Summary of the Fall Meeting of
the
American Statistical Association
(ASA)
Committee on Energy
Statistics
October 24-25, 2002
.................with the Energy Information
Administration
1. Update on the Commercial Buildings
Energy Consumption Survey (CBECS), by Dwight French, Office of Energy
Markets and End Use, EIA
At the
Spring, 2002 Committee meeting Dwight French gave a presentation on three major
methodological issues being studied in the post-2000 redesign of EIA’s
Commercial Buildings Energy Consumption Survey (CBECS):
A. Whether population or a commercial
measure should be used as the measure of size for selecting first stage area
sampling units rather than using population;
B. Whether the building should continue to
be the sole unit of data collection, or whether a hybrid
facility/building/tenant approach should be used; and
C. Whether or not a national building list
available from the Insurance Services Office (ISO) should be used as the basic
list frame to supplement the CBECS area sample.
The
Committee provided quite a bit of comment and suggestions regarding these 3
issues at the Spring 2002 meeting.
This
update to the Committee neither sought nor received further
advice.
2. Update on the Completion of EIA’s
System for the Analysis of Global Energy Markets (SAGE), by John Conti,
Office of Integrated Analysis and Forecasting, EIA
Following
a demonstration of the System for Analyzing Global Energy (SAGE) at the fall,
2001 meeting, the ASA Committee was briefed further on the SAGE model in Spring
2002. At that time, the Committee
was told that a proof of concept, prototypes for 15 regions of the world, a
common naming convention, and a friendly user interface and report writer had
been developed. The Committee
recommended that a probabilistic approach to avoid knife-edge decisions be
adapted, that demand price elasticities be directly estimated, and that non-CO2
emissions from energy and non-energy sectors be included in
SAGE.
Since the
spring, EIA has researched these ideas, and has developed and tested a
market-sharing algorithm that will be presented. It has modified its regional templates
so that elasticities are easily input, transparent, and easily inspected across
regions of the model. EIA has
also
evaluated
the non-CO2 gases and has incorporated methane and will incorporate nitrogen
dioxides. Incorporation of other
gases (sulfur dioxides and mercury) will require further research because
meaningful estimates will require greater detail for coal types and
post-combustion equipment modeling than currently planned for
SAGE.
Most of
the effort since the Spring 2002 meeting has involved developing the upstream
and conversion sectors of the model, collecting and implementing better data,
developing new software to streamline the model execution and review process,
and verifying model results. An
independent team of experts reviewed the model in September
2002.
This
update to the Committee neither sought nor received further
advice.
3. Information Quality Guidelines
Completed. What’s
Next? Jay Casselberry,
Statistics and Methods Group, EIA
EIA has
completed a project to establish Information Quality Guidelines. In addition to establishing the
Guidelines, EIA updated its standards to support EIA’s quality efforts in data,
analysis, and forecasting. These
efforts were discussed with the Committee in the Fall 2001 and Spring 2002
meetings.
With the
Guidelines and standards in place, EIA will focus additional resources on
ensuring the quality of disseminated information and has upcoming quality
projects that
include:
(1)
Developing an EIA-wide survey managers’ quality process to include
self-assessments, selecting annual targets for improvement, and monitoring
progress toward them;
(2)
Auditing EIA data systems (first systems audited will be coal, standard
energy processing system (STEPS) used by the Office of Oil and Gas, and electric
power);
(3)
Assessing EIA model documentation;
(4)
Evaluating the status of documentation and back-up computer systems
necessary to assure that EIA could operate in the event of an emergency;
and
(5)
Collecting core performance measures.
EIA
sought Committee advice in three areas:
(1) Where
should EIA focus its quality resources?
(2) What
efforts would be expected to yield higher benefits relative to
costs?
(3) What
suggestions do the Committee have for the projects mentioned.
ASA Committee
Advice
Recommendations
for the projects (performance measures, self-assessments, etc) are being
considered as the projects are developed.
