7-A.2 TEST PROCEDURE AND FIELD STUDIES 

This section describes the DOE test procedure, then lists field studies of energy 

consumption by refrigerator-freezers and distills their results. 

7A.2.1 DOE Test Procedure 

“The DOE test is a compromise between realism and minimizing the costs of performing 

a reliable, repeatable laboratory test” (Meier, 1993). The DOE procedure for evaluating the 

annual energy consumption of refrigerator-freezers comprises the following features (10 CFR, 

Chapter II, Part 430, Appendix A1). 

•	 The standard test temperature for the fresh food compartment is 45°F. 

•	 The standard test temperature for the freezer compartment is 5°F. 

•	 The test is performed in a chamber that is maintained at an ambient temperature of 90°F. 

•	 The temperatures of the freezer and fresh food compartments are measured using three 

independent thermocouples, one for each compartment. Five thermocouples are used 

when the refrigerator height is over 40”. 

•	 The appliance’s energy consumption is calculated by interpolating test results that 

bracket the standard freezer temperature (5°F). Interpolation is done around the 5°F 

temperature (freezer compartment) and the 45°F temperature (fresh food compartment). 

•	 Ambient relative humidity is not specified. 

•	 Doors are not opened during the test. 

•	 The fresh food and freezer compartments are empty. 

•	 Ice making capability, if present, is not powered on or evaluated by the test. 

The DOE test procedure is currently undergoing a rulemaking process which may change 

some of the above details. In particular, changes have been proposed to the test temperatures for 

the refrigerator and freezer compartments. 

The DOE test procedure does not measure the effects of door opening, cooling warm 

food, or ice making. However, this test procedure provides standardized results that can serve as 

the basis for comparing the performance of appliances. Although the DOE test does not precisely 

mirror any single unit’s performance in situ, it serves as a foundation to which field 

measurements may be compared to develop estimates that account for a range of real-life 

circumstances (KEMA, 2004). 

A summary of new refrigerator-freezer unit energy consumption values provided by 

manufacturers by year shows the annual variation of shipment-weighted refrigerator energy 

consumption from 1960s to the year 2006 (Table 2.1). These data are based on “nameplate” 

values. For the model years before the DOE energy standards (1989 and earlier), the test 

conditions are unknown in which energy consumption quantities were measured, although it is 

likely that manufacturers used the American Home Appliance Manufacturers (AHAM) test 

procedure or the test procedure prescribed by California state energy conservation standards. 

7-A-2 

EERE-2008-BT-STD-0012 COMMENT 20
 

 

Table 7-A.2.1 Refrigerator Energy Consumption Data by Year 

Model Year 

Shipment Weighted Average 

Use (kWh/yr) Model Year 

Shipment Weighted Average 

Use (kWh/yr) 

2006 564 1990 988 

2005 550 1989 1006 

2004 559 1988 1049 

2003 589 1987 1052 

2002 576 1986 1165 

2001 611 1985 1147 

2000 779 1984 1139 

1999 762 1983 1160 

1998 738 1982 1191 

1997 728 1981 1190 

1996 708 1980 1278 

1995 693 1975 – 1979 1530† 

1994 693 1970 – 1974 1730† 

1993 699 1965 – 1969 1540† 

1992 877 1961 – 1964 1150† 

1991 918 

Source: AHAM Fact Books 

†: Approximate 

7A.2.2 Field Studies 

 In situ conditions account for several important factors including: ambient air 

temperature; the number and duration of door openings; the temperature of food loaded into the 

unit; the placement of the unit in relation to walls, ovens, and stoves; the temperature setting in 

the field; and the ice maker setting in the field. 

Since the early 1980s, utilities and government agencies have collected data on fieldmeasured refrigerator-freezer energy consumption in order to evaluate the effects of refrigerator 

“early replacement” programs. The collected data varies tremendously by sample size, the type 

of refrigerator-freezer studied, the length of time each appliance was monitored, and their 

operating conditions. The studies summarized in Table 2.2 describe the performance of 

refrigerator-freezers as measured in various ways. 

7A.2.2.1 KEMA-Xenergy Findings 

The private consulting firm KEMA-Xenergy in 2002 reviewed numerous reports of in 

situ performance studies for Southern California Edison. Several reports were summarized by 

KEMA-Xenergy but are not available to be reviewed by DOE. These reports are indicated by a 

“#” in Table 2.2. 

7-A-3 

EERE-2008-BT-STD-0012 COMMENT 20
Table 7-A.2.2 Literature summary 

Authors(s) Year Ratio Averagea Ratio Range 

Comparison Type Location Refrigerator Type 

Arthur D. Little, Inc. # 1982 >1.2 C to A Florida unknown 

Topping & Vineyard 1982 0.85 to 1.5b C to A Norfolk, VA New 

Meier & Jansky 1993 0.85 is “typical” 0.56 to 1.17 C to A Cold climates (many in Pacific Northwest) Relatively new Meier et al. 1993 B to A: 0.99, C to A: 0.87 B to A: 0.89 to 1.10 B and C to A Rochester, NY New, “energy efficient”, frost-free 

Bos # 1993 “considerably” > 1 B to A Sacramento, CA At replacement 

Quantum Consulting 1994 

0.87 for “highefficiency”, 1 for 

“super-efficiency” 

95% between 

roughly 0.7 

and 1.25 

C to A Southern CA (SCE) 1-3 years old 

Proctor Engineering (Dutt et al.) 1994 Between 0.86 and 0.9c C to A Northern CA (PG&E) New, “energy efficient” 

Goett # 1995 approx. 1 Unknown CA (PG&E and SCE) New 

Barakat & Chamberlin 

# 1996 “significantly more” than 1 B to A Unknown At replacement 

Miller & Pratt 1998 1.1 0.72 to 1.2e C to A New York City (multi­ family public housing) Some new, some older 

Kinney & Belshe 2001 0.96 (new); 1.3 (mixture) C to A New York City (multi­ family public housing) 220 old, 56 new 

ICF Consulting 2003 approx. 0.5 C to statistical model of C CA (Bay Area) At replacement 

Mowris # 2003 1.06 wide variation C to A Northern CA (6 cities) At replacement 

KEMA 2004 1.46 (median) 0.85 to > 3 B to A California At replacement 

Peterson et al. 2007 median 1.4, mean 1.5 B to A California At replacement 

ADM, Athens, et al. 2008 

0.81 to 0.88, 

depending on weather 

model 

C to B California At replacement 

a A value greater than 1 for this ratio for a C to A comparison implies that energy use in the field (C) was greater than the labeled energ# KEMA-Xenergy (2004) is DOE’s only reference for the results of this study. b Seasonal variation for a single model c Ratio of average C to average A over sample d Adjusted for typical meteorological year (TMY) at location e Variation in the mean of various types of refrigerators in various use environments 

7-A-4 

EERE-2008-BT-STD-0012 COMMENT 20
7-A.3 LITERATURE ANALYSIS 

DOE’s interest in surveying the refrigerator-freezer energy use literature is to evaluate the 

range of possible appropriate values for the ‘usage adjustment factor’, or UAF. The UAF is a 

“(C) to (A)”-type measurement, relating energy use in situ to the DOE test result for a new 

appliance. 

Studies of new appliances include Meier & Jansky (1993), Meier et al. (1993), Dutt et al. 

(1994), Quantum (1994), Goett (1995), Miller & Pratt (1998), and Kinney & Belshe (2001). The 

average (or typical) values of the ratio of (C) to (A) for these studies range from 0.85 to 1.1, and 

there is significant variation, with ratios ranging from 0.56 to 1.25. The majority of these studies 

are not adjusted for ambient temperature variations or climate (although several use year-long 

samples to eliminate seasonal effects). The only of these studies which is adjusted (Dutt et al.) is 

normalized to the climate of the particular location of the measurements, rather than to a national 

average climate model. Taken collectively, these studies do not allow DOE to draw conclusions 

regarding possible national variation in new-refrigerator energy use, particularly due to 

variations in climate. They do indicate that the labeled energy consumption of a new appliance is 

likely to be accurate in situ to within 40%, as suggested by Meier (1995). 

Studies of refrigerators at the time of replacement by utility programs show higher energy 

use relative to the labeled energy consumption than do new refrigerators. For older refrigerators, 

studies predominantly take two forms: (B) to (A) or (C) to (A). (B) to (A) studies isolate the 

effects of age from any other effects (such as behavior or ambient temperature in situ), while (C) 

to (A) studies give a direct indication of the ‘UAF’ of old appliances. These studies are not 

necessarily representative of all older refrigerators, because they study only those units and 

households participating in utility refrigerator recycling programs. 

 Test-procedure-only comparison studies include Bos (1993), Barakat & Chamberlin 

(1996), KEMA (2004) and Peterson et al. (2007). All four of these studies show significant 

energy use increase in the DOE test procedure; KEMA and Peterson both indicate an energy use 

increase of close to 50%, with wide variation. Only 7% of the refrigerators measured by KEMA 

used less than their labeled consumption. 25% of the refrigerators measured by Peterson et al. 

used more than 70% more that their labeled consumption. 

