What Drives U.S. Gasoline Prices?

October 2014

Independent Statistics & Analysis

www.eia.gov

U.S. Department of Energy

Washington, DC 20585
U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? i

This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and 

analytical agency within the U.S. Department of Energy. By law, EIA’s data, analyses, and forecasts are 

independent of approval by any other officer or employee of the United States Government. The views 

in this report therefore should not be construed as representing those of the U.S. Department of Energy 

or other federal agencies.
U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? ii

Table of Contents

Preface ..........................................................................................................................................................1

Executive Summary.......................................................................................................................................3

Gasoline and Crude Oil Price Relationships..................................................................................................5

Part 1: The relationship between gasoline prices and crude oil prices...................................................5

Part 2: Global gasoline price relationships..............................................................................................9

Changing global gasoline price relationships..................................................................................10

Changing U.S.gasoline supply patterns...........................................................................................12

Changing global gasoline trade flows..............................................................................................14

Gasoline-distillate market interactions...........................................................................................18

Appendix: Statistical Methodology for Relationships between Gasoline and Crude Oil Price...................21

Econometric analysis.............................................................................................................................21

Results of the regression analysis..........................................................................................................24

Dynamic linear modeling.......................................................................................................................32
U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? iii

Tables

Table 1. Percentage of weeks with lowest average weekly gasoline spot price 2000-10..........................15

Table 2. Percentage of weeks with lowest average weekly gasoline spot price 2011-14..........................15

Table 3. Dickey-Fuller test and autocorrelogram results............................................................................22

Table 4. Summary regression results for Equation Set 1............................................................................24

Table 5. Summary regression results for Equation Set 2............................................................................26

Table 6. Detailed regression results for Equation Set 1..............................................................................28

Table 7. Detailed regression results for Equation Set 2..............................................................................30
U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? iv

Figures

Figure 1. Weekly average Brent and WTI crude oil spot prices....................................................................6

Figure 2. Annual average retail gasoline to crude oil price spread...............................................................7

Figure 3. Global gasoline spot prices are highly correlated........................................................................10

Figure 4. New York Harbor gasoline spot price differentials to ARA and Singapore..................................11

Figure 5. U.S. Gulf Coast gasoline spot price differentials to NYH, ARA, and Singapore............................12

Figure 6. Monthly refinery production of gasoline minus regional consumption......................................13

Figure 7. U.S. Gulf Coast monthly gasoline exports by destination............................................................16

Figure 8. U.S. Gulf Coast monthly gasoline exports to Africa .....................................................................17

Figure 9. U.S. Gulf Coast monthly gasoline exports to Asia and the Middle East.......................................18

Figure 10. Weekly average 3-2-1 crack spreads versus Brent ....................................................................19

Figure 11. U.S. Gulf Coast weekly average distillate and gasoline crack spreads versus Brent .................20

Figure 12 (appendix). Brent model, crude oil coefficient...........................................................................33

Figure 13 (appendix). WTI model, crude oil coefficient..............................................................................34

Figure 14 (appendix). PADD 1B (NYH): Brent model, spread coefficient....................................................34

Figure 15 (appendix). PADD 1B (NYH): WTI model, spread coefficient......................................................35

Figure 16 (appendix). PADD 2: Chicago spot ..............................................................................................36

Figure 17 (appendix). PADD 3: Gulf Coast spot ..........................................................................................37

Figure 18 (appendix). PADD 5: Los Angeles spot........................................................................................38
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 1

Preface

U.S. oil production has grown rapidly in recent years. U.S. Energy Information Administration (EIA) data, 

which reflect combined production of crude oil and lease condensate, show a rise from 5.6 million 

barrels per day (bbl/d) in 2011 to 7.4 million bbl/d in 2013. EIA's Short-Term Energy Outlook (STEO) 

projects continuing rapid production growth in 2014 and 2015, with forecast production in 2015 

averaging 9.5 million bbl/d. While EIA's Annual Energy Outlook (AEO) projects further production 

growth, its pace and duration remain uncertain, as shown by the significant differences between 

Reference case and High Oil and Gas Resource case projections, which differ in both the timing and level 

of the highest volume of U.S. crude oil production. EIA’s next update to the AEO will raise projected 

production significantly in the Reference case. 

Recent and forecast increases in domestic crude production have sparked discussion on the topic of how 

rising crude oil volumes will be absorbed. Given the likelihood of continued growth in domestic crude 

production, and the recognition that some absorption options, such as like-for-like replacement of 

import streams, are inherently limited, the question of how a relaxation in current limitations on crude 

exports might affect domestic and international markets for both crude and products continues to hold 

great interest for policymakers, industry, and the public. In response to multiple requests, EIA is 

developing analyses that shed light on this question.

A change in current limitations on crude oil exports could have implications for both domestic and 

international crude oil prices. To the extent that current limitations on exports cause domestic crudes 

to sell at lower prices than could occur if those limitations were relaxed, such a relaxation could raise 

the price of domestically produced oil. If higher prices for domestic crude were to spur additional U.S. 

production than might otherwise occur, the increase to global crude oil supply could reduce the global 

price of crude. The extent to which domestic crude prices might rise, and global crude prices might fall, 

depends on a host of factors, including the degree to which current export limitations affect prices 

received by domestic producers, the sensitivity of future domestic production to price changes, the 

ability of domestic refiners to absorb domestic production, and the reaction of key foreign producers to 

changes in the level of U.S. crude production.

While crude oil prices matter to those involved in producing oil or refining oil into products, most 

Americans, and the policymakers who represent and serve them, are mainly concerned with the price of 

gasoline and other refined products. With U.S. gasoline consumption running at 8.8 million bbl/d and 

the average retail price of gasoline for all grades at $3.58 per gallon, the average American household 

spent $2,600 on gasoline in 2013. Recognizing that the possible relaxation of current export limitations 

could cause the prices of domestic and international crude grades to move in opposite directions (the 

former tending to rise, the latter tending to fall) one question of interest to policymakers and the public 

is which crude prices, domestic or international, matter most to the determination of gasoline prices in 

the United States. This paper focuses on that question, and also explores how linkages across regional 

and international markets where gasoline is sold have evolved over time and influence gasoline pricing 

in domestic markets.
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 2

While the linkages that motivate the hypothesis that a relaxation of limitations on crude oil exports 

could cause domestic and international crude grades to move in opposite directions are briefly 

discussed above, the extent of any actual change in domestic production or the domestic or 

international price of crude oil that might follow from a relaxation of crude oil export limitations is not 

addressed in this paper. EIA is undertaking further analyses that will examine those issues and expects 

to report additional results over the coming months.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 3

Executive Summary

This analysis provides context for considering the impact of rising domestic light crude oil production on 

the price that U.S. consumers pay for gasoline, and provides a framework to consider how changes to 

existing U.S. crude oil export restrictions might affect gasoline prices. 

Given the likelihood of continued growth in domestic crude production, and the recognition that some 

absorption options, such as like-for-like replacement of imported crude oil streams, are inherently 

limited, the possibility that a relaxation of current policy limitations on crude exports might affect 

domestic and international markets for both crude oil and products, particularly gasoline, is an 

important issue. 

EIA's analysis of the factors affecting U.S. gasoline prices is twofold. The analysis first considers the 

relationship between U.S. spot gasoline prices and international and domestic spot crude oil prices, 

represented by Brent and West Texas Intermediate (WTI), respectively. The second part of the analysis 

focuses on the interrelationship of U.S. and worldwide gasoline prices and the extent to which global 

gasoline prices are important in determining U.S. gasoline prices. This analysis takes into account 

regional and global gasoline supply/demand balances and arbitrage, as well as how the competitive 

advantage of U.S. Gulf Coast (USGC) refineries is changing the dynamics of U.S. regional and global 

gasoline pricing. 

Key observations from EIA’s analysis of the relationship between gasoline and crude oil prices include:

• Brent crude oil prices are more important than WTI crude oil prices as a determinant of U.S. 

gasoline prices in all four regions studied, including the Midwest.

• The effect that a relaxation of current limitations on U.S. crude oil exports would have on U.S. 

gasoline prices would likely depend on its effect on international crude oil prices, such as Brent,

rather than its effect on domestic crude prices.

• The WTI crude oil price lost much of its power to explain changes in U.S. gasoline prices after 

2010, when its differential to Brent crude became wider and more volatile.

• The Brent crude oil price lost very little of its power to explain changes in U.S. gasoline prices in 

the post-2010 period. 

Key observations from EIA’s analysis of global gasoline price relationships include:

• Gasoline is a globally traded commodity and, as a result, prices and changes in prices are highly 

correlated across global spot markets.

• Gasoline balances and flows around the world are changing.

– Increasing demand in Asia, Latin America, and the Middle East has been outpacing 

increases in gasoline production in those regions.

