SS-Part-B-PM-10-26-2006

B. COLLECTING INFORMATION BY STATISTICAL METHODS
A.

“Refiners‘ Monthly Cost Report”: EIA-14

1.

Description of the Survey Plan

The target population for the EIA-14 survey is all refiners of crude oil. There were
approximately 206 refiners originally identified from the Oil and Gas Journal when the
survey begin in 1983. Of the 206 refiners on the original list, 67 are currently active and
filing Form EIA-14. The frame is kept current using information from other EIA surveys.
2.

Sampling Methodology and Estimation Procedures
a. Sampling. There is no sampling for the EIA-14 since the universe is small.
b. Estimation Procedures. As in all petroleum price surveys, a volume weighted
price is used. Total cost (price times volume) is divided by a corresponding total
volume to arrive at a volume weighted average cost.

3.

Maximizing Response Rates

To encourage maximum response to the EIA-14, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site. For nonresponse, a nonrespondent
listing is generated within five days of the reporting deadline. Nonrespondent firms are
telephoned and asked to submit data. If a firm still does not respond, a noncompliance
letter requesting submission by a specific date is sent. The average response rate for the
EIA-14 for reference months November 2005 thru March 2006 was 99.8.
4.

Tests of Procedures

Procedures for conducting the EIA-14 survey have been successfully employed for the
past 24 years and require no further study.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical aspects of this survey. The Project Manager for the EIA-14
survey is Elizabeth Scott who can be contacted at (202) 586-1258. The contractor
responsible for collection and processing of the survey data is:
ABACUS Technology Corporation
8601 Georgia Avenue, Suite 400
Silver Spring, MD 20910

PM 2006, OMB No. 1905-0174

-1-

B.

“Domestic Crude Oil First Purchase Report”: EIA-182

1.

Description of the Survey Plan

The target population for the EIA-182 survey is all firms that buy domestic crude oil at
the lease boundary, acquiring ownership of the crude in a first purchase transaction. The
list initially was compiled from the 1974 Federal Energy Administration (FEA) Oil and
Gas Survey of Producers and Operators. Collection of data from first purchasers began
in February 1976. By 1978, the frame consisted of 340 respondents. Of these, 198
purchased more than 150,000 barrels per year and together represented 99.9 percent of
the total reported volume. Following decontrol in January, 1981, many small firms went
out of business or were absorbed by larger companies. By January, 1986 the frame had
been reduced to 170 respondents. Over the years, adjustments to the frame have mostly
been deaths, with relatively few births. Currently, the EIA-182 frame list consists of 84
active firms.
2.

Sampling Methodology and Estimation Procedures
a. Sampling. There is no sampling performed for the EIA-182.
b. Estimation Procedures. Total cost (amount paid times volume purchased) is
divided by corresponding total volume to arrive at a national weighted average
price.

Subsequently, the data are sorted by crude stream within each State. These data are
aggregated across all companies reporting purchases from a given State. Weighted
average prices for crude oil are then derived for each producing State (plus the Outer
Continental Shelf regions, Alaska North Slope and Alaska Other).
Imputation procedures are used to account for missing data and outliers as follows:
Outliers - Imputation is performed when reported data fail standardized edit checks. The
data are imputed by obtaining the month-to-month percentage change for the item in
question for all respondents excluding the respondent in question and applying that
change to the respondent‘s prior reporting month‘s value. Imputation can be for both
volume and/or cost, and is noted in both the survey data files and on the forms.
Non-respondents – Imputation for non-respondents’ volumes is performed automatically,
each month, by one program in the First Purchase System. Program-imputed volumes
that are generated in report format, are used for intermediate crude oil production
estimation purposes only. The volumes are not used to generate published prices in the
PMM. Published prices are derived from either respondent or manually imputed data
only. The data are imputed in the same manner as data which failed the edit checks.
Respondents may make revisions to original data. These revisions are posted to the data
base. Most revisions are within 30 days of the original submissions. Hence, the data are
initially published as “Preliminary” data. The data for the previous month are revised, if

PM 2006, OMB No. 1905-0174

-2-

necessary, and published as “Final.” Revisions beyond the previous month are made if
resubmissions, corrections, or late filings significantly alter the former final price. These
revisions are included in the Petroleum Marketing Annual (PMA) and published in the
Petroleum Supply Monthly (PSM) concurrent with the publication of the PMA.
3.

Maximizing the Response Rate

To encourage maximum response to the EIA-182, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site. In addition, the form is mailed out
monthly with a business reply return envelope or mailing label included. Use of the
postage paid return envelope/mailing label increases survey response rates and lowers
overall survey costs. For nonresponse, a nonrespondent listing is generated within five
days of the reporting deadline. Nonrespondent firms are telephoned and requested to
submit data. If a firm still does not respond, a noncompliance letter is sent requesting
submission by a specific date. The response rate is currently 100%.
4.

Tests of Procedures

There has been no recent test of procedures for conducting the EIA-182 survey. Current
procedures have been successfully employed for the past three years.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, is responsible for the
statistical aspects of this survey. The Project Manager for the EIA-182 survey is David
Gatton who can be contacted at (202) 586-5995. The contractor responsible for
collection and processing of the survey data is:
ABACUS Technology Corporation
8601 Georgia Avenue, Suite 400
Silver Spring, MD 20910
C.

“Resellers’/Retailers’ Monthly Petroleum Product Sales Report”: EIA-782B

1.

Description of the Survey Plan

The EIA-782B survey has a target population of all resellers of motor gasoline, and
resellers and retailers of No. 2 distillate, residual fuel oil, and propane. The original EIA782B used a frame of distillate fuel oil dealers that consisted of respondents to the EIA402, “Fuel Oil Identification Survey,” a one-time survey implemented in 1979 and mailed
to a listing of 30,000 fuel oil related businesses. The frame was updated using data from
the EIA-9A, No. 2 Distillate Price Monitoring Report (the predecessor to the EIA-782B),
and the EIA-172, Sales of Fuel Oil and Kerosene.

