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 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 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.
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.
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 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.
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.
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.
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 email@example.com.