– Demand is declining in the United States, but refinery production of gasoline is rising, 

resulting in increases in U.S. exports of gasoline into the global market.
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 4

– Demand is declining in Europe, adding to its gasoline oversupply; excess European 

gasoline now competes with increased exports from the United States.

– Because of these changing supply and demand patterns, global gasoline price 

relationships are changing; USGC and Chicago spot gasoline prices, which are closely 

linked, are now often the lowest in the world during the fall and winter months.

• U.S. gasoline exports grew rapidly from 2009-2012 but have since leveled off; however, Gulf 

Coast gasoline is now being exported to more distant markets, routinely including Africa and,

during the winter months, Asia.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 5

Gasoline and Crude Oil Price Relationships

Part 1: The relationship between gasoline prices and crude oil prices

Crude oil is the main input cost in the production of gasoline, and changes in crude oil price, along with 

changes in gasoline market conditions, drive changes in wholesale and retail gasoline prices. EIA 

estimates that about two-thirds of the price of gasoline at the pump is attributable to the refinery cost 

of crude oil. When the price of crude oil changes, the price of wholesale gasoline adjusts concurrently to 

reflect the increased refinery input cost, other market factors being equal. 

Past EIA research and analysis1 has shown that changes in wholesale gasoline spot prices have a 

consistent and predictable effect on changes in retail gasoline prices. Other factors equal, a $1-perbarrel change in the price of crude oil will result in a $1-per-barrel, or $0.024-per-gallon (1/42 of $1 

because there are 42 gallons in one barrel) change in the price of wholesale and retail gasoline. 

Statistical analysis demonstrates about half of the change in crude oil price is passed through to retail 

prices within two weeks of the price change, all other market factors equal.2

U.S retail gasoline prices are generally determined by four broad elements: 1) the price of crude oil, 2) 

refining costs and profit margins, 3) retail and distribution costs and profit margins, and 4) taxes.3

Elements three and four compose the retail segment of the supply chain, and they tend to be relatively 

stable. Because this paper addresses how gasoline prices change over time, it focuses on the first two 

elements, which account for most of the variability in retail prices. 

Prices for a wide array of crude oils and wholesale gasoline specifications are available in markets, or 

trading hubs, around the world. These prices are commonly called spot prices. The spot market is often 

the first pricing point for petroleum products such as gasoline. At this level, sales of product for 

immediate delivery take place at a convenient transfer point, such as a refinery, port, or pipeline 

junction. The spot price for a product reflects the cost of crude oil and other inputs to refiners as well as 

the costs and profits of processing that crude oil into products.4

Because the purchases and sales reflected by spot prices generally occur in actively traded markets with 

many participants, they very quickly reflect market supply and demand conditions for that commodity. It 

is this variability in crude oil prices and spot gasoline prices that causes most of the variation in retail 

gasoline prices.

Prior to 2011, the question of whether Brent was more or less significant than WTI in determining U.S. 

gasoline prices was not very important. Historically, the price spread between Brent and WTI was 

relatively narrow and consistent, reflecting the cost of moving light sweet crude from the North Sea or 

West Africa to the United States (Figure 1). However, beginning in mid-2010, growing deliveries of

 1 Gasoline Price Pass-through (January 2003): http://www.eia.gov/petroleum/archive/gasolinepass.htm 2 While EIA recognizes that wholesale gasoline and crude oil prices are interdependent, because demand for crude oil is very 

highly related to the demand for refined products, this analysis focuses on the first order relationship between changes in crude 

oil price and wholesale gasoline price. 3 http://www.eia.gov/petroleum/gasdiesel/pump_methodology.cfm

4 This Week In Petroleum (November 24, 2010): http://www.eia.gov/petroleum/weekly/archive/2010/101124/twipprint.html
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 6

Canadian crude oil to Cushing, Oklahoma, and increasing U.S. light sweet crude oil production from tight 

oil formations, such as Bakken, Permian, and Eagle Ford, caused transportation bottlenecks in the U.S. 

Midcontinent. These bottlenecks caused the prices of U.S. crudes, like WTI, to decline compared with

the prices of globally-traded crudes such as Brent. From 2011 through June 2014, weekly average WTI 

discounts to Brent ranged from $2 to $28 per barrel.

Figure 1. Weekly average Brent and WTI crude oil spot prices

Source: Bloomberg LP.

As WTI prices declined relative to Brent, U.S. gasoline prices generally maintained their previous 

relationship with Brent. From 2000 through 2010, the average annual spread between the U.S. average 

regular gasoline retail price and Brent spot price was $0.91 per gallon (Figure 2). From 2011 through 

2013, the retail spread to Brent averaged $0.92 per gallon, almost unchanged from the 2000-2010 

period. The relationship between spot gasoline in major markets across the United States and Brent also 

remained generally constant over the entire period. 

Unlike the spread between gasoline and Brent, the spread between gasoline and WTI changed 

significantly when Brent and WTI prices diverged in 2011. From 2000 through 2010, the average annual 

spread between the U.S. average regular gasoline retail price and the WTI spot price was $0.87 per 

gallon.

5 However, from 2011 through 2013, the spread between the price of retail gasoline and WTI 

crude oil was significantly higher, ranging from $1.17 to $1.38 per gallon. In the United States, WTI 

 5 During this period the highest average annual spread of $1.07 per gallon occurred in 2007 when global gasoline supply was 

extremely tight. The spread between gasoline and Brent was also $1.07 in 2007. 

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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 7

prices are more widely quoted than Brent prices by press and media outlets, and the price of WTI is 

often reported as the price of crude oil. As a result, the change from historical levels in the price 

difference between retail gasoline prices and WTI prompted questions about whether the relationship 

between crude oil and retail gasoline prices had changed. While not as visible to consumers, a similar 

shift occurred between the price of WTI and the spot price of gasoline at major markets across the 

United States. 

The consistency over time of the pricing relationship between gasoline and Brent crude oil, and the 

apparent change in the pricing relationships between gasoline and WTI when Brent and WTI diverged 

significantly starting in 2011, suggest that Brent, rather than WTI, has been more important in 

determining U.S. gasoline prices. 

Figure 2. Annual average retail gasoline to crude oil price spread

Source: U.S. Energy Information Administration and Thomson Reuters.

The issue of which crude oil matters most for U.S. gasoline prices is particularly relevant as policymakers 

in the Executive Branch and Congress consider the possibility of changes in current limitations on crude 

oil exports. To the extent that current limitations on exports cause domestic crudes to sell at lower 

prices than could occur if those limitations were relaxed, such a relaxation could raise the price of 

domestically produced oil. If higher prices for domestic crude were to spur additional U.S. production 

than might otherwise occur, the increase to global crude oil supply could reduce the global price of 

crude. The extent to which domestic crude prices might rise, and global crude prices might fall, depends 

on a host of factors, including the degree to which current export limitations affect prices received by 

domestic producers, the sensitivity of future domestic production to price changes, the ability of 

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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 8

domestic refiners to absorb domestic production, and the reaction of key foreign producers to changes 

in the level of U.S. crude production.

The extent of any actual change in domestic production or the domestic or international price of crude 

oil that might follow from a relaxation of crude oil export limitations, which will be the subject of further 

analyses, is beyond the scope of this paper. However, the possibility that prices of domestic crudes,

such as WTI, and international crudes, such as Brent, would move in opposite directions highlights the 

importance of understanding which type of crude drives U.S. gasoline prices, which may be the most 

salient petroleum product price for the public and many policymakers. 

For this reason, EIA decided to undertake statistical modeling to dig deeper into the question of how 

gasoline prices are linked to various types of crude oil. Despite the evidence reviewed above suggesting 

that Brent was more important than WTI, EIA developed its statistical analysis in a symmetric fashion, 

running specifications for both Brent and WTI in parallel. 

The analysis considers the relationship of weekly changes in spot gasoline prices in the four regions of 

the United States that have viable spot markets for gasoline (New York Harbor (NYH), USGC, Chicago, 

and Los Angeles) as a function of weekly changes in the spot price of Brent and WTI crude oils and the 

change in the deviation of regional gasoline inventories from the most recent five-year average level. 

The deviation in regional inventory was included as a proxy for regional gasoline supply-demand 

conditions. The period covered by the analysis begins in 2000 and continues through June 2014.

The analysis examines the gasoline-crude oil price relationships over two periods. The first period runs

from 2000 through year-end 2010, a period when the Brent-WTI spread was consistently narrow. During 

the second period, which begins in January 2011 and continues through the end of June 2014, the BrentWTI spread was typically wider and quite volatile. The econometric equations test how well Brent and 

WTI crude oil prices independently explain changes in gasoline prices in each of the two periods. They

also examine whether adding the other crude oil as an independent variable (e.g., adding a Brent 

component into the equation where WTI is the explanatory variable) in the form of the Brent-WTI 

spread improves the explanatory power of the equation. 