PM 2006, OMB No. 1905-0174

-3-

The current EIA-782B survey, sample 15 initiated in 2004, used the EIA-863 (reference
year 2002), Petroleum Products Sales Identification Survey, as the sampling frame. The
EIA-863 survey was mailed to a listing of approximately 25,000 petroleum products
sellers. In addition, data from the EIA-821 for reference year 2002 were mapped to the
EIA-863 file because EIA-821 respondents were not required to file the EIA-863. Using
this frame file, and data from the previous years‘ EIA-782B and EIA-821 samples, a
national sample of motor gasoline, distillate fuel oil, and residual fuel oil resellers and
retailers was designed and selected. The original sample size was 2,067 companies. The
reporting sample decreases through time as businesses sell, merge and go out of business.
A company is required to report their sales in all states that they sell petroleum products.
If a company is reporting for several states on the frame, each state they report for is
treated as a separate company/state reporting unit for sampling purposes because sample
allocations are defined at the state level. The current stratification table indicating
population and initial sample sizes is available upon request.
2.

Sampling Methodology and Estimation Procedures

a.

Accuracy Criteria. The required level of accuracy for each of ten target variables
is defined by a volume coefficient of variation (CV) of 15 percent at the published
State level for No. 2 distillate, and 10 percent for motor gasoline, residual fuel oil,
and propane. A description of these target variables is contained in the sample
design description below. Studies on the relationship of volume CV to price CV
have shown that this is expected to produce price CV’s of less than one percent.
The reliability of current month estimates will vary from these goals due to the
deterioration of the frame over time and the changing distribution of prices and
volumes on a monthly basis.

b.

Sample Design. The EIA-782 sample uses Pareto sampling, a variant of Poisson
sampling (a form of Probability Proportional to Size sampling) that is appropriate
for use with permanent random numbers (PRNs). Pareto sampling assigns
probabilities of selection p that add up to n and assigns a random number r
between 0 and 1 to each unit. The n smallest values of (r-rp)/(p-rp) were selected.
The EIA-782 design also uses a technique called “collocation” as a form of
implicit stratification. Collocation is performed within a cell by applying a
monotonic transformation that insures that there will be exactly one number
within the interval [(k-1)/n, k/n] for each positive integer k less than or equal to k.
For the EIA-782 the number is assigned randomly within the interval.
PRNs are used to draw the sample where the relative position or the value of the
number determines whether the unit is sampled or not. The sampling scheme may
even be changed for a subsequent sample. This is done using the same set of
PRNs derived from the first sample and transforming it accordingly to draw the
second sample.
The probabilities, based on the proportion of the volumes each company sells for
each frame product, geographic area, and type of sale classification relative to the

PM 2006, OMB No. 1905-0174

-4-

cell total, were calculated using an algorithm developed by Chromy (1987) and
implemented in a SAS program by Laura Zayatz and Richard Sigman (1995). A
minimum probability .01, was set so as to cap all weights at 100. A fixed number
of companies were sampled, prior to any determination that some of the
companies sampled are out of scope. The number of companies was then allotted
to companies in scope, so that additional companies were selected in sequence
until the desired number is achieved.
The first 2,200 companies (inclusive of refiners that file the EIA-782A) in this
ordering were then selected for the sample. The noncertainty companies were then
post-stratified within each geographic/type-of-sale category by their volume. The
sample weights, the inverse of the probabilities, were multiplied by the sample
expectation adjustment which was the ratio of the sum of the probabilities of
selection for all frame units in the stratum to the actual sample size of the stratum.
The geographic areas were defined as (a) the 24 States in which No. 2 distillate
was a significant heating source and 50 States and the District of Columbia for
residual and motor gasoline, (b) the 25 States in which propane was a significant
energy source, or as (c) the PAD Districts for districts where not all State
estimates are provided. Four volume-of-sales strata (certainty, zero, low, and
high) were defined with volume boundaries differing by State, sales type, and
product. The design of the EIA-782B sample was based on ten target variables:
total retail motor gasoline, total wholesale motor gasoline, residential No. 2 fuel
oil, other retail No. 2 fuel oil, total wholesale No. 2 fuel oil, residential propane,
total other retail propane, wholesale propane, total retail residual fuel oil, and total
wholesale residual fuel oil. A sample size of 2,200 was expected to yield a median
level of accuracy for each target variable of volume coefficients of variation (CV)
of 15 percent for No. 2 distillate and 10 percent for the other products, determined
at the publishable State level (24 States for distillate, 25 for propane, 50 States
and the District of Columbia for motor gasoline and residual). Studies on the
relationship of volume CV to price CV have shown that this will produce price
CVs of less than 1 percent. The reliability of current month estimates will vary
from these goals due to the deterioration of the frame over time and the changing
distributions of price and volume.
Certainty units are re-evaluated each sample selection/rotation and noncertainty
units rotated at roughly 50%. For sample rotation, the random numbers used in
the previous cycles (in the sample at the time) were used as initial random
numbers in the rotation procedure. New companies (births) were given new
uniformly distributed random numbers. The entire set of random numbers was
collocated again by home state and Metropolitan Statistical Area (MSA) status;
the collocation simply fit the new cases uniformly among the old. A new set of
PRNs was defined using the joint formulas:
1) If x>kp then x’=x-kp
2) If x< kp then x’=x-kp+1

PM 2006, OMB No. 1905-0174

-5-

where x was the original PRN, p was the probability of selection of the unit and k
was a constant.
The actual draw of sample 15, the current sample, began with the random
numbers used to draw the previous sample 14, with new numbers assigned to any
companies that were not in the previous frame. The numbers were then
collocated within home state in order to spread out the random numbers through
cells reflecting the home states of the companies. Hence, two random numbers
were used in the process: one to determine the interval in which a company was
placed and the other to determine its position in the interval. This procedure yields
a geographically representative sample. Finally the rotation was applied to this
new set of numbers, using .37 as the k in the equations above, the same
coefficient that was used the previous cycle.
c.

