[en] This paper analyzes the connotation of core competence theory, Discusses the definition, composition and main aspects of the theory in professional information agency, And analyzes the core competence of an authoritative information agency-Energy Information Administration, discusses the main measures of improving core competencies in professional information agency. (authors)

[en] This directory contains abstracts and ordering information for EIA publications released in the above time period. The abstracts are arranged by broad subject category such as coal, petroleum, natural gas, and electric power. A comprehensive subject index, a title index, and a report number index are included. Each entry gives the title, report number, publication frequency, date, number of pages, and ordering information

[en] This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA's energy models. Division is made for each energy type and end use sector. Nuclear electric power is included

[en] Highlights: • Government-Owned Broadband Networks (“GONs”) are sometimes funded by shifting costs to a municipal electric utility. • This shift of broadband costs to the electric utility is expected to increase electricity rates. • The effect of funding method on electricity rates is analyzed using a Difference-in-Differences estimator. • The analysis reveals sizable electric utility rates increases when the utility-funded model is used. Most Government-Owned Broadband Networks (“GONs”) are funded by city finances in some way, in some cases by shifting costs to a municipally-operated electric utility. This shift of broadband costs to the electric utility is expected to increase electricity rates, while other funding arrangements are not expected to affect electricity rates of the municipal utilities. In this article, a statistical analysis is conducted on the municipal electric utility rates of four Tennessee cities that constructed GONs in or around 2008. Using electric utility data from the Energy Information Administration, the analysis starkly reveals sizable electric utility rates increases for residential and commercial customers when the utility-funded model is used, but not for alternative funding arrangements.

[en] The purpose of the present study is to estimate the effects of the Jones Act on spot gasoline prices. Although the Jones Act pertains to the domestic shipment of all types of goods, the present study will only focus on gasoline. The present study will use data obtained from the Energy Information Administration in order to determine if the price of gasoline declined during Jones Act waiver periods. Looking at daily prices, the results regarding the effects of the Jones Act on spot gasoline prices are mixed. When using a t-test, the results indicated either that there was no significant difference or that prices were actually higher during the waiver periods. When using a first-order autoregressive model, it was found that prices were lower during the 2005 waiver period but higher during the 2012 waiver. Given these inconclusive results, it is not possible to conclude that the Jones Act restrictions contribute to higher gasoline prices. - Highlights: • I examine the effect of the Jones Act on spot gasoline prices. • I use daily price data over a seven year period. • I find that the results are mixed. • For the Hurricane Katrina waiver, prices fell, but for the Hurricane Sandy waiver, prices rose

[en] The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's short-term energy outlook (STEO) and the futures market for the period from 1998 to 2004. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and US wellhead natural gas prices and between Henry Hub and US wellhead spot prices. The results indicate that, on average, Henry Hub is a slightly better predictor of natural gas prices with an average error of -0.52 and a standard deviation of 1.25 than STEO with an average error of -0.83 and a standard deviation of 1.34. In addition, the results reveal that during the 13-24 months of the 2-year ahead forecast, STEO is a biased predictor of natural gas prices. This analysis suggests that as the futures market continues to report longer forward prices (currently out to 5 years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work

[en] This publication presents 5 years (1990--94) of summary financial data and current year detailed financial data on the major publicly owned electric utilities. Generator and nongenerator summaries are presented. Composite tables present: Aggregates of income statement and balance sheet data, financial indicators, electric operation and maintenance expenses, electric utility plant, number of consumers, sales of electricity, and operating revenue, and electric energy account data

[en] According to the long-term scenarios of the International Energy Agency (IEA) and the US Energy Information Administration (EIA), conventional oil production is expected to grow until at least 2030. EIA has published results from a resource-constrained production model which ostensibly supports such a scenario. The model is here described and analyzed in detail. However, it is shown that the model, although sound in principle, has been misapplied due to a confusion of resource categories. A correction of this methodological error reveals that EIA's scenario requires rather extreme and implausible assumptions regarding future global decline rates. This result puts into question the basis for the conclusion that global 'peak oil' would not occur before 2030.

[en] Concerns over impacts from U.S. energy use on the environment, the economy and the national security warrant an understanding of the key drivers of energy consumption. This paper focuses on decomposing U.S. household energy consumption changes into several factors that have affected its growth. The interval analyzed is based on household surveys conducted by the U.S. Energy Information Administration from 1980 through 2005. Drivers of total household energy consumption, total household electricity consumption and natural gas use for space heating are analyzed and contrasted. While not definitive, sub-period analyses split at 1990, show greater reductions in energy intensity in the later sub-period and provide prima fascia evidence of the efficacy of U.S. efforts to promote energy efficiency through various standards and programs. - Highlights: ► Three decompositions of household energy use are developed using household surveys. ► For total energy and NG, region, housing type and weather had different effects. ► For electricity consumption, these effects all acted to increase energy intensity. ► The change in NG heating use attributed to a 2.0 quads reduction in intensity. ► The 1990–2005 period exhibited intensity declines greater than in the earlier one.

[en] Highlights: • Residential electricity rates of North American utilities are analyzed. • Results show that despite some progress, dynamic pricing, active load management and EV rate options remain marginal. • Volumetric rates, in $/kWh, remain dominant, fueling concerns on the recovery of fixed cost. • A large majority of utilities are not ready for changes in load profiles. - Abstract: Over recent years, utilities supplying the residential electricity sector have struggled with a growing discrepancy between revenues and costs. The increasing share of fixed costs became difficult to recover through traditional rate structures, based on volumetric pricing. This trend is exacerbated by the increase in distributed and intermittent generation from renewable sources, and by changes in demand profiles. This study asks whether utilities across North America are adapting to these changes and taking advantage of dynamic pricing tools and demand response technologies, by taking stock of common tariffing practices to see if utilities do implement rates better tailored to support these transformations. We look at the U.S. Energy Information Administration's national survey, and then refine our analysis with 31 cases across North America. By looking at utilities’ current rate practices with regard to dynamic pricing, distributed generation, the integration of new technologies, demand response possibilities, as well as electric vehicle recharge, this exploration makes it clear that a large majority are not ready for these challenges and must innovate rapidly. Moreover, regulatory agencies must ensure that utilities do have the option of designing rates that move away from volume-based pricing and allow for the deployment of sophisticated demand response management.