The econometric analysis supports three important findings:

1. For both the 2000-2010 and 2011-2014 periods, the equations in which the Brent price was used 

as the independent variable have more explanatory power than the equations in which WTI was 

the independent variable. This holds true for all regional markets, including the Midwest.

2. The equations that use Brent as the independent variable lose very little explanatory power 

from period one (2000-2010) to period two (2011-June 2014), while equations with WTI as the 

independent variable lose considerable explanatory power from period one to period two.

3. Introducing the Brent-WTI spread to equations in which WTI is the independent variable 

significantly improves the explanatory power of the equations, while introducing this spread to 

equations that use Brent as the independent variable does not significantly improve the 

explanatory power.
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 9

Together, these findings support the conclusion that the Brent crude oil price is more important than 

WTI crude oil price as a determinant of U.S. gasoline prices. The second conclusion shows that this was 

the case during both times of narrow and stable Brent-WTI spreads and times of relatively wide and 

volatile spreads.

A detailed discussion of the econometric analysis and results is included in the Statistical Methodology 

for Relationships between Gasoline and Crude Price appendix of this report. 

Part 2: Global gasoline price relationships

The previous section shows that Brent prices, rather than WTI prices, are the main crude oil price 

determinant of spot, and therefore retail, U.S. gasoline prices. However, crude oil prices are not the 

sole determining factor for spot gasoline prices. Spot gasoline prices are also a function of the wholesale 

gasoline margin, often referred to as the gasoline crack spread, i.e., the difference between spot 

gasoline price and crude oil price. Wholesale gasoline margins take into account supply/demand 

conditions for gasoline at the prevailing crude oil price, including refining costs and refining profits. 

Together, the price of Brent crude oil and the wholesale gasoline margin in a given market compose that 

market’s spot gasoline price. 

The major markets for gasoline in the United States include NYH, the USGC, Chicago, and Los Angeles. 

Outside the United States, the major gasoline market hubs are Amsterdam-Rotterdam-Antwerp (ARA), 

the Mediterranean, and Singapore. NYH, the USGC, ARA, and the Mediterranean are part of the actively 

traded Atlantic Basin petroleum market. Chicago is directly linked to the Atlantic Basin market through 

infrastructure connections to the USGC. Singapore is a major trading hub in the Pacific Basin market, 

which also includes Los Angeles.

Prices at these different trading hubs are linked through arbitrage, and the differences between prices 

at different trading hubs reflect transportation costs between the regions, differences in gasoline 

quality, such as octane rating, and regional supply/demand balances. Gasoline moves from markets with 

surplus supply to markets in need of supply based on these price differences. This means that spot 

gasoline prices in markets that produce more gasoline than they consume, assuming no difference in 

quality specifications, need to be lower than prices in markets that consume more gasoline than they 

produce, in order to encourage gasoline to flow from the market with excess supply to the market in 

need of supply. In this way, the price of gasoline in different locations both in the United States and 

around the world is set by supply and demand conditions in the various regional markets that make up 

the global market. 

Because the United States is an active participant in the global petroleum market as both an exporter 

and importer of gasoline, U.S. gasoline prices are tied to global gasoline prices. As quality specification 

differences among the major gasoline markets are relatively small, and because gasoline can be shipped 

between markets for a relatively low cost, the price differences among the major gasoline trading hubs 

tend to be small and price movements highly correlated (Figure 3). 
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 10

Figure 3. Global gasoline spot prices are highly correlated

Source: Bloomberg LP and Thomson Reuters.

Changing global gasoline price relationships

Spot gasoline prices in NYH, ARA, and Singapore can be broadly thought of as being representative of 

the western Atlantic basin, the eastern Atlantic Basin, and the Pacific Basin, respectively. Prior to 2008, 

the United States, in particular the U.S. East Coast, was a large and growing gasoline market that needed 

to import large amounts of gasoline from the international market to meet demand. To attract gasoline 

supply to the U.S. East Coast from Europe, and at times from the Pacific Basin, NYH gasoline prices

typically traded at a premium to prices in ARA and Singapore.

Around 2008, economic recession, efficiency policies, and U.S. ethanol mandates began eroding gasoline 

demand in the Atlantic Basin, while gasoline demand in Asia continued growing, led by major consuming 

countries China, India, and Indonesia. This shift in demand growth contributed to an increase in 

Singapore gasoline prices relative to prices in NYH and ARA. Since 2008, the price of gasoline in 

Singapore has typically been the highest price among the three major trading hubs, reflecting the need 

for gasoline supply to flow into the Pacific Basin (Figure 4). Despite the erosion in Atlantic Basin gasoline 

demand and the increase in demand in Asia, the relationship between gasoline prices in the ARA and 

NYH has remained relatively unchanged from the period before 2008. The stability of the ARA-NYH price 

relationship reflects the continuing need for the East Coast to import gasoline, much of which has been 

and continues to be supplied from northwest Europe.

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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 11

Figure 4. New York Harbor gasoline spot price differentials to ARA and Singapore

Source: Bloomberg LP and Thomson Reuters.

Both NYH and the USGC are submarkets in the western Atlantic Basin. The USGC, which is home to half 

of U.S. refining capacity and about 10% of total global refining capacity, has long been a major supplier 

of gasoline and other refined products to other regions of the United States. More recently, the USGC 

has become a major supplier to the rest of the world. The combination of increasing USGC production of 

refined products and stagnating Atlantic Basin demand has had a major impact on global gasoline 

markets.

Historically, USGC spot gasoline priced in a tight range with other Atlantic Basin and U.S. gasoline prices. 

From 2000 through 2010, USGC spot gasoline prices averaged a $0.07-per-gallon premium to ARA, 

reflecting the United States’ status as a major gasoline importer. During the 2000-2010 period, USGC 

gasoline prices were slightly lower on average than NYH and Chicago, reflecting the region’s position as 

a supplier to those markets. As was the case in other Atlantic Basin markets, in 2008, USGC prices 

shifted from typically being at a premium to Singapore to typically being at a discount, reflecting the 

easing supply-demand balances in the Atlantic Basin and the tightening balances in the Pacific Basin. 

Beginning in 2011, USGC gasoline prices began to price at a discount to prices at all other major market 

hubs for much of the calendar year, and the volatility of the spread between USGC gasoline prices and 

other global gasoline prices increased. USGC gasoline prices fell to a discount to ARA, NYH, and 

Singapore prices of $0.01, $0.10, and $0.13 per gallon, respectively, on average from January 2011

through June 2014. Additionally, USGC gasoline price discounts to other locations reached particularly 

wide levels during the past three winters when seasonally lower demand and record refinery runs in the 

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basin and demand growth in Asia
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 12

United States substantially increased supply in the USGC gasoline market (Figure 5). As a result, the 

USGC exported an average of 436,000 bbl/d of total gasoline in 2013, up from 119,000 bbl/d in 2008. 

Monthly USGC gasoline exports reached a high of 659,000 bbl/d in December 2012.

Figure 5. U.S. Gulf Coast gasoline spot price differentials to NYH, ARA, and Singapore

Source: Bloomberg LP and Thomson Reuters.

Changing U.S.gasoline supply patterns

Changes in regional supply-demand balances in both the USGC and the Midwest have contributed to 

changes in gasoline price relationships and supply flows. From 2008 through 2013, USGC petroleumbased (non-ethanol) gasoline consumption increased only modestly, and in the Midwest, consumption

decreased by 100,000 bbl/d, largely due to increased ethanol blending and fleet efficiency gains as a 

result of corporate average fuel economy (CAFE) standards. Over the same period, access to priceadvantaged crude oil and natural gas feedstock increased the relative competitiveness of U.S. refineries 

in the global market, as did refinery investment in upgrading capacity and capacity expansions. Since 

2008, when USGC refinery production of gasoline bottomed out at 4.0 million bbl/d, refineries increased 

gasoline production to an average of almost 4.4 million bbl/d during 2013. Over the same period,

Midwest refineries increased gasoline production from 1.8 million bbl/d to almost 2.0 million bbl/d. On 

an average annual basis, the USGC’s surplus of gasoline production over consumption increased from 

2.7 million bbl/d in 2008 to 3.0 million bbl/d in 2013. In the Midwest, the supply shortfall decreased by 

half, dropping from 0.6 million bbl/d in 2008 to just 0.3 million bbl/d in 2013 (Figure 6). Because the 

Midwest’s shortfall of gasoline is supplied from the USGC, the reduction in the amount of gasoline 

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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 13

needed to meet demand in the Midwest pushed gasoline supply back to the USGC, directly adding to 

supplies available on the USGC.