Sample Rotation. To distribute respondent burden in an equitable manner, the
EIA-782B sample is rotated as described in the sample design. The current
sample was initiated in October 2004 and is referred to as sample 15.
Approximately fifty percent of the noncertainty units in the sample were replaced
by new ones randomly selected from the frame.

d.

Estimation Procedures. The EIA-782 used three stages of weighting. The initial
weights were simply the inverse of the probability of selection. The second stage
was the adjustment that capped the weights. An examination of the sum of the
inverse probabilities indicated that they could yield an overestimate of the number
of company clusters in the frame. In the past this number has exceeded the
number of companies in the frame. This seems to have been due to a large number
of small probability companies making it into the sample. These companies had a
probability of selection of .01, and hence a sampling weight of 100. During the
previous cycle reducing the maximum weight to 75 brought the estimated number
of companies much closer to the actual count. The third level of weights were
post-stratification weights. Each State and product was divided into up to four
noncertainty strata (zero, low, medium and high) plus a certainty stratum (frame
non-respondents will be combined with zeroes). These strata were collapsed to
insure at least three sampled companies in each stratum, and then the ratio of the
sum of the probabilities for the entire frame to the number of sampled companies
was multiplied by the weight of each company in the stratum. This had the effect
of increasing the weights when the sample size for the stratum was smaller than
expected and decreasing the weights when the sample size was bigger than
expected. This final sampling weight is multiplied by the ratio of the population
total to the sum of the weights for a specific product, so that the sum of these
adjusted weights equals the population total for the specific product.
Missing data (resulting from incomplete reporting, nonresponse, and values that
fail editing) are imputed by weighting together the previous month’s reported
value and the previous month’s predicted value to yield a predicted value (the
geometric average) for the current month for each company. The sum of the

PM 2006, OMB No. 1905-0174

-6-

weighted predicted values for nonrespondents in the current month is then
multiplied by a chain link multiplier (the ratio of the sum of the weighted,
reported values for respondents in the current month to the sum of the weighted,
predicted values for respondents in the current month).
Volume estimates are calculated as the sum of the companies’ volumes times the
sample weights divided by the sum of the companies’ weights. Price estimates are
calculated as the sum of the product of each company’s volume, price, and final
adjusted weight divided by the sum of each company’s volume times final
adjusted weight.
3.

Maximizing the Response Rate

To encourage maximum response to the EIA-782B, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site or the PC Electronic Data Reporting
Option (PEDRO) software. In addition, the form is mailed out monthly with a business
reply return envelope or mailing label included. Use of the postage paid return
envelope/mailing label increases survey response rates and lowers overall survey costs.
For nonresponse, a nonrespondent listing is generated within five days of the reporting
deadline. Nonrespondent firms are telephoned and requested to submit data. If a firm
still does not respond, a noncompliance letter is sent requesting submission by a specific
date. Additional noncompliance letters are sent as needed. The expected response rate
for resellers and retailers, based on a six month performance from November 2005 thru
March 2005 for the EIA-782B, is 91.0 percent.
4.

Tests of Procedures

Sample design procedures have been modified and updated as sample requirements have
changed. New sample rotations are overlapped for two reporting periods to smooth
transition of samples and survey respondents. Statistical procedures for
imputation/estimation have been in operation on the EIA-782 for 24 years. The
methodology has been updated, as the industry, and sample and data requirements have
changed. A more detailed description of procedures and methodology is available
electronically in the “Explanatory Notes” of the Petroleum Marketing Annual at
http://www.eia.doe.gov/pub/oil_gas/petroleum/data_publications/petroleum_marketing_a
nnual/current/pdf/enote.pdf
5.

Statistical Consultations

The respondent sample for the EIA-782B was designed and selected by:
Macro International, Inc.
11785 Beltsville Drive
Calverton, MD 20705

PM 2006, OMB No. 1905-0174

-7-

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, was
the EIA Senior Statistician and project manager for the sample design, selection,
initiation, as well as survey methodology. The Project Manager for the EIA-782 survey
is Tammy Heppner who can be contacted at (202) 586-4748. The contractor responsible
for collecting and processing the survey data currently under contract is:
ABACUS Technology Corporation
8601 Georgia Avenue, Suite 400
Silver Spring, MD 20910
D.

“Refiners’/Gas Plant Operators’ Monthly Petroleum Product Sales
Report”: EIA-782A, and “Monthly Report of Prime Supplier Sales
of Petroleum Products Sold for Local Consumption”: EIA-782C

1.

Description of the Survey Plan

The target population for the EIA-782A includes the universe of refiners and gas plant
operators. The original frame was derived from a consolidated list of refiners known to
have reported on several EIA surveys; and the frame of gas plant operators from the EIA64, Natural Gas Liquids Operations Report. The frame is kept current using information
from other EIA surveys as well as information from industry journals. The EIA-782A
frame currently contains 95 entities reporting monthly. The actual response rate is 99100 percent. The target population for the EIA-782C includes all suppliers who make the
first sale of any of the products listed on the EIA-782C, and deliver that product into a
State for consumption in that State. The product slate includes motor gasoline, No. 1
distillate, kerosene, fuel oil, diesel fuel, aviation gasoline, jet fuel, No. 4 fuel, residual
fuel oil, and propane. The original frame was derived from the respondent frame of the
former EIA-25, Prime Supplier’s Monthly Report. The current frame has been
supplemented with firms qualifying as prime suppliers identified from the EIA-863,
Petroleum Products Sales Identification Survey, the EIA-782B, and other available
sources. The EIA-782C frame is currently composed of 185 prime suppliers.
2.

Sampling Methodology and Estimation Procedures

a.

Sampling. The EIA-782A and EIA-782C are census surveys and no sampling
takes place.

b.

