[Federal Register Volume 76, Number 35 (Tuesday, February 22, 2011)]
[Proposed Rules]
[Pages 9696-9700]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2011-3873]


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DEPARTMENT OF ENERGY

10 CFR Parts 430 and 431

[Docket No. EE-2008-BT-STD-0012]


Equipment Price Forecasting in Energy Conservation Standards 
Analysis

AGENCY: Office of Energy Efficiency and Renewable Energy, Department of 
Energy.

ACTION: Notice of data availability; request for comment.

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SUMMARY: 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.

DATES: Written comments and information are requested on or before 
March 24, 2011.

ADDRESSES: 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:
    <bullet> E-mail: to <a href="/cdn-cgi/l/email-protection#1240776140777454607777683f2022222a3f4146563f22222320527a633c767d773c757d64"><span class="__cf_email__" data-cfemail="81d3e4f2d3e4e7c7f3e4e4fbacb3b1b1b9acd2d5c5acb1b1b0b3c1e9f0afe5eee4afe6eef7">[email protected]</span></a>. Include 
EE-2008-BT-STD-0012 in the subject line of the message.
    <bullet> 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.
    <bullet> 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.

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: <a href="/cdn-cgi/l/email-protection#0e427b6d6f7d204f6a67604e6b6b206a616b20696178"><span class="__cf_email__" data-cfemail="f3bf86909280ddb2979a9db39696dd979c96dd949c85">[email protected]</span></a>.
    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: <a href="/cdn-cgi/l/email-protection#1e5b7277647f7c7b6a7630557176725e766f307a717b30797168"><span class="__cf_email__" data-cfemail="97d2fbfeedf6f5f2e3ffb9dcf8fffbd7ffe6b9f3f8f2b9f0f8e1">[email protected]</span></a>.

SUPPLEMENTARY 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

[[Page 9697]]

freezers (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.

Background

    Forecast Method. An extensive economic literature discusses the 
``learning'' or ``experience'' curve phenomenon, typically based on 
observations in the manufacturing sector.\1\ 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:
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    \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.

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Y = aX<SUP>-b</SUP>,

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<SUP>-b</SUP>
    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.

[[Page 9698]]



                         Table 1--Historical Data Regarding Refrigerator, Refrigerator-Freezer, and Freezer Prices and Shipments
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                                                         Inflation-adjusted       Inflation-adjusted                               Cumulative Shipments
                        Year                                price index             price  (2009$)       Shipments  (millions)          (millions)
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1947................................................                     3.95                   $4,132                     4.01                    26.23
1948................................................                     4.03                    4,218                     5.46                    31.68
1949................................................                     3.96                    4,144                     4.94                    36.62
1950................................................                     3.83                    4,001                     7.09                    43.71
1951................................................                     3.73                    3,906                     5.09                    48.79
1952................................................                     3.52                    3,686                     4.60                    53.39
1953................................................                     3.37                    3,522                     4.69                    58.08
1954................................................                     3.12                    3,258                     4.65                    62.73
1955................................................                     2.94                    3,071                     5.27                    68.00
1956................................................                     2.50                    2,611                     4.78                    72.78
1957................................................                     2.22                    2,326                     4.45                    77.23
1958................................................                     2.09                    2,186                     4.23                    81.45
1959................................................                     2.07                    2,164                     4.91                    86.36
1960................................................                     1.99                    2,081                     4.61                    90.98
1961................................................                     1.94                    2,032                     4.63                    95.61
1962................................................                     1.88                    1,967                     4.94                   100.56
1963................................................                     1.81                    1,890                     5.31                   105.87
1964................................................                     1.75                    1,829                     5.75                   111.61
1965................................................                     1.67                    1,747                     6.15                   117.76
1966................................................                     1.56                    1,633                     6.21                   123.97
1967................................................                     1.51                    1,581                     5.96                   129.93
1968................................................                     1.47                    1,536                     6.42                   136.35
1969................................................                     1.42                    1,482                     6.58                   142.94
1970................................................                     1.38                    1,439                     6.59                   149.53
1971................................................                     1.35                    1,410                     7.02                   156.54
1972................................................                     1.31                    1,366                     7.66                   164.21
1973................................................                     1.23                    1,289                     8.14                   172.35
1974................................................                     1.17                    1,226                     7.38                   179.73
1975................................................                     1.21                    1,262                     6.00                   185.72
1976................................................                     1.20                    1,250                     6.27                   192.00
1977................................................                     1.16                    1,217                     7.20                   199.19
1978................................................                     1.15                    1,200                     7.43                   206.62
1979................................................                     1.09                    1,137                     7.31                   213.93
1980................................................                     1.02                    1,062                     6.80                   220.73
1981................................................                     0.99                    1,031                     6.73                   227.46
1982................................................                     1.01                    1,055                     6.29                   233.75
1983................................................                     1.01                    1,055                     7.47                   241.22
1984................................................                     0.98                    1,028                     7.99                   249.20
1985................................................                     0.94                      984                     8.24                   257.44
1986................................................                     0.92                      957                     8.68                   266.12
1987................................................                     0.88                      923                     9.08                   275.20
1988................................................                     0.86                      895                     9.34                   284.53
1989................................................                     0.83                      872                     8.88                   293.41
1990................................................                     0.79                      823                     8.97                   302.37
1991................................................                     0.75                      782                     8.99                   311.37
1992................................................                     0.72                      758                     9.52                   320.88
1993................................................                     0.72                      753                     9.84                   330.72
1994................................................                     0.73                      766                    10.39                   341.11
1995................................................                     0.71                      747                    10.56                   351.68
1996................................................                     0.70                      736                    10.93                   362.60
1997................................................                     0.68                      712                    10.90                   373.51
1998................................................                     0.63                      659                    11.98                   385.49
1999................................................                     0.60                      630                    13.02                   398.51
2000................................................                     0.57                      596                    13.18                   411.69
2001................................................                     0.54                      561                    13.37                   425.05
2002................................................                     0.52                      539                    14.84                   439.89
2003................................................                     0.49                      514                    15.90                   455.79
2004................................................                     0.48                      499                    16.69                   472.48
2005................................................                     0.47                      494                    16.73                   489.21
2006................................................                     0.46                      482                    15.39                   504.60
2007................................................                     0.45                      475                    15.09                   519.69
2008................................................                     0.45                      475                    14.37                   534.06
2009................................................                     0.47                      496                    14.27                   548.34
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    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:

[[Page 9699]]

    <bullet> 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.
    <bullet> 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.
    <bullet> 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.\2\ 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.\3\
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    \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.
    \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.
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Issues on Which DOE Seeks Comment and Information

Data Sources

    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.

Potential Methodologies

    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

[[Page 9700]]

described 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.

Procedural Issues

    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.

    Issued in Washington, DC, on February 15, 2011.
Cathy Zoi,
Assistant Secretary, Energy Efficiency and Renewable Energy.
[FR Doc. 2011-3873 Filed 2-18-11; 8:45 am]
BILLING CODE 6450-01-P


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