Miller & Pratt (1998), Kinney & Belshe (2001), and Mowris (2003) undertook direct 

evaluation of the ratio of in situ to labeled consumption for older refrigerators. The average ratio 

in all three studies was measured to be larger than one, although smaller than the test-procedurebased comparisons. Mowris indicated wide variation in energy use relative to the label, and 

Miller & Pratt’s sub-categories show a range of energy consumptions from 28% below the label 

to 20% above. 

Only one study reviewed by DOE compared in situ energy use to the DOE test on the 

same appliance (ADM, Athens, et al., 2008), a (C) to (B) comparison. Depending on the weather 

7-A-5
 

EERE-2008-BT-STD-0012 COMMENT 20
model used to adjust the in situ measurements, they found that on average the DOE test 

procedure overestimated the in situ use by 13 to 23%. This study does not include an indication 

of how the DOE test consumption compared with the labeled consumption. 

Testing has confirmed that age, in combination with other refrigerator characteristics, 

accounts for the degradation of refrigerator energy efficiency (KEMA, 2004; Peterson, 2007). 

Therefore, energy efficiency degradation is a factor in calculating the savings between new and 

replacement units. Energy use increases when barriers to cabinet air and heat leakage degrade. 

For example, door seals no longer close tightly, damaged walls allow air flow, and wet or 

degraded insulation no longer performs its function. 

Two studies (KEMA, 2004 and Miller & Pratt, 1998) used regression analysis to measure 

the average effect of annual degradation on appliance energy use. KEMA determined an energy 

use growth rate of roughly 40 kWh/year, depending on model characteristics. Miller & Pratt’s 

regression model predicts a 1.37% increase in energy use each year. Smit (2006) reports that 

Athens (1998) calculated a degradation rate of 0.6% per year. 

7-A.4 SUMMARY 

This appendix summarizes current literature pertaining to the difference between DOEtest based measurements (when new or at retirement) and field-based measurements of 

refrigerator-freezer energy consumption. In situ energy use was found to be close to labeled 

consumption for new refrigerators, but higher than labeled at the time of replacement. This 

appendix has examined the mean values and variability from the literature; the variability across 

a national sample is likely much greater than the range addressed here. 

Degradation of the refrigerator unit contributes to the discrepancy between the DOE test 

and field measured energy consumption data. However, the precise rate of efficiency decrease 

(and particularly its variability) cannot be determined from the literature. 

7-A.5 BIBLIOGRAPHY 

ADM Associates, Inc. 2004. Southern California Edison 1994 Residential Appliance Efficiency 

Incentive Program Ninth Year Retention Study. CEC Study ID #546A. Prepared for 

Southern California Edison Company. July 2004. 

ADM Associates, Inc.; et al. 2008. Evaluation Study of the 2004-05 Statewide Residential 

Appliance Recycling Program; 2004-2005 Programs #1114, #1157, #1232 and #1348 

Final Report and Appendices. Prepared by ADM Associates, Inc.; Athens Research; 

Hiner & Partners; and Innovologie LLC. Prepared for Southern California Edison. April, 

2008. 

7-A-6
 

EERE-2008-BT-STD-0012 COMMENT 20
Athens Research, 1998. Refrigerator/Freezer UEC Estimation, 1996 ARCA/SCE Turn-In 

Program. In Support of Xenergy Inc’s Evaluation of the 1996 Appliance Recycling 

Program. 

Dohrmann, Donald R. et al. Net Savings Estimation in Appliance Recycling Programs: A Review 

and Empirical Analysis with Recent California Data ADM Associates, Inc., Athens 

Research, Innovologie LLC for Southern California Edison. 

Dutt, Guatam, et al., 1994. “Large Scale Residential Refrigerator Field Metering”, in 1994 

ACEEE Summer Study in Energy Efficiency in Buildings, pp. 2.77. 

ICF Consulting, 2003. Evaluation of the Energy and Environmental Effects of the California 

Appliance Early Retirement and Recycling Program: Final Report. Prepared for: 

California Public Utilities Commission and Appliance Recycling Centers of America. 

May 12, 2003. 

KEMA. 2004. 2003 EM&V RARP Study:Degradation and Market Potential Analysis. Prepared 

for Southern California Edison, Rosemead, CA. Prepared by KEMA Inc., Madison, WI. 

December 23, 2004. CALMAC STUDY ID SCE0205 ma:project:scee0015 rarp 03 

evaluation:report:title. 

KEMA, 2004. Final Report: Measurement and Evaluation Study of the 2002 Statewide 

Residential Appliance Recycling Program. February, 2004. Prepared for: Southern 

California Edison. February 13, 2004. 

Kinney, Larry and Rana Belshe. 2001. Refrigerator Replacement in the Weatherization 

Program: Putting a Chill on Energy Waste: A special report for the Weatherization 

Assistance Program. E Source. September, 2001. 

Market Transformation Programme. 2007. BNC11: Domestic Refrigerator Test Standard Vs 

Real-Use Energy Consumption. April 30, 2007. 

http://www.mtprog.com/SelectProductStrategy.aspx?intSelection=1&intSector=1 

Meier, Alan, 1995. “Refrigerator energy use in the laboratory and in the field,” Energy and 

Buildings, 22, pp. 233-243. 

Meier, A.. and R. Jansky. Field Performance of Residential Refrigerators: A Comparison with 

the Laboratory Test. 1991. Lawrence Berkeley Laboratory: Berkeley, CA. Report No. 

LBL-31795. 

Meier, A. and M. Martinez. Energy Use of Icemaking in Domestic Refrigerators. ASHRAE 

Transactions: Symposia. 1996. AT-96-19-2. 

7-A-7
 

EERE-2008-BT-STD-0012 COMMENT 20
Meier. A., A. Megowan, B. Litt, and B. Pon. The New York State Residential Refrigerator 

Electrical Energy Monitoring Project: Final Report. 1993. Lawrence Berkeley National 

Laboratory: Berkeley, CA. Report No. LBL-33708. 

Miller, J.D. and R.G. Pratt. Estimates of Refrigerator Loads in Public Housing Based on Metered 

Consumption Data. 1998. Pacific Northwest National Laboratory. Report No. PNNL11991. 

Peterson, J., D. Dohrmann, T. Alereza, S. Samiullah, S. Westberg, and J.H. Redd. Gross Savings 

Estimation for Appliance Recycling Programs: the Lab Versus in situ Measurement 

Imbroglio and Related Issues. Proceedings of the 2007 International Energy Performance 

Evaluation Conference (IEPEC). 2007. Chicago, IL. August. Report 653. 17 pp. 

Quantum Consulting. 1994. 1991 Refrigerator Rebate Program Metering Study for Southern 

California Edison, Final Report. P646.070. 

Smit, Kevin L. 2006. 2005 Refrigerator/Freezer Recycling Program Evaluation. Snohomish 

County Public Utility District No. 1. March. 

Topping, Richard F. and Edward A. Vineyard. 1982. Field Test of a High-Efficiency, AutomaticDefrost Refrigerator Freezer. Prepared by AD Little and ORNL for the ASHRAE SemiAnnual Meeting, Toronto Canada. June 27-July 1, 1982. 

7-A-8
 

EERE-2008-BT-STD-0012 COMMENT 20
APPENDIX 7-B. DATA FOR ESTIMATING DISTRIBUTION OF 

REFRIGERATOR AND FREEZER SIZE IN THE RECS SAMPLE 

TABLE OF CONTENTS 

7-B.1 INTRODUCTION ................................................................................................. 7-B-1 

7-B.2 RESULTS .............................................................................................................. 7-B-1 

LIST OF FIGURE 

Figure 7-B.2.1 Models of Top Mount Freezer without through-the-door ice (Product 

Class 3)....................................................................................................... 7-B-2 

Figure 7-B.2.2 Models of Bottom Mount Freezer without through-the-door ice 

(Product Class 5)........................................................................................ 7-B-3 

Figure 7-B.2.3 Models of Side Mount Freezer with through-the-door ice (Product 

Class 7)....................................................................................................... 7-B-4 

Figure 7-B.2.4 Models of Upright Freezer with automatic defrost (Product Class 9)....... 7-B-5 

Figure 7-B.2.5 Models of Chest Freezers (Product Class 10)............................................ 7-B-6 

Figure 7-B.2.6 Models of Compact Refrigerator and Refrigerator-Freezer with manual 

defrost (Product Class 11).......................................................................... 7-B-7 

Figure 7-B.2.7 Models of Compact Chest Freezer (Product Class 18).............................. 7-B-8 

7B-i 

EERE-2008-BT-STD-0012 COMMENT 20
APPENDIX 7-B. DATA FOR ESTIMATING DISTRIBUTION OF REFRIGERATOR 

AND FREEZER SIZE IN THE RECS SAMPLE 

7-B.1 INTRODUCTION 

DOE used the California Energy Commission (CEC) appliance database1 to determine 

the distribution of refrigerator and freezer volumes in the market. The Energy Information 

Administration’s (EIA) Residential Energy Consumption Surveys (RECS)2

 provides the volumes 

of household refrigerators only within bins (ranges). In order to estimate the labeled energy 

consumption of a household’s standard-sized appliance, DOE selected a volume from within the 

appropriate RECS bin. DOE then selected a more precise volume randomly from the distribution 

of volumes within the RECS bin, basing the probability of selecting each volume on the number 

of models in the CEC database having that volume. The figures in this appendix show the 

volume distributions by number of models in the CEC database (narrower, solid bars in figures) 

and the distributions of refrigerator volumes reported by RECS respondents (wider, empty bars 

in figures). For each standard-sized refrigeration product DOE first identified the appropriate 

RECS bin and product class, then chose a more precise volume from the relevant part of the CEC 

distribution. 