The committee’s suggestion
to use findings from data quality measures and audits to direct self-assessments
is an excellent idea. The
self-assessment process should provide EIA with an opportunity to address the
committee’s suggestions for more standardized operating procedures, especially
within program offices.
EIA
Response
EIA
plans to proceed with the sell-assessment project, currently under development.
4. Natural Gas Data Program Updates –
Covering the Weekly Natural Gas Storage Survey and Changes in the Natural Gas
Data Collection Program, Elizabeth Campbell, William Trapmann and Sylvia
Norris
EIA is
in the midst of changes to improve the scope and quality of the natural gas data
program. The presentation began with an update on implementation of the new
weekly natural gas storage survey, including results of a recent public comment
period and analyses relating to data revisions. Next was an overview of efforts to
improve the scope and quality of natural gas data in several areas, including
production data, extraction loss, liquefied natural gas operations, and
consumption volumes and prices.
Some of these efforts were part of the Fall 2002 forms clearance project,
while others were being analyzed to resolve future approach and requirements. As
an example of the work in progress, the presentation featured a summary of the
objectives and implementation schedule for the redesigned annual natural gas
supply and disposition survey.
ASA Committee
Advice
The
Committee advice (from Dr. Phipps) was that the form and instructions for the
EIA-912 be integrated, meaning that more items from the instructions be included
on the form.
EIA
Response
EIA
has added a number of definitions to the EIA-912 form.
5. Using Data from Combined Heat and
Power Plants to Estimate Natural Gas Industrial Prices, by Ruey-Pyng Lu,
Statistics and Methods Group, EIA
The
Energy Information Administration (EIA) collects and publishes data on prices
and volumes of natural gas delivered to customers in five sectors (residential,
commercial, industrial, vehicle fuel, and electric utilities). EIA has been
obtaining the data by surveying local utilities and pipeline companies. Since
industrial customers bought more natural gas from marketers or suppliers than
their local utilities, EIA’s natural gas prices for the industrial sector
represent only about 18% of the gas consumed in that
sector.
In 2000
SMG contracted with the Census Bureau to conduct a feasibility study for
surveying natural gas customers in the manufacturing sector (based on a frame
maintained by the Census Bureau). The feasibility study demonstrated that the
required information could be collected. However, the estimated cost exceeded
EIA’s budget. EIA is studying alternatives to estimate natural gas industrial
price.
Many
industrial facilities that consume natural gas use it to generate electricity
and now report on the EIA-423 (Monthly Report of Cost and Quality of Fuels for
Electric Plants). The EIA-423 surveys all facilities with a nameplate capacity
of 50 megawatts or greater and collects information about cost and quality of
all fuels used to generate electricity. It is hoped that by matching the natural
gas consumers in the EIA-423 with the natural gas customers in the EIA-176
(Annual Report of Natural and Supplemental Gas Supply and Disposition), a model
can be developed to estimate the price of the natural gas used in the industrial
sector. This session will present the work done to date and solicit the
committee’s advice.
ASA Committee
Advice
1.
Determine a relationship between the price for the cogeneration part of the
natural gas industry and non-cogeneration. Explore it using MECS; it carries
this kind of information. If you have some kind of common covariates between the
423 and the MECS for price, then you may be able to use that to predict or to
estimate the relationship.
2. From
MECS and from EIA-423, plot facility size by price and plot volume by price to
see if a model leaps out. It may also be useful to segment the industrial sector
by size. The large ones may follow the pattern for utilities.
EIA
Response
1. Plot
industrial natural gas volume by price and the facility size by price using
EIA-423 monthly data, at the state, census division, or census region
level.
2. Check
the plots segmented by NAICS code (22 or not) (industrial/commercial) to see if
a model leaps out. If they exist, match the industrial natural gas volume with
857 or 176 volumes and work on the discrepancy.
3. Look
at all characteristics of the surveys: MECS, EIA-857 and EIA-176, EIA-423 and
FERC 423.
