for the Spring Meeting of the
American Statistical Association (ASA)
Committee on Energy Statistics
April 22 and 23, 2004
Energy Information Administration
1000 Independence Ave., SW.
Washington, D.C. 20585
Thursday, April 22, 2004
Natural Gas Prices and Industrial Sector Responses: An Experimental Module for the Short-Term Integrated Forecasting System (STIFS), Dave Costello, Office of Energy Markets and End Use (EMEU) and Frederick L. Joutz, Associate Professor, Department of Economics, The George Washington University. The Short-Term Integrated Forecasting System (STIFS) generates monthly forecasts of energy demand, supply and prices using some forecast information that is incorporated into STIFS that is generated by other models that do not run in an integrated framework with STIFS. This includes the macroeconomic forecasts and projections for certain energy supply variables. There is no direct feedback between the macroeconomic models projections and STIFS components. Members of the STIFS Team can attempt to coordinate iterations between the two models. However, this is not desirable for two main reasons. First, it suffers from specification problems in the richness and complexity of the dynamic interactions because the feedback is not directly estimated. Second, the iteration process requires staff time and resources that are limited.
This project tests an experimental model for the interaction between natural gas prices, natural gas consumption, and industrial sector activity. Two strategies are followed. The first involves a simple VAR framework capturing the time series dynamics testing for Granger causality and examining impulse response functions and forecast error variance decompositions. In the second approach, energy and economic variables are analyzed in terms of integration, co-integration for a long-run relationship between oil and natural gas prices. The general to specific modeling methodology is used to develop a data coherent parsimonious representation. Issues related to parameter constancy, encompassing, and forecasting are discussed. The forecasting performance of the two strategies is compared and the potential gain from using the experimental module is discussed.
Measuring the Quality of EIA Analysis: A Revised Approach, Bill Weinig, with support from Howard Bradsher-Fredrick, Tom Broene Stan Freedman, Inderjit Kundra, Herb Miller, Renee Miller, and Joseph Sedransk, SMG, EIA. During a session at EIA’s fall, 2003, meeting with the Committee, we suggested asking Independent Expert Reviewers to assess the quality of EIA’s analytical products. The committee thought that the reviewers were too close to individual products, the reviewer sample was too narrow, the survey questionnaire was not clear and had other criticisms. This session will revisit EIA’s need to assess the quality of EIA’s analytical products, called for in EIA’s Strategic Plan. The methodology has been reviewed and revised, the survey has been redirected toward a new population, and the questionnaire revised.
The Energy Information Administration is implementing a plan to expand the coverage of the current Short-Term Integrated Forecasting System (STIFS) from a single-region national model to a multi-region model. Variations in regional demand, supply, and prices provide opportunities to assess and estimate impacts of energy prices on energy demand, choices fuels, and choices of energy efficient technologies. A regional approach in projecting the short-term energy outlook also allow users to get more detailed information on regional energy demand, supply, storage, movement of fuels, and potential transportation bottlenecks. There are, however, statistical issues as well as econometric issues that need to be resolved before a sound operational model can emerge.
This paper intends to examine two specific issues facing the modeling team. The first one deals with specification of demand equations. An econometric model specification can be based on demand for each type of fuel such as demand for natural gas, electricity fuel, and oil. The approach allows modelers to specify demand and supply for a fuel. For example a model can estimate the demand for natural gas by end-use sectors and estimate gas demand and supply equations simultaneously. Econometrically, both demand and supply equations can be identified if adequate data are available. In addition, demand equations with emphasis on end-user sectors allow modelers to impose different restrictions on model parameters and could provide insights that may be useful to stakeholders. For example, modeling residential demand by fuel type allows analysts to study the effects of fuel prices on fuel substitution and efficiency improvement. We are exploring the pros and cons of these two different specifications and the their performance in providing good predictors.
The second issue deals with electricity demand and power generation. Monthly statistics on electricity demand do not reflect hourly variations in demand. In a hot summer day, peak load demand in the afternoon can be several folds higher than early morning demand. Power generation required to meeting peak demand could impose binding conditions to the electrical system. We propose to create pseudo load curves based on monthly data. For example, electricity demand in April and May are relatively flat. This information can be used to mimic the low-end of a summer month load curve. High-frequency weather and other information on the shape of load curves from Independent System Operators (ISO) may be used to infer peak demand during summer months. The cost of generation for each type of power plan will be calculated based on fuel costs, thermal conversion efficiency, and operating and maintenance costs. The cost of electricity and the shape of the load curve will then be used to determine dispatching of electricity from generators. Differences in regional power supply and demand will be used to assess interregional electricity flow. This approach could provide insights to the effects of forced outage and peak load demand on regional power flow and fuel shares in the power generation sector.