Estimation Procedures. For the EIA-782A the average price is calculated for each
product and marketing level. The price and volume data for each company are
multiplied and then aggregated across all companies to obtain a total revenue
figure. This revenue is then divided by corresponding total volume to arrive at a
volume weighted average price.
Because the EIA-782C is a census survey and only totals are published, the only
estimation procedures used are for summing across companies. Missing data for

PM 2006, OMB No. 1905-0174

-8-

the EIA-782A and EIA-782C are imputed using the same methodology as the
EIA-782B.
3.

Maximizing the Response Rate

The response rates for the EIA-782A and C are maximized in a similar manner as the
EIA-782B, previously described with the exception that the forms are not mailed out. To
minimize costs, the forms are not mailed out by EIA since respondents prefer alternate
modes of transmission. The response rates for both the EIA-782A and EIA-782C surveys
are 99-100 percent.
4.

Tests of Procedures

The procedures used for the EIA-782A and C have been successfully employed for the
past 24 years. Further testing and comparison of methodology is an ongoing project.
The methodology has been updated, as the industry and the data requirements have
changed. A complete history of procedures and methodology is available electronically
in the “Explanatory Notes” of the Petroleum Marketing Annual at:
http://www.eia.doe.gov/pub/oil_gas/petroleum/data_publications/petroleum_marketing_a
nnual/current/pdf/enote.pdf
5.

Statistical Consultations

Contractor and government personnel responsible for the EIA-782 survey series are listed
in the section describing the EIA-782B.
E.

“Annual Fuel Oil and Kerosene Sales Report”: EIA-821

1.

Description of the Survey Plan

The target population for the EIA-821 includes all companies that deliver or sell fuel oil
or kerosene to ultimate consumers (end-users). The survey’s scientifically drawn sample
was selected from the EIA-863 sampling frame, and supplemented by retailers/resellers
and importers of residual fuel oil who were not identified by the EIA-863 survey. The
EIA-863 (2002) survey collected State-level sales information for calendar year 2002,
including volumes of No. 2 distillate fuel oil, residual fuel oil, and motor gasoline sold to
end-users and resellers. Most companies that sell only kerosene or distillate fuel oil other
than No. 2 were not targeted by the EIA-863. Companies on the frame reporting only
kerosene, #1, or #4 fuel are eligible for sampling as a zero volume distillate/residual fuel
dealer. The sample was lasted selected for the 2003 reference year. The original sample
size was 4,041 companies, but the size has been reduced since selection due to sales,
mergers, and companies ceasing operation.

PM 2006, OMB No. 1905-0174

-9-

2.

Sampling Methodology and Estimation Procedures

a.

Accuracy Criteria. For the EIA-821, accuracy is defined and fixed in terms of
relative error, and cost is defined, but not fixed, as respondent and government
burden. The goal is to minimize burden, or sample size, while designing for a
fixed relative error, or coefficient of variation. Five variables, or product sales
categories, specify target coefficients of variation. These are:
-

Residential No. 2 distillate volume
Non-Residential No. 2 distillate volume
Wholesale No. 2 distillate volume
Retail residual fuel oil volume
Wholesale residual fuel oil volume

(“Retail” and “Wholesale” are considered synonymous with “For End Use” and
“For Resale” for ease of exposition). Coefficients of variation were targeted at 5
percent at the state and other aggregate levels. The sample design was based on
the volumetric target primarily because volumes from the EIA-821 are published.
b.

Certainty Strata. The following companies were declared certainties:
a) The company (or one of its subsidiaries) was a refiner
b) The company sold any EIA-821 products in at least five States
c) The company’s sum across states of the maximum of the percentages of each of
the three distillate products at the State level was five or more percent
d) The company reported over five percent of the total weighted volume in any
state for the specifically targeted product/end use categories (such as distillate
vessel bunkering, distillate electric utility use, etc).
e) The company reported residual fuel oil sales
The selection of these companies enhanced the efficiency of the sampling design,
reduced sampling error and assisted in data continuity from year to year. For the
2003 sample, 746 companies were designated as certainty.

c.

Volumetric Stratification. After frame out-of-scope firms, nonrespondents and
certainty elements were removed from consideration, the remaining companies in
a State were cross-stratified according to volume of residential No. 2 distillate and
the maximum of other retail and wholesale No. 2 distillate (i.e., a two dimensional
stratification.). Nonrespondents were sampled as a separate stratum.
For the EIA-821, the number of strata, as well as the cutoff points, were specific
to the product and the State. For each State and product there was a
nonrespondent stratum, a certainty stratum, and a zero volume stratum. The other
State/product stratifications varied from one to three strata, representing low to
high volume.

PM 2006, OMB No. 1905-0174

- 10 -

The Dalenius-Hodges procedure was used to define the boundaries for the strata.
This procedure derived by T. Dalenius and J. L. Hodges, Jr. (Minimum Variance
Stratification, Journal of the American Statistical Association, 54:88-l0l) was
implemented separately for each State.
In particular, using the data from the frame for each State and distillate product
the nonrespondents, zero volume respondents and the designated certainties were
removed and the Dalenius-Hodges procedure was used to define three stratum
boundaries for the product for each State. This was done dividing volumes by
100,000 and by 10,000. If the division by 100,000 resulted in an initial number of
categories that was too small, then the division by 10,000 was used. Fourteen
different stratifications were obtained for each end-use creating from one to four
noncertainty levels (possibly including zero). Residential distillate was crossed
with the maximum stratum of nonresidential retail distillate and resale distillate,
using the same conceptual stratification for nonresidential retail and resale
distillate. For example, if for nonresidential retail the low and zero levels were
combined and the high and medium were combined, then the same was done for
resale distillate.
d.