4.
Request the Census Bureau to prepare plots of Natural gas volume by price for
power cogenerators and power generators for purpose of comparing with EIA-423
data to verify the model. We may request similar plots of the facility size by
price.
6. Managing Risk in Energy Markets,
by Douglas R. Hale, Statistics and Methods Group, EIA
In
early January 2001 the Enron Company’s
stock was selling for as much as $81.39 per share. Enron seemed the model of a
successful, innovative energy company. In less than 16 years it had grown from
the merger of two pipeline companies into “one
of the world’s
largest energy, commodities and services companies”.
It reported revenues of $101 billion in 2000 and had an interest in 30,000 miles
of gas pipeline and in electricity generating facilities around the
world.
By
December 2001 the stock was worthless and the company was in bankruptcy. Many of
Enron’s
20,000 employees lost most of the value of their 401-K retirement plan because
they had invested almost exclusively in Enron Stock. Top Enron executives sold
about a billion dollars worth of stock before its value tumbled. As the company
struggled through the late summer and fall, newspapers were full of stories
about accounting rules, special purpose entities, synthetic loans and
derivatives.
Derivatives
are financial instruments that Enron and others used in apparent natural gas and
electricity sales to acquire debt and overstate earnings. Derivatives have also
been used legitimately in other industries to manage business risks. In view of
Enron’s
prominent role in the U.S. energy industry and its importance as an energy
trader, the company’s
collapse has raised concerns on the part of energy analysts about the potential
damage to domestic energy markets and, in particular plans for the deregulation
of retail electricity markets in several states.
In
February, 2002 the Secretary of Energy directed the Energy Information
Administration to report on the nature of derivatives in the petroleum, natural
gas and electricity industries. EIA was established by Congress to provide the
Federal Government with unbiased, professional analyses of energy issues.
Federal law prohibits EIA from advocating policy. Specifically the Secretary
directed the EIA report to include:
(1) A description of energy risk management
tools;
(2) A description of exchanges and
mechanisms for trading energy contracts;
(3) Exploration of the varied uses of energy
risk management tools;
(4) Discussion of the impediments to the
development of energy risk management tools;
(5) Analysis of energy price volatility
relative to other commodities;
(6) Review of the current regulatory
structure for energy derivatives markets; and
(7) A survey of the literature on energy
derivatives and trading.
Although
the Enron debacle was the impetus for this study, this report is not about
Enron. The reasons for its failure are under active investigation elsewhere.
This report is concerned with how derivatives and their uses-both legitimate and
inappropriate-in energy applications. It also discusses what might be done to
strengthen the environment for their beneficial uses. The study was subsequently released in
December, 2002.
This
briefing to the Committee neither sought nor received further
advice.
7. Methods for Estimating Weekly State
Level Coal Production, Richard
Bonskowski, Office of Coal, Nuclear, Electric and Alternate Fuels,
EIA
The Coal
Team, Office of Coal, Nuclear, Electric and Alternate Fuels (CNEAF), EIA, is
redesigning the model used to estimate State-level U.S. coal production on a
weekly basis. Previously, CNEAF
used a totally top-down model based upon shares and factors, developed as
averages from historical data, some of which pre-dated the forecast period by
several years. In its redesigned
model, CNEAF has proposed and is using statistical autoregressive methods to
estimate the parameters in two equations:
(1) National coal production as a function
of railcar loadings of coal, heating degree days, and cooling degree days,
and
(2) Share of each State in national coal
production as a function of lagged share, heating degree days, and cooling
degree days
These
equations are used to forecast coal production in all States except
Wyoming. Values for the independent
or explanatory variables—railcar loadings, heating degree days, cooling degree
days, and lagged shares—are available for the most current week. The values are plugged into the
equations to estimates State-level weekly coal
production.