For compact products (product classes 11 and 18), for which DOE did not use a 

household sample, DOE used the distribution of volumes from the CEC database to characterize 

the distribution of volumes sold in the market and determine the distribution of energy use. 

7-B.2 RESULTS 

Figures 7-B.2.1 through 7-B.2.7 depict the volume distributions on the number of models 

in the CEC database and the distribution of refrigerator and freezer volumes reported in RECS. 

7-B-1
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

700 

600
 

500
 

400
 

300
 

200
 

100
 

0 

CEC directory 

RECS bins 

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 
 

Total Volume (cu ft ) 

Figure 7-B.2.1 Models of Top Mount Freezer without through-thedoor ice (Product Class 3) 

7-B-2
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

160
 

140
 

120
 

100
 

80
 

60
 

40
 

20
 

0
 

CEC directory 

RECS bins 

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
 

Total Volume (cu ft ) 

Figure 7-B.2.2 Models of Bottom Mount Freezer without throughthe-door ice (Product Class 5) 

7-B-3
 

EERE-2008-BT-STD-0012 COMMENT 20
0 

100 

200 

300 

400 

500 

600 

700 

800 

900 

Frequency 

CEC directory 

RECS bins 

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 

Total Volume (cu ft ) 

Figure 7-B.2.3	 Models of Side Mount Freezer with through-thedoor ice (Product Class 7) 

7-B-4
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

50
 

45
 

40
 

35
 

30
 

25
 

20
 

15
 

10
 

5
 

0
 

CEC directory 

RECS bins 

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
 

Total Volume (cu ft ) 

Figure 7-B.2.4 Models of Upright Freezer with automatic defrost 

(Product Class 9) 

7-B-5
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

70 

60
 

50
 

40
 

30
 

20
 

10
 

0 

CEC directory 

RECS bins 

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
 

Total Volume (cu ft ) 

Figure 7-B.2.5 Models of Chest Freezers (Product Class 10) 

7-B-6
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

70 

60
 

50
 

40
 

30
 

20
 

10
 

0 

CEC directory 

1 2 3 4 5 6 7 8 9 10 
 

Total Volume (cu ft ) 

Figure 7-B.2.6 Models of Compact Refrigerator and RefrigeratorFreezer with manual defrost (Product Class 11) 

7-B-7
 

EERE-2008-BT-STD-0012 COMMENT 20
Frequency 

30 

25
 

20
 

15
 

10
 

5
 

0 

CEC directory 

1 2 3 4 5 6 7 8 9 10 
 

Total Volume (cu ft ) 

Figure 7-B.2.7 Models of Compact Chest Freezer (Product Class 

18) 

7-B-8
 

EERE-2008-BT-STD-0012 COMMENT 20
 

 

 

REFERENCES 

1	 California Energy Commission. Appliances Database—Refrigeration. 

<www.energy.ca.gov/appliances/database/excel_based_files/Refrigeration/> (Last accessed April 25, 

2009.) 

2	 U.S. Department of Energy–Energy Information Administration. Residential Energy 

Consumption Survey, 2005 Public Use Data Files. 2009. U.S. Department of Energy: 

Washington, D.C. <www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html> 

7-B-9
 

EERE-2008-BT-STD-0012 COMMENT 20
CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS 

TABLE OF CONTENTS 

8.1 INTRODUCTION ........................................................................................................... 8-1 

8.1.1 Approach.......................................................................................................................... 8-1 

8.1.2 Summary of Inputs........................................................................................................... 8-2 

8.2 INPUTS TO LIFE-CYCLE COST ANALYSIS ............................................................. 8-7 

8.2.1 Inputs to Product Cost...................................................................................................... 8-8 

8.2.1.1 Baseline Retail Prices .................................................................................... 8-8 

8.2.1.2 Increases in Manufacturer Selling Price ........................................................ 8-9 

8.2.1.3 Markup and Sales Tax ................................................................................. 8-11 

8.2.1.4 Installation Cost ........................................................................................... 8-11 

8.2.1.5 Consumer Product Cost ............................................................................... 8-11 

8.2.2 Inputs to Operating Cost ................................................................................................ 8-13 

8.2.2.1 Annual Energy Consumption....................................................................... 8-14 

8.2.2.2 Energy Prices ............................................................................................... 8-15 

8.2.2.3 Energy Price Trends.....................................................................................8-16 

8.2.2.4 Repair and Maintenance Costs..................................................................... 8-17 

8.2.3 Product Lifetimes........................................................................................................... 8-17 

8.2.3.1 Estimated Survival Function........................................................................ 8-18 

8.2.3.2 Conversion of First to Second Refrigerators ............................................... 8-23 

8.2.3.3 Standard-Size Freezers................................................................................. 8-25 

8.2.3.4 Compact Refrigeration Products.................................................................. 8-27 

8.2.4 Discount Rates ............................................................................................................... 8-28 

8.2.4.1 Discount Rates for Residential Consumers.................................................. 8-28 

8.2.4.2 Assignment of Discount Rates to Sample Households................................ 8-31 

8.2.4.3 Discount Rates for Commercial Purchasers ................................................ 8-31 

8.2.5 Effective Date of Standard............................................................................................. 8-34 

8.2.6 Base-Case Energy Efficiencies...................................................................................... 8-35 

8.3 INPUTS TO PAYBACK PERIOD ANALYSIS........................................................... 8-37 

8.4 RESULTS OF ANALYSES .......................................................................................... 8-38 

8.4.1 Standard-Size Refrigerator-Freezers.............................................................................. 8-39 

8.4.1.1 Summary of Results..................................................................................... 8-39 

8.4.1.2 Distributions of Impacts............................................................................... 8-40 

8.4.2 Standard-Size Freezers................................................................................................... 8-45 

8.4.2.1 Summary of Results..................................................................................... 8-45 

8.4.2.2 Distributions of Impacts............................................................................... 8-46 

8.4.3 Compact Refrigeration Products.................................................................................... 8-50 

8.4.3.1 Summary of Results..................................................................................... 8-51 

8.4.3.2 Distributions of Impacts............................................................................... 8-52 

8.5 REBUTTABLE PAYBACK PERIOD.......................................................................... 8-56 

8.5.1 Metric............................................................................................................................. 8-56 

8.5.2 Inputs to Rebuttable Payback Period Analysis .............................................................. 8-56 

8-i 

EERE-2008-BT-STD-0012 COMMENT 20
8.5.3 Results of Analysis ........................................................................................................ 8-56 

LIST OF TABLES 

Table 8.1.1 Standard-Size Refrigerator-Freezers: Summary of Inputs to Calculations.......... 8-5 

Table 8.1.2 Standard-Size Freezers: Summary of Inputs to Calculations .............................. 8-6 

Table 8.1.3 Compact Refrigeration Products: Summary of Inputs to Calculations................ 8-7 

Table 8.2.1 Residential Refrigeration Products: Average Baseline Retail Price.................... 8-9 

Table 8.2.2 Standard-Size Refrigerator-Freezers: Increases in Manufacturer Selling 

Prices.................................................................................................................. 8-10 

Table 8.2.3 Standard-Size Freezers: Increases in Manufacturer Selling Prices.................... 8-10 

Table 8.2.4 Compact Refrigeration Products: Increases in Manufacturer Selling Prices..... 8-11 

Table 8.2.5 Standard-Size Refrigerator-Freezers: Average Consumer Cost ........................ 8-12 

Table 8.2.6 Standard-Size Freezers: Average Consumer Cost ............................................. 8-12 

Table 8.2.7 Compact Refrigeration Products: Average Consumer Cost .............................. 8-13 

Table 8.2.8 Standard-Size Refrigerator-Freezers: Average Annual Energy Use by 

Efficiency Level................................................................................................. 8-14 

Table 8.2.9 Standard-Size Freezers: Average Annual Energy Use by Efficiency Level...... 8-15 

Table 8.2.10 Compact Refrigeration Products: Average Annual Energy Use by 

Efficiency Level................................................................................................. 8-15 

Table 8.2.11 Average Electricity Prices in 2007 .................................................................... 8-16 

Table 8.2.12 Standard-Size Refrigerator-Freezers: Comparison of Survey and 

Shipments Data with Modeled Stock................................................................. 8-21 

Table 8.2.13 Standard-Size Freezers: Comparison of Survey and Shipments Stock to 

Modeled Stock ................................................................................................... 8-26 

Table 8.2.14 Types of Household Debt and Equity by Percentage Shares............................. 8-29 

Table 8.2.15 Average Nominal Interest Rates for Household Debt ....................................... 8-29 

Table 8.2.16 Average Real Effective Interest Rates for Household Debt .............................. 8-30 

Table 8.2.17 Average Nominal and Real Interest Rates for Household Equity ..................... 8-30 

Table 8.2.18 Average Interest on Household Debt and Equity .............................................. 8-31 