Figure 6. Monthly refinery production of gasoline minus regional consumption

Source: U.S. Energy Information Administration, Petroleum Supply Monthly.

Because most incremental supply in the Midwest comes from the USGC, the reduction in USGCproduced gasoline needed to supply the Midwest, along with the increasing production on the USGC 

itself, combined to increase the annual average USGC supply relative to consumption by almost 0.6 

million bbl/d since 2008. 

USGC gasoline oversupply is particularly high during the winter months when gasoline demand in the 

United States is at a seasonal low. Again, the Midwest is a key driver of this dynamic. While Midwest 

gasoline production was 390,000 bbl/d below consumption on average from March–October 2013, the 

shortfall was just 90,000 bbl/d on average during the winter months of November 2013–February 2014.

However, the dramatic narrowing of the gasoline production gap in the Midwest during the winter is a 

recent development. As recently as the winter months of November 2010–January 2011, the Midwest 

production shortfall averaged 270,000 bbl/d. 

A combination of declines in demand and increases in refinery crude runs in the late autumn and early 

winter have increased gasoline oversupply in the USGC. From November 2013 to January 2014, USGC 

refinery gross inputs to distillation units were 8.3 million bbl/d, up almost 0.5 million from the same 

period in 2010-11. Much of this increase was the result of increased capacity rather than higher 

utilization of existing capacity. Utilization for USGC refineries remained unchanged at 91% over those 

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Midwest

million barrels per day
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 14

periods. In the Midwest, gross inputs increased 0.2 million bbl/d from November 2010–January 2011 to 

average 3.5 million bbl/d from November 2013 to January 2014.

Although a lower call on USGC gasoline by the Midwest and more surplus gasoline production in the 

USGC have made more gasoline available on the USGC, pipeline infrastructure and marine shipping 

constraints limit how much USGC-produced gasoline can be economically transferred to other U.S. 

regions, particularly the U.S. East Coast, which produces less gasoline than it consumes. As a result, 

USGC refinery utilization is now very much a function of export demand, and USGC spot gasoline prices 

reflect the shift. 

Changing global gasoline trade flows

As noted above, the differences between product prices at different market hubs reflect transportation 

costs between the regions, differences in gasoline quality, and regional supply-demand balances. As the 

USGC produces increasingly more gasoline than it consumes, the spot gasoline prices in the USGC have

shifted to export parity, declining versus gasoline prices in Europe, Singapore, NYH, and the rest of the 

world, and encouraging the export of gasoline to the marginal market for USGC production. Spot 

gasoline prices in the USGC are now typically the lowest in the world for at least some part of the year.

Tables 1 and 2 below provide percentage data by month on the number of weeks the gasoline price in a 

particular market hub was the lowest among the identified group of major hubs. As gasoline typically 

flows from regions of lower price where there is excess supply to regions of higher price where supply is 

needed, these data can be used as a proxy for global gasoline balances and trade flows. Data on 

individual and aggregated global refined product balances and flows are difficult to accurately develop 

because of differences in the availability of country-level and regional data and concerns about data 

integrity. Table 1 covers the period 2000-2010 and the Table 2 the period 2011-14. These two time 

periods were chosen for consistency with the analysis of the relationship between U.S. gasoline prices 

and crude oil prices. The gasoline-crude analysis takes into account the observed January 2011 break 

point between the relationship of gasoline and crude oil prices that resulted from the decline in U.S. 

crude prices relative to global crude prices. The decline in U.S. crude oil prices, combined with access to 

low-cost natural gas, created incentives for U.S. refineries to increase crude runs leading to higher 

gasoline production. The combination of higher gasoline production and stagnating Atlantic basin 

gasoline demand resulted in changes in global gasoline price relationships. 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 15

Table 1. Percentage of weeks with lowest average weekly gasoline spot price 2000-10

Month NYH USGC Chi LA Europe Sing

January 0% 0% 8% 0% 84% 8%

February 0% 0% 7% 0% 91% 2%

March 0% 0% 4% 0% 82% 14%

April 0% 0% 2% 0% 64% 34%

May 0% 0% 0% 0% 48% 52%

June 0% 0% 0% 0% 46% 54%

July 0% 8% 4% 0% 33% 54%

August 0% 6% 6% 0% 53% 35%

September 0% 0% 0% 0% 70% 30%

October 0% 6% 0% 0% 65% 29%

November 0% 4% 9% 0% 74% 13%

December 0% 0% 8% 0% 84% 8%

Source: Bloomberg LP and Thomson Reuters.

Table 2. Percentage of weeks with lowest average weekly gasoline spot price 2011-14

NYH USGC Chi LA Europe Sing

January 0% 0% 81% 0% 19% 0%

February 0% 25% 25% 0% 50% 0%

March 0% 6% 6% 0% 89% 0%

April 0% 12% 18% 0% 71% 0%

May 0% 28% 0% 0% 72% 0%

June 0% 38% 6% 0% 38% 19%

July 0% 15% 8% 8% 62% 8%

August 0% 14% 0% 7% 43% 36%

September 0% 77% 0% 0% 8% 15%

October 0% 33% 25% 0% 33% 8%

November 0% 57% 29% 0% 14% 0%

December 0% 15% 62% 0% 23% 0%

Source: Bloomberg LP and Thomson Reuters.

As the data in Table 1 indicate, during the period 2000-2010, the lowest gasoline spot prices were most 

often in Europe and Singapore. The Singapore price was lowest particularly during the summer,

although mostly prior to 2008. The price was less-frequently lowest at a U.S. market hub, and only in the 

USGC or Chicago. NYH and Los Angeles never had the lowest price.

In 2011, as the USGC gasoline supply surplus began to increase, the relationship between global gasoline 

prices began to change. As the data in Table 2 show, during the winter months of the 2011-through-
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 16

June-2014 period, the price of gasoline in the USGC or Chicago was most often the lowest, while the 

gasoline price in Europe was typically lowest during the spring and in July. Over the 2011–June 2014 

period, the price of gasoline in Singapore was lowest less frequently and only during the June through 

October period. NYH was never the lowest price gasoline market because the region depends on 

imports of gasoline.

Lower prices on the USGC are now needed to clear the larger gasoline surplus in that market. Lower 

prices make it economic to export gasoline to more distant markets, thus redefining the incremental

market for USGC gasoline. Prior to 2011, USGC gasoline rarely moved to markets beyond the Americas

(Figure 7). However, as the gasoline surplus in the USGC has increased, relatively lower USGC prices 

have been needed to make it economic to move gasoline to more distant markets. In the winter 

months, when U.S. gasoline demand is seasonally lowest and the surplus in the USGC peaks, USGC 

gasoline prices are at their lowest compared with other market hubs.

It is useful to think of the various market hubs as “faucets” and “sinks.” The faucet hubs are long on 

product, meaning that the region produces more gasoline than can be locally consumed. The sink hubs 

are short product, meaning that the region consumes more gasoline than it produces. Faucet markets 

typically supply product to the closest sink market, minimizing transportation costs and maximizing

revenue, and prices equilibrate to encourage the flow. Once demand in the closest market is satisfied, 

prices equilibrate to encourage supply to the next-closest market, which becomes the new marginal 

market.

Figure 7. U.S. Gulf Coast monthly gasoline exports by destination

Source: U.S. Energy Information Administration, Petroleum Supply Monthly.

0

100

200

300

400

500

600

700

800

Europe

Asia, Middle East, & Africa

Americas

thousand barrels per day

winter
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 17

Most USGC exports of gasoline continue to supply the Americas, primarily Mexico, as it is the closest 

export market to the USGC. More recently, USGC exports have started to reach markets outside the 

Americas. The still small but growing share of exports to these markets indicates that USGC refineries 

have likely captured as much of the Americas gasoline market as is currently possible. As Figure 7 

illustrates, demand for USGC gasoline in the Americas has been declining slowly since 2011.

With limited opportunity to increase exports to the Americas, USGC gasoline exports are moving to

Africa, a market historically supplied by European refineries. In the past year, exports of gasoline from 

the USGC to Africa, which were historically unusual, have averaged at least 20,000 bbl/d (Figure 8). This 

consistent level of exports suggests that African gasoline demand is now part of the base market

supplied by USGC refiners. However, the African gasoline market is relatively small, and its proximity to 

major refining centers in Europe and the Middle East, for which Africa is likely the marginal market, 

limits the potential to increase supply of U.S.-produced gasoline.

Figure 8. U.S. Gulf Coast monthly gasoline exports to Africa

Source: U.S. Energy Information Administration, Petroleum Supply Monthly.

