Short-Term Energy Forecasting Petroleum 

Product Price Module

Independent Statistics & Analysis

www.eia.gov

U.S. Department of Energy

Washington, DC 20585

Last Updated 2020
U.S. Energy Information Administration | Short-Term Energy Forecasting Petroleum Product Price Module ii

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.

1. Introduction

The Short-Term Energy Outlook (STEO) Petroleum Product Prices Module forecasts the following data 

series:

• U.S. average wholesale prices of the following fuels:

o Motor gasoline

o Diesel fuel

o Jet fuel

o Residual fuel oil

• U.S. average retail prices of the following fuels:

o Regular-grade motor gasoline

o On-highway diesel fuel

o Heating oil

• Petroleum Administration for Defense District (PADD) level retail prices of regular-grade motor 

gasoline

• Refiners average imported cost of crude oil

• Refiners average acquisition cost of crude oil 

For each month of the STEO’s release, the Petroleum Products Prices Module uses linear models to 

forecast these prices over a 13-to-24 month time horizon. Every January, the STEO forecast is extended 

through December of the following year. 

The Petroleum Product Prices Module is organized as a series of linear regression equations (see Section 

B.1) and accounting identities used to derive each price forecast. In the linear regression models, 
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functions of the various prices are the dependent variables, and the independent variablies typically 

include items such as economic indicators, product inventories, regional demand shares, refinery 

activity, weather forecasts, and related fuel and commodity prices, among other variables. 

2. Data Sources

With the exception of the heating oil retail price, the monthly price and volume data used in the 

Petroleum Product Prices Module appear in three EIA publications: the Petroleum Supply Monthly

(PSM), Petroleum Marketing Monthly (PMM), and Weekly Petroleum Status Report (WPSR). Data in the 

PSM and PMM are published with a two-month lag. For example, the PMM released at the end of March 

will contain data through January. For any given data series, if WPSR data are available, STEO uses those 

data to fill in the intervening months between the last PMM data point and the present. If WPSR data 

are not available, STEO uses modeled results to fill in the intervening months.

Key data inputs include the following:

• Monthly average U.S. wholesale prices (refiner price for resale) of motor gasoline, number 2 diesel 

fuel, and number 2 fuel oil, and the refiner price to end users for kerosene-type jet fuel, from the 

PMM.

• PADD-level gasoline and diesel fuel retail prices (including taxes) and daily Brent crude oil spot 

prices, from the WPSR. Monthly average gasoline and diesel retail prices are calculated as simple 

averages of the weekly prices.

• The national average heating oil retail price, obtained from the Bureau of Labor Statistics’ monthly 

consumer price survey.

• Monthly volume data from surveys of primary suppliers such as refineries, pipelines, and bulk 

terminals, as well as regional monthly gasoline consumption and end-of-month inventories,

reported in the PSM. These data are used for weighting regional-level prices to arrive at the U.S. 

average price.

3. Linear Regression Models

3.1. Common Independent Variables

Prices for refined petroleum products are driven by multiple factors, including the price of crude oil (the 

main input cost for production), supply and demand conditions for a given fuel, seasonal factors, and 

the cost of transporting fuels from production hubs to demand centers. Some of these variables, e.g. 

crude oil prices, are observable and readily available for inclusion in our models, while other variables 

are more difficult to directly observe. EIA uses proxy variables to account for unobservable factors. For 

example, to approximate supply and demand conditions for a fuel, EIA uses the level of inventory in a 

given month compared to typical levels for that time of year.

To capture the primary effects driving fuel prices, many of the linear regression models described below 

include the following types of independent variables:

a) Monthly change in the Brent crude oil price (which drives wholesale product prices)
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b) Monthly change in the the wholesale product price (which drives retail product prices)

c) Difference between the current month’s consumption of a given petroleum product and average 

consumption of that product during a previous multi-year period

d) Difference between the current month’s inventories of a given petroleum product and average 

inventories of that product during a previous multi-year period

e) Monthly dummy variables, to capture seasonal effects

f) A trend variable

g) A one-month lagged dependent variable, to capture the effect of the previous month’s dependent 

variable on the current month’s dependent variable

The monthly price changes (a and b) reflect the passthrough of prices from one part of the supply chain 

to the next, which typically occurs with a short lag. Positive consumption differences from a monthly 

average (c) would be expected to put upward pressure on prices, while below-average consumption

would be expected to put downward pressure on prices. Similarly, positive inventory differences from a 

monthly average (d) would be expected to put downward pressure on prices, while below-average 

inventories often push prices up. Trend variables (f) and lagged dependent variables (g) capture price 

trends driven by evolving market conditions.