Sample Allocation. Totals and standard deviations were calculated for each
product and stratum. In order to account for the inexactitude of the values over
time, inflation factors were used. The factors used were 1.4, 1.2, and 1.0 for small,
medium and large volumes respectively (if only two nonzero strata were defined,
the inflation factors were 1.3 and 1.0, respectively). Neyman allocations were used
for each product, and the maximum allocation was assigned to the cell. Allocations
of 100% were used for the certainty stratum and half the sampling fraction was
assigned for the combined noncertainty respondent stratum and the nonrespondent
stratum when appropriate. A minimum of 3 respondents was selected from each
cell. The allocations were designed to obtain a target Coefficient of Variation of 5
percent.
A random variable was used to draw the sample. A company was selected if one of
its states was selected (company state unit, CSU). If a CSU was selected it is
referred to as part of the “basic” sample. CSU from the same company cluster not
selected are referred to as “volunteer”.
CSU weights were obtained dividing the population of the cell by the allocation. A
company weight was obtained analytically, since the samples for different States
were independently drawn. The formula used was : 1/W =1-(1-1/w1)x(1-1/w2)x
...(1-1/wk) where W is the company weight, and w1 to wk are the CSU weights.
Company weights were provided through this procedure, but for an individual
product the weights were adjusted at the stratum level so that the sum of the
weights of sampled companies will equal the population at the stratum level.

PM 2006, OMB No. 1905-0174

- 11 -

e.

Estimation Procedures. For obtaining total estimates of volume, the adjusted
probability estimator is used. This estimator, the sum of the weighted volumes, is
defined as follows:
^
V = Σh (ΣiWihVih), where:
^
V = total estimated volume,
Σh = summation over strata,
Σi = summation over units within stratum h,
Wih = weight attached to unit i in stratum h
(the reciprocal of the probability of selection, Pih, for that unit), and
Vih = volume reported or imputed for units i in stratum h.
Survey nonrespondent volumes are also imputed as the mean of their strata.
3.

Maximizing the Response Rate

To encourage maximum response to the EIA-821, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site. In addition, the form is mailed out
annually with a business reply envelope included. Use of the postage paid return
envelope increases survey response rates and lowers overall survey costs. For
nonresponse after due date, second request letters are mailed to all sample companies
who have not responded two weeks after the filing deadline. If no response is received to
the second request letter, telephone follow-up procedures are then used to solicit
responses. If the telephone follow-up procedures are not successful, then data are
imputed for nonrespondents. The response rate for the EIA-82l survey was 90.9 percent
for the reference year 2004. This level of response is expected to continue.
4.

Tests of Procedures

The procedures used for the EIA-82l survey have been successfully employed for the past
eight years. Minor changes are implemented as necessary to adjust to changes in the
industry. Further testing and analysis are part of an ongoing project.
5.

Statistical Consultations

The EIA-82l sample design and sample selection were performed under the guidance of
Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, Energy Information
Administration. Ms. Weir can be reached at (202) 586-l262. The Project Manager for
the EIA-821 survey is Daniel Walzer who can be contacted at (202) 586-3511.
PM 2006, OMB No. 1905-0174

- 12 -

The contractor responsible for collecting and processing the survey data is:
Science Applications International Corporation
1710 Goodridge Drive
McLean, VA 22102
F.

“Monthly Foreign Crude Oil Acquisition Report”: EIA-856

1.

Description of the Survey Plan

All companies that were reporting data on the ERA-51, “Transfer Pricing Report,” as of
June 1982, are required to prepare and submit an EIA-856 each month, regardless of the
total volumes of crude oil that were imported. In addition, all other companies acquiring
more than 500,000 barrels of foreign crude oil in the report month for importation into
the United States are required to submit an EIA-856 for that month. There are currently
39 companies reporting each month.
2.

Sampling Methodology and Estimation Procedures

a.

Sampling. There is no sampling for the EIA-856 because of the small population.

b.

Estimation Procedures. Data are aggregated for publication by calculating a
volume weighted average price.

3.

Maximizing Response Rates

To encourage maximum response to the EIA-856, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site. For nonresponse, a nonrespondent
listing is generated within five days of the reporting deadline. Nonrespondent firms are
telephoned and asked to submit data. If a firm still does not respond, a noncompliance
letter requesting submission by a specific date is sent. The average response rate for the
EIA-856 for reference months November 2005 thru March 2006 was 99.7 percent.
4.

Tests of Procedures

Procedures for conducting the EIA-856 survey have been successfully employed for the
past 24 years and require no further study.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical aspects of this survey. The Project Manager for the EIA856 survey is Elizabeth Scott who can be contacted at (202) 586-1258. The contractor
responsible for collecting and processing the survey data is:

PM 2006, OMB No. 1905-0174

- 13 -

ABACUS Technology Corporation
8601 Georgia Avenue, Suite 400
Silver Spring, MD 20910
G.

“Petroleum Products Sales Identification Survey”: EIA-863

1.

Description of the Survey Plan

The purpose of the EIA-863 is to construct an enumeration of the universe of resellers
and retailers of No. 2 distillate, propane, and residual fuel oil, and resellers of motor
gasoline. The form also identifies companies that sell other petroleum products such as
kerosene, No. 1 distillate, etc. The survey form collects information on annual sales of
the major products by State and by sales category. The EIA-863 survey frame was
initially developed from the match/merge of the predecessor survey EIA-764, the Dun &
Bradstreet Market Identifiers File, State energy office lists, and association mailing lists.
The frame is approximately 25,000 companies.
2.

Sampling Methodology and Estimation Procedures

a.

Sampling. The EIA-863 survey is a census survey. The respondent frame
resulting from this survey will be used for sampling purposes by petroleum
sample surveys.

b.

Estimation Procedures. The data received are edited using information from the
previous EIA-863 survey, information from other EIA surveys, and information
obtained from the States or industry organizations. Tabulations are processed for
validation purposes but no estimation or imputation is performed. Company-level
status and volume information is the end product.

3.