As noted earlier, USGC gasoline prices are at their lowest compared with other trading hubs during the 

winter months, between November and February. This deeper discount of USGC gasoline to prices in the 

rest of the world is needed to support sales to regions beyond the Americas and Africa. During the 

winter months of the past three years, the USGC has exported increasing volumes of gasoline to Asia

(Figure 9), including Japan, South Korea, China, and Singapore. Exports to Asia are not economic during 

the U.S. summer when U.S. demand is seasonally higher and the price of gasoline in the USGC is not so 

steeply discounted versus prices in the rest of the world. Thus, evidence suggests that Asia is now the 

0

10

20

30

40

50

60

70

80

90

thousand barrels per day
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 18

marginal market for USGC gasoline supplies during the winter months of November–February, while

Africa is the marginal market during the balance of the year.

Figure 9. U.S. Gulf Coast monthly gasoline exports to Asia and the Middle East

Source: U.S. Energy Information Administration, Petroleum Supply Monthly.

Gasoline-distillate market interactions

The foregoing analysis of the gasoline market focuses on gasoline supply and demand and does not 

explore how distillate supply-demand, including both diesel fuel and heating oil, affects gasoline market 

dynamics. Strong diesel fuel demand growth in recent years has caused diesel to price at a premium to 

other refined petroleum products for most of the year. The behavior of the 3-2-1 crack spread, which 

approximates the margin a refinery would realize from processing (cracking) three barrels of crude oil to 

produce two barrels of gasoline and one barrel of distillate, during the winter months when gasoline 

demand around the world is lowest, suggests that refineries are running the last barrel of crude oil to 

capture distillate margins (Figures 10 and 11). During the late autumn and early winter, gasoline margins

in recent years have been very small or even negative, while distillate margins, buoyed by winter 

distillate demand for space heating fuel, have been strong. Without distillate demand and the

contribution of distillate to refining margins, refineries might opt to reduce crude oil inputs during this 

time of the year, a move which would reduce the supply of gasoline in the global market and change 

absolute and relative gasoline prices around the world. 

0

10

20

30

40

50

60

70

80

90

thousand barrels per day
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 19

Figure 10. Weekly average 3-2-1 crack spreads versus Brent

Source: Bloomberg LP.

Source: Distillate price used to calculate crack spread is heating oil.

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Gulf Coast (Brent)

New York (Brent)

ARA (Brent)

dollars per gallon
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 20

Figure 11. U.S. Gulf Coast weekly average distillate and gasoline crack spreads versus Brent

Source: Bloomberg LP.

Source: Distillate price used to calculate crack spread is heating oil.

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Distillate

Gasoline

dollars per gallon
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 21

Appendix: Statistical Methodology for Relationships between

Gasoline and Crude Oil Price

Econometric analysis

The purpose of this analysis is to determine which benchmark light sweet crude oil (Brent or WTI) better 

explains (i.e., is more statistically significant in determining) gasoline spot price behavior in the various 

Petroleum Administration for Defense Districts (PADD) of the United States, and whether gasoline-crude 

oil price relationships have changed over time. To do this, EIA created models that analyze changes in 

gasoline spot prices as a function of changes in crude oil prices, regional inventories and crude oil price 

spreads. The time period chosen for the study is January 2000–June 2014. January 2011, when WTI 

prices first moved to a significant discount to Brent prices, offers a useful breakpoint for testing crude 

oil-gasoline price relationships. EIA confirmed the statistical validity of using January 2011 as a 

breakpoint for the data series by employing a Chow Breakpoint test. The estimated model examined 

the change in weekly average WTI price as a function of the change in Brent price and an error 

correction term (lagged WTI and lagged Brent price level). The test involved an examination of the 

Brent-WTI price relationship using a single model (the restricted model) for the whole time period, along 

with individual models (the unrestricted model) for each of the two sub-time periods (2000-10 and 

2011-14), and using an F-test to compare the Sum of Squared Errors (SSE) of the restricted model with 

the SSE of the unrestricted model. The null hypothesis of no statistically significant change in the SSE’s of 

the restricted and unrestricted models was rejected, indicating that January 2011 is a breakpoint in the 

Brent-WTI price relationship. As a result, EIA broke the data into two periods. Period 1 runs from 

January 2000 through December 2010, while Period 2 runs from January 2011 through June 2014. 

The data analyzed consisted of Brent and WTI crude oil spot prices, regional gasoline spot prices, and 

regional gasoline inventories. Daily gasoline and crude oil spot prices were obtained from Bloomberg LP.

The daily prices were averaged to a weekly frequency for each of the crude oils and each of the four 

regions with viable gasoline spot market prices: U.S. East Coast, U.S. Gulf Coast (USGC), Midwest and 

West Coast. These markets are represented by gasoline spot price series in: New York Harbor (NYH), 

USGC, Chicago (CHI), and Los Angeles (LA), respectively. To account for the effects of seasonal behavior, 

the regional inventories were adjusted to be deviations from the previous five-year averages.6

 The 

regional gasoline price series were adjusted to account for a very small number of extraordinary onetime events (e.g., Hurricane Katrina).7

Energy market spot price series are well known to be non-stationary in the long term, although they 

may demonstrate stationary behavior during short time periods.8

 To investigate the behavior of the 

series, EIA used autocorrelograms and augmented Dickey-Fuller (DF) tests; the results of these tests, for 

 6 Energy Information Administration; Form EIA-800 “Weekly Refinery and Fractionator Report,” Form EIA-801 “Weekly Bulk 

Terminal Report,” Form EIA-802 “Weekly Product Pipeline Report,” 

http://www.eia.gov/dnav/pet/pet_stoc_wstk_a_epm0_sae_mbbl_w.htm. 7 Modified data points include Hurricane Katrina 9/2/05 (all regions); Hurricanes Gustav and Ike 9/12/08 and 9/26/08 (NYH, CHI,

and USGC); Summer 2012 Chicago price spike 8/3/12 (CHI only); and 2012 California price spike 10/5/12 (LA only).

8 A stationary series reverts to a constant, long-term mean and has a constant variance independent of time. A non-stationary 

series does not display these characteristics and is considered a “random walk.”
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U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 22

the three time periods considered, are shown in Table 3. Unlike spot prices, all four of the regional 

gasoline inventory series demonstrate stationary behavior in both sub-time periods. The gasoline and 

crude oil price series are clearly non-stationary in Period 1. In Period 2, some of the test results indicate 

that both gasoline and crude oil prices demonstrate some stationary behavior. The time series 

properties of data series can be affected by the presence of major market events (e.g., the 2008 crude 

oil price spike) and transitory outliers principally due to weather events (especially in the gasoline price 

series), which make correct interpretation of the low power DF test results difficult; however, this does 

not appear to be the case in Period 2. 

Table 3. Dickey-Fuller test and autocorrelogram results

DF test1 Autocorrelogram

Period Period

Full 1 2 Full 1 2

Inventory Deviation 

from 5-year avg

reject H0 accept H1 reject H0 stationary stationary stationary

Crude Oil Prices weak 

accept H0

accept H0 reject H0 random 

walk

random 

walk

stationary

Gasoline Prices reject H0 weak2

accept H0

reject H0 random 

walk

random 

walk

stationary

1

Note: "accept" means "not reject."

2

Note: New York Harbor is "reject" in Period 1.

Because market spot price series are known to be non-stationary in the long term, EIA assumed nonstationary price series for this study. As the various combinations of crude oil and gasoline price series 

were found to be cointegrated by the Johansen method, EIA used error correction models (ECM) as the 

basis for this analytical work. Additionally, all the error correction terms in the estimated equations are 

significantly different from zero and are of the correct (negative) sign.

The Error Correction Term was created from the residuals (εt ) of the following equation:

Equation 1: yt = β xt + seasonal dummy variables + εt, 

where 

• yt is gasoline spot price (NYH, CHI, USGC, or LA) at time t;

• xt is crude oil spot price (WTI or Brent) at time t.

The weekly seasonal dummy variables were defined as all weeks in a particular month. Gasoline prices 

demonstrate regular seasonal fluctuations; the significance test for the seasonal dummy variables shows 

them to be jointly different from zero.

The basic model used to investigate the regional gasoline spot price behavior was as follows:

Equation 2: ∆yt = C + ∆x‘β + ∆w‘ τ + γ*BWspreadt + λ∗ECTt-1 + εt + AR(1) correction 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 23

where

• ∆x is a vector of current (and lagged) change in crude oil price (WTI or Brent);

• ∆w is a vector of current and/or lagged change deviations from normal regional inventory;

• BWspread is the change in the Brent-WTI price differential;

• Bolded items indicate vectors.

Since the Breusch-Pagan-Godfrey test and White’s test indicated the presence of residual 

heteroskedasticity in all of the equations, the Newey-West HAC estimator was used to calculate the 

covariance matrix. The expected sign of the estimated coefficient on inventory variables is negative, the 

expected sign on the estimated coefficient on change in crude oil price is positive with the sum equal to 

approximately 0.0238. The sign of the estimated coefficient on the error correction term is negative. 