Table 8.2.19 Data for Calculating Weighted-Average Cost of Capital for Commercial 

Sectors................................................................................................................ 8-33 

Table 8.2.20 Weighted-Average Cost of Capital for Commercial Sectors............................. 8-34 

Table 8.2.21 Discount Rates for Commercial Sectors............................................................ 8-34 

Table 8.2.22 Standard-Size Refrigerator-Freezers: Base-Case Efficiency Distributions ....... 8-36 

Table 8.2.23 Standard-Size Freezers: Base-Case Efficiency Distributions............................ 8-36 

Table 8.2.24 Compact Refrigeration Products: Base-Case Efficiency Distributions ............. 8-37 

Table 8.4.1 Product Class 3, Top-Mount Refrigerator-Freezers: Analytical Results........... 8-39 

Table 8.4.2 Product Class 5, Bottom-Mount Refrigerator-Freezers: Analytical Results ..... 8-40 

Table 8.4.3 Product Class 7, Side-by-Side Refrigerator-Freezers with Through-theDoor Ice Service: Analytical Results................................................................. 8-40 

Table 8.4.4 Product Class 9, Upright Freezers: Analytical Results...................................... 8-46 

Table 8.4.5 Product Class 10, Chest Freezer: Analytical Results......................................... 8-46 

Table 8.4.6 Product Class 11, Compact Refrigerators: Analytical Results .......................... 8-51 

8-ii 

EERE-2008-BT-STD-0012 COMMENT 20
Table 8.4.7 Product Class 18, Compact Freezers: Analytical Results.................................. 8-51 

Table 8.5.1 Standard-Size Refrigerator-Freezers: Rebuttable Payback Periods................... 8-57 

Table 8.5.2 Standard-Size Freezers: Rebuttable Payback Periods........................................ 8-57 

Table 8.5.3 Compact Refrigerators and Freezers: Rebuttable Payback Periods................... 8-58 

LIST OF FIGURES 

Figure 8.1.1 Flow Diagram of Inputs for Life-Cycle Cost and Payback Period Analyses ...... 8-4 

Figure 8.2.1 Residential and Commercial Electricity Price Trends (2007 = 1) ..................... 8-17 

Figure 8.2.2 Comparison of Modeled Refrigerator Age Distribution with Data from
 

Residential Energy Consumption Surveys......................................................... 8-22 

Figure 8.2.3 Survival Function for Standard-Size Refrigerator-Freezers .............................. 8-22 

Figure 8.2.4 Function for Conversion of First to Second Refrigerator-Freezers ................... 8-25 

Figure 8.2.5 Survival Function for Standard-Size Freezers ................................................... 8-27 

Figure 8.4.1 Product Class 3, Top-Mount Refrigerator-Freezers: Distribution of LifeCycle Cost Impacts for Efficiency Level 5........................................................ 8-41 

Figure 8.4.2 Product Class 3, Top-Mount Refrigerator-Freezers: Distribution of 

Payback Periods for Efficiency Level 5............................................................. 8-41 

Figure 8.4.3 Product Class 3, Top-Mount Refrigerator-Freezers: Range of Life-Cycle 

Cost Savings by Efficiency Level...................................................................... 8-42 

Figure 8.4.4 Product Class 5, Bottom-Mount Refrigerator-Freezers: Range of LifeCycle Cost Savings by Efficiency Level ........................................................... 8-43 

Figure 8.4.5 Product Class 7, Side-by-Side Refrigerator-Freezers: Range of Life-Cycle 

Cost Savings by Efficiency Level...................................................................... 8-43 

Figure 8.4.6 Product Class 3, Top-Mount Refrigerator-Freezers: Range of Payback 

Periods by Efficiency Level............................................................................... 8-44 

Figure 8.4.7 Product Class 5, Bottom-Mount Refrigerator-Freezers: Range of Payback 

Periods by Efficiency Level............................................................................... 8-44 

Figure 8.4.8 Product Class 7, Side-by-Side Refrigerator-Freezers: Range of Payback 

Periods by Efficiency Level............................................................................... 8-45 

Figure 8.4.9 Product Class 9, Upright Freezers: Distribution of Life-Cycle Cost 

Impacts for Efficiency Level 5 .......................................................................... 8-47 

Figure 8.4.10 Product Class 9, Upright Freezers: Distribution of Payback Periods for 

Efficiency Level 5.............................................................................................. 8-47 

Figure 8.4.11 Product Class 9, Upright Freezers: Range of Life-Cycle Cost Savings by 

Efficiency Level................................................................................................. 8-48 

Figure 8.4.12 Product Class 10, Chest Freezers: Range of Life-Cycle Cost Savings by 

Efficiency Level................................................................................................. 8-49 

Figure 8.4.13 Product Class 9, Upright Freezers: Range of Payback Periods by 

Efficiency Level................................................................................................. 8-50 

Figure 8.4.14 Product Class 10, Chest Freezers: Range of Payback Periods by Efficiency 

Level .................................................................................................................. 8-50 

Figure 8.4.15 Product Class 11, Compact Refrigerators: Distribution of Life-Cycle Cost 

Impacts for Efficiency Level 5 .......................................................................... 8-52 

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EERE-2008-BT-STD-0012 COMMENT 20
Figure 8.4.16 Product Class 11, Compact Refrigerators: Distribution of Payback Period 

for Efficiency Level 5 ........................................................................................ 8-53 

Figure 8.4.17 Product Class 11, Compact Refrigerators: Range of Life-Cycle Cost 

Savings by Efficiency Level .............................................................................. 8-54 

Figure 8.4.18 Product Class 18, Compact Freezers: Range of Life-Cycle Cost Savings 

by Efficiency Level............................................................................................ 8-54 

Figure 8.4.19 Product Class 11, Compact Refrigerators: Range of Payback Periods by 

Efficiency Level................................................................................................. 8-55 

Figure 8.4.20 Product Class 18, Compact Freezers: Range of Payback Periods by 

Efficiency Level................................................................................................. 8-55 

8-iv 

EERE-2008-BT-STD-0012 COMMENT 20
 

CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS 

8.1 INTRODUCTION 

This chapter describes the Department of Energy (DOE)’s method and metrics for 

analyzing the economic impacts on individual consumers of potential energy efficiency 

standards for refrigeration products. The effects of standards on individual consumers include a 

change (usually a decrease) in operating cost and a change (usually an increase) in product cost. 

DOE analyzed the economic impacts related to potential new energy efficiency standards for 

standard-size refrigerator-freezers (top-mount, bottom-mount, and side-by-side); standard-size 

freezers (upright and chest); and compact refrigeration products (refrigerators and freezers), a 

total of 7 product classes. DOE examined the life-cycle cost, payback period, and rebuttable 

payback period of all potential efficiency standards on all product classes. The terms used in this 

analysis are defined below. 

•	 Life-cycle cost (LCC) is the total cost consumers incur during the life of an appliance, 

including purchase and operating costs (including energy expenditures). DOE 

discounts future operating costs to the time of purchase, and sums them over the 

lifetime of a product. 

•	 Payback period (PBP) measures the amount of time it takes consumers to recover the 

assumed higher purchase cost of more energy efficient products through lower 

operating costs. 

•	 Rebuttable payback period, a special case of the payback period, is based on 

laboratory conditions (specifically, those that reflect the DOE test procedure) for 

energy use. Its other inputs (including electricity prices) reflect representative realworld operating conditions. 

Inputs to the LCC and the PBP are discussed in sections 8.2 and 8.3, respectively, of this 

chapter. Results of the LCC and PBP analyses are presented in section 8.4. The rebuttable PBP is 

discussed in section 8.5. Key variables and calculations are presented for each of the three 

metrics listed above. DOE performed the calculations discussed here using a series of Microsoft 

Excel spreadsheets that are accessible on the Internet 

(www.eere.energy.gov/buildings/appliance_standards/). Details regarding and instructions for 

using the spreadsheets are discussed in appendix 8-A. 

8.1.1 Approach 

Recognizing that several inputs to the analysis of consumer LCC and PBP are either 

variable or uncertain, DOE used Monte Carlo simulation and probability distributions to model 

both the uncertainty and variability of inputs. Appendix 8-B provides a detailed explanation of 

Monte Carlo simulation and the use of probability distributions. DOE developed LCC and PBP 

spreadsheet models that incorporate both Monte Carlo simulation and probability distributions 

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EERE-2008-BT-STD-0012 COMMENT 20
 

by using Microsoft Excel® spreadsheets combined with Crystal Ball®, a commercially available 

add-in program. 

In addition to using probability distributions to characterize several of the inputs to the 

calculation, DOE developed samples of individual households that use standard-size 

refrigeration products. DOE performed the LCC and PBP calculations for each household in the 

sample to account for the variability in energy consumption and/or energy price associated with a 

range of households. 

As described in chapter 7, DOE used the DOE Energy Information Administration 

(EIA)’s 2005 Residential Energy Consumption Survey (RECS) to develop household samples 

for standard-size refrigeration products.1

 EIA constructed the 2005 RECS to represent the range 

of households throughout the United States. 