Maximizing the Response Rate

To encourage maximum response to the EIA-863, alternative reporting methods are
provided. Respondents are allowed to report by mail, fax, phone, or electronically
through the excel forms available on EIA’s web site. The survey form and instructions
are mailed out with a business reply return envelope or mailing label included. Use of
the postage paid return envelope/mailing label increases survey response rates and lowers
overall survey costs. For nonresponse after due date, second request letters are sent by
mail to all companies who have not responded by the filing deadline. If no response is
received to the second request letter, telephone follow-up procedures are then used to
solicit responses. For post office returns, a concerted effort is made to obtain address
corrections for mailing.

PM 2006, OMB No. 1905-0174

- 14 -

4.

Tests of Procedures

Procedures for conducting the EIA-863 (2006) survey will be similar to the procedures
used in the 2002 survey. The procedures used to conduct the quadrennial survey are
constantly reviewed for improvement.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical aspects of this survey and is the project manager. The
contractor and subcontractor responsible for collecting and processing the survey data
are:
Science Applications International Corporation
1710 Goodridge Drive
McLean, VA 22102
ORC MACRO
11785 Beltsville Drive
Calverton, MD 20705
H.

“Winter Heating Fuels Telephone Survey”: EIA-877

1.

Description of the Survey Plan

Approximately 1200 companies selected for the EIA-877 survey are sent an initial letter
explaining the survey. The selected companies are telephoned each week during the
heating season (October 1 through March 15) to collect data on No. 2 heating oil and
residential propane prices and stocks. If an emergency situation arises, the period of the
heating season will be expanded. Most of the companies are telephoned by the State
Energy Offices and the data are provided electronically to EIA for processing. The states
are responsible for most of the data collection activities and submission of the price data
to EIA. EIA aggregates the data and the results are published electronically in the Weekly
Petroleum Status Report and made available on Petroleum’s website through Petroleum
Navigator. Information on individual company or outlet sample weights or volumes in
the sample is not shared with the states
2. Sampling Methodology and Estimation Procedures
For the No. 2 heating oil data, the sampling frame was derived from the current EIA-863,
“Petroleum Product Sales Identification Survey” containing sales volume information by
selecting active companies that reported sales of residential No. 2 heating oil. A stratified
sample design on residential No. 2 heating oil sales volumes by State was used.
Certainty stratum for each state was defined as 5% or more of sales volume in the state
based on frame sales volumes.

PM 2006, OMB No. 1905-0174

- 15 -

The allocations were determined in two iterations. The first step involved a bootstrap on the
previous heating oil sample and reported data. From each stratum, in each bootstrapped
frame, a sample of the same size as the actual sample was drawn and an average price
estimate was obtained. A standard error was calculated using the root mean square of
deviations from the estimate yielded by the actual sample and divided by the mean to obtain
the Coefficient of Variation (CV). Allocations were derived by dividing the CV by .01 (the
target CV), the ratio was squared, and multiplied by the allocation of the previous 2001
sample. Maximum state level allocations were set to 35, and minimum allocations set to 15.
A Neyman allocation algorithm was used to allocate the noncertainty cases to each of the
three stratum, with a minimum of two per stratum. Because the EIA-863 volumes do not
reflect the exact volumes of the CSUs several years later, we multiplied the standard errors
of the non-certainty strata by inflation factors, to account for the likelihood that some
companies have grown and others have contracted. The inflation factors used were 1.7 for
the low stratum, 1.4 for the medium and 1.1 for the high (these factors were used in the EIA782 design for a number of years and were found adequate for that survey). The factors
reflect a differential likelihood that a CSU will drift out of a stratum or change its volume
considerably. The frame was sorted by State and stratum, and then sampled randomly
within each stratum, to obtain the stratified random sample. The original residential fuel oil
sample selected in 2004 contained 522 companies. Sample weights were calculated as the
inverse of the probability of selection (N/n). The expected price coefficient of variation
is one to two percent.
Unlike the heating oil sample, the propane sample used outlets as the primary selection unit.
Similarly, the active companies that reported sales of residential propane on the EIA-863
formed the sampling frame for the propane portion of the EIA-877 survey. A separate
sample design on residential propane sales volumes by state was used. A certainty
stratum was defined as companies with volumes of 5% or greater in the state based on
frame sales volumes. The certainty companies were mapped to a propane outlet level
file. The number of outlets for selection was determined by the multiple of five percent
that each certainty company accounted for in the frame volume. For example, a certainty
that represented 10% of the state’s volume required that two outlets were selected.
In parallel to heating oil, the allocations were conducted in two iterations. The first step was
a bootstrap on the previous residential propane sample. However, the bootstrap took into
account the fact that a certainty unit could have multiple outlets. From each stratum in each
bootstrapped frame, a sample of the same size as the actual sample was drawn and an
average price estimate was obtained. A standard error was calculated from the estimate
yielded by the actual sample. The standard error was divided by the mean to get the CV.
Allocations were derived by dividing the CV by .01 (the target CV), the ratio squared, and
multiplied by the allocation of the previous 2001 sample. Maximum state level allocations
were set to 30, and minimum allocations set to 15.
A Neyman allocation algorithm was used to allocate the noncertainty cases to each of two
stratum, with a minimum if two per stratum. Because the frame volumes did not reflect the
exact volumes of the companies several years later, inflation factors were applied to the