EIA’s Frames: How Do We Know if They are Sufficient? Grace Sutherland, Introduction, with participation from Renee Miller, Howard Bradsher-Fredrick, Shawna Waugh and Alethea Jennings, SMG, EIA
The quality of EIA’s data has been made a priority and has been made part of its Strategic Plan. Goal 1 of the EIA Strategic Plan states “…EIA’s information products will retain or improve their high quality…” One of the performance measures and targets for this goal involves evaluating the EIA frames. The measure is the percent of EIA survey frames with sufficient industry coverage to produce reliable supply, demand and price statistics.
We began by preparing a list of EIA survey frames and update procedures. We are now in the process of gathering existing information on the quality of our frames. Activities to assess frame quality include:
1. Checking the frame against alternative lists at the respondent level (suggestion taken from the Statistical Policy Working Paper 15).
2. Data Comparisons at an aggregate level (certain EIA data compared with similar data outside of EIA).
3. Examining Supply/Disposition Balances (supply should equal disposition, but because the data that comprise the supply/disposition balances are from different surveys, a balancing item is needed. If the balancing item becomes large, it could be an indication of a frame or other data quality problem).
This presentation will provide examples of these activities and ask for the Committee’s guidance on other activities that could be used to assess our frames. We are also interested in the Committee’s thoughts on how we can develop criteria to define sufficient coverage.
Electricity 2005, Robert Schnapp, Director, Electric Power Division, Office of Coal, Nuclear, Electric and Alternate Fuels, EIA
“Electricity 2005” is a project that EIA’s Electric Power Division began in 2003 to revise the electric power surveys to accurately capture the changing industry. The presentation will focus on the four phases of the project; the issues and potential changes that are most important; and the relevance of EIA’s data confidentiality policy. Special attention is given to transmission data needs to tie this presentation to the following one on focus groups held to elicit input on the transmission data that EIA should collect.
Electricity Transmission Data Needs Focus Group Results, Howard Bradsher-Fredrick and Phillip Tseng, SMG, EIA
The Energy Information Administration (EIA) is charged with providing timely and relevant data to stakeholders. In response to changes in the electricity industry in recent years, EIA will use its normal review process to update the EIA survey forms, collect information consistent with the market, and publish reports that meet stakeholders’ needs. A normal procedure is holding stakeholders meetings to receive inputs and suggestions. We will report our findings at this ASA meeting.
Four focus groups were conducted from November 2003 through January 2004 on the topic of electricity transmission data needs. The participants in each of these groups were fairly homogenous with the following groupings: EIA, DOE policy offices, other Federal organizations, and non-Federal organizations. Each focus group had from 9 to 12 participants. These sessions were audio taped for the purposes of writing the report. The participants were asked questions from a structured protocol; these questions involved the following topics: characterizing EIA’s present transmission data collection, emerging issues in transmission, specific data needs, sources of data, and confidentiality issues.
The focus group participants stated that EIA should begin to provide more data regarding electricity transmission. Some of the data could be collected through existing forms. Other data could possibly be collected through alternative sources and by editing and processing data collected by other agencies and organizations.
Transmission Data for Public Policy, Douglas R. Hale, EIA Senior Scientist on loan to Lawrence Berkeley Laboratory, DOE. At the fall, 2003 meeting Doug Hale briefed the committee on a project to document the Federal Government's needs for transmission data (October 17, 2003). He has since written the report along the lines he discussed with the committee, and has also incorporated most of the committee's suggestions and those of EIA staff and Independent Expert Reviewers.
The report is now in interagency review, and is available to the committee on the ASA Meeting Home Page. Doug will return from the Lawrence Berkeley Laboratory to join us for the meeting and to answer questions and discuss suggestions and complaints the committee may have with the report.