DOE used the 2005 RECS to establish the variability in the annual energy use of 

refrigeration products and in energy prices. DOE was able to assign a unique annual energy use 

and/or energy price to each household in the sample. Because of the large sample of households 

considered in the LCC and PBP analyses, annual energy use and/or energy prices vary greatly. 

Thus, although the annual energy use and/or energy prices are known for any particular 

household, their variability across all households contributes to the range of LCCs and PBPs 

calculated for any particular possible standard. 

DOE did not develop a household sample for compact refrigeration products, because 

many such products are used in lodging, dormitories, and other commercial establishments. DOE 

estimated the fractions of shipments of compact refrigeration products used in the residential and 

commercial sectors, then used appropriate inputs for those fractions. 

DOE displays LCC and PBP results as distributions of impacts compared to baseline 

conditions. Results, presented in section 8.4, were derived from 10,000 samples for each Monte 

Carlo simulation run. To illustrate the implications of the analysis, DOE generated a frequency 

chart that depicts the variation in LCC and PBP for each standard level considered for 

refrigeration products. 

8.1.2 Summary of Inputs 

The LCC represents the total consumer cost during the life of a product, including 

purchase and operating costs (including energy expenditures). DOE discounts future operating 

cost to the time of purchase, then sums them over the lifetime of each product. The PBP is the 

change in purchase cost due to an increased efficiency standard divided by the change in annual 

operating cost that results from the standard. The PBP represents the number of years it will take 

the customer to recover the increased purchase cost through decreased operating cost. 

DOE uses two types of inputs to the calculation of LCC and PBP: (1) inputs for 

establishing the purchase cost, otherwise known as the consumer product cost, and (2) inputs for 

determining the operating cost. 

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EERE-2008-BT-STD-0012 COMMENT 20
The following are the primary inputs for establishing the consumer product cost. 

•	 Baseline selling price: The price at which a manufacturer sells a product identified as 

a baseline-efficient model. 

•	 Increases in manufacturer selling price (MSP): The change in manufacturer selling 

price associated with producing a product that meets a particular efficiency level. 

•	 Markups and sales tax: The costs associated with converting increases in the MSP 

into consumer product cost. 

The following are the primary inputs for calculating the operating cost. 

•	 Product energy consumption: The site energy use associated with operating a given 

product. 

•	 Product efficiency: The energy consumption associated with a product that has an 

efficiency greater than that of the baseline product. 

•	 Energy prices: The prices consumers paid for energy (electricity) in a recent year. 

•	 Energy price trends. Energy prices forecasted into the future. DOE based these trends 

on the EIA’s Annual Energy Outlook (AEO) 2009.2 

•	 Repair and maintenance costs: Repair costs are associated with repairing or replacing 

components that fail. Maintenance costs are associated with maintaining the operation 

of a product. 

•	 Lifetime: The age at which a product is retired from service. 

•	 Discount rate: The rate at which DOE discounted future expenditures to establish 

their present value. 

Figure 8.1.1 graphically depicts the relationships among the inputs for installed cost and 

operating cost used to calculate the LCC and PBP. The yellow boxes in Figure 8.1.1 indicate 

inputs; the green boxes indicate intermediate outputs; and the blue boxes indicate the final 

outputs of LCC and PBP. 

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EERE-2008-BT-STD-0012 COMMENT 20
Baseline 

Manufacturer 

Selling Price 

Std-Level 

Manufacturer 

Selling Price 

Retailer 

Markup 

Sales Tax 

Installation 

Cost 

Total Installed 

Cost

 Energy 

Consumption 

Equipment 

Price 

Lifetime 

Operating 

Cost 

Annual Energy 

Cost 

Product 

Lifetime 

Repair and 

Maintenance 

Cost 

Discount Rate 

Energy Price 

Trends 

Annual 

Operating 

Cost 

Payback 

Period 

Life-Cycle 

Cost 

Energy Prices 

Figure 8.1.1	 Flow Diagram of Inputs for Life-Cycle Cost and Payback Period 

Analyses 

Tables 8.1.1 through 8.1.3 summarize the input values that DOE used to calculate the 

LCC and PBP for refrigeration products. The inputs for calculating total installed and operating 

costs included the product lifetime, discount rate, and energy price trends. DOE used single-point 

values to characterize all inputs to total cost, but used probability distributions to capture the 

uncertainty and/or variability of several inputs to operating cost. For those inputs characterized 

using probability distributions, the values in the following tables are average or typical values. 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.1.1 Standard-Size Refrigerator-Freezers: Summary of Inputs to Calculations 

Input Product Class Average or Typical Value Characterization 

Baseline retail 

price 

Top-mount refrigeratorfreezer 

Bottom-mount 

refrigerator-freezer 

Side-by-side refrigeratorfreezer with TTD* 

550 2008$ 

1,615 2008$ 

1,332 2008$ 

Custom distribution 

Custom distribution 

Custom distribution 

Increase in 

manufacturer 

selling price† 

All Varies by efficiency level Single-point value 

Retailer 

markup All Baseline = 1.45 Incremental = 1.15 Single-point value 

Sales tax All 7.1% Single-point value 

Annual energy 

use 

Top-mount refrigeratorfreezer 

Bottom-mount 

refrigerator-freezer 

Side-by-side refrigeratorfreezer with TTD 

Baseline use = 657 kWh‡ 

Baseline use = 699 kWh 

Baseline use = 1,087 kWh 

Varies depending on usage 

Varies depending on usage 

Varies depending on usage 

Energy prices All 11.4 cents per kWh Varies depending on region 

Energy price 

trend All AEO 2009 reference case2 

Two additional scenarios: 

AEO high and low 

growth** 

Lifetime All 16.2 years (median) Weibull distribution 

Discount rate All 4.8% Custom distribution 

* Through-the-door ice service. 

† Includes manufacturer markup. 

‡ Kilowatt hours 

** See section 8.2.2.3. 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.1.2 Standard-Size Freezers: Summary of Inputs to Calculations 

Input Product Class Average or Typical Value Characterization 

Baseline retail price Upright 

Chest 

469 2008$ 

304 2008$ 

Custom distribution 

Custom distribution 

Increase in manufacturer 

selling price* All Varies by efficiency level Single-point value 

Retailer markup All Baseline = 1.45 

Incremental = 1.15 Single-point value 

Sales tax All 6.59% Single-point value 

Annual energy use Upright 

Chest 

Baseline use = 980 kWh† 

Baseline use = 623 kWh 

Varies depending on usage 

Varies depending on usage 

Energy prices All 11.4 cents per kWh Varies depending on region 

Energy price trend All AEO 2009 reference case2 Two additional scenarios: 

AEO high and low growth§ 

Lifetime All 21.7 years (median) Weibull distribution 

Discount rate All 4.8% Custom distribution 

* Includes manufacturer markup. 

† Kilowatt hours. 

§ See section 8.2.2.3. 

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Table 8.1.3 Compact Refrigeration Products: Summary of Inputs to Calculations 

Input Product Class Average or Typical Value Characterization 

Baseline retail price Refrigerator 

Freezer 

153 2008$ 

193 2008$ 

Custom distribution 

Custom distribution 

Increase in manufacturer 

selling price* 

All Varies by efficiency level Single-point value 

Retailer markup All Baseline = 1.45 

Incremental = 1.15 Single-point value 

Sales tax All 6.9% Single-point value 

Annual energy use Refrigerator 

Freezer 

Baseline use = 325 kWh† 

Baseline use = 313 kWh 

Varies depending on usage 

Varies depending on usage 

Energy prices All 10.8 cents per kWh Varies depending on region 

Energy price trend All AEO 2009 reference case2 Two additional scenarios: 

AEO high- and low-growth§ 

Lifetime 

Refrigerator 5.6 years (mean) Weibull distribution 

Freezer 7.5 years (mean) Weibull distribution 

Energy prices All 4.8% (residential users) 

6.2% (commercial users) Custom distribution 

* Includes manufacturer markup 

† Killowatt hours. 

§

 See section 8.2.2.3. 

8.2 INPUTS TO LIFE-CYCLE COST ANALYSIS 

Life-cycle cost (LCC) is the total consumer cost during the life of an appliance, including 

purchase and operating costs (including energy costs). DOE discounted future operating costs to 

the time of purchase, then summed them over the lifetime of the product. DOE used the 

following equation to define LCC. 

LCC = PC +∑

N OCt 

t (1+ r)

Where: 

t =1 

LCC = life-cycle cost in dollars; 

PC = consumer product cost in dollars; 

∑ = sum over the lifetime, from year 1 to year N; 

N = lifetime of appliance in years; 

OC = operating cost in dollars; 

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EERE-2008-BT-STD-0012 COMMENT 20
 

 

 

 

r = discount rate; and 

t = year for which operating cost is being determined. 

DOE expresses dollar values in 2008$ because it gathered most of its data for the LCC and PBP 

analysis in 2008. 

8.2.1 Inputs to Product Cost 

DOE calculated the cost consumers pay for baseline products based on the following 

equation. 

PC = (RSP )×(TAX ) BASE BASE 

Where: 

PCBASE = consumer cost for baseline product, 

RSPBASE = retail selling price for baseline product, and 

TAX= sales tax. 

DOE calculated the consumer cost for products having higher efficiency levels based on the 

following equation. 