PM 2006, OMB No. 1905-0174

- 16 -

noncertainty strata standard errors to account for the likelihood that some companies have
grown and others have contracted. The inflation factors used were 1.4 for the low stratum
and 1.1 for the high based on the use of those factors successfully in the EIA-782 design.
The factors reflected a differential likelihood that a CSU would drift out of a stratum or
change its volume considerably.
For sample selection, noncertainty outlets were ordered by State and within stratum by zip
code. Using a random starting point, outlets were sampled systematically, that is, every kth
outlet was selected, where k is the inverse of the outlet-level stratum sampling fraction.
Sampling weights for noncertainties in each State were assigned by taking the inverse of the
probability of selection for that State and stratum, where the probability of selection for each
State equaled the total number of outlets selected for the State, divided by the total number
of outlets in the State. Volumes for sampled noncertainty outlets were calculated by
dividing the total company volume by the number of noncertainty outlets on the frame
representing the company. The original propane sample size as selected in 2004 was 643
outlets.
The name and address outlet list was constructed originally by extracting from the EIA863 survey companies known to sell propane augmented by a list of individual propane
outlets provided by industry associations, Dun and Bradstreet file of primary and
secondary retail propane dealers, and respondents to other EIA surveys collecting any
information on propane. This file has been maintained as births and deaths are reported
on EIA surveys, and through intermittent updates through electronic sources.
Volume weighted average prices are estimated each week for residential propane and
residential fuel oil by summing the product of each respondent’s reported price by the
frame volume and the sample weight and dividing the sum of the sample weighted
volumes in each state. All companies in the sample are contacted by telephone to obtain a
high response rate. Nonrespondent firms are telephoned up to three (3) times and
requested to submit data.
Tests of Procedures
4.
These procedures have been followed for a number of years and no significant problems
were encountered. The procedures used to conduct the survey are constantly reviewed
for improvement.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical design. The Project Manager for the EIA-877 survey is
Marianne Holly who can be contacted at (202) 586-4051. Each State Energy Office
participating in the grants program is responsible for collecting the data from the sample
provided by EIA for that particular state and submitting the data to EIA for aggregation.

PM 2006, OMB No. 1905-0174

- 17 -

I.

“Motor Gasoline Price Survey”: EIA-878

1.

Description of the Survey Plan

The gasoline outlets selected for the EIA-878 survey are first initiated by telephone and
confirmed to be in business. In-business outlets are informed of the purpose of the
mandatory survey and informed of the confidentiality and protection afforded their data.
Each week the individual outlets are called and asked to report the pump price, by grade,
of unleaded gasoline. The collection takes place using a computer assisted telephone
interview (CATI) with built in editing. Companies who prefer to report through the
headquarters on behalf of their selected outlets are allowed to do so. Companies
preferring to report by fax or email are also permitted to report by that method. Data
obtained through non-phone methods are entered into the CATI system and treated the
same as phone collected prices.
2.

Sampling Methodology and Estimation Procedures

The sample for the Motor Gasoline Price Survey was drawn from a frame of
approximately 115,000 retail gasoline outlets. The gasoline outlet frame was constructed
by combining information purchased from a private commercial source with information
contained on existing EIA petroleum product frames and surveys. Outlet names and zip
codes were obtained from a private commercial data source. Additional information was
obtained directly from companies selling retail gasoline to supplement information
deficient on the commercial list. The individual frame outlets were mapped to counties
using their zip codes. The outlets were then assigned to the published geographic areas as
defined by the EPA program area, or for conventional gasoline areas, as defined by the
Census Bureau’s Standard Metropolitan Statistical Areas (SMSA) using their county
assignment.
The gasoline outlet sample is an area sample comprised of both an augmentation to, and
rotation of the previous sample cycle of the gasoline survey, the EIA-878 in order to
insure continuity in the historical data series. The augmentation outlets were obtained by
first, sampling counties, and then, sampling the outlets from the gasoline outlet frame
within those counties within each sampling cell. Every county in the U.S. was assigned to
the corresponding sampling cell as defined. After the counties were assigned, the
standard deviations of gasoline prices for these sampling cells were estimated using the
prices from the previous sample of the gasoline survey. These deviations and the number
of stations from the Census Bureau’s County Business Patterns (CBP) were used to
determine the required number of outlets to be sampled. The statistical technique used
was the Chromy allocation algorithm, an iterative procedure to determine the number of
units required for each sampling cell. A Goodman-Kish PPS sampling method was used
to select counties ordering counties within states by number of stations. A constant
number of stations per county was assumed and the proper number of stations were
randomly selected for the outlet frame file within each selected county. Once this
augmentation portion of the sample was obtained, standard deviations were re-estimated,
combining the previous gasoline sample outlets and newly sampled outlets. The Chromy

PM 2006, OMB No. 1905-0174

- 18 -

algorithm was applied again to determine the revised sample cell requirements. The
previous sample’s outlets were then sub-sampled to insure a self-weighting sample within
each stratum, and allocations satisfied by sampling half from each of the self-weighting
sub-sample and the old sample.
To estimate average prices, sample weights were constructed based on the sampled
outlet’s number of pumps as a proxy for sales volume. These weights are applied each
week to the reported outlet gasoline prices to obtain averages for the specific
formulations, grades and geographic areas. Weights used in aggregating across grades,
formulations and geographic areas were derived using volume data from the EIA-782C
“Monthly Report of Prime Supplier Sales of Petroleum Products Sold for Local
Consumption”, and demographic data from the Bureau of the Census and Department of
Transportation on population, number of gasoline stations and number of vehicles.
The target coefficient of variation was set for .4 for the United States, .55 for PADDs and
U.S. formulations, .70 for sub-PADDS and the PADD formulations, .85 for cities and
states, and 1.0 for the remaining cells (e.g. state and sub-PADD formulations). The
sample size is 800 outlets. The survey is conducted every Monday (Tuesday on Federal
holidays), and more frequently during emergency situations and data are released on
EIA’s website:
http://www.eia.doe.gov/oil_gas/petroleum/data_publications/wrgp/mogas_home_page.html

by 5 p.m. each Monday (Tuesday on Federal holidays). Data are made available through
email notification to those customers who sign up for that service. The U.S., PADD, and
sub-PADD level regular gasoline average prices are made available on EIA’s prerecorded
telephone hotline at (202) 586-6966 and in the publication Weekly Petroleum Status
Report.
3.