Because gasoline prices demonstrate regular seasonal fluctuations, the significance test for the seasonal 

dummy variables confirmed them to be jointly different from zero.

For each of the four gasoline (mogas) spot prices considered, EIA created two different sets of 

equations:

1. Equation Set 1

a. ∆(mogas)t= β1∆(Brent)t + β2∆(regional inv)t + other terms

b. ∆(mogas)t= β1∆(WTI)t + β2∆(regional inv)t + other terms

2. Equation Set 2

a. ∆(mogas)t= β1∆(Brent)t + β2∆(regional inv)t + β3∆(Brent-WTI)t + other terms

b. ∆(mogas)t= β1∆(WTI)t + β2∆(regional inv)t + β3∆(Brent-WTI)t +other terms

where

• ∆(Brent) and ∆(WTI) = weekly change in Brent and WTI spot price, including lags in some 

cases

• ∆(regional inv) = weekly change in the deviation of in-region gasoline inventories from the

previous 5-year average, including lags in some cases

• ∆(Brent-WTI) = weekly change in crude oil spot price differential

• Other terms include the error correction term and an AR (1) variable

These four equations were estimated for two periods:

• Period 1: January 2000–December 2010: period of narrow Brent – WTI price differentials

• Period 2: January 2011–June 2014: period of wide and variable Brent – WTI price 

differentials

Equation Set 1 shows changes in each of the regional gasoline spot prices as a function of the change in 

the respective benchmark crude oil. Comparing the results of Equations 1a and 1b will indicate whether 

Brent or WTI price change had more explanatory power in determining U.S. gasoline spot prices. 

Additionally, comparing the results of Equations 1a and 1b in Periods 1 and 2 will show whether each 

crude oil’s explanatory power went up or down after WTI began selling at a significant discount to Brent 

in January 2011. 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 24

Equation Set 2 introduces the change in the Brent-WTI spread to Equation Set 1. Adding this variable 

allows evaluation of whether adding Brent prices to an equation that has WTI prices as an independent 

variable, or vice-versa, adds statistically significant explanatory power to the equation. The reasoning is 

as follows: if Brent is the crude oil price that explains gasoline price changes, then introducing WTI (in 

the form of WTI-Brent spread to reduce multicollinearity) into the gasoline/Brent estimation should add 

no explanatory power (i.e., result in an insignificant coefficient). However, under the same hypothesis, 

introducing Brent into the gasoline/WTI equation should add explanatory power (i.e., result in a 

statistically significant coefficient). As shown in the following section, this hypothesis is confirmed. 

Results of the regression analysis 

Tables 4 and 5 summarize (i.e., with the “other terms” not shown) results of the regression analysis. 

Tables 6 and 7 show the detailed estimation results. 

Table 4. Summary regression results for Equation Set 1

Equation 1a: ∆(mogas) = β1∆(Brent) + β2∆(regional inv)

Period 1: 2000-10 ∆(Brent) ∆(inv)1,2 Adj

β lags β lags R-sq

New York Harbor 0.023 0 -12.0 1 0.63

U.S. Gulf Coast 0.024 0 -15.6 2 0.60

Chicago 0.023 0 -15.9 2 0.43

Los Angeles 0.024 0 -36.9 2 0.44

Equation 1a: ∆(mogas) = β1∆(Brent) + β2∆(regional inv)

Period 2: 2011-14 ∆(Brent) ∆(inv)1,2 Adj

β lags β lags R-sq

New York Harbor 0.023 0 -27.2 2 0.59

U.S. Gulf Coast 0.024 0 -13.0 1 0.54

Chicago 0.021 0 -20.6 1 0.37

Los Angeles 0.028 0 -41.7 2 0.44

Equation 1b: ∆(mogas) = β1∆(WTI) + β2∆(regional inv)

Period 1: 2000-10 ∆(WTI)1 ∆(inv)1,2 Adj

β lags β lags R-sq

New York Harbor 0.021 0 -11.7 1 0.58

U.S. Gulf Coast 0.021 0 -14.1 2 0.55

Chicago 0.024 1 -16.3 2 0.39

Los Angeles 0.022 0 -38.2 2 0.41
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 25

Equation 1b: ∆(mogas) = β1∆(WTI) + β2∆(regional inv)

Period 2: 2011-14 ∆(WTI)1 ∆(inv)1,2 Adj

β lags β lags R-sq

New York Harbor 0.019 0 -20.7 1 0.42

U.S. Gulf Coast 0.020 0 -16.8 1 0.41

Chicago 0.015 0 -25.6 1 0.30

Los Angeles 0.027 1 -49.1 2 0.36 1

Note: Where lags have been included in the equation, the reported coefficients are the sums of the lagged 

and present period coefficients. 2

Note: All inventory coefficients are x106.

Comparing the results of Equations 1a and 1b (shown in Table 4) for both sub-time periods indicates 

that changes in Brent prices are more important than changes in WTI prices for all regions in explaining 

changes in gasoline price, as evidenced by higher R-squared values for Equation 1a for each respective 

gasoline spot price. Additionally, from Period 1 to Period 2 the R-squared values in Equation 1a 

decreased only slightly, between 0.00 and 0.06, showing the explanatory power of changes in Brent 

price stayed relatively unchanged. However, for WTI the R-squared values decreased between 0.05 and 

0.16 from Period 1 to Period 2, showing the explanatory power of changes in WTI price went down. The 

lower R-squared values for both crudes in Period 2 are likely the result of changes in the U.S. gasoline 

market in Period 2 that reflect increasing refinery runs and declining domestic demand, which have 

changed historical levels and variation of U.S. gasoline-crude differentials. However, the changing 

nature of the U.S. gasoline market is a topic for further study.

The coefficient for change in crude oil price is expected to be approximately 0.0238 (i.e., a $1 per barrel 

change in the price of crude oil leads to 2.38 cents per gallon change in the price of gasoline, or 1/42). 

This coefficient represents full price pass-through from crude oil prices to gasoline prices. Coefficients 

for Brent in Period 1 are consistent with those expectations. Those coefficients change somewhat in 

Period 2 for Chicago and Los Angeles, likely because of differences in the nature of U.S. gasoline 

markets. This is responsible for the lower R-squared values described above for those hubs. For WTI, 

the coefficients are largely in line with expectations for Period 1, but to a lesser extent than Brent. 

However, in Period 2 for WTI, the coefficients deviate from the expected 0.0238 level. In both periods, 

the p-values indicate that the coefficients of both changes in Brent and WTI prices are significant at the 

99% confidence level. While equations with Brent as the independent variable have higher R-squared 

values than those with WTI, week-to-week changes in WTI price are still very highly correlated with the 

week-to-week changes in Brent price, and thus with gasoline prices, even in Period 2. Additionally, the

current period and lagged inventory variables are generally significant at least at the 90% confidence 

level across the board. (See Table 6 and 7 for details.)

For both periods and sets of equations, the R-squared values (reported in Tables 4 and 5) for New York 

Harbor and the USGC are higher than for Chicago and Los Angeles. This is because the Chicago and Los 

Angeles markets have more volatile gasoline-crude oil margins, which reflect those markets’ relative 

isolation. Unlike New York Harbor and the USGC, they cannot directly pull supply from the actively 

traded Atlantic Basin, causing differentials in these markets to widen further in times of tight supply to 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 26

encourage resupply from other more distant markets. As a result, more of the variation in gasoline price 

in these markets is related to price changes in the gasoline market itself, rather than changes in the 

price of crude oil. The inventory variable is included to capture changes in gasoline market conditions, 

but it is imperfect in that function. This is particularly true in markets such as Los Angeles and Chicago. 

For example, New York Harbor gasoline inventories comprise a significant amount of total PADD 1B 

(Central Atlantic) gasoline inventories, likely better reflecting supply-demand conditions in that market. 

However, changes in total PADD 5 (West Coast) gasoline inventory levels could vary significantly from 

changes in inventories in Los Angeles, as PADD 5 has several other large markets, including San 

Francisco, Seattle, and Portland. Thus, PADD 5 inventories might not accurately reflect gasoline market 

conditions in Los Angeles. 

Table 5 shows regression results for Equations 2a and 2b, which include the Brent-WTI price differential 

as an independent variable. As discussed above, the results support the hypothesis that changes in the 

Brent price, rather than in the WTI price, explain changes in gasoline prices. 