PCSTD = PCBASE + (ΔMSPSTD × MU ×TAX ) RETINCR 

Where: 

PCSTD = consumer product cost for higher-efficiency products, 

PCBASE = consumer cost for baseline product
 

ΔMSPSTD = change in MSP for more efficient model, 

MURET_INCR = incremental retailer markup, 

TAX= sales tax. 

8.2.1.1 Baseline Retail Prices 

DOE’s engineering analysis (see chapter 5) did not attempt to estimate the manufacturing 

sales price (MSP) for baseline models. Instead, it developed incremental increases in MSP 

associated with increases in efficiency level. This approach required DOE to estimate retail 

prices for the baseline model in each product class. 

DOE drew upon proprietary retail price data collected by The NPD Group.3

 These data 

reflect prices and sales at many retail outlets in the United States, representing more than 50 

percent of retail sales nationwide. The data include model number, refrigerated volume, 

configuration of doors and ice-making, and whether the unit is an ENERGY STAR product. 

Based on these data DOE developed a sales-weighted price distribution for non-ENERGY STAR 

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EERE-2008-BT-STD-0012 COMMENT 20
 

appliances in each product class.a For the LCC and PBP analyses of standard-sized products, 

DOE assigned a baseline price from that distribution to each household sampled from the EIA’s 

2005 Residential Energy Consumption Survey (RECS).1

 For compact product classes, DOE 

assigned a baseline price from the distribution to each sampled product. Appendix 8-C presents 

the distribution histograms DOE developed for each product class. The average baseline retail 

prices before sales tax for each refrigeration product class are shown in Table 8.2.1. 

Table 8.2.1 Residential Refrigeration Products: Average Baseline Retail Price 

Product Class Baseline Retail Price 

2008$ 

Product class 3: Top-mount refrigerator-freezer 550 

Product class 5: Bottom-mount refrigerator-freezer 1,615 

Product class 7: Side-by-side refrigerator-freezer with TTD* 1,332 

Product class 9: Upright freezer 469 

Product class 10: Chest freezer 304 

Product class 11: Compact refrigerator 153 

Product class 18: Compact freezer 193 

* Through-the-door ice service. 

8.2.1.2 Increases in Manufacturer Selling Price 

DOE used a combination of cost data submitted by the Association of Home Appliance 

Manufacturers (AHAM)4 and a reverse engineering analysis to estimate increases to 

manufacturing cost associated with increases in efficiency levels for refrigeration products. Refer 

to Chapter 5, Engineering Analysis, for details. Adding the manufacturer markup described in 

chapter 6 yielded the MSP increases for each considered efficiency level and product class 

shown in Tables 8.2.2 through 8.2.4. 

a

 DOE assumed that prices for non-ENERGY STAR models are a reasonable approximation of prices for the 

baseline models. 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.2.2 Standard-Size Refrigerator-Freezers: Increases in Manufacturer Selling Prices 

Efficiency Level 

% less than 

baseline energy use 

Increase in MSP 2008$ 

Product Class 3: 

Top-Mount 

Refrigerator-Freezer 

Product Class 5: 

Bottom-Mount 

Refrigerator-Freezer 

Product Class 7: 

Side-by-Side 

Refrigerator-Freezer 

with TTD Ice Service 

10 3.50 1.80 11.18 

15 7.68 5.79 18.96 

20 16.39 13.72 54.26 

25 34.92 31.38 106.00 

30 62.06 45.06 167.29 

35 103.91 110.05 228.96 

40 156.20 183.33 310.77 

45 208.14 251.25 

* Through-the-door. 

Table 8.2.3 Standard-Size Freezers: Increases in Manufacturer Selling Prices 

Efficiency Level Increase in MSP 2008$ 

% less than baseline energy 

use 

Product Class 9: 

Upright Freezer 

Product Class 10: 

Chest Freezer 

10 6.41 2.35 

15 11.45 6.05 

20 13.57 24.08 

25 27.51 29.26 

30 46.58 34.84 

35 76.82 74.35 

40 124.06 77.12 

45 196.78 136.90 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.2.4 Compact Refrigeration Products: Increases in Manufacturer Selling Prices 

Efficiency Level 

% less than baseline 

energy use 

Increase in MSP 2008$ 

Product Class 11: 

Compact Refrigerator or 

Refrigerator-Freezer 

Product Class 18: 

Compact Chest Freezer 

10 3.36 6.05 

15 6.32 9.65 

20 8.85 34.03 

25 20.56 42.62 

30 21.63 60.19 

35 26.77 63.00 

40 39.24 75.22 

45 57.49 89.70 

8.2.1.3 Markup and Sales Tax 

To derive the incremental increase in consumer product cost for each efficiency level, 

DOE applied an incremental retail markup and sales tax to the MSP increases shown above. 

Refer to Chapter 6, Markups for Equipment Price Determination, for details. DOE also applied 

sales tax to the baseline retail prices. 

8.2.1.4 Installation Cost 

Because the cost to install refrigeration products does not change as efficiency increases, 

DOE did not incorporate installation costs in its analysis. 

8.2.1.5 Consumer Product Cost 

Tables 8.2.5 through 8.2.7 present the shipment-weighted consumer product cost at each 

considered efficiency standard level for the refrigeration product classes under consideration for 

new standards. These costs reflect the market efficiency distributions discussed in section 8.2.6. 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.2.5 Standard-Size Refrigerator-Freezers: Average Consumer Cost 

Efficiency Level 

% less than baseline 

energy use 

Product Class 3: 

Top-Mount 

2008$ 

Product Class 5: 

Bottom-Mount 

2008$ 

Product Class 7: 

Side-by-Side 

2008$ 

Baseline 591 1,758 1,459 

10 595 1,759 1,463 

15 599 1,759 1,469 

20 609 1,760 1,499 

25 631 1,782 1,563 

30 665 1,799 1,638 

35 716 1,879 1,714 

40 781 1,969 1,815 

45 845 2,053 

Table 8.2.6 Standard-Size Freezers: Average Consumer Cost 

Efficiency Level 

% less than baseline energy use 

Product Class 9: 

Upright 

2008$ 

Product Class 10: 

Chest 

2008$ 

Baseline 505 325 

10 511 328 

15 517 332 

20 520 355 

25 537 361 

30 561 368 

35 598 416 

40 656 420 

45 745 493 

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EERE-2008-BT-STD-0012 COMMENT 20
 

Table 8.2.7 Compact Refrigeration Products: Average Consumer Cost 

Efficiency Level 

% less than baseline energy use 

Product Class 11: 

Compact Refrigerator 

2008$ 

Product Class 18: 

Compact Freezer 

2008$ 

Baseline 166 207 

10 170 214 

15 173 218 

20 176 248 

25 191 259 

30 192 281 

35 198 284 

40 214 299 

45 236 317 

8.2.2 Inputs to Operating Cost 

DOE defines operating cost (OC) by the following equation. 

OC = EC + RC + MC
 

Where: 

EC = energy cost associated with operating the product, 

RC = repair cost associated with component failure, and 

MC = cost for maintaining appliance operation. 

DOE used the following equation to calculate the annual operating cost for baseline 

products. 

OC BASE = ( AEC BASE × PRICE ENERGY BASE BASE ) + RC + MC

Where: 

OCBASE = operating cost for baseline product, 

AECBASE = annual energy consumption for baseline product, 

PRICEENERGY = energy price, 

RCBASE = repair costs associated with component failure for baseline product, and 

MCBASE = maintenance costs for baseline product. 

DOE used the following equation to calculate the annual operating cost for higher 

efficiency products. 

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EERE-2008-BT-STD-0012 COMMENT 20
 

 

 

OC STD = (AEC STD × PRICE ENERGY STD STD ) + RC + MC

Where: 

OCSTD = operating cost of higher efficiency product, 

AECSTD = annual energy consumption of higher efficiency product, 

PRICEENERGY = energy price in each year, 

RCSTD = repair costs associated with component failure for higher efficiency product, 

and 

MCSTD = maintenance costs for higher efficiency product. 

8.2.2.1 Annual Energy Consumption 

As described in Chapter 7, Energy Use Determination, DOE developed samples of 

individual households that use each of the standard-sized refrigeration products considered 

herein. By developing the samples, DOE was able to calculate the LCC and PBP for each 

household to account for the variability in both energy use and energy price associated with that 

household. 

Tables 8.2.8 through 8.2.10 are derived from the analysis described in chapter 7. The 

values shown for annual energy consumption are averages in the field. For compact products, 

DOE did not use the RECS sample, and the energy consumption is as measured using the DOE 

test procedure. DOE captured the variability in energy consumption by using a range of values in 

its LCC and PBP analyses. 

Table 8.2.8 Standard-Size Refrigerator-Freezers: Average Annual Energy Use by 

Efficiency Level 

Product Class 3: 

Top-Mount RefrigeratorFreezer 

Product Class 5: 

Bottom-Mount RefrigeratorFreezer 

Product Class 7: 

Side-by-Side RefrigeratorFreezer with TTD† 

Efficiency Level 

% less than baseline 

energy use 

Energy 

Use 

kWh* 

Efficiency Level 

% less than baseline 

energy use 

Energy 

Use 

kWh 

Efficiency Level 

% less than baseline 

energy use 

Energy 

Use 

kWh 

Baseline 657 Baseline 699 Baseline 1,087 

10 591 10 629 10 979 

15 558 15 594 15 924 

20 526 20 559 20 870 

25 493 25 524 25 815 

30 460 30 489 30 761 

35 427 35 454 35 707 

40 394 40 419 40 652 

45 361 45 384 - -

* Kilowatt hours. 

