statistics and Analysis. (n.d.).
Retrieved October 06, 2020, from
https://www.eia.gov/todayinenergy/detail.php?id=43875
Wagner, I. (2020, May 14). U.S. - Number of Vehicles in Operation in the United States between
1st Quarter 2016 and 4th Quarter 2019. Retrieved October 04, 2020, from
https://www.statista.com/statistics/859950/vehicles-in-operation-by-quarter-united-states/