Also, rather than modeling an absolute price, for all of the series in the Petroleum Product Prices 

Module, EIA models a price margin, which is the difference between two prices (e.g., the gap between a 

wholesale and a retail price). After EIA forecasts a price margin, EIA adds the margin to an actual price

forecast to generate the forecast for the other price in the margin (e.g., to forecast a retail price, we add 

the retail price margin to the forecast wholesale price).

3.2 Motor Gasoline Prices

Gasoline is sold in two different formulations: conventional and reformulated. Each of these 

formulations is produced at refineries as a product called blendstock for oxygenate blending (BOB). BOB

can be blended with ethanol at different ratios to produce finished motor gasoline that is sold at retail 

gasoline stations. However, it is most common for both of the two formulations to be blended at a ratio 

of 90% BOB and 10% ethanol, a blend called E10. For both finished conventional and reformulated 

gasoline, there are also three grades of gasoline based on octane content: regular, mid-grade, and 

premium. 

The motor gasoline price model begins with a forecast of the U.S. average motor gasoline wholesale 

price. We use this U.S. average wholesale price as a proxy for the motor gasoline spot price in each 

region. We model retail regional motor gasoline prices, including taxes, as a function of the wholesale 

price and regional inventories. Retail prices of regular grade gasoline, all formulations, which cover over 

80 percent of all motor gasoline sold in the United States, are forecast for the five PADDs and the 

national average. A national average retail price for all grades of motor gasoline is also forecast. 

Gasoline price time series are long-memory series; that is, they contain unit roots (see Section B.2). 

Because of the unit roots, the price series are transformed to stationary series by calculating price 

spreads. This transformation allows the price series to be more meaningfully modeled using linear 

regression. The dependent variable in the motor gasoline wholesale price equation is the difference 
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between the average U.S. motor gasoline wholesale price and the Brent crude oil spot price (in cents per 

gallon). For regional retail prices, the dependent variable is the difference between the PADD regular 

gasoline retail price and the U.S. average motor gasoline wholesale price.

3.2.1. Motor gasoline wholesale prices

Because motor gasoline is a product of crude oil refining, EIA assumes the wholesale gasoline price is 

directly related to the marginal cost of crude oil. Because of the many different grades of crude oil, 

there are many measures of crude oil prices. STEO uses the Brent crude oil spot price in the regression 

model that forecasts the wholesale gasoline price. EIA research shows that motor gasoline wholesale 

prices are more strongly related to Brent crude oil prices than to West Texas Intermediate (WTI) crude 

oil prices (see EIA, What Drives U.S. Gasoline Prices?, October 30, 2014). EIA therefore uses the price 

difference between the average U.S. motor gasoline wholesale price and the average cost of Brent crude 

oil (converted from dollars per barrel to cents per gallon), referred to here as the wholesale gasoline 

margin, as the dependent variable for forecasting motor gasoline wholesale prices. The wholesale 

gasoline margin is estimated as a function of the following variables:

• The change in the spot price of Brent crude oil 

• Inventory deviation from the previous four-year average

• A trend variable starting in 2003

• Monthly dummy variables

• A lagged dependent variable.
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3.2.2. Motor gasoline retail prices including taxes

Figure 3.1. Regional Gasoline Retail Price Model

Regional motor gasoline retail prices for each PADD x are estimated as a function of the average U.S. 

motor gasoline wholesale price and regional gasoline inventories as illustrated in Figure 3.1. The model 

includes equations that estimate the regular-grade gasoline retail prices for the five PADDs (Figure 3.2). 