†

Through-the-door ice service. 

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EERE-2008-BT-STD-0012 COMMENT 20
 

 

Table 8.2.9 Standard-Size Freezers: Average Annual Energy Use by Efficiency Level 

Product Class 9: 

Upright Freezer 

Product Class 10: 

Chest Freezer 

Efficiency Level 

% less than baseline 

energy use 

Energy Use 

kWh* 

Efficiency Level 

% less than baseline 

energy use 

Energy Use 

kWh 

Baseline 980 Baseline 623 

10 882 10 561 

15 833 15 530 

20 784 20 498 

25 735 25 467 

30 686 30 436 

35 637 35 405 

40 588 40 374 

45 539 45 343 

* Kilowatt hours. 

Table 8.2.10 Compact Refrigeration Products: Average Annual Energy Use by Efficiency 

Level 

Product Class 11: 

Compact Refrigerator 

Product Class 18: 

Compact Freezer 

Efficiency Level 

% less than baseline 

energy use 

Energy Use 

kWh* 

Efficiency Level 

% less than baseline 

energy use 

Energy Use 

kWh 

Baseline 325 Baseline 313 

10 292 10 282 

15 276 15 266 

20 260 20 250 

25 244 25 235 

30 227 30 219 

35 211 35 203 

40 195 40 188 

45 179 45 172 

* Kilowatt hours. 

8.2.2.2 Energy Prices 

Using data from EIA Form 8615

, DOE derived average energy prices for 13 geographic 

areas in the United States: the nine U.S. Census divisions, plus four large states (New York, 

Florida, Texas, and California) considered individually. For Census divisions containing one of 

those large states, DOE left out data for the large state when calculating average regional values. 

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EERE-2008-BT-STD-0012 COMMENT 20
For example, the Pacific region average excludes California, and the West South Central region 

excludes Texas. Using the modified regional data, DOE assigned an appropriate energy price to 

each household in the sample. 

DOE used data from EIA to estimate electricity prices for residential consumers in each 

of the 13 geographic areas These data, which are published annually, include annual electricity 

sales in kilowatt hours (kWh), revenues from electricity sales, and number of consumers by 

sector for every utility that serves final consumers. The calculation of an area-average residential 

or commercial electricity price proceeds in two steps. 

1.	 For each utility, an average sector (residential or commercial) price is estimated by 

dividing sector revenues by sector sales. 

2.	 An average regional price is calculated, whereby each utility having customers in a 

region is weighted by the number of residential consumers served in that region. 

The calculation used the most recent EIA data available at the time the analysis was conducted. 

Table 8.2.11 shows the average residential and commercial electricity price in 2007 for each 

Census division and large state. 

Table 8.2.11 Average Electricity Prices in 2007 

Geographic Area 

Average Residential Price 

2008$/kWh 

Average Commercial Price 

2008$/kWh 

New England 0.162 0.153 

Middle Atlantic 0.127 0.111 

East North Central 0.102 0.091 

West North Central 0.088 0.075 

South Atlantic 0.099 0.085 

East South Central 0.087 0.086 

West South Central 0.093 0.085 

Mountain 0.097 0.084 

Pacific 0.099 0.094 

New York State 0.178 0.169 

California 0.150 0.136 

Texas 0.128 0.119 

Florida 0.117 0.102 

Source: U.S. Department of Energy–Energy Information Administration EIA Form 861. 

8.2.2.3 Energy Price Trends 

To estimate energy prices in future years, DOE multiplied the average prices listed in 

Table 8.2.11 by the forecast of annual average price changes in the EIA’s AEO 2009.2

 To 

estimate the trend after 2030, DOE followed guidelines that the EIA had provided to the Federal 

8-16 

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Energy Management Program, which called for using the average rate of change for electricity 

during 2020–2030. 

The Department calculated LCC and PBP for each class of refrigeration products using 

three separate projections from AEO 2009: reference, low, and high economic growth. 

Alternative assumptions regarding the future growth in energy markets reflects the uncertainty 

regarding economic conditions during the forecast period. Figure 8.2.1 shows the projected 

trends in residential and commercial electricity prices based on the AEO 2009 reference case. 

For the LCC results presented in this chapter, DOE used only the energy price forecasts from the 

AEO reference case. 

Electricity Price Trends 

1.2 

1.1 

1.0 

0.9 

0.8 

AEO 2009 Reference Res Elec 

AEO 2009 Reference Com Elec 

2000 2005 2010 2015 2020 2025 2030 

Source: Energy Information Administration, Annual Energy Outlook. 2009. 

Figure 8.2.1	 Residential and Commercial Electricity Price 

Trends (2007 = 1) 

8.2.2.4 Repair and Maintenance Costs 

Because DOE found no evidence that repair or maintenance costs change as the 

efficiency of refrigeration products increases, it excluded those costs from its analysis. 

8.2.3 Product Lifetimes 

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EERE-2008-BT-STD-0012 COMMENT 20
 

8.2.3.1 Estimated Survival Function 

The Energy Information Agency (EIA)’s Residential Energy Consumption Survey 

(RECS)1

 of occupied primary housing units records the presence of various appliances in each 

household, and places the age of each appliance into bins comprising several years. Data from 

the U.S. Census’s American Housing Survey (AHS),6

 which surveys all housing including vacant 

and second homes, enabled DOE to adjust the RECS data to reflect some appliance use outside 

of primary residences. By combining the results of both surveys with the known history of 

appliance shipments (collected from Appliance magazine or directly from manufacturer trade 

associations), DOE estimated the percentage of appliances of a given age still in operation. This 

survival function, which DOE assumed has the form of a cumulative Weibull distribution, 

provides an average and a median appliance lifetime. 

 The Weibull distribution is a probability distribution commonly used to measure failure 

rates.b

 Its form is similar to an exponential distribution, which models a fixed failure rate, except 

that a Weibull distribution allows for a failure rate that changes over time in a particular fashion. 

The cumulative Weibull distribution takes the form: 

⎛ x−θ ⎞

β

−⎜ ⎟ P(x) = e ⎝ α ⎠ for x > θ and 

P(x) = 1 for x ≤ θ

Where: 

P(x) = probability that the appliance is still in use at age x; 

x = appliance age; 

α = scale parameter, which would be the decay length in an exponential distribution; 

β = shape parameter, which determines the way in which the failure rate changes through 

time; and 

θ = delay parameter, which allows for a delay before any failures occur. 

When β = 1, the failure rate is constant over time, giving the distribution the form of a 

cumulative exponential distribution. In the case of appliances, β commonly is greater than 1, 

reflecting an increasing failure rate as appliances age. 

The RECS survey is DOE’s primary resource for appliance ages. For several appliances, 

including refrigerators and freezers, the survey asks respondents to identify the appliance’s age 

as: 

• less than 2 years old, 

• 2 to 4 years old, 

• 5 to 9 years old, 

b

 For reference on the Weibull distribution, see sections 1.3.6.6.8 and 8.4.1.3 of the NIST/SEMATECH e-Handbook 

of Statistical Methods, <www.itl.nist.gov/div898/handbook/>. 

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• 10 to19 years old, or 

• more than 20 years old. 

The RECS survey has been conducted every three or four years for the past several 

decades. For this analysis, DOE used the surveys conducted in 1990, 1993, 1997, 2001, and 

2005. DOE used the AHS count of housing units that contain refrigerators to scale the RECS 

data to better match the total installed stock. The U.S. Census AHS does not include data on 

freezers. DOE used the RECS micro-data to exclude from this analysis refrigerators that are both 

“half-height” and less than 10 cubic feet in capacity, because such refrigerators are not standardsized. To determine overall refrigerator lifetime, DOE included all appropriately sized 

refrigerators, whether the household’s first (primary) or second refrigerator. Households that did 

not know the age of their appliance were allocated among the remaining age bins according to 

the distribution of respondents who did report the appliance age. 

Refrigerator ownership exhibits complex consumer behavior, which is not adequately 

reflected in AHS. In particular, AHS records only whether a housing unit contains a refrigerator, 

not the number of refrigerators. In addition, AHS may record a unit as containing a refrigerator 

when it contains a compact, rather than standard-size, appliance. Therefore, DOE used AHS only 

to scale the number of first refrigerators recorded by RECS. The baseline number of refrigerators 

reported in each RECS age bin is the sum of the AHS-scaled first refrigerators and the un-scaled, 

standard-size second refrigerators. 

DOE adjusted the RECS survey data to account for the fact that the RECS survey begins 

its reference year with July, whereas shipments data are provided for each calendar year. DOE 

adjusted the data by using the survival function to model the additional retirement and 

replacement of appliances that takes place in the latter half of a survey year (after a given 

respondent is surveyed). 