For
Wyoming, real-time data on the number of rail cars loaded with coal in Wyoming
are used to estimate coal production in Wyoming. The real-time coal loading data significantly improves the accuracy of
the Wyoming estimate in the new model compared with both the old and redesigned
models. Because Wyoming coal
production represents about 32% of national coal production, this outcome
represents a significant improvement in forecast
precision.
Data for
fitting the model includes coal production at the State-level starting in the
1st quarter 1990 up to the current date, as obtained from surveys run by EIA
through 1997 and by the Mine Safety Health Administration thereafter. The statistical model is fit on data
through 1999, quarter 3. Model
forecasts, for the 8 quarter period:
2000 quarter 1 through 2001 quarter 4, are compared with actual
State-level coal production from national surveys. Forecasts from the old model also are
compared with actual surveyed State-level production for the 8-quarter
period: 2000 quarter 1 through 2001
quarter 4. Improvements in
statistical forecast precision are measured as the average reduction in
State-level absolute error (weighted by State-level quarterly coal production in
tons), comparing results from the new model with the old
model.
EIA
Questions for the ASA Committee
EIA hopes
the ASA Committee members can help to identify ways in which the model could be
improved in order to obtain even greater forecast precision. CNEAF has tried using a bottoms-up
method (similar to the new Wyoming method) with Western coal producing States,
expecting that there could be improvements similar to those shown by the Wyoming
forecast. Rail car loading data can
be disaggregated to the State level in the western U.S. but not in the eastern
U.S. Thus far, however, the
forecasts from the new statistical equations have been more precise.
Also,
CNEAF is exploring the role that “periodic-event” information should play in
model intervention to improve forecast accuracy. For example, industry sources reported
an anomalous build-up of coal stocks in the supply chain in 2002, leading
certain major coal producing companies to temporarily shut down some of their
mines. CNEAF is looking to the
committee to possibly advise it on systematic ways in which this kind of
information can be used to temper the statistical forecasts and improve forecast
accuracy.
ASA Committee Advice:
1. The paper would benefit from a clear
statement about which of two models discussed in the paper was the actual model
used to estimate national coal production.
2. The authors should identify clearly the
statistical methods used for the national coal production model: Are the methods
straight regression, auto-regressive, other?
3. The paper should have more discussion of
the method used in estimating/determining the State shares of national weekly
coal production.
4. The Committee suggested that the
statistical model be formulated as a simultaneous multi variate model, which
accounts for all state shares and restricts their sum to be
1.
5. Several committee members suggested that
the data be broken into regions and the statistical models be fitted using the
regional data, certainly east of the Mississippi and west of the Mississippi.
Other regions if feasible.
6. Committee members suggested that Wyoming
be analyzed as one of the states in the state share models. Then this
statistical model should be used to estimate Wyoming production. This alternate
estimate should be compared with the Wyoming-specific railroad loading model
estimate. Such an exercise would clarify whether or not the existing bottom-up
process for Wyoming is a better estimator than the alternate statistical model.
7. Committee members recommended that spot
coal price and other energy prices be added as variables to explain variation in
coal production
8. The Committee questioned whether there
were important constraints such as the availability of railroad cars, which need
to be accounted for in the estimating model.
9. Committee members pointed out that
railroad car loadings are a direct measure of coal shipments but only a proxy
indicator of coal production. A related point was the observation that additions
to and subtractions from coal stockpiles mask the relationship between
production and shipment.
EIA
Response:
1. Additional statistical analysis will
test spot coal prices and other energy prices as variables to explain coal
production (Committee suggestion #6)
2. The data will be disaggregated into east
of Miss and west of Miss and the models fitted using that regional data, per
Committee suggestion 4.
3. Wyoming will be analyzed using state
share and the railroad-based methods so that comparisons of the two methods can
be made, per Committee suggestion 5
4. The paper will be revised is line with
Committee suggestions at 1, 2, 3, and 8 above
5. Also, the revised paper will incorporate
result from additional statistical analysis, as recommended by the
Committee
6. The
coal team will post a final paper with these changes onto the coal web
page.
8. Estimating Monthly Data: Creating a Monthly Estimated Data Series
for Non-utility Generation and Fuel Consumption from an Annual and a Monthly
Related Time Series, Presentation by Preston Mc Downey, Statistics and
Methods Group, EIA
In this
session we will discuss methods to estimate monthly data from an annual data
series. EIA started collecting data on non-utility power producers in 1989
through an annual census survey.
EIA changed the data collection method to a monthly sample survey (using
a cut-off design) in 2000. An
annual survey is still conducted for those companies that do not report data
monthly. EIA also has monthly data
from utility power producers from 1989 through the present. The topics to be discussed are:
advantages and limitations of the current work in progress, practical
alternative estimation approaches and reasonable validation processes. The resulting data will be used in
Monthly Energy Time Series (METS), an extended set of monthly energy data
corresponding to those released in the Energy Information Administration’s
Monthly Energy Review, where monthly data are generally available for only the
most recent two or three years. Wherever possible, METS provides continuous time
series from January 1973 forward.
ASA Committee
Advice
The
Committee expressed concerns about estimating historic data. Members were concerned that the data
would be misleading and users might not be able to distinguish real data from
synthetic data and misinterpret EIA’s assumptions as facts. If EIA did provide
estimates, the Committee strongly suggested footnoting estimates to distinguish
them from real data. The Committee
also noted that there would be no way to validate any of the estimates.
With
respect to Independent Power Producers (IPPs), there seemed to be an agreement
to use the seasonal patterns found in the electric utility data. The committee also agreed that EIA
should compare facilities where EIA has monthly data available as both utility
and nonutility.
With
respect to Combined Heat and Power Plants (CHPPs), the committee offered two
options. The first option was to
not provide monthly estimates. They
suggested noting that historic monthly data are not available, and to show
confidence intervals for the monthly data EIA does have.
The
second option was to only apply trend adjustments to the data and no adjustments
for seasonal factors. This would
provide data with some variation and demonstrate a smooth plot when the data set
is graphed. The alternative would
be to divide the annual total by twelve to calculate a monthly average. This would resemble a step function when
data set is graphed.
EIA
Response
EIA will
apply the seasonal factors found in the electric utility data to the trend
adjusted IPP data by sector by fuel type.
The same seasonal factors will be applied to only certain combinations of
sector and fuel type data that exhibit characteristics similar to electric
utility data. For those
combinations that do not exhibit characteristics similar to the utilities, EIA
will investigate other data series within the sectors for similar
characteristics. If no other data series can be found that exhibit similar
characteristics, EIA will provide either trend adjusted estimates or average
monthly data for those combinations that have relatively consistent monthly
consumption and generation.
9. Estimating and Presenting Power
Sector Fuel Use in EIA Publications and Analyses, Presented by Robert Schnapp, Coal, Nuclear,
Electric and Alternate Fuels, EIA, and Renee Miller, Statistics and Methods
Group, EIA, on where we
were then, where we are now, and what we learned. Topic will cover what was done and
why. Additional subjects to
include a) How did the data look before, how do they look now and lessons
learned; b) Impact on EIA products, i.e., AER, MER, others; and c) How we
present the changes.
As a
result of the changing structure of the electricity industry, the Energy
Information Administration (EIA) is changing how it presents data on the fuels
used to produce electricity. The
purpose of these changes is to ensure that the data are reported consistently
throughout EIA publications and to give analysts a better understanding of how
fuels are used – whether in plants that only produce electricity
(electricity-only plants) or in plants that produce electricity and some form of
thermal energy (combined-heat-and-power plants). At the last meeting we told the
Committee about some of the changes and about our data cleaning
efforts.
By the
upcoming meeting the first publication to appear with the changes, the Annual
Energy Review 2001, will be available as a Web product. This topic will cover the impact of the
changes in categorization and reporting of data, as well as revisions to
historical data on fuel consumption in EIA products. The Committee had suggested that when we
release the AER that we prepare documentation describing the changes. We have prepared documentation and
welcome the Committee’s comments on it.
ASA Committee
Advice
The
Committee commended EIA for putting together the documentation on the changes
due to recategorization and revision of data on fuel use for electric
power. They thought the
documentation was strong in describing the reasons for the changes, but they
thought an overview of the basic categorizations and how they differ from what
was done in the past would make it clearer. They suggested the use of graphics in
the documentation to show before and after sorts of tables, or at least table
shells. They also thought that we
should make a statement about the quality of the revisions. They agreed with our decision to use the
NAICS classification of the owner to classify the plant and didn’t think that
the lag in implementation of the monthly publications with revised data would be
a huge problem. In the longer
range, they suggested that the Web document be the core in generating the text
document. They also thought that we
should find out from a small group of diverse users whether the document meets
their needs.
EIA
Response
In
consultation with the two ASA reviewers, we added before and after graphics to
describe both the industrial and electric power sectors. We also added graphs that show the
impact of the revisions. In
addition, we incorporated a statement about the quality of the revisions. These changes are in both the Web and
printed version. We will discuss
getting user feedback on the documentation and maintaining a Web and printed
version.
10. EIA’s “Enhanced” Voluntary
Reporting of Greenhouse Gases (1605B) Program, Paul McArdle, Office of Integrated
Analysis and Forecasting, EIA
EIA’s Voluntary
Reporting of Greenhouse Gases Program, created under Section 1605(b) of the
Energy Policy Act of 1992 (EPACT), affords an opportunity for any company,
organization or individual to establish a public record of emissions,
reductions, or sequestration achievements in a national database. A total of 222 U.S. companies and other
organizations reported to the Program that, during 2000, they had undertaken
1,882 projects to reduce or sequester greenhouse gases. Reported emission
reductions included 187 million metric tons of carbon dioxide equivalent
(MMTCO2e) in direct emission reductions, 61 MMTCO2e in indirect emission
reductions, and 9 million metric tons of reductions from carbon sequestration
under the EIA 1605 form, as well as 12 million metric tons of reductions
reported under the EIA 1605EZ form, which does not specify whether reported
reductions are direct reductions or indirect reductions.
Since 1994, the
number of entities reporting to the program has grown by 106 percent and the
number of projects reported has grown by 197 percent. On February 14, 2002, President Bush
announced his Climate Change Initiative that calls on the Department of Energy
(DOE) and EIA to expand the Voluntary Reporting Program to encourage greenhouse
gas emission reductions and create a new, transferable credit system for those
reductions. The initiative is an important tool for achieving President Bush's
national goal to reduce the greenhouse gas intensity of the American economy by
18 percent by 2012. As part of that
initiative, the President called on DOE and EIA to “enhance (the) measurement
accuracy, reliability, and verifiability” of reductions reported to the
Program.
This paper attempted
to explore, in practical/theoretical terms, some of the important survey-design,
data-collection, data-processing, and data-quality issues in implementing the
initiative.
ASA Committee
Advice
The Committee
recommended EIA implement OMB recommendations, create some standardization of
the emissions mitigation definition, and employ independent verification, and
look at the Clean
Development Mechanism program for parallels that can be followed.
(Edmonds) On international emissions the best
known rule is probably that followed in calculating national GDP. It might be
useful to look at how the value added of international firms (i.e., firms
located abroad and with part foreign ownership) is treated when determining
national product. Dr. Khanna
recommended an
absolute baseline rather than an intensity baseline. (An intensity baseline is hard to defend
in the case of entity or project level reporting since its entirely possible
that all project/entity intensities decline while national emissions intensity
rises) (Khanna) Further, the
inclusion of indirect emissions
would lead to a huge amount of double counting which would be hard to
quantify. Other points
regarding:
A. Sequestration - Do not include sequestration option. While plant growth does indeed fix
carbon, the same quantity of carbon is released when the plant is burnt or
allowed to decompose. So on a life cycle basis the net change in emissions is
zero. Therefore, emissions reductions via by plant sequestration occur only when
there is a net increase in plant matter over the long term.
(Khanna)
B. OMB Recommendations, Definitions and
Verification - Implement the OMB recommendations, create some
standardization of the definition of emissions mitigation, and employ
independent verification. (Edmonds)
C. Clean
Development Mechanism - Look at the Clean Development Mechanism program for
parallels that can be followed. (Edmonds)
D. International Emissions - On international emissions the best known
rule is probably that followed in calculating national GDP. It might be useful
to look at how the value added of international firms (i.e., firms located
abroad and with part foreign ownership) is treated when determining national
product. (Khanna)
E. Baselines
- As regards the choice between an absolute baseline and an intensity baseline,
I would prefer an absolute baseline. An intensity baseline is hard to defend in
the case of entity or project level reporting since its entirely possible that
all project/entity intensities decline while national emissions intensity rises.
(Khanna)
F. Indirect Emissions - The inclusion
of indirect emissions would lead to
a huge amount of double counting which would be hard to keep track of.
(Khanna)
G. Sequestration - Do not include sequestration option. While plant growth does indeed fix
carbon, the same quantity of carbon is released when the plant is burnt or
allowed to decompose. So on a life cycle basis the net change in emissions is
zero. Therefore, emissions reductions via by plant sequestration occur only when
there is a net increase in plant matter over the long term.
(Khanna)
H. Reporting Level - Entity level
reporting is a more tractable unit of analysis, especially since entities can be
defined to be fairly small units such as a single manufacturing facility or
household. Project level reporting would increase the probability of double
counting and would also make third party verification more difficult, if not
impossible.
(Khanna)
I. GHGs Reported - Report CO2 and other
gases using standardized coefficients and methodologies
(Khanna).
J. Transparency, Reliability and Accuracy -
This can be achieved by: (1) Annual reporting by all facilities and all gases,
(2) Require reporting of energy and chemical use to cross-verify emissions data.
(3) Standardized coefficients and worksheets, (4) Develop mechanisms to reward
companies that report comprehensive data every year, and (5) Require independent
3rd party verification with random checks.
EIA
Response
1. EIA will continue to evaluate the OMB
recommendations in the 1605b survey terms of clearance and how they will fit
with the next version of the 1605b data collection. Some of these recommendations EIA has
already adopted.
2. EIA will forward all of the Committee’s
advice to DOE’s Office of Policy, who, with EIA’s technical support, has the
lead in developing revised guidelines for the 1605b data collection within the
President’s Climate Change Initiative.
3. EIA will independently, and in concert
with DOE’s Office of Policy, evaluate the important GHG accounting rules and
determine how they can be best fit into a new/revised reporting form and
reporting software.
11. Organization and Delivery of Energy
Information in Spatially Referenced Form, David F. Morehouse, Office of Oil
and Gas, EIA
Data are
spatially referenced when they are linked to a location. This presentation is
intended to introduce the Committee to the current status of, and the rapidly
increasing emphasis on, data organization and data delivery in spatially
referenced form (via geographical information systems technology), at four
levels: world- and US-wide, in government, at DOE, and at EIA. Today's objective is to initiate a
continuing "when-and-as-necessary" elicitation of the Committee’s guidance
relative to the questions of whether, how, where, and to what extent EIA should
implement this approach to the organization and delivery of energy
information.
ASA Committee
Advice
Members of the ASA
Committee on Energy Statistics offered five recommendations on
Organization and Delivery of Energy Information in Spatially Referenced
Form. The recommendations
were:
1. Develop a multi-year EIA Geospatial
Strategy plan that will accommodate the present and expected future requirements
of internal and external users for energy data provided in geospatial
format. The plan should define the
needs for spatial presentation of energy data and for spatial analyses of energy
data (i.e.: What data presentation or analysis needs now exist that are not
being met adequately or at all? What can be done better -- via the combination
of georefenced energy data and GIS technology -- than its being done now
?). The plan should be structured
along three complementary vectors:
A. Hardware and Software: Consider the kinds of spatial analysis
that will be done when selecting the software platform.
B.
Data What limited,
spatially referenced energy data would be useful in the near future? What spatially referenced energy data
would be useful in the medium and long terms? How much do you cooperate with
other agencies [re data, presumably inclusive of joint finance of acquisition
and maintenance]? Early emphasis
should be on the data rather than on specific maps. Mapping will follow
naturally when the data is available.
C.
Staff EIA clearly
needs to develop and/or acquire a larger complement of GIS-competent staff to do
this.
2. Creation of a web-based National Energy
Atlas is a good goal. The Atlas
needs to be defined/mocked up; this could materially assist in developing the
strategic plan.
3. County level spatial energy data would
be nice to have; in some instances it could be difficult to
develop.
4. Develop displays and analyses on the
spatial relationships between land use and energy.
5. Develop interactive map applications for
the EIA Kid’s Page that will facilitate learning of both geography and
fundamental spatial energy relationships.
EIA
Response
Mr. Morehouse will
work with senior EIA managers to form a Geospatial Data Working Group of representatives from each EIA office. This working
group will be
tasked with developing a formal EIA Geospatial Strategy and a supporting budget
within one year, and creating a plan for the development and dissemination of a
National Energy Atlas.
12. ASA Committee on Energy Statistics
Contributions to EIA, presented by Dr. Calvin Kent, Marshall University,
Huntington, West Virginia, past ASA Committee member, and previous EIA
Administrator
The
Energy Information Administration was established as an independent statistical
agency within the new Department of Energy when the latter was established in
1977. The Department of Energy
brought together over 50 diverse agencies and departments from other branches of
the Federal Government. The only
common factor among these was their concern with some aspect of energy. The need to bring the diverse data
bases, sources of information and methods of collection together was a
formidable task for EIA. To assist
the American Statistical Association was asked to sponsor and help form a
Committee on Energy Statistics.
That Committee began its work in 1979 and continues to this day. Over the past twenty plus years the role
of the Committee has remained the same, but the issues which it deals have not
been static reflecting the changes in mission and the crises in energy markets
with which EIA has had to deal.
This paper is to review and analyze the work of the ASA Committee on
Energy Statistics.
This
paper on ASA Committee history was developed by Dr. Kent as an ASA
initiative. ASA and EIA discussion
followed Dr. Kent’s presentation.
ASA
Committee Advice
The
Committee recommended that (1) EIA provide papers earlier for Committee and
discussant review, (2) asked that EIA not substitute outlines or slides for
papers where questions are being asked and discussion is expected, (3) EIA write
to the ASA Committee regarding EIA responses to ASA advice, rather than take
Committee time at the meeting to provide reactions at subsequent meetings, (4)
provide data, code and other details in (or with) papers in order to communicate
more clearly in advance of the meeting, and (5) suggested that intended
presenters be available for questions to ASA discussants prior to the
meeting.
Note: The Fall meeting was held
Thursday, October 24, all day, and Friday morning, October 25, 2002 at the James
Forrestal Building at 1000 Independence Ave., SW, Washington, DC, 20585. This summary account is found on EIA’s
Home Page under Energy Events. Once
there, one clicks on Fall 2002.
Additional meeting
documentation (general and detailed agenda, abstracts, papers and brief ASA
Committee member bibliographies) may be found on the meeting home page by
clicking: http://eia.doe.gov/smg/asa_meeting_2002/fall/.
Questions, comments and
requests for access to a paper transcript and session hand-outs, may be referred
to Bill Weinig, EI-70. Bill is
EIA’s liaison with the American Statistical Association Committee on Energy
Statistics, and can be reached at (202) 287-1709, or by email at william.weinig@eia.doe.gov.