Review of Key International Demand Elasticities for Major Industrializing Economies
This report conducts a selective review of various estimates for energy demand responses. It emphasizes recent empirical studies that include trends from studies published after 2000. Emphasis is placed on the five major emerging or transitional economies in Brazil, China, India, Mexico and Russia, although other important nations like Chile and South Korea are also discussed when studies are available.  The review focuses attention on the long-run responses to changes in prices and income after capital stock turnover has been completed. The terminology often refers to elasticities, or the percentage change in energy use divided by the percentage change in price (or income), holding constant all other factors that could influence energy-use decisions. Most studies have focused upon household and transportation use of liquid fuels; many fewer studies have investigated fuels used by industry or commerce or for electric generation. Based upon the available estimates, price and income elasticities for liquid fuels are generally less than one (unity) for many countries and sectors, except for the long-run income effect for transportation purposes, which can range widely by country between 0.24 and 1.75 while averaging 0.94 for all countries.

released: January 2018; contact author(s): Vipin Arora

The Relationship between Oil Prices and Exchange Rates: Theory and Evidence
This paper reviews existing theoretical and empirical research on the relationship between oil prices and exchange rates. We start with theoretical transmission channels—which point to bi-directional causality. Empirical research—focused on either explaining or forecasting one variable with the other—shows that the evidence varies substantially depending on sample, country choice and empirical method. Yet there are some common patterns: (i) strong links between exchange rates and oil prices are frequently observed over the long-run; and (ii) either exchange rates or oil prices are a potentially useful predictor of the other variable in the short-run, but the effects are strongly time-varying. We also identify some important avenues for future research such as addressing time-varying predictability and optimal sample choice for forecasting.

released: June 2017; contact author(s): Vipin Arora

Oil Prices and Stock Markets
We reviewed literature on the complex relationship between oil prices and stock market activity. The majority of papers surveyed study the impacts of oil markets on stock markets—little research in the reverse direction exists. In general, we find that the causal effects between oil and stock markets depend heavily on whether research is performed using aggregate stock market indices, sectoral indices, or firm-level data—and whether stock markets operate in net oil-importing or net oil-exporting countries. Additionally, conclusions vary depending on whether studies use symmetric or asymmetric changes in the price of oil, or whether they focus on unexpected changes in oil prices. Finally, we find that most studies show oil price volatility transmits to stock market volatility, and that including measures of stock market performance improves forecasts of oil prices and oil price volatility

released: June 2017; contact author(s): Vipin Arora

Oil-Consumption-Weighted GDP: Description, Calculation, and Comparison
We outline an alternative measure of gross domestic product (GDP) for regional country groupings that accounts for the relative level of oil consumption within each of the component countries. This analysis specifically focuses on aggregate oil-weighted GDP indices for the OECD (Organization for Economic Cooperation and Development), non-OECD, and world. We detail the calculation of this oil-weighted GDP index and compare growth rates for the OECD, non-OECD, and world with those from GDP series based on purchasing power parity (PPP) and market exchange rates (MER). We then explore these differences by showing how oil intensity—oil consumption as a share of GDP—varies for these groups based upon the GDP series used.

released: May 2016; contact author(s): Vipin Arora, Tyler Hodge, and Tancred Lidderdale

Aggregate Productivity under an Energy-Based Approach
Obtaining reliable data on capital is a recurring challenge when estimating economy-wide productivity growth, especially for developing countries. In this paper, I construct energy-based productivity series, which use energy consumption instead of capital when making such estimates. I first show that—for the U.S. and select OECD countries—growth in the energy-based series is strongly correlated with other sources historically. I then estimate energy-based productivity growth for other OECD and non-OECD countries where data on capital and productivity is more limited.

released: May 2016; contact author(s): Vipin Arora

Currency Conversion and Energy Projections: Some Questions and Answers
International economic models—particularly those with an energy component—need to work in a common currency when using concepts such as GDP. Such conversions can be done using market exchange rates (MER)—those you hear about on the news every night—or purchasing power parity (PPP) exchange rates, which you learned about a long time ago and never wanted to see again. While both have strengths and weaknesses, PPP exchange rates are appropriate when generating energy projections.  I discuss why in this paper, covering common questions about each type of exchange rate—from how they are calculated or determined to their appropriate use.

released: November 20, 2015; contact author(s): Vipin Arora

Energy Production and Trade: An Overview of Some Macroeconomic Issues
Large increases in American oil and gas production have opened a debate about relaxing export restrictions on crude oil and natural gas. Unfortunately, many of the approaches used to defend opposing positions can be difficult to understand and follow. This paper attempts to review, outline, and clarify some of the key points associated with trade theory, evidence, and data as they relate to energy exports and macroeconomics. The goal is to sketch a framework for thinking about energy production and trade that fits with standard macroeconomic theory, both in international trade and international finance.

released: November 19, 2014; contact author(s): Vipin Arora

Electricity Use as an Indicator of U.S. Economic Activity
We argue for the resurrection of an old idea: electricity use as an indicator of U.S. economic activity. Our analysis relies on associations–the 40-year correlation between growth rates in real GDP and electricity use can be as high as 89% –and intuition. Electricity use and economic conditions should move together. The vast majority of goods and services are still produced using electricity; services may require less electricity, but they still require some. Electricity use also has other strengths –it is broad-based and the data are available weekly, possibly hourly by 2015.

released: November 19, 2014; contact author(s): Vipin Arora, Jozef Lieskovsky

Alternative Measures of Welfare in Macroeconomic Models
The impacts and costs and benefits of different policies and scenarios can be calculated in several different ways. The measure chosen often depends on the class of model employed and the purposes of the policy and/or study. The sum total of costs and benefits, or changes in costs and benefits, is termed welfare. Traditionally, EIA has used measures such as GDP, consumption, and unemployment (among others) as ways to describe the overall economic impacts of policies, mainly highlighting changes in consumption as a proxy for welfare. Using a variety of different measures of welfare to evaluate policy changes is desirable. This is particularly true in the case of utility, which is unique because it can incorporate the direct and indirect costs and benefits of different policies. Given the assumptions and complications required to make welfare calculations using the current NEMS setup, using a CGE model to make such calculations is a good option.

released: December 11, 2013; contact author(s): Vipin Arora

The Price Elasticity of U.S. Shale Oil Reserves
We formulated a model of shale oil development that identifies how much of the U.S. resource base is likely to be economically viable at various price levels, and what share of potential drilling sites are likely to be exploited. The analysis is driven by the lognormal variability in productivity of individual wells.

released: July 2017; contact author(s): Thomas Lee, James L. Smith

Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump
This paper provides a comprehensive analysis of the forecastability of the real U.S. price of gasoline, drawing on state-of-the-art regression-based forecasting methods.

released: July 15, 2015; contact author(s): Thomas K. Lee

Incorporating International Petroleum Reserves and Resource Estimates into Projections of Production
This paper describes EIA's petroleum reserves and resource assessment methodology, comparable long-term outlooks' approaches to resource uncertainties, production decline rates, resource terminology, and the available estimates.

released: June 7, 2011; contact author(s): John Staub

Projecting the scale of the pipeline network for CO2-EOR and its implications for CCS infrastructure development
This paper looks at the required infrastructure construction to support NEMS projections of CO₂ use for oil recovery.  It considers the scale of the infrastructure and potential implications for adaptation of it for CO2 transport for CCS.

released: October 25, 2010 | author(s): Mathew Tanner

The Challenge of Achieving California's Low Carbon Fuel Standard
Paper looks at California’s Low Carbon Fuel Standard (LCFS) reductions in the carbon intensities (CIs) of both gasoline and diesel transportation fuel types and compliance scenarios envisioned by CARB to meet the LCFS schedule.

released: May 24, 2010; revised July 16, 2010; contact author(s): Peter Gross

On Inaccuracies in a Published Journal Article
The article referenced above analyzes the renewable electricity results from the Reference case scenarios of several successive historical editions of EIA's Annual Energy Outlook (AEO). It makes a retrospective analysis of these results, infers (incorrectly) that the NEMS model is fundamentally flawed, and on that basis calls into question its utility for policy analysis.

released: May 2016; contact author(s): Chris Namovicz, David Daniels

A Network-Based View of the U.S. Energy Sector
We describe portions of the U.S input-output tables through the tools of networks analysis—focusing on industries that are either energy intensive or part of the energy sector. We first represent both energy intensives and the energy sector visually through network diagrams for the years 1997, 2002, and 2007. Next, we show that the energy sector is generally more densely connected than either energy intensives or all industries over those years, and is more likely to have groups of three sub-sectors all linked as well.

We then move to the level of individual industries within the broad sectors and find that energy intensive industries have the most in-coming connections on average for these tables.  Energy sector ones have fewer, but the number grows over time, as do outgoing connections. Other measures of centrality—closeness and betweenness—vary over time for both the energy sector and energy intensives. In terms of specific industries, petroleum refining and electricity generation stand out for their centrality, drilling oil and gas wells for its lack of centrality.

released: January 2016; contact author(s): Vipin Arora and Elizabeth Sendich

CHP Industrial Bottoming and Topping Cycle with Energy Information Administration Survey Data
The Energy Information Administration (EIA) Form 860 Survey data of electricity generators from 2013 is used to analyze the current state of the Combined Heat and Power (CHP) industrial bottoming and topping cycle. The bottoming cycle is the focus of the paper since this approach to CHP is underutilized and also presents challenges in addition to those for the topping cycle.  CHP technology is overviewed before the data analysis is presented.

released: August 17, 2015; contact author(s): Paul Otis

Update to Industrial drivers in the AEO2015 as a result of new input-output data
This paper will discuss major methodological changes for macroeconomic modeling of the industrial sector from the AEO2014 to the AEO2015, highlighting how industrial sector output (agriculture, mining, construction, and manufacturing) and explanatory GDP components, also called final demand categories, affect the projection of industrial output. It will focus on how BEA's IO table updates, combined with greater use of available data, have changed the relationship between final demand and supply chain requirements and industry output across various aggregates of the industrial sector.

released: May 4, 2015; contact author(s): Elizabeth Sendich

Natural Gas and U.S. Industrial Production: A Closer Look at Four Industries
We consider the relationship between natural gas prices and production in the U.S. resins, agricultural chemicals, cement, and aluminium industries. Overall, our analysis using various tests and regressions does not allow for generalizations about the association between natural gas prices and production across these four energy-intensive industries. Rather, the relationships between natural gas and production appear to be driven by the particular institutional details of each industry.

released: August 30, 2014; contact author(s): Vipin Arora and Elizabeth Sendich

The Flight Paths for Biojet Fuel
Jet fuel is a 22-billion-gallon per year market in the United States and about 80 billion gallons per year worldwide. Biofuels have made inroads into gasoline and diesel fuel supplies, but are only beginning to enter the jet fuel market. "Biojet" is a term that describes fuel made from renewable, biologically-derived raw materials and, once blended with petroleum jet fuel, is suitable for use in an unmodified jet engine. "Alternative jet fuel" is a more general term that describes jet fuel blending components made from biogenic and fossil (e.g. coal, natural gas, industrial waste gases, or the non-biogenic portion of municipal solid waste) feedstocks. There are several reasons for interest in biojet. Airlines and the U.S. Department of Defense are looking to biojet to diversify fuel supplies and lower fuel costs in the long run. As with other transportation modes, greenhouse gases are a concern for aviation. The International Civil Aviation Organization (ICAO), the United Nations body that sets standards and recommended practices for international aviation, has set a goal for international aviation to achieve carbon-neutral growth from 2020.

released: October 9. 2015; contact author(s): Tony Radich

Issues and Methods for Estimating the Share of Ethanol in the Motor Gasoline Supply
This paper describes publicly available fuel ethanol data and suggests methodologies to estimate the percentage of ethanol used in the United States gasoline supply. These methods, which use historical U.S. Energy Information Administration (EIA) survey data and information from other sources, involve calculations based on motor gasoline and ethanol production, net imports, and inputs into refineries and blenders.

released: October 13, 2011; contact author(s): Tony Radich and Sean Hill

The Resource Hierarchy Relationship
Estimates of technically recoverable resource (TRR) are a necessary part of any long-term projection of future hydrocarbon production. TRR can be related to economically recoverable resources (ERR) and original resource in-place (ORIP) by the following relation: 0 <= ERR <= TRR <= ORIP. It is therefore possible to indirectly bound TRR within the context of ERR and in-place estimates, as opposed to estimating it directly.

Estimates of TRR have an implicit or explicit relationship to price, and the accompanying application of technology or industry practice allowed by that price. TRR can be estimated without solving for the upper constraint of total resource size, but a more thorough understanding of the total resource equation is obtained by including the geologically based upper limit.

released: September 27, 2015; contact author(s): Troy Cook

Improving Well Productivity Based Modeling with the Incorporation of Geologic Dependicies
The U.S. Energy Information Administration (EIA) utilizes supply-side modeling of well-level performance measures quantified at the county level for resource plays. Well performance, however, does not depend upon political boundaries. Aligning well-productivity with underlying geologic dependencies will improve production projections by better quantifying the area, and the well-performance in that area, of potential future development.

The choice of geologic dependencies can be as flexible and numerous as time and resources permit, or a derivative product of multiple dependencies. The summation of the well-performance and area is also a reasonable method to estimate an amount of resource that might be recoverable under a given set of technological and economic conditions.

released: October 14, 2014; contact author(s): Troy Cook and Dana Van Wagener

Quantifying Drilling Efficiency
This paper examines the methods used to measure drilling efficiency and the difficulties encountered when using various data sources. The analysis exames the technologies used before, during, and after rotary rig iperation which shape overall productivity results.

released: August 13, 2010; author(s): John Cochener

Global Natural Gas Overview: A Report Prepared by Leidos, Inc., Under Contract to EIA
The attached report, prepared by Leidos, Inc., under contract to EIA, provides a broad overview of today's global natural gas markets, possible drivers of the evolution of the global gas market, and a high level overview of select economic theories that may be applied to describe basic market interactions in current and future global natural gas markets.

released: August 26, 2014; contact author(s): Angelina LaRose

The Information Role of Spot Prices and Inventories
Using a rational expectations approach, we show why and how differences in beliefs, as well as the volume of speculative futures trading, may vary across commodities and through time. We demonstrate that equilibrium differences in beliefs are determined by characteristics of the underlying commodity, including storage costs, the amplitude of shocks, the accuracy of information available to informed investors, the numbers of informed and uninformed traders, and the elasticity of demand and supply. We also demonstrate that passive investors magnify equilibrium differences in beliefs and expand the scope for financial speculation--even though they do not themselves speculate. Finally, we argue that fundamental determinants of speculative futures trading may have been misinterpreted by some as "excessive" speculation in the energy markets in recent years.

released: June 24, 2014; contact author(s): Thomas Lee

Are there Gains from Pooling Real-Time Oil Price Forecasts?
The answer depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years. Even more accurate forecasts, however, are obtained when allowing the forecast combinations to vary across forecast horizons. While the latter approach is not always more accurate than selecting the single most accurate forecasting model by horizon, its accuracy can be shown to be much more stable over time. The MSPE of real-time pooled forecasts is between 3% and 29% lower than that of the no-change forecast and its directional accuracy as high as 73%. Our results are robust to alternative oil price measures and apply to monthly as well as quarterly forecasts. We illustrate how forecast pooling may be used to produce real-time forecasts of the real and the nominal price of oil in a format consistent with that employed by the U.S. Energy Information Administration in releasing its short-term oil price forecasts and we compare these forecasts during key historical episodes.

released: February 14, 2014; contact author(s): Thomas Lee

Contango in Cushing? Evidence on Financial-Physical Interactions in the U.S. Crude Oil Market
While there has been considerable focus, especially in the aftermath of the 2007-08 oil price spike, on the role of financial speculators in influencing oil prices, a question that lies at the heart of this debate -- how oil futures trading is related to spot oil prices — remains unresolved. A financial speculator who expects future oil prices to rise and wants to take a speculative position based on this expectation would typically go long in financial futures contracts. An index investor who wants to invest in oil will take a similar long position in futures contracts, which would be rolled over periodically. If such speculative or investment activity increases the futures price sufficiently relative to the prevailing spot price, a rational market response would be for arbitrageurs to step in to buy oil in the spot market and store it while simultaneously selling futures.

released: March 23, 2012; contact author(s): Thomas Lee

Implications of Changing Correlations Between WTI and Other Commodities, Asset Classes, and Implied Volatility
Crude oil price movements are constantly changing as the market reacts to new information regarding current production, consumption and inventory levels of crude oil and petroleum products. Oil prices are also affected by changes in the market’s expectations of the future supply and demand balance. Depending on market conditions and sentiment, different time periods can have news and events related to either supply or demand issues as the dominant factors dictating price movements. The analysis presented here attempts to identify time periods when crude oil prices are responding more to either supply or demand, relative to the other, by examining the magnitude and sign of the correlation of crude oil prices against other commodities and asset classes.

released: March 23, 2012; contact author(s): James Preciado