Table 5. Summary regression results for Equation Set 2

Equation 2a: ∆(mogas) = β1∆(Brent) + β2∆(regional inv) + β3∆(Brent-WTI)

Period 1: 2000-10 ∆(Brent) ∆(inv)1,2 ∆(Brent-WTI) Adj

β lags β lags β

pvalue R-sq

New York Harbor 0.023 0 -11.8 1 -0.004 0.133 0.63

U.S. Gulf Coast 0.024 0 -15.2 2 -0.004 0.236 0.60

Chicago 0.023 0 -15.9 2 0.002 0.640 0.43

Los Angeles 0.024 0 -36.9 2 -0.004 0.410 0.44

Equation 2a: ∆(mogas) = β1∆(Brent) + β2∆(regional inv) + β3∆(Brent-WTI)

Period 2: 2011-14 ∆(Brent) ∆(inv)1,2 ∆(Brent-WTI) Adj

β lags β lags β

pvalue R-sq

New York Harbor 0.024 0 -27.2 2 0.000 0.955 0.59

U.S. Gulf Coast 0.025 0 -13.6 1 -0.005 0.124 0.55

Chicago 0.021 0 -20.6 1 -0.001 0.883 0.37

Los Angeles 0.030 0 -44.7 2 -0.008 0.096 0.45
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 27

Equation 2b: ∆(mogas) = β1∆(WTI) + β2∆(regional inv) + β3∆(Brent-WTI)

Period 1: 2000-10 ∆(WTI) ∆(inv)1,2 ∆(Brent-WTI) Adj

β lags β lags β

pvalue R-sq

New York Harbor 0.023 0 -12.0 1 0.017 0.000 0.63

U.S. Gulf Coast 0.024 0 -15.1 2 0.018 0.000 0.60

Chicago 0.023 0 -15.0 2 0.022 0.000 0.43

Los Angeles 0.024 0 -17.5 2 0.019 0.000 0.44

Equation 2b: ∆(mogas) = β1∆(WTI) + β2∆(regional inv) + β3∆(Brent-WTI)

Period 2: 2011-14 ∆(WTI) ∆(inv)1,2 ∆(Brent-WTI) Adj

β lags β Lags β

pvalue R-sq

New York Harbor 0.023 0 -14.6 1 0.020 0.000 0.54

U.S. Gulf Coast 0.023 0 -15.6 1 0.017 0.000 0.50

Chicago 0.018 0 -23.0 1 0.016 0.000 0.33

Los Angeles 0.028 0 -37.3 1 0.020 0.000 0.41 1

Note: Where lags have been included in the equations, the reported coefficients are sums of the lagged and 

present period coefficients.

2

Note: All inventory coefficients are x106.

For Equation 2a, the coefficients on the Brent and inventory variables are largely unchanged, for the 

different markets and time periods, from Equation 1a. Importantly, the addition of the change in the 

price differential between Brent and WTI does not add explanatory power to the Brent equations. The 

coefficients of the Brent-WTI spread in Equation 2a are insignificant with the exception of Los Angeles in 

Period 2, which is barely significant at the 90% level. In this case, the coefficient is likely picking up other 

trends in the data, as the Los Angeles gasoline market is not meaningfully connected to the WTI market. 

Additionally, the R-squared values for Equation 2a are generally unchanged from Equation 1a. This 

indicates that including the spread between Brent and WTI prices adds no explanatory power to the 

change in gasoline price when Brent is already an independent variable. However, the addition of the 

price spread between Brent and WTI prices does add explanatory power to the WTI equations (Equation

2b in Table 5). The coefficients of the Brent-WTI spread in Equation 2b are all significant at the 99%

confidence level. Furthermore, the R-squared values for Equation 2b all exceed those for Equation 1b. 

That Brent adds explanatory power to the WTI equations, but not vice-versa, is a particularly important 

result. This evidence supports the conclusion that the price of Brent, rather than the price of WTI, is the 

more important crude oil in determining U.S. gasoline prices. 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 28

Tables 6 and 7 present a detailed version of the regression results. 

Table 6. Detailed regression results for Equation Set 1

New York Harbor Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_ny ∆ mg_ny ∆ mg_ny ∆ mg_ny

equation 1a 1b 1a 1b

constant 0.000 0.001 0.000 0.002

∆ brent 0.023 *** 0.023 ***

∆ wti 0.021 *** 0.019 ***

∆ dsa_stock -4.3E-06 ** -4.6E-06 ** -6.5E-06 -1.0E-05 **

∆ dsa_stock(-1) -7.7E-06 *** -7.1E-06 *** -1.1E-05 *** -1.1E-05 **

∆ dsa_stock(-2) -1.0E-05 **

ECT(-1) -0.152 *** -0.126 *** -0.395 *** -0.144 ***

AR(1) 0.171 ** 0.136 ** 0.368 ** 0.184 *

no. obs. 571 571 178 178

adj. R2 0.627 0.576 0.593 0.417

S.E. regression 0.046 0.049 0.058 0.069

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.

Gulf Coast Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_gc ∆ mg_gc ∆ mg_gc ∆ mg_gc

equation 1a 1b 1a 1b

constant 0.001 0.001 -0.001 -0.000

∆ brent 0.024 *** 0.024 ***

∆ wti 0.021 *** 0.020 ***

∆ dsa_stock -6.5E-06 *** -5.3E-06 ** -6.4E-06 * -9.0E-06 **

∆ dsa_stock(-1) -4.2E-06 *** -3.4E-06 ** -6.6E-06 ** -7.8E-06 **

∆ dsa_stock(-2) -4.9E-06 *** -5.34E-06 ***

ECT(-1) -0.148 *** -0.137 *** -0.386 *** -0.182 ***

AR(1) 0.161 ** 0.141 ** 0.256 ** 0.223 *

no. obs. 570 570 178 178

adj. R2 0.602 0.553 0.543 0.414

S.E. regression 0.050 0.053 0.063 0.072

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 29

Chicago Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_chi ∆ mg_chi ∆ mg_chi ∆ mg_chi

equation 1a 1b 1a 1b

constant 0.000 0.000 0.001 0.003

∆ brent 0.023 *** 0.021 ***

∆ wti 0.0193 *** 0.015 ***

∆ wti(-1) 0.0044 ***

∆ dsa_stock -4.4E-06 * -4.2E-06 *

∆ dsa_stock(-1) -7.3E-06 *** -7.0E-06 ** -2.1E-05 *** -2.6E-05 ***

∆ dsa_stock(-2) -4.2E-06 * -5.2E-06 **

ECT(-1) -0.185 *** -0.1615 *** -0.572 *** -0.460 ***

AR(1) 0.143 ** 0.1041 * 0.359 *** 0.340 **

no. obs. 570 570 179 179

adj. R2 0.426 0.385 0.375 0.300

S.E. regression 0.072 0.074 0.107 0.113

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.

Los Angeles Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_la ∆ mg_la ∆ mg_la ∆ mg_la

equation 1a 1b 1a 1b

constant 0.000 0.000 0.000 0.001

∆ brent 0.024 *** 0.028 ***

∆ wti 0.022 *** 0.023 ***

∆ wti(-1) 0.004

∆ dsa_stock -9.8E-06 ** -9.7E-06 ** -1.3E-05 -1.2E-05

∆ dsa_stock(-1) -1.6E-05 *** -1.8E-05 *** -1.6E-05 -2.3E-05 **

∆ dsa_stock(-2) -1.1E-05 *** -1.1E-05 *** -1.3E-05 -1.4E-05

ECT(-1) -0.176 *** -0.174 *** -0.361 *** -0.254 ***

AR(1) 0.195 *** 0.203 *** 0.146 0.158

no. obs. 565 565 178 178

adj. R2 0.441 0.409 0.445 0.361

S.E. regression 0.075 0.077 0.095 0.102

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 30

Table 7. Detailed regression results for Equation Set 2

New York Harbor Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_ny ∆ mg_ny ∆ mg_ny ∆ mg_ny

equation 2a 2b 2a 2b

constant 0.000 0.000 0.002 0.001 ***

∆ brent 0.023 *** 0.024 ***

∆ wti 0.023 *** 0.023 ***

∆ dsa_stock -4.2E-06 ** -4.2E-06 ** 0.000 -7.4E-06 *

∆ dsa_stock(-1) -7.6E-06 *** -7.3E-06 *** -1.1E-05 *** -7.3E-06 *

∆ dsa_stock(-2) -1.0E-05 *

∆ brent-wti -0.004 0.017 *** -0.000 0.020 ***

ECT(-1) -0.147 *** -0.123 *** -0.393 *** -0.126 **

AR(1) 0.163 ** 0.154 ** 0.366 ** 0.190 *

no. obs. 571 571 178 178

adj. R2 0.630 0.625 0.590 0.542

S.E. regression 0.046 0.046 0.058 0.061

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.

Gulf Coast Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_gc ∆ mg_gc ∆ mg_gc ∆ mg_gc

equation 2a 2b 2a 2b

constant 0.001 0.001 -0.001 -0.001

∆ brent 0.024 *** 0.025 ***

∆ wti 0.024 *** 0.023 ***

∆ dsa_stock -6.3E-06 *** -6.4E-06 *** -6.8E-06 * -8.3E-06 **

∆ dsa_stock(-1) -4.0E-06 *** -3.9E-06 *** -6.9E-06 ** -7.3E-06 **

∆ dsa_stock(-2) -4.9E-06 *** -4.8E-06 ***

∆ brent-wti -0.004 0.018 *** -0.005 0.017 ***

ECT(-1) -0.144 *** -0.132 *** -0.382 *** -0.140 **

AR(1) 0.154 ** 0.149 ** 0.260 ** 0.149

no. obs. 570 570 178 178

adj. R2 0.604 0.602 0.547 0.333

S.E. regression 0.050 0.050 0.063 0.110

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 31

Chicago Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_chi ∆ mg_chi ∆ mg_chi ∆ mg_chi

equation 2a 2b 2a 2b

constant 0.000 0.000 0.001 0.003

∆ brent 0.023 *** 0.021 ***

∆ wti 0.023 *** 0.018 ***

∆ wti(-1) 0.003 **

∆ dsa_stock -4.5E-06 * -4.4E-06 *

∆ dsa_stock(-1) -7.3E-06 *** -7.0E-06 ** -2.1E-05 *** -2.3E-05 ***

∆ dsa_stock(-2) -4.1E-06 * 0.000

∆ brent-wti 0.002 0.022 *** -0.001 0.016 ***

ECT(-1) -0.189 *** -0.172 *** -0.570 *** -0.515 ***

AR(1) 0.152 ** 0.152 ** 0.357 *** 0.417 ***

no. obs. 570 570 179 179

adj. R2 0.426 0.432 0.371 0.333

S.E. regression 0.072 0.071 0.107 0.110

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.

Los Angeles Period 1 (Jan 2000 - Dec 2010) Period 2 (Jan 2011 - Jun 2014)

dependent var ∆ mg_la ∆ mg_la ∆ mg_la ∆ mg_la

equation 2a 2b 2a 2b

constant 0.000 0.000 0.000 0.000

∆ brent 0.024 *** 0.030 ***

∆ wti 0.024 *** 0.028 ***

∆ wti(-1)

∆ dsa_stock -9.8E-06 ** -1.0E-05 *** 0.000 -1.8E-05 *

∆ dsa_stock(-1) -1.7E-05 *** -1.7E-05 *** -1.8E-05 * -1.9E-05 *

∆ dsa_stock(-2) -1.1E-05 *** -1.1E-05 *** 0.000

∆ brent-wti -0.004 0.019 *** -0.008 * 0.020 ***

ECT(-1) -0.176 *** -0.164 *** -0.290 *** -0.170 ***

AR(1) 0.197 *** 0.191 ***

no. obs. 565 565 179 179

adj. R2 0.442 0.441 0.447 0.413

S.E. regression 0.075 0.075 0.095 0.098

Note: Significance level indicators are * at the 10%, ** at the 5%, and *** at the 1% level.
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 32

Dynamic linear modeling

Further evidence of the importance of Brent in determining U.S. gasoline prices is found by investigating 

parameter behavior over time using Dynamic Linear Modeling (DLM). Previous analysis found that 

market conditions changed due to major exogenous changes to the crude oil and/or gasoline 

distribution structure; this occurred on or about January 2011. This exercise determines whether or not 

the model coefficients significantly changed during the analysis period. A simplified model was 

employed using only current variables analyzing spot gasoline price as a function of crude oil price, 

PADD level gasoline inventory (adjusted for seasonal patterns), and the Brent/WTI spread. 

The models (for NYH spot gasoline price) were 

Brent:

mga_nyt= α + βt(Brentt) + δ t(P1B_Inv t) + ωt(BWspread t) + ε t

βt+1 = βt + ν t

ωt+1 = ωt + η t

WTI:

mga_nyt= α + βt(WTI t) + δ t(P1B_Inv t) + ωt(BWspread t) + ε t

βt+1 = βt + ν t

ωt+1 = ωt + η t

where 

• mga_nyt = NYH spot gasoline price at time t;

• (Brent) and (WTI) = Brent and WTI spot prices at time t;

• (P1B_Inv) = deviation of in-region gasoline inventories from 5-year average at time t;

• (BWspread) = crude oil spot price differential (Brent – WTI) at time t; and

• ε t, ν t, and η t are normally distributed random error series.

In this study, the behavior of inventories was not of interest and was not dynamically analyzed.

The results of the New York Harbor model estimation are shown as graphs of smoothed state estimates 

for the coefficient on crude oil (Figures 12 and 13) and for the coefficient on the Brent/WTI spread 

(Figure 14 for Brent and Figure 15 for WTI). The figures also show confidence bands of ± 2 RMSE, where 

RMSE is the root mean squared error.

As expected, the crude oil coefficients (SV1 state variable) for both models are very similar, and vary by 

a value of about 0.25 over the entire time period. However, what is noticeable is that the state 

estimated standard errors for the period beginning in January 2011 are much larger than for the earlier 

period. These results show that the relationship between crude oil price changes and gasoline price 

changes fluctuates over the analysis period (coefficient range is 0.19 to 0.34) and that the gasoline price 
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 33

change is similar for both crude oils. The latter result is not surprising, given that the correlation 

between the two crude oil prices is 0.98.

Figures 14 and 15 show the changing relationship (SV3 state variable) over time between gasoline prices 

and the WTI/Brent crude oil price spread. Both state estimates show a significant decrease during the 

analysis time period (from 0.015 to 0.003 for the Brent model and -0.010 to -0.020 for the WTI model). 

The estimated coefficient reached its largest value at the time that the crude oil market began its 

recovery after the dramatic collapse late in 2008. The important thing to note is that in the Brent model, 

the coefficient is statistically different from zero from January 2000 to the middle of 2006, and is 

insignificant thereafter. In contrast, the coefficient in the WTI model is statistically less than zero for the 

entire time period, with the coefficient becoming larger in absolute value over time. These results seem 

to imply that while Brent was the crude oil determining gasoline price in the recent period, both (or 

other) crudes impacted gasoline prices in the earlier period.

Figure 12 (appendix). Brent model, crude oil coefficient

.018

.020

.022

.024

.026

.028

.030

.032

.034

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

SV1 ± 2 RMSE

Smoothed SV1 State Estimate
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 34

Figure 13 (appendix). WTI model, crude oil coefficient

Figure 14 (appendix). PADD 1B (NYH): Brent model, spread coefficient

.018

.020

.022

.024

.026

.028

.030

.032

.034

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

-.025

-.020

-.015

-.010

-.005

.000

.005

.010

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

SV3 ± 2 RMSE

Smoothed SV3 State Estimate
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 35

Figure 15 (appendix). PADD 1B (NYH): WTI model, spread coefficient

The estimation results for the other regions show similar results (Figures 16-18). The shift of the crude 

oil coefficients (SV1 coefficient) around 2008 is similar to the coefficient shift in PADD 1B. Additionally, 

in PADD 2 (Midwest), the spread coefficient (SV3) is insignificant in the Brent model for most of the 

analysis period. PADD 3 (Gulf Coast) and PADD 5 (West Coast) differ from the other regions in that the 

spread coefficient (SV3) is not significantly different from zero for most of the first half of the sample 

period.

.000

.005

.010

.015

.020

.025

.030

.035

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

SV3 ± 2 RMSE

Smoothed SV3 State Estimate
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 36

Figure 16 (appendix). PADD 2: Chicago spot

.015

.020

.025

.030

.035

.040

.045

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

Brent Model

-.04

-.03

-.02

-.01

.00

.01

.02

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate

.015

.020

.025

.030

.035

.040

.045

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

W

TI model

-.01

.00

.01

.02

.03

.04

.05

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 37

Figure 17 (appendix). PADD 3: Gulf Coast spot

.020

.024

.028

.032

.036

.040

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

Brent Model

-.03

-.02

-.01

.00

.01

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate

.020

.024

.028

.032

.036

.040

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

WTI Model

.00

.01

.02

.03

.04

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate
October 2014

U.S. Energy Information Administration | What Drives U.S. Gasoline Prices? 38

Figure 18 (appendix). PADD 5: Los Angeles spot

.01

.02

.03

.04

.05

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

Brent Model

-.06

-.04

-.02

.00

.02

.04

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate

.016

.020

.024

.028

.032

.036

.040

.044

.048

2000 2002 2004 2006 2008 2010 2012 2014

SV1 ± 2 RMSE

Smoothed SV1 State Estimate

WTI Model

-.02

.00

.02

.04

.06

2000 2002 2004 2006 2008 2010 2012 2014

SV3 ± 2 RMSE

Smoothed SV3 State Estimate