DOE used the RECS data on appliance ages, combined with the history of appliance 

shipments, to develop survival functions for refrigeration products. For example, DOE summed 

the total shipments from 5 to 9 years before each RECS survey, then compared this number with 

the number of units still in use at the time of the survey to approximate the percentage of 

surviving appliances within that age bin. By combining the age bins from the five RECS surveys 

with shipments data, DOE had enough data to use a least-squares method to build a fit to a 

Weibull distribution and find the parameters (α, β, θ) that best approximate the number of 

surviving units. Because the first two (youngest) RECS bins tend to have a large scatter relative 

to the shipments in those years, DOE combined the RECS and shipments data in the first two 

bins. Refrigerators and freezers generally do not fail during their first four years, so combining 

bins did not lower appreciably the accuracy of the distribution. DOE weighted each bin’s 

contribution to the sum of squares by the inverse of the variance in RECS survey results, which 

controls for the changes in sample size between bins and through time.c

 RECS has a complex 

c

 See sections 4.1.4.3, 4.4.3.2, and 4.4.5.2 of NIST/SEMATECH e-Handbook of Statistical Methods, 

<www.itl.nist.gov/div898/handbook/>. 

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EERE-2008-BT-STD-0012 COMMENT 20
error model. DOE used only the error due to finite sample size to determine the variance for 

weighting the age bins. The equation for the sum of squares that DOE minimized is: 

(RECSi − Survi )

2 

∑ σ2 , i i,RECS 

Where: 

i = the identifier for a bin from a single RECS; 

RECSi = the number of appliances reported by RECS in bin I; 

Survi = the number of surviving appliances in bin i predicted by the Weibull distribution 

applied to the number of appliances shipped (a function of α, β, and θ); and 

σi,RECS = the standard error (square root of the variance) of the RECS data point for bin i. 

Table 8.2.13 shows the RECS data for refrigerators, the associated total shipments, and 

the best-fit Weibull calculation of stock by age bin. Figure 8.2.2 plots the data from the third and 

fourth columns of Table 8.2.12 against each other to show the quality of the fit. DOE allowed the 

delay parameter, θ, to vary only between 1 and 5 years, which corresponds to common warranty 

periods (see discussion below). For refrigerators and freezers, the best fit within this range is 5 

years. 

The Weibull distribution, shown in Figure 8.2.3, is characterized by the parameters α = 

13.91, β = 1.68, and θ = 5.0. This distribution has a mean refrigerator lifetime of 17.43 years and 

a median lifetime of 16.18 years. 

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Table 8.2.12 Standard-Size Refrigerator-Freezers: Comparison of Survey and Shipments 

Data with Modeled Stock 

RECS 2005 

All Refrigerators Second Refrigerators 

Modeled Modeled 

Age Bin years Shipments RECS Stock Stock RECS Stock Stock 

0 to 4 51,119,128 56,880,896 51,119,128 5,311,005 3,041,016 

5 to 9 42,988,500 40,150,841 41,031,292 4,983,112 3,524,129 

10 to 19 68,088,000 36,771,769 40,997,548 8,672,157 6,942,353 

20 or more 165,800,000 10,337,608 12,039,872 4,139,841 4,628,220 

RECS 2001 

All Refrigerators Second Refrigerators 

Modeled Modeled 

Age Bin years Shipments RECS Stock Stock RECS Stock Stock 

0 to 4 44,319,100 46,312,479 44,319,100 2,460,510 2,637,703 

5 to 9 36,982,000 39,491,335 35,298,172 3,868,224 3,031,985 

10 to 19 60,556,000 35,970,898 36,813,807 6,572,685 6,198,453 

20 or more 144,325,000 11,301,203 11,920,574 3,955,496 4,580,842 

RECS 1997 

All Refrigerators Second Refrigerators 

Modeled Modeled 

Age Bin years Shipments RECS Stock Stock RECS Stock Stock 

0 to 4 38,185,000 44,356,564 38,185,000 2,047,982 2,274,485 

5 to 9 32,698,000 36,760,359 31,123,487 2,782,204 2,695,071 

10 to 19 56,244,000 31,056,224 33,972,064 5,078,190 5,724,270 

20 or more 122,660,000 10,989,427 11,832,244 3,879,197 4,475,841 

RECS 1993 

All Refrigerators Second Refrigerators 

Modeled Modeled 

Age Bin years Shipments RECS Stock Stock RECS Stock Stock 

0 to 4 33,088,000 37,322,759 33,088,000 1,605,544 1,972,965 

5 to 9 31,584,000 35,001,768 30,138,108 2,289,052 2,591,010 

10 to 19 52,400,000 32,735,032 30,891,143 4,695,960 5,348,774 

20 or more 101,577,000 13,119,858 11,723,329 5,708,862 4,296,210 

RECS 1990 

All Refrigerators Second Refrigerators 

Modeled Modeled 

Age Bin years Shipments RECS Stock Stock RECS Stock Stock 

0 to 4 32,670,000 38,098,670 32,670,000 1,784,095 1,950,717 

5 to 9 26,419,000 30,724,176 25,249,353 2,227,766 2,158,527 

10 to 19 56,584,000 34,088,557 33,242,186 5,316,297 5,767,417 

20 or more 82,797,000 12,571,836 10,159,632 4,869,236 3,737,018 

Source: U.S. Department of Energy–Energy Information Agency. Residential Energy Consumption Survey. 1990, 

1993, 1997, 2001, and 2005. 

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EERE-2008-BT-STD-0012 COMMENT 20
Calculated number of refrigerators by bin 40000000 

30000000 

20000000 

10000000 

0 

bins 

ideal 

0 10000000 20000000 30000000 40000000 

RECS reported number of refrigerators by bin 

Figure 8.2.2 Comparison of Modeled Refrigerator Age Distribution with Data 

from Residential Energy Consumption Surveys 

1.2 

1.0 

Fraction surviving 

0.8 

0.6 

0.4 

0.2 

0.0 

16.18 

17.43 

Survival function 

Median lifetime 

Mean lifetime 

0 5 10 15 20 25 30 35 40 45 

Age (years) 

Figure 8.2.3 Survival Function for Standard-Size Refrigerator-Freezers 

8-22 

50 

EERE-2008-BT-STD-0012 COMMENT 20
The method DOE used to calculate product lifetimes incorporates several assumptions: 

•	 Appliance lifetime can be modeled by a survival function. In particular, a Weibull 

distribution is an appropriate survival function. 

•	 The appliance survival function does not change through time. 

•	 The survival function is independent of other household factors (such as household 

size or geographic region) as well as product class (within standard-size refrigerators 

or freezers). 

•	 RECS respondents neither systematically overestimated nor underestimated the 

current age of their appliance. 

•	 The historical shipment data are accurate. 

•	 The shipped appliances are installed exclusively (or almost exclusively) in residences. 

•	 The Weibull delay parameter, θ, is limited to between 1 and 5 years. 

Three of these assumptions reflect analytical choices made by DOE. The first is the 

assumption that a Weibull distribution is the appropriate distribution to use for rates of appliance 

retirement. This distribution is the standard one used in lifetime analyses, but it is not guaranteed 

to reflect actual real-world experience. The second assumption is that consumer behavior and 

mechanical appliance lifetime have not changed over time. This assumption required DOE to 

treat equally all data from the several RECS surveys. Using only recent surveys (which may 

better reflect recent consumer behavior and appliance lifetime) would provide only a few data 

points for attempting least-squares fits, producing large statistical uncertainty. 

The third assumption concerns the Weibull delay parameter. DOE limited the delay 

parameter to between 1 and 5 years to reflect the range of common appliance warranties. A delay 

of less than 1 year would imply that some appliances fail or are replaced within their first year of 

use. A delay of more than 5 years would imply that no appliances are replaced for some time 

after the end of the longest standard warranty. Fits using θ > 5 also commonly show nonsensical 

behavior, with sharp changes in consumer behavior or appliance survival immediately following 

the delay period. 

8.2.3.2 Conversion of First to Second Refrigerators 

When a household purchases a new refrigerator, sometimes it uses its original unit as a 

secondary appliance in the basement or garage. DOE modeled the process by which first 

refrigerators are converted to second refrigerators as a Weibull process having a cumulative 

distribution of the form: 

⎛ ⎜

⎛ x−θ ⎞

β

− ⎞ ⎟ P(x) = δ + (1−δ )×⎜1− e ⎝ α ⎠ ⎟ for x > θ and ⎜ ⎟ ⎝ ⎠

P(x) = δ for x ≤ θ

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EERE-2008-BT-STD-0012 COMMENT 20
Where: 

P(x) = probability that the appliance has been converted at age x; 

x = appliance age; 

α = the scale parameter, which would be the decay length in an exponential distribution; 

β = the shape parameter, which determines the way in which the conversion rate changes 

through time; 

δ = the percentage of shipments that are used immediately as second refrigerators; and 

θ = the delay parameter, which allows for a delay before any conversions occur. 

Rather than comparing second refrigerators to shipments, DOE compared them with the 

existing total installed base of refrigerators of a certain age, as measured by RECS. As with 

calculating appliance lifetime, the RECS data were adjusted with AHS data. In essence, DOE 

constructed a Weibull distribution to model a conversion function rather than a survival function. 

In addition, the model allows for the direct purchase of a new second refrigerator. A refrigerator 

bