Office of Energy Efficiency and Renewable Energy, Department of Energy.
Notice of data availability; request for comment.
The U.S. Department of Energy (DOE) seeks information related to potential technical improvements its energy conservation standards rulemaking analysis, and requests comment on corresponding revisions to the analysis for energy conservation standards for refrigerators, refrigerator-freezers and freezers.
Written comments and information are requested on or before March 24, 2011.
Interested persons are encouraged to submit comments using the Federal eRulemaking Portal at http://www.regulations.gov. Follow the instructions for submitting comments. Alternatively, interested persons may submit comments, identified by docket number EE-2008-BT-STD-0012, by any of the following methods:
- E-mail: to ResRefFreez-2008-STDemail@example.com. Include EE-2008-BT-STD-0012 in the subject line of the message.
- Mail: Ms. Brenda Edwards, U.S. Department of Energy, Building Technologies Program, Mailstop EE-2J, Equipment Price Forecasting in Energy Conservation Standards Analysis, EE-2008-BT-STD-0012, 1000 Independence Avenue, SW., Washington, DC 20585-0121. Phone: (202) 586-2945. Please submit one signed paper original.
- Hand Delivery/Courier: Ms. Brenda Edwards, U.S. Department of Energy, Building Technologies Program, 6th Floor, 950 L'Enfant Plaza, SW., Washington, DC 20024. Phone: (202) 586-2945. Please submit one signed paper original.
Instructions: All submissions received must include the agency name and docket number for this rulemaking.
Docket: For access to the docket to read background documents, or comments received, go to the Federal eRulemaking Portal at http://www.regulations.gov.Start Further Info
FOR FURTHER INFORMATION CONTACT:
Requests for additional information may be sent to Mr. John Cymbalsky, U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Building Technologies Program, EE-2J, 1000 Independence Avenue, SW., Washington, DC 20585-0121. Telephone: 202-586-4617. E-mail: Lucas.Adin@ee.doe.gov.
In the office of the General Counsel, contact Ms. Elizabeth Kohl, U.S. Department of Energy, Office of the General Counsel, GC-71,1000 Independence Ave., SW., Room 6A-179, Washington, DC 20585. Telephone: 202-586-7796; E-mail: Elizabeth.Kohl@hq.doe.gov.End Further Info End Preamble Start Supplemental Information
On January 18, 2011, the President issued Executive Order (the Order) 13563, meant to ensure that regulations seek more affordable, less intrusive means to achieve policy goals, and that agencies give careful consideration to the benefits and costs of those regulations. Among other things, the Order requires agencies propose or adopt a regulation only upon a reasoned determination that its benefits justify its costs, the regulation imposes the least burden on society consistent with obtaining the regulatory objectives, and that in choosing among alternative regulatory approaches, agencies choose those approaches that maximize net benefits.
The Order also contains provisions that bear on the analysis of benefits and costs. It provides that agencies must “use the best available techniques to quantify anticipated present and future benefits and costs as accurately as possible.” In subsequent guidance on February 2, 2011, the Office of Information and Regulatory Affairs explained that such techniques include “identifying changing future compliance costs that might result from technological innovation or anticipated behavioral changes.”
In light of the Order, DOE has examined its processes for establishing energy efficiency standards for consumer products and commercial equipment. In examining its analytical approaches for developing these regulations, DOE has developed a supplemental approach to help quantify the impacts flowing from the setting of efficiency levels for a given product or equipment. This approach is intended to improve accuracy in the assessment of future compliance costs. As part of this notice, DOE is soliciting comment on the potential inclusion of this approach for its future rulemaking activities. Additionally, DOE is seeking comment on the merits of adopting this approach within the context of its ongoing rulemaking to set standards for refrigerators, refrigerator-freezers, and Start Printed Page 9697freezers (collectively, “refrigeration products”).
Price Forecast Methodology
One of the key estimates that DOE currently makes during the analysis of energy conservation standards is the impact of efficiency regulations on equipment price. DOE uses its engineering analysis—which determines a given appliance's cost as a function of its efficiency (through the development of cost-efficiency curves)—as the basis for estimating these equipment price impacts. The technology costs derived in the engineering analyses form the basis for product prices used in the national impact analysis that estimates regulatory impacts for products sold over the 30-year analysis period. Consequently, the price projections affect the economic impacts calculated for any potential energy conservation standard levels.
Currently, DOE's analyses assume that the manufacturer costs and retail prices of products meeting various efficiency levels remain fixed, in real terms, after the compliance date and throughout the period of the analysis. This assumption is conservative. Examination of historical price data for certain appliances and equipment that have been subject to energy conservation standards indicates that the assumption of constant real prices and costs may, in many cases, over-estimate long-term appliance and equipment price trends. Economic literature and historical data suggest that the real costs of covered products and equipment may in fact trend downward over time according to “learning” or “experience” curves. A draft paper, “Using the Experience Curve Approach for Appliance Price Forecasting,” posted on the DOE Web site along with this notice at http://www.eere.energy.gov/buildings/appliance_standards, provides a summary of the data and literature currently available to DOE that is relevant to price forecasts for selected appliances and equipment.
In light of these data and DOE's aim to improve the accuracy and robustness of its analyses, DOE is considering assessing future costs by incorporating learning over time, consistent with the analysis in the currently available literature, in its analysis of regulatory options in the energy conservation standards for refrigeration products, in an attempt to create a more accurate and robust forecast of the pricing effects that accompany amended energy efficiency standards for these products. The consequences of this approach are outlined below. DOE is also considering applying this approach generally to its energy conservation standards-related analyses for appliance and commercial equipment.
DOE seeks comment on the merits of this approach, particularly with respect to its application to an analysis of potential energy efficiency standards for refrigeration products and the data presented in this notice.
In addition, DOE requests information regarding the potential for improving the methodology for projecting the cost of efficiency improvements over the analysis period in general. DOE provides additional background in the following paragraphs and seeks input on three broad categories: (1) Data sources; (2) potential methodologies; and (3) procedural issues.
Forecast Method. An extensive economic literature discusses the “learning” or “experience” curve phenomenon, typically based on observations in the manufacturing sector. In the experience curve method, the real cost of production is related to the cumulative production or “experience” with a product. To explain the empirical relationship, the theory of technology learning is used to substantiate a decline in the cost of producing a given product as firms accumulate experience with the technology. A common functional relationship used to model the evolution of production costs in this case is:
Y = aX−b,
where a is an initial price (or cost), b is a positive constant known as the learning rate parameter, X is cumulative production, and Y is the price as a function of cumulative production. Thus, as experience (production) accumulates, the cost of producing the next unit decreases. The percentage reduction in cost that occurs with each doubling of cumulative production is known as the learning rate (LR), given by:
LR = 1−2−b
DOE's current price forecast methodology is a special case of the forecast equations specified above, but to date, DOE has assumed that the learning rate parameter is 0 in its energy conservation standards analysis. This notice describes an approach for improving this assumption and estimating non-zero learning rate parameters consistent with historical cost data.
Data. In typical learning curve formulations, the learning rate parameter is derived using two historical data series: Cumulative production and price (or cost). On the basis of previous rulemakings, DOE is aware of several relevant data sets. Annual shipments (for calculating cumulative production) of several appliances can be found in industry publications (e.g., Appliance Magazine) and industry association (e.g., the Air-Conditioning, Heating, and Refrigeration Institute (AHRI), the Association of Home Appliance Manufacturers (AHAM) Fact Book, etc.) data sets. Historical shipment-weighted efficiency data could be gathered from these sources, as well as from the Energy Information Administration (EIA). Historical price or cost data for several products could be derived from the Bureau of Labor Statistics' (BLS) Producer Price Index (PPI) and/or Consumer Price Index (CPI).
Table 1 provides these data for refrigerators, refrigerator-freezers, and freezers (including compacts). The inflation-adjusted price index is derived from CPI data for 1947 to 1997 and PPI data from 1998 to 2009. The inflation-adjusted price is derived from a current price estimate for refrigerator-freezers that is then scaled over time by the inflation-adjusted price index. DOE estimates that cumulative refrigerator, refrigerator-freezer, and freezer shipments are 22.22 million in 1946 and then they increase each year with the current year shipments.Start Printed Page 9698
|Year||Inflation-adjusted price index||Inflation-adjusted price (2009$)||Shipments (millions)||Cumulative Shipments (millions)|
Application to Standards. Given the information currently available to DOE, DOE believes (and invites comments on the view that) the following methodology may provide the most accurate method for forecasting the incremental cost of efficiency given the potential impact of long-term product price trends or technological learning:Start Printed Page 9699
- When sufficiently long-term data are available on the cost trends for equipment or technologies for particular efficiency design options, an empirical experience curve fit to the available data may be used to forecast future costs of such design option technologies. If a statistical evaluation indicates a low level of confidence in estimates of the design option cost trend, this method should not be used to forecast costs.
- When sufficiently long term data are not available for forecasting the cost of products or equipment using specific efficiency-improving components, the experience curve cost trend for the product or equipment as a whole should be applied to both the product or equipment price and the incremental product or equipment price.
- When sufficiently long term data are not available for a specific product or equipment, it may be appropriate to apply the experience curve cost trend for a similar product or equipment, or a product or equipment grouping that includes the product or equipment at issue, to both the product or equipment price and the incremental product or equipment price. Alternatively, DOE may use experience curve parameters from review studies that may indicate that certain parameter ranges apply to certain classes or groups of products or equipment that include the product or equipment under analysis. If data are not available for estimating a price trend, DOE may use a constant real price trend as in past rulemakings.
In other words, when data are available to help guide DOE in projecting potential cost reductions over time for a particular appliance or equipment, DOE plans to use these data as part of its analyses. In those instances where such data are unavailable, DOE will continue to employ the methods it currently uses, which is to hold costs at a fixed level for purposes of long-term impact projections.
For the energy conservation standards analysis for refrigerators, refrigerator-freezers and freezers, long-term data are available on overall product costs. DOE is therefore considering use of the long term trend in product price to forecast the long term trend in the incremental cost of efficiency. DOE posts updated national impact analysis spreadsheets that incorporate price trend forecasting at http://www.eere.energy.gov/buildings/appliance_standards for public review.
To improve the accuracy and reliability of price forecasts, DOE may periodically review the performance of equipment and incremental efficiency cost forecasts and may make further methodological improvements that improve forecast accuracy and reliability.
In the next section, DOE seeks information on all of the issues covered in this section, as well as additional topics.
General Discussion of Potential Consumer Welfare Impacts
DOE also notes that the economics literature provides a wide-ranging discussion of how consumers trade-off upfront costs and energy savings in the absence of government intervention. Much of this literature attempts to explain why consumers appear to undervalue energy efficiency improvements. This undervaluation suggests that regulation that promotes energy efficiency can produce significant net private gains (as well as producing social gains by, for example, reducing pollution). There is evidence that consumers undervalue future energy savings as a result of (1) a lack of information, (2) a lack of sufficient savings to warrant delaying or altering purchases (e.g. an inefficient ventilation fan in a new building or the delayed replacement of a water pump), (3) inconsistent (e.g. excessive short-term) weighting of future energy cost savings relative to available returns on other investments, (4) computational or other difficulties associated with the evaluation of relevant tradeoffs, and (5) a divergence in incentives (e.g. renter versus owner; builder v. purchaser). In the abstract, it may be difficult to say how a welfare gain from correcting under-investment compares in magnitude to the potential welfare losses associated with no longer purchasing a machine or switching to an imperfect substitute, both of which still exist in this framework.
Other literature indicates that with less than perfect foresight and uncertainty about the future, consumers may trade off these types of investments at a higher than expected rate between current consumption and uncertain future energy cost savings. Some studies suggest that this seeming undervaluation may be explained in certain circumstances by differences between tested and actual energy savings, or by uncertainty and irreversibility of energy investments.
The mix of evidence in the empirical literature suggests that if feasible, analysis of regulations mandating energy efficiency improvements should explore the potential for both welfare gains and losses and move toward fuller economic framework where all relevant changes can be quantified. While DOE is not prepared at present to provide a fuller quantifiable framework for this discussion, DOE seeks comments on how to assess these issues.
Issues on Which DOE Seeks Comment and Information
1. DOE seeks data related to observed trends in historical costs, retail prices, and shipment efficiencies of products and equipment covered by the Energy Conservation Standards program.
2. DOE seeks data related to observed trends in historical costs, retail prices, and shipment efficiencies of products and equipment that, while not covered by the Energy Conservation Standards program, may be of use to DOE with respect to its treatment of technology learning curves and consumer welfare impacts.
3. DOE seeks data related to historical costs and prices of covered products and equipment delineated by efficiency level.
4. DOE seeks information on the appropriate range of values for learning parameters found in the relevant literature, either in the aggregate or associated with specific appliances, equipment, technologies, or production processes.
1. DOE specifically seeks comment on the methodology described in the “Background” section above.
2. DOE seeks information on alternative methodologies for forecasting equipment price trends in its analyses.
3. DOE seeks comment on how changes in other product attributes, including efficiency, could be “ normalized” or “corrected” based on historical data.
4. DOE seeks comment on methods for calculating changes in historical costs or prices, including the use of the PPI and CPI.
5. DOE seeks comment on methods of deriving historical production volumes.
6. DOE seeks comment on the details of the method, data and references Start Printed Page 9700described in the draft paper “Using the Experience Curve Approach for Appliance Price Forecasting” posted on the DOE Web site at http://www.eere.energy.gov/buildings/appliance_standards.
7. DOE seeks comment on data sources and analytical methods for estimating potential consumer welfare impacts from energy conservation standards, including information on specific consumer subgroups of products regulated under the energy conservation program.
1. DOE seeks comment on the details of how equipment price forecasts and consumer welfare impacts may be incorporated into specific downstream analyses that rely on the engineering analysis outputs and what other methodological changes to those analyses might be merited.
2. DOE seeks comment on products or equipment, or groups of products or equipment, that are likely to have the greatest and least improvement in price forecast accuracy from the application of experience curve methodology.
3. DOE seeks information on alternative methods for modeling persistent price trends for regulated products or equipment.
General Analysis Methodology
1. DOE seeks comments and information regarding additional ways of improving the accounting of costs and benefits in its energy conservation standards analysis, including comment on benefits and costs that may not have been included in energy conservation standards analyses to date.
2. DOE seeks information on how standards can affect the dynamics of innovation and investment in U.S. appliance and equipment industries.
3. DOE seeks comment on ways in which standards-induced innovation and investment might impact the competitiveness of U.S. products and companies in the global marketplace.
4. DOE seeks comment on the additional global benefits that may arise from standards that may encourage U.S. appliances and equipment to have efficiency performance levels exceeding the efficiency performance levels of appliances and equipment in other countries.
The purpose of this NODA is to solicit feedback from industry, manufacturers, academia, consumer groups, efficiency advocates, government agencies, and other stakeholders on issues related price forecasts in DOE's engineering analyses for Energy Conservation Standards rulemakings. DOE is specifically interested in information and sources of data related to covered products and equipment that could be used in formulating a methodology regarding long term equipment price forecasts, and a methodology regarding consumer welfare impacts. Respondents are advised that DOE is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted under this NODA. Responses to this NODA do not bind DOE to any further actions related to this topic.Start Signature
Issued in Washington, DC, on February 15, 2011.
Assistant Secretary, Energy Efficiency and Renewable Energy.
1. See, for example, the review paper: Weiss, M., Junginger, H.M., Patel, M.K., Blok, K., (2010a). A Review of Experience Curve Analyses for Energy Demand Technologies. Technological Forecasting & Social Change. 77:411-428, which provides an extensive list of studies that have performed experience curve analyses.Back to Citation
2. A good review of the literature related to this issue can be found in Gillingham, K., R. Newell, K. Palmer. (2009). “Energy Efficiency Economics and Policy,” Annual Review of Resource Economics, 1: 597-619; and Tietenberg, T. (2009). “Energy Efficiency Policy: Pipe Dream or Pipeline to the Future?” Review of Environmental Economics and Policy. Vol. 3, No. 2: 304-320.Back to Citation
3. A draft paper, “Notes on the Economics of Household Energy Consumption and Technology Choice,” proposes a broad theoretical framework on which an empirical model might be based and is posted on the DOE Web site along with this notice at http://www.eere.energy.gov/buildings/appliance_standards.Back to Citation
[FR Doc. 2011-3873 Filed 2-18-11; 8:45 am]
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