EIA uses the the retail margin, which is the difference between the average PADD-level motor gasoline 

retail price and the average U.S. gasoline wholesale price, as the dependent variable. In addition to 

capturing retail gasoline distribution costs and profits, the retail margins include all federal, state, and 

local taxes. For each PADD, the retail margin is estimated as a function of the following variables:

• The change in the gasoline wholesale price from the previous month

• The deviation in regional gasoline inventories from their prior four-year average, 

• A trend variable beginning in 2003

• Monthly dummy variables

• A lagged dependent variable
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Figure 3.2. Petroleum for Administration Defense Districts (PADDs)

3.2.3. Retail motor gasoline price, all grades

The regional motor gasoline retail prices are for regular-grade gasoline only, which makes up about 80%

of the total motor gasoline market. Premium and mid-grade gasoline make up the remainder. The 

difference between the average price for all grades of gasoline and regular-grade gasoline has been 

fairly consistent, although growing slightly, over the past several years. EIA estimates the difference 

between the U.S. average price for all grades of gasoline and the U.S. average price of regular-grade 

gasoline (the all-grade margin) as a function of the following variables:

• The U.S. average regular-grade retail gasoline price level

• A trend variable beginning in 2009

• Monthly dummy variables

• A lagged dependent variable.

3.2.4. Motor gasoline consumption shares

Estimated regional gasoline consumption volumes are needed to weight regional regular-grade gasoline 

retail prices in the calculation of monthly average U.S. prices as well as quarterly and annual average

regional and U.S. average prices. The regional consumption share is the total regional gasoline 

consumption divided by total U.S. gasoline consumption. EIA estimates the regional motor gasoline 

consumption shares from linear regression models with monthly dummy variables as the independent 

variables. Additional dummy variables may be included in individual models to control for observed 

outliers in the data series.

The error in the calculated average prices is expected to be much smaller than the error in the estimated 

consumption shares. For example, consider two regions, one with a price of $3.50 per gallon and the 

other with a price of $3.00 per gallon. Assume actual consumption is identical in the two regions but is
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measured with 20 percent error in opposite directions: region A’s measured consumption share is 60%

and region B’s is 40%, rather than 50% each. While the errors in the consumption shares are large, the 

error in the volume-weighted average price is much smaller: $3.30 per gallon when consumption is 

measured with error and $3.25 per gallon when consumption shares are correct (a 1.5% error).

3.3. Distillate Fuel Prices

Distillate fuel includes diesel fuels and fuel oils. Products known as No. 1, No. 2, and No. 4 diesel fuel are 

used in on-highway diesel engines, such as those in trucks and automobiles, as well as off-highway 

engines, such as those in railroad locomotives and agricultural machinery. Diesel fuel is primarily sold as 

ultra-low sulfur diesel (ULSD), which contains a maximum 15 parts per million (ppm) sulfur. ULSD 

accounted for about 96% of U.S. total distillate consumption in 2017. 

Products known as No. 1, No. 2, and No. 4 fuel oils are used primarily for space heating and electric 

power generation. Distillate fuel is also distinguished by sulfur levels. Fuel oil, commonly referred to as 

heating oil, has different sulfur specifications depending on the state in which the fuel is sold (Figure 

3.3). Although heating oil is used across the United States, its use is concentrated in the Northeast, 

where more than 80% of all U.S. heating oil was consumed in 2017. 

Figure 3.3. Heating oil sulfur specifications in Northeast States.

Note: 

Notes: Specifications change on July 1 of the years shown, with the exception of Maine's 15 ppm requirement, which changes 

on January 1, 2018.

* Philadelphia, Pennsylvania changed from 2,000 ppm to 15 ppm on July 1, 2015.

The petroleum product prices module includes average U.S. diesel fuel and heating oil wholesale prices (refiner prices for 

resale) and average U.S. diesel fuel and heating oil retail prices.
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3.3.1. Diesel fuel oil wholesale price

Because distillate fuel is a product of crude oil refining, EIA assumes the wholesale price of distillate fuel

is directly related to the marginal cost of crude oil. EIA selected the Brent crude oil spot price as the 

crude oil price that is most strongly related to distillate fuel wholesale prices.

The monthly price difference between the average U.S. wholesale diesel fuel price and the crude oil 

price (converted from dollars per barrel to cents per gallon), referred to as the wholesale diesel margin,

is estimated as a function of the following variables:

• The monthly change in the spot price of Brent crude oil 

• The difference between current-month distillate fuel consumption and the prior two-year average 

for the reference month

• The difference between beginning-of-month distillate fuel inventories and the prior four-year 

average inventories

• Monthly dummy variables

• A lagged dependent variable

3.3.2. Diesel fuel retail price including taxes

The retail margin, which is the difference between the U.S. average diesel fuel retail price and the diesel 

fuel wholesale price, captures retail diesel distribution costs and profits and includes all federal, state, 

and local taxes. It is estimated as a function of the following variables:

• The diesel fuel wholesale price change from the previous month

• A trend variable beginning in 2011

• Monthly dummy variables

• A lagged dependent variable 

3.3.3. Heating oil wholesale price

Because heating oil and diesel are very similar fuels, their prices are affected by many of the same 

drivers, with heating oil prices generally following diesel prices, except for the effects of some market 

dynamics unique to heating oil. EIA therefore models the price difference between the U.S. average 

heating oil wholesale price and the U.S. average diesel fuel wholesale price (the heating oil-diesel 

margin). In general, we expect the heating oil wholesale price to be lower than the diesel wholesale 

price, because of the more relaxed heating oil product specifications, such as sulfur level. However, 

heating oil-diesel margins can turn positive during very cold winter months, primarily in the Northeast,

where more than 80% of the households that use heating oil as their primary space-heating fuel are 

located.

The heating oil-diesel margin is estimated as a function of the following variables:

• The change in the diesel fuel wholesale price from the previous month

• The difference between beginning-of-month distillate fuel inventories and the prior four-year 

average inventories
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• Heating degree day (HDD) deviations from normal in the Northeast census region (New England and 

Middle Atlantic census divisions), weighted by the number of households in each division that use 

heating oil as their primary space-heating fuel 

• Monthly dummy variables

• A lagged dependent variable

3.3.4. Heating oil retail price

To estimate the U.S. average heating oil retail price, EIA models the difference between the retail and 

wholesale heating oil prices (the heating oil retail margin). In addition to capturing retail heating oil 

distribution costs and profits, this margin includes all federal, state, and local taxes. The heating oil retail 

margin is estimated as a function of the following variables:

• The change in the heating oil wholesale price from the previous month

• The difference between beginning-of-month distillate fuel inventories and the prior four-year 

average inventories

• U.S. Northeast HDD deviations from normal 

• Monthly dummny variables

• A lagged dependent variable

3.4. Other Petroleum Product Prices

3.4.1. Jet fuel refiner price to end users

Jet fuel and diesel fuel are produced at similar distillation ranges within a refinery, and refineries have 

significant abilities to adjust production towards one fuel or the other. Because jet fuel and diesel are 

very similar fuels, their prices are affected by many of the same drivers, with jet fuel prices generally 

following diesel prices, except for the effects of some market dynamics unique to jet fuel. EIA therefore 

models the price difference between the U.S. average jet fuel wholesale price and the U.S. average 

diesel fuel wholesale price (the jet fuel-diesel margin). The world real gross domestic product is included 

as an explanatory variable to capture world economic growth as a proxy for global air travel and jet fuel 

demand.

The jet fuel-diesel margin is estimated as a function of the following variables:

• The change in the diesel fuel wholesale price from the previous month

• World real gross domestic product

• Monthly dummy variables

• A lagged dependent variable

• Residual fuel refiner price to end users

3.4.2. Residual fuel oil refiner price to end users

Residual fuel oil is a general classification for the heavier oils, known as No. 5 and No. 6 fuel oils, that 

remain after the distillate fuel oils and lighter hydrocarbons are distilled away in refinery operations. It 
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conforms to ASTM Specifications D 396 and D 975and Federal Specification VV-F-815C. No. 5 fuel oil, a 

residual fuel oil of medium viscosity, is also known as Navy Special and is defined in Military 

Specification MIL-F-859E, including Amendment 2 (NATO SymbolF-770). It is used in steam-powered 

vessels in government service and inshore power plants. No. 6 fuel oil includes Bunker C fuel oil and is 

used for the production of electric power, space heating, vessel bunkering, and various industrial 

purposes.

EIA estimates the difference between the average U.S. residual fuel price to end users and the cost of 

crude oil to U.S. refiners (the residual fuel margin). EIA includes total U.S. HDD in the model, because 

residual fuel use in the electric power sector typically increases during times of very cold weather, when 

natural gas that would otherwise be used for power generation is diverted to residential and 

commercial space heating use. 

The residual fuel margin is estimated as a function of the following variables:

• The change in the cost of crude oil to U.S. refiners from the previous month

• U.S. average HDD

• A time trend beginning in 2003

• A time trend beginning in 2008

• Monthly dummy variables

• A lagged dependent variable