EIA publishes “Stocks of Crude Oil and Petroleum Products” weekly and monthly at
http://www.eia.gov/pub/oil_gas/petroleum/data_publications/weekly_petroleum_status_report/current/pdf/table03.pdf . All components of “Monthly Other Oils“ stocks are collected from all respondents in a census. In order to present more timely “Other Oils” stocks, the “Weekly Other Oils” stocks are estimated from the “Monthly Other Oils” stocks. Due to the seasonality and other unexpected disruptions, there are some discrepancies between these two series of stock number.
We want to determine the best way to estimate weekly stocks of other oils excluding propane (based on weekly data for major oil products, plus monthly data for major oil products and other oils products) and to evaluate alternative methods by comparing the estimate to monthly data.
What is the criterion to decide the best estimate of weekly other oils stocks? The least sum of absolute deviation? The least sum of squared errors?
What is the best way to estimate weekly “other oils stocks”??
EIA Survey Testing Methods, Stanley Freedman & Robert Rutchik, SMG, EIA
The purpose of this breakout session is to describe, discuss, and seek ASA Committee Advice on EIA’s testing methods used in survey design. EIA would like to get advice from the Committee on the suitability of these methods for energy establishment surveys.
EIA has used several methods in the past six years to develop and redesign surveys to meet changing industry structures. These methods include:
Within these broad categories we have used combinations and permutations of these methods.
The Committee will be asked to discuss:
Natural Gas Production Monthly Survey, Inderjit Kundra. The purpose of this survey is to provide monthly estimates of natural gas production at the National and regional levels. The regions are Texas, Federal Gulf, Louisiana, New Mexico, Oklahoma, Wyoming and the others. For selecting a sample, the 2002 EIA-23 Frame will be used. The operators showing zero or blank production will be excluded from this frame. Two separate small samples of the operators showing zero or blank production will be selected to validate their responses. We are in the process of designing the sample. By the time we meet we will be in a position to ask the Committee=s comments about what we have done to accomplish the survey.
Friday, April 23, 2004
Improving EIA’s Website: Creating a Vision for the Future Colleen Blessing, National Energy Information Center and Melinda Hobbs, Office of Information Technology, EIA. EIA is embarking on a new phase of web development. This session will cover the process EIA has begun to gather information about what works and doesn’t work on the site and how we will use the feedback to develop a web strategy for the future. We will highlight some recent improvements as a hint of things to come. ASA members are encouraged to comment on the specific improvements or on anything related to EIA’s website.
Revising Data Together Across EIA: Issues and Opportunities, Renee Miller and Alethea Jennings, SMG, EIA
We have spoken to the Committee about how EIA has expanded its use of data collected in electric power surveys across the organization, such as natural gas, petroleum, and the integrated statistics publications. As a result, revisions to electric power data affect more than just the electric power publications. In addition, it is easier to revise data on the Web than in hard copy format. These two events have raised questions about the need to coordinate revisions across EIA.
We will present background on EIA’s current revision standard (which the Committee helped us develop in the eighties) and recent events that led to its review. Representatives from each affected office are working together to determine the best way to meet user needs and interoffice goals in support of EIA’s mission. We will present conclusions from recent discussions/debates and will ask for the Committee’s guidance on coordinating revisions.
In addition to thinking about the coordination of revisions, EIA is examining the circumstances under which data are revised. In our attempt to reduce the frequency of publishing revised data, we are examining the situations and events that prompt data revisions. EIA may be revising data more often than is necessary to meet user needs. Various situations cause data to revise, such as resubmissions, benchmarking (to the Annual publication), data corrections (where problems were discovered with the data originally reported) and late submissions. We will present an example of data to illustrate revisions occurring over time. We hope to obtain suggestions and ideas for reducing the number of revisions that we publish.
To satisfy users who are interested in having the latest data available, it has been suggested that EIA provide the latest versions of the data via the Website and inform users of this option. We will discuss some of the advantages and disadvantages of this approach and ask for the Committee’s thoughts.
Survey Quality Assessments at EIA, Tom Broene, SMG
Other statistical agencies and private firms have found it helpful to conduct assessments of on-going surveys on a regular basis. EIA formed an inter-office team in 2003 to develop the procedure for an assessment and determine what data should be collected. This talk will present the matrix used to collect the data and discuss its development. So far, only a handful of assessments have been completed, but we hope to have an assessment for all EIA surveys by this summer.