Maximizing Response Rates

All companies in the sample are contacted through the computer assisted telephone
interview system. Companies who prefer to report through the headquarters on behalf of
their selected outlets are allowed to do so. Companies preferring to report by fax or
email are also permitted to report by that method once they have made arrangements with
EIA. Nonrespondent firms are telephoned up to three times. The average response rate
for 2006 through July was 98.2%
4.

Tests of Procedures

This survey began on August 15, 1990. Company cooperation has been outstanding, and
no significant problems have been encountered. The sample design and procedures used
to conduct the survey are constantly reviewed for improvement, and have been updated a
number of times to incorporate those improvements.

PM 2006, OMB No. 1905-0174

- 19 -

5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical design of this survey and is the project manager. The
contractor responsible for collection and processing of the survey data is:
ORC Macro
126 College Street, Suite 2A
Burlington, VT 05401
ORC Macro
11785 Beltsville Drive
Calverton, MD 20705
J.

“On-Highway Diesel Fuel Price Survey”: EIA-888

1.

Description of the Survey Plan

The EIA-888 survey collects the pump price of diesel fuel sold through gasoline stations
and truck stops. With this clearance, prices will be collected for two types of diesel, ultra
low sulfur and low sulfur in keeping with the industry’s implementation of new EPA
requirements during the period in which two types are sold. Companies selected for the
EIA-888 survey were sent an initial letter explaining the survey. Replacement
respondents are either faxed or mailed the letter at the time of initiation and informed of
the confidentiality and protection afforded their data. Each week the individual outlets
are called and asked to report the pump price, by type, of on-highway use diesel fuel.
The collection takes place using a computer assisted telephone interview (CATI) with
built in editing. Companies who prefer to report through the headquarters on behalf of
their selected outlets are allowed to do so. Companies preferring to report by fax or
email are also permitted to report by that method. Data obtained through non-phone
methods are entered into the CATI system and treated the same as phone collected prices.
2.

Sampling Methodology and Estimation Procedures

The sample for the survey was designed to yield price estimates at the Petroleum
Administration Defense District (PADD), sub-PADD, national level and for the State of
California. The sample size is 350 outlets. A standard error of one cent was targeted for
PADDS 1, 2 and 3, and one and a half cents of PADDS 4, 5, sub-PADDs 1A, 1B, 1C,
and the State of California.
To determine the sample allocations across regions, average standard errors across
reporting periods for the previous year of weekly diesel fuel survey prices were
calculated for each of the cells. An average sample size was first determined using these
standard errors. In addition, a second allocation based on proportional representation
within the next larger cell (i.e., more aggregated level cell that the original cell would

PM 2006, OMB No. 1905-0174

- 20 -

contribute to) was also obtained. The maximum of these two allocations for each cell
was then designated as the cell allocation.
The sample design used a two-phase two stage design. The first phase used the EIA-782
B sample from two rotations, samples 10 and 11. The second sampling phase had two
stages, selecting first the company and then the actual outlet. The first stage of the
second phase of the sample design used annual state sales volumes for two sample cycles
from the EIA-782A and EIA-782B surveys divided by the unit’s probability of selection
in the monthly survey as a measure of size for Probability Proportionate to Size sampling.
These size measures from the two cycles were normalized by assigning 1/2 of the
allocation necessary to achieve the target errors in the cell to each cycle and multiplying
the allocation by the proportion of the total weighted volume in the cell for the 12 month
time period of data for the company state unit (CSU). This allocation procedure yielded a
targeted second phase size of 350 outlets for the diesel fuel survey.
Units were selected for the second phase of the sample using probability proportional to
size. The frame CSUs were sorted by state and randomly ordered within each state. The
normalized size measures were then used to define sampling intervals of 1.0. Using the
random order, cumulative size measures were determined where a CSU’s cumulative size
was the sum of the sizes of all CSUs preceding it and including it. A random number
between 0 and 1 was chosen as a seed, and assigned to the first CSU in PADD 1A. The
first CSU whose cumulative size exceeded the seed was sampled and 1.0 was added to
the seed. If the CSU’s cumulative size measure still exceeded the seed plus 1, the CSU
was sampled again and 1 was again added. The sampling continued in this manner
selecting the next CSU whose size measure exceeded the count plus seed, until the
desired outlet sample size was obtained. The second stage of the second phase took place
with the initiation of the sampled companies who were contacted and asked to provide
outlet telephone numbers and addresses for the number of outlets in each state that the
company sampled. If the CSU was sampled more times than the company had outlets in
that state, an outlet was counted more than once.
Since allocations were derived at the cell level, cell averages were just simple averages of
the CSU prices (the weights from the first and second phases cancel). The U.S. average
was a weighted average of the cell/PADD averages where the weights were derived by
taking the inverse of the probability proportional to the PADD weighted volumes.
The design resulted in 2207 company state units in the first phase, 282 company state
units in the second phase first stage, and 350 outlets in the second state.
3.

Maximizing Response Rates

All companies in the sample are contacted through the computer assisted telephone
interview system. Companies who prefer to report through the headquarters on behalf of
their selected outlets are allowed to do so. Companies preferring to report by fax or
email are also permitted to report by that method once they have made arrangements with

PM 2006, OMB No. 1905-0174

- 21 -

EIA. Nonrespondent firms are telephoned up to three times. The average response rate
for 2006 through July was 98.9%.
4.

Tests of Procedures

This survey began on February 14, 1994. Company cooperation has been outstanding,
and no significant problems have been encountered. The procedures used to conduct the
survey are constantly reviewed for improvement.
5.

Statistical Consultations

Ms. Paula Weir of the Petroleum Division, Office of Oil and Gas, (202) 586-1262, is
responsible for the statistical design of this survey and is project manager. The
contractor responsible for collection and processing of the survey data is:
ORC Macro
126 College Street, Suite 2A
Burlington, VT 05401
ORC Macro
11785 Beltsville Drive
Calverton, MD 20705

PM 2006, OMB No. 1905-0174

- 22 -