SUMMARY of the
Fall Meeting of the
American Statistical Association (ASA)
Committee on Energy Statistics
with the
Energy Information Administration
1000 Independence Ave., SW.
Washington, D.C.  20585
October 16 and 17, 2003

Thursday, October 09, 2003


EIA's Strategic Plan and Performance Goals for 2003-2008  (Plenary Session):

Session emphasis was on the action plan for Goal 1, the first of the three EIA Goals:

Goal 1: EIA's information program is relevant, reliable and consistent with changing industry structures, and EIA's information products are high quality and timely. 

Goal 2: EIA's resource base is sufficient to accomplish its mission

Goal 3: EIA employees rate EIA high in the areas of leadership management, and meaningful work; and they rate themselves high in motivation and productivity

Goal 1: EIA's information program is relevant, reliable and consistent with changing industry structures, and EIA's information products are high quality and timely.

1.  Quantifying Analytical Quality Through Assessments by Independent Expert Reviewers  Bill Weinig, SMG, EIA  Paper developed by a team of Howard Bradsher-Fredrick, Tom Broene, Stan Freedman, Herb Miller and Bill Weinig.

Session Overview

EIA has been conducting surveys and other methodologies to assess the quality, timeliness and other attributes of EIA products for several years.  However, a systematic quantitative assessment of these attributes related to EIA analytical products has not been conducted.  In this paper, we are proposing a limited survey of subject matter experts who review EIA draft products through the Independent Expert Review program and other review media.

Questions to the Committee:

  1. Are EIA’s proposed survey questions balanced and comprehensive given the goal?
  2. Are the Independent Expert Reviewers likely to be the appropriate survey audience?
  3. Is the pretest group of two or three reviewers, described earlier, sufficient?
  4. Are there other questions we should be asking?

ASA Committee Advice

The Committee felt the survey questions were comprehensive and balanced but were fairly complex and open to some range of interpretation which could be dissected by cognitive testing and research.  EIA’s use of  definitions in the proposed questionnaire suggested this too.  The small sample size could lead to fairly unstable results.  While the form supported tabular results, the results were not likely to provide rich information.  The Committee suggested EIA consider open-ended questions, and a qualitative evaluation. Independent reviewers might be good at qualitative evaluations, and might be surveyed through Independent Expert Review contracts at intervals after their reviews.  The committee was mixed on the value of keeping the reviews animus, and was generally not supportive of the survey in its current methodology or form. 

EIA’s Intended Response to ASA Advice

EIA intends to rework the survey for clarity, replace the independent expert reviewers by surveying a larger group of EIA’s analytical customers at the spring 2004 National Energy Modeling System Conference in March, 2004 instead, and improve the survey methodology in form and description.  The topic will be presented again at the spring 2004 meeting.

2.  Natural Gas Overview: EIA’s Data Initiatives in Natural Gas  Introductory presentation by Elizabeth Campbell, Office of Oil and Gas, EIA (Plenary Session). Overview topics included DOE Secretary’s Data Initiative, and relationships to recent and planned work including natural gas production estimates, price estimation, and a proposed new LNG survey.

2.a.  Criteria to Select and Implement Estimation Procedures: Comparative Evaluation of Two Methods to Estimate Natural Gas Production in Texas, Kara Norman , SMG, EIA

Session Overview

At a prior ASA Committee Meeting, a natural gas production estimation method was proposed by Crystal Linkletter.  Her model was compared to the existing model utilizing an Evaluation of Methods.  The purpose of this session was to evaluate the Evaluation of Methods.  Ultimately, the Evaluation of Methods would be used in the future to compare new or improved methods as they are proposed.

The questions posed to the Committee were as follows:

1) Are the outlined criteria adequate and appropriate? 
2) Was the Evaluation of Methods applied correctly and sufficiently? 
3) Would, or more likely, how should the criteria change, based on the comparisons of different methodologies? 
4) Now that that multinomial method has been selected, what improvements could be made to the chosen estimation procedure, such as corrections for bias?

ASA Committee Advice

On the subject of the Evaluation of Methods, the committee suggested using all of the available data rather than a shorter window for comparing two methods.  The committee advised analyzing the robustness of the models.  The committee recommended running simulations with fabricated disturbances to analyze the effects on the resulting estimates.  The committee proposed the use of sensitivity analysis in conjunction with these simulations.  The committee would like to see more extensive use of time series analysis to include the calculation of residuals and the correlations of these residuals. 

On the topic of the Multinomial Model, which was selected based on the Evaluation of Methods, the committee again recommend using all of the available data and furthermore modeling any changes in reporting patterns.  The committee also suggests the use of weighted likelihoods to decrease the weight of contributions from later observations.  The committee condones the continued analysis of the bias, such as the exponential smoothing process already under examination.  The committee tempers these recommendations with a warning that complex additions to the selected model will result in a less transparent method. 

The committee lastly strongly advocates contacting Crystal Linkletter to share these discoveries, as well as to request that she seek to publish her thesis documentation on the Multinomial Model.

EIA’s Intended Response to ASA Advice

EIA plans to examine the advice regarding the Evaluation of Methods in future comparisons of models.  The suggestion to include all available data is one we plan to heed when returning to the analysis of the Multinomial Model.  The suggested additions of robustness comparisons, simulation and extensive time series analysis are improvements to the Evaluation of Methods that will be incorporated as the need arises in the future to compare other models.

EIA is intrigued by the suggestions for improving the Multinomial Model.  EIA will certainly continue to examine the bias as well as to run the model again using all of the available data, as mentioned above.  We certainly plan to contact Crystal Linkletter as we would love to see her work published, which would potentially allow us even further feedback on the selected model.

2.b. Estimating Industrial Natural Gas Prices  Presentations by Ruey-Pyng Lu, SMG, EIA and Michael Taylor, University of Michigan graduate student and SMG Summer Intern, EIA. (Break Out Session)

The Energy Information Administration (EIA) collects and publishes data on prices and volumes of natural gas delivered to customers in four sectors (residential, commercial, industrial, and electric power). EIA publishes the average price for a state computed as revenue averaged by volume. Natural gas industry restructuring has resulted in industrial customers consuming less than 20 percent of the gas purchased from companies that physically deliver it to the facilities.  EIA’s respondents cannot report a revenue stream associated with the 80 percent for which they are transporting “for the account of others”.  To estimate the price of the natural gas consumed by the industrial sector, EIA has been exploring the use of another survey, Form EIA-423 [Monthly Cost and Quality of Fuels for Electric Plants] which surveys all non-utility electricity generating facilities with a nameplate capacity of 50 megawatts or greater.  At the April 2003 meeting we showed the committee some plots of the relationship between price and volume from that survey. Since there was not a discernible relationship the committee suggested that we develop a model using the cost and volume from the Form EIA-423, and data reported by deliverers of natural gas on the EIA-857.

Meanwhile we have been receiving and reviewing additional EIA-423 data, which we believe represent off-system prices (the deliveries for the account of others) for industrial facilities that generate electricity and meet the threshold for the EIA-423 survey.  Since the EIA857 represents the on-system prices, the question is how best to estimate the off-system prices for the industrial facilities that either don’t generate electricity or generate electricity, but do not qualify for Form EIA-423. 

Our approach is to model the difference between natural gas prices paid by EIA-423 respondents in 2002 (the first year of the survey’s existence) and a day-weighted average of monthly Henry Hub (a large natural gas distribution hub in Southern Louisiana) prices.  Six models were to be made, corresponding to the following areas: the Northeast Census Region, the Midwest Census Region, the South Census region excluding Louisiana, Texas and Oklahoma (which were found to be significantly different from the remainder of the region), Louisiana, Texas and Oklahoma as a block, the West Census Region excluding California, and California by itself following the same rationale used above.  The state-level purchased price reported by EIA would be a weighted average of prices reported on surveys EIA-857, EIA-423 and the predicted price difference from the model added to the day-weighted monthly average of spot gas prices. An enhanced model is adopted to use a day-weighted average of monthly regional Henry Hub (Chicago, New York, California, Oregon and Louisiana) prices. There are some promising results in this modeling approach.

The subsequent task to improve the estimation of industrial natural gas price is to use the count of natural gas use facilities and the natural gas volume consumed by them in the industrial sector of EIA-906 [Power Plant Report] and Manufacturing Energy Consumption Survey (MECS) 2002 data (available in Fall 2004) to validate the natural gas industrial price estimated by the difference of regional Henry Hub prices and EIA-423 respondents.  We will be asking the committee for guidance in determining the tabulations we should request from MECS to validate our estimate of the industrial price and also for guidance on presenting our estimates.

ASA Committee Advice

It is useful "to add a column showing the price paid by industrial combined heat and power plants from the EIA-423 survey along with the percent of total industrial sales that it represents." And it seems a bit premature of "presenting a separate table that shows several estimates that attempt to represent a price for the entire industrial sector based on the 4 options we presented," they advise against this.

EIA’s Intended Response to ASA Advice

We refer this advice to CNEAF staff and they will add a column when they revise the EIA-423. After the Fall meeting Census Bureau staff contacted EIA offered to help collecting natural gas industrial price data, EIA natural gas division staff will give the data requirement to Census Bureau and Census Bureau staff will prepare a contract and cost of conducting a survey to manufacturers monthly.

2.c. Natural Gas Production Estimation in the Gulf of Mexico  Presentation by John Wood, Director, Reserves and Production Division, OOG, EIA, in Dallas, Texas. (Break out session).

Completion level production data collected and reported by the Minerals Management Service is used to estimate current Gulf of Mexico gas production.  This reported data is essentially complete in mid 2001 and progressively less complete closer to current months.  The basic concept assumes that the incomplete data in recent months is a sample distribution of what will ultimately be reported when complete.  Both complete and incomplete (sample) distributions are very skewed.  Estimates are made for the missing data in each class in the sample distribution based on an expected number of producing completions, which depends on an average or standard complete distribution.  Various methods and procedures for filling in the classes of the sample distributions will be discussed.

ASA Committee Advice

Most of the discussion that followed the presentation concerned the distribution of well completions.  How and why it was determined the way it was determined and then what should you do or not do with it.  Do we really gain anything with the 12 class distribution, filling in what we determine to be missing completions?  There was also a good bit of discussion on the data, where it came from, what it meant, how good it is, and its interpretation.

Committee Suggestions:

  1. Evaluate this methodology.  How well does it work and is there enough history to make a comparison to final data?
  2. Look at the largest wells individually.
  3. Model the production of each individual well completion.
  4. Model the well completions by groups (possibly classes) to account for the business perspective (or influences) as well as the engineering perspective.
  5. Predict or project the number of missing wells in each class rather than filling in the number of missing wells as a difference from some standard.

EIA’s Response:

The suggestions made by the committee are very much appreciated.  We plan to pursue these suggestions as stated below.

  1. Since the data we are using is only recently available, and this methodology can only be used with this data (and not the historical data set), there is no history of actual final data to compare with.  However, as the historical data set builds over time, we will make comparisons of estimates to actual to evaluate the accuracy of this methodology.  We will always try to make a qualitative judgment even if a quantitative evaluation can’t be done.
  2. We currently look at all the wells individually in the top 2 classes now.  We will look into adding a third class (another 50 or so wells).
  3. Modeling the production from each individual well is something we’ve discussed often.  So far, time and resources have precluded us from doing this.  However, we are headed in this direction and hope to eventually put a system in place to model each individual well completion.  In this case, dealing with the economic influences may be more of a challenge than simply modeling the normal physical production declines.
  4. Besides modeling the class behavior, wells could also be grouped by vintages.  We have some experience doing this now in other projects.  This may add unwarranted complexity and less transparency than simply modeling the individual well production.
  5. Accurately predicting the number of missing wells in each class would likely improve our current methodology.  We looked at this briefly in the early stages of this project.  However, finding the proper drivers for such a model may prove difficult.  A simple time series model would be insufficient.

It seems that the best course of action at this time may be to pursue the modeling of the individual well production of the missing wells.  In the meantime, we’ll certainly consider the other suggestions of the committee.

2.d. Evaluation of EIA-910 Survey of Natural Gas Marketers:  Commercial and Residential Prices  Presentation by Tom Broene, SMG, EIA.  (Break out session)

Session Overview

EIA has been conducting the 910 survey in 5 states since August 2001.  The survey supplements the 857 survey of utilities.  An evaluation by SMG shows that:

  1. The volumes of natural gas sold by marketers do not match what the utilities claim to be transporting for resale, but are judged to be acceptable.
  2. Compared to the utilities, the marketer prices are little difference for residential, lower for commercial, but higher for both in GA.
  3. Minimal growth in the number of customers purchasing natural gas from marketers.
  4. Minimal impact on national prices.

Questions for the committee are:

  1. Does the form make sense?  This is the usual set of questions that EIA uses to obtain a weighted average price.

2.      EIA currently publishes only the average (integrated) price, which is the weighted average of the price from the marketer and the price from the utilities.  Is this reasonable, or should EIA publish both prices?  Should EIA include a variance or range for the marketer’s prices?

ASA Committee Advice

The questions before the committee concern EIA's relatively new survey (number 910) of marketers supplying natural gas to residential and commercial customers, which was started in 2002 in five states. The committee recommended that decisions for expanding into additional states be based on three factors: number of marketers operating in the state, the percent of natural gas sold by marketers, and total volume of natural gas consumed by residential and commercial customers.

The committee decided to not comment on whether users would want price estimates for areas smaller than a state. The committee concurred with EIA's current practice of releasing only a composite price estimate, since releasing the marketer price might violate confidentiality requirements. The committee concurred with the variance calculation method currently in use for the composite price, which reflects only the sampling error, and treats the marketer's data as a constant since based on a census.

EIA’s Intended Response to ASA Advice

EIA is taking the Committee’s advice to expand the EIA-910 survey into additional states based on three factors mentioned above, and otherwise accepts the Committee’s endorsement also mentioned above.

3.  EIA and the Confidential Information Protection and Statistical Efficiency Act (CIPSEA) Presentation by Jay Casselberry, SMG, EIA (Plenary session)

Session Overview

The E-Government Act of 2002, Public Law 107-347, was signed into law on December 17, 2002.  Title V of that Act is the Confidential Information Protection and Statistical Efficiency Act of 2002 (CIPSEA).   CIPSEA’s Subtitle A, Confidential Information Protection, affords a possible new level of confidentiality protection to statistical data and information collected by the EIA and other Federal agencies.

The presentation focused on the process to identify which EIA surveys would be collected under CIPSEA.  Major issues affecting the decisions were:  (1) Can EIA insure the confidentiality protection of a survey’s information and (2) Should the survey information be limited to sharing for exclusively statistical purposes.  Any violation of confidentiality protection could result in significant fines as set forth in CIPSEA.  Any authorized sharing for non-statistical purposes would require that affected respondents provide informed consent.  EIA’s questions focused on informed consent forms and identifying whether non-EIA uses of survey information are consistent with CIPSEA’s definition of “statistical purposes.”

ASA Committee Advice

The Committee members and Dr. Calvin Kent (discussant, past Committee member, previous EIA Administrator, and current guest) provided extremely insightful comments on the presentation, the Confidential Information Protection and Statistical Efficiency Act (CIPSEA), and how EIA should address the questions raised.  Recommendations:

  1. Define what are EIA’s “statistical data.”
  2. Deal with ambiguity of informed consent form (i.e., what informed may be released, under what circumstances, for what time period, what will any receiving agency do with the information).
  3. Make clear to respondents when data may be shared and for what purposes.
  4. Consider doing reimbursable work for other agencies that need our survey data for non-statistical purposes.

EIA’s Intended Response to ASA Advice

  1. All data collected in EIA-sponsored surveys are collected for EIA’s statistical purposes.  However, there are legitimate non-EIA uses that serve the larger Federal government’s role.  While EIA aggressively acts to undertake non-statistical work proposed by other agencies that would involve survey information categorized as confidential by EIA, given existing laws EIA cannot deny request for information for official Federal uses.
  2. EIA has modified its confidentiality wording and implemented it in all 2004 surveys.  The wording helps clarify for respondents what data may be shared and for what uses.
  3. EIA is developing a training program to educate staff on CIPSEA, its requirements, and its impact on EIA.
  4. EIA is participating in an interagency committee led by OMB to develop CIPSEA guidance for agencies.  That guidance is still under development.
  5. Additional work on informed consent forms for non-statistical uses has been delayed while EIA works on more pressing issues and awaits OMB’s guidance.

EIA has currently identified 12 surveys to collect information under CIPSEA.  In addition, EIA considers further extending CIPSEA to other collections as those collections undergo the process for OMB approval.

4.  Electricity Transmission Data Needs  Presentation by Douglas R. Hale, EIA Senior Scientist on loan to the Lawrence Berkeley Laboratory.  (Plenary session)

For much of the year EIA analysts have been working on a report on transmission data. This work has been in part motivated by the Department of Energy’s concerns with reliability and modernization of the high voltage grid and by the Federal Energy Regulatory Commission’s (FERC) reliance on the grid to promote competition. The major motivation was the Energy Information Administration’s (EIA) interest in providing policy relevant information.

The first objective of this report is to itemize transmission data currently collected by the Federal government.  An equally important objective is to examine whether the data informs the discussion of basic transmission policy issues. The study is restricted to information that is produced by the Federal and State governments, their agents and regulated entities, such as Independent System Operators (ISOs). North American Electric Reliability Council (NERC) data that are routinely supplied to DOE, EIA and FERC are also included. Privately produced data and proprietary analysis tools are not considered.

Data alone cannot answer many policy questions. For example in February 2003, Congress directed the Secretary of Energy to analyze

…the possible impact on regional electricity prices of FERC's proposed rule for Standard Market Design (SMD)…This independent analysis must compare wholesale and retail electricity prices and the impact on the safety and reliability of generation and transmission facilities in the major regions of the country both under existing conditions and under the proposed new rule.

Answering these kinds of questions requires a comparison of an existing with a hypothetical situation. That is almost always done by creating a mathematical model of the electrical-economic system and seeing how it functions under different policy rules. [1]

A third objective of this report is to assess the extent available models are able to help answer policy questions. The availability and quality of data severely limit what models can reliably predict. At the same time developments in economic research and in electricity markets are indicating the importance for behavior of new kinds of information. For example, congestion and transmission rights were of little public interest a decade ago. Now investors, customers and policy makers want to know future congestion costs and the value of transmission rights.

The final objective of this report is to suggest specific improvements in data collection and analysis tools that would support better answers to policy questions.

This talk is an update on the project’s status and a preliminary discussion of general issues of data collection and dissemination raised by the complexity of transmission data. In particular, the detailed electrical data required to answer questions about reliability and the extent of individual markets cannot be generally available because of National Security concerns. But, some of this data must be available by some means to inform public debate.

Market data-prices, production, imports, congestion-are increasingly available on web sites operated by ISOs. The amount of market data, some at 5-minute intervals, is overwhelming. The ISOs do not report the same data the same way, so it is difficult to compare across ISOs.   While it makes little sense for the Federal Government to compile and archive this data it may be worthwhile for FERC to promote standardization.

There are some limited areas where additions to EIA’s on going data collections may provide a better picture of transmission relevant data. Some preliminary suggestions are discussed. There are also areas where changes to FERC’s Form 1 might allow a clearer picture of the economics of transmission organizations.

ASA Committee Advice

The committee suggested that:

  1. Data and data needs depend on the industry structure, which is still in flux;
  2. Because of the interconnected nature of the industry, models will be indispensable for analyzing reliability and markets.  There is a policy question of how to do that well;
  3. Homeland security and reliability analysis are intimately tied together, and that link needs to be clear;
  4. The number of market participants, size and complexity of the industry makes data collection difficult; and
  5. Regulatory complexity and different authorities will require Federal agencies to work closely together on defining and collecting necessary data.

EIA’s Intended Response to ASA Advice

The points are good and will be incorporated in the final report.

5.  Data Edits for the EIA-920, Previously the EIA-906 Presentation by Bob Rutchik.

Session Overview

EIA has designed and tested a new survey to go to combine heat and power facilities.  The major data elements collected are:

  1. Total fuel consumed at the facility,
  2. Fuel used to generate electricity by prime mover type, and
  3. Stocks of coal and petroleum products at the facility.

This survey is new, both in layout and in some of the data elements.  Most importantly we are no longer collecting information on useful thermal output from these facilities.  Instead, we are asking for fuel used to generate electricity at the prime mover level.

EIA is working on designing new edits for this survey.  We are interested in edits that the respondent can use in the internet data collection, while filling in the form, and summary edits that are used by survey staff to verify the data submissions. 

EIA wanted to the Committee’s advice on the following questions concerning implementation of the edit system for the On-line versions of the Form EIA-920, Combined Heat and Power Plant Report.

ASA Committee Advice

The discussion focused mainly on the first three points. For example, would outliers that are correct be flagged for edit and inliers that are false not be flagged.  Are standard deviations or exponentially smoothed means better to calculate the edit ranges than plus or minus a certain percent from the previous month or year’s submission.  Should survey respondents get edit flags “in real time,” as they are completing the survey, or receive a complete summary of edits when they have completed the survey?

The Committee’s overall advice was to proceed slowly because there are problems with any type of edit, implementations, and feedback system.  EIA needs to get more respondent feedback.

EIA’s Intended Response to ASA Advice

Currently, EIA will use percent from the previous month’s or year’s submission for most edits and respondents will be asked to run an edit summary at the end of their EIA-920.  As more data becomes available, EIA could consider exponential smoothing for edit ranges and possibly real time edit flags.  The Program Office is proceeding slowly.

6.  Proposed Relative Standard Errors (RSEs) Guidance  Presentation by Shawna Waugh and Kara Norman, SMG, and Jim Knaub, Coal, Nuclear, Electric and Alternate Fuels, EIA.

Session Overview

The purpose of this session was to:

  1. define relative standard errors (RSEs) and their importance;
  2. identify current uses of RSEs by end-user and supplier surveys;
  3. recommend best practices; and
  4. determine whether to adopt the proposed guidance on Relative Standard Errors.

Relative Standard Errors are typically a tool for evaluating sampling errors (but not bias) of estimates. Some managers use RSEs to edit data; other managers use RSEs to select a sample.  The most prevalent practice is to publish RSE Tables in which each cell corresponds to estimates in a published table, thereby providing users with information on the reliability of estimates.

RSEs serve to improve the design and implementation of surveys and assess reliability of published estimates.

  1. RSEs may be used to select sample design or to select a sample.
  2. RSEs may be used to identify errors prior to publication.
  3. RSEs should be used to restrict publication of unreliable estimates.
  4. RSEs should be to inform data users about the reliability of estimates.
  5. RSEs may be used to compare data.

Over time on a single survey and among current surveys the criteria select for restricting publication of unreliable estimates differs.  Some managers would advocate restricting any estimate with an RSE greater than 10; other managers support publishing estimates with an RSE less than 50; and a few managers would support publishing all estimates regardless of the RSE. When selecting criteria to restrict publication of estimates, it is important to balance accessibility to estimates with importance of publishing reliable estimates.

Following an evaluation of existing practices of RSEs at EIA and other statistical organizations, guidance was proposed on uses of RSEs for quality improvement, quality control and quality assurance.

ASA Committee Advice

The Committee agreed that guidance on Relative Standard Errors would be useful to EIA survey managers and data users, and recommended:

EIA’s Intended Response to ASA Advice  

The RSE guidance will be revised to adopt the committee's advice to examine autocorrelation for time series data.  The RSE guidance will not include the committee’s recommendation of publishing confidence intervals given the problems associated with this suggestion.

SMG staff will meet with Program Offices to propose, consider and review RSE guidance prior to adopting this guidance.

7.  Closing Session: Committee Suggestions for the Spring, 2004 Meeting

Chairman Breidt reinforced the value of break-out sessions allowing more focused discussion.  (Dr. Kirkendall offered that this break-out session allowed EIA to come to the Committee earlier for advice.) Dr. Feder thought that EIA staff coming to the Committee earlier was better and more helpful. Dr. Edmonds suggested that the Committee might be used to certify (new or changing?) EIA products for use, and that the ASA Committee might consider bringing in specialists for more focused reviews and certification. Dr. Kent, guest, suggested the Committee consider using a group of experts to focus on specific “hot topics.” Vice Chair Hengartner reinforced the value of break-out sessions and believed that these sessions increased participation and engagement by EIA staff.  (Dr. Kirkendall offered that members of her SMG staff were doing lots of work with other EIA staff and on their behalf which extends SMG involvement and EIA coverage.  Dr. Kent suggested that other EIA staff could serve as discussants.  Dr. Hammitt suggested that major model changes be reviewed by the Committee.  He and Dr. Kent suggested adding industry specialists to the Committee, ones who supply or use EIA data, and who are industry statisticians.  As a topic, Dr. Edmonds suggested a session on CIPSEA and its application to home security. Dr. Hammitt offered that home security had many dimensions including the usual idea of security of the home land, and also energy security and energy foreign policy such as with North Korea. And finally, Dr. Edmonds offered that we use “energy security” as an organizational metaphor/theme that goes through issues, and that as collector of the data, EIA needs to understand energy security.

Additional information follows on the next page.


Questions regarding EIA’s fall meeting with the American Statistical Association Committee on Energy Statistics and this summary may be directed to Bill Weinig, EIA’s liaison with the ASA Committee by email at or by phone at the (202) 287-1709. 

The meeting agenda, papers, slides, and information on the committee members and EIA may be found on EIA’s Home Page at

An unedited transcript may be found on EIA’s Home Page under Energy Events, Summary of Advice from the American Statistical Association, at

[1] Occasionally the alternative policy is followed somewhere outside of the area considering a change. The UK’s early success with restructuring its electricity industry was used by supporters of California’s restructuring as evidence that competitive markets would increase generation investment and lower electricity prices. Another way to evaluate a proposal is to create artificial markets in a controlled setting and see how real people act when the rules are changed. A good analysis method, either mathematical modeling, historical analogy or experimental, would correctly anticipate real world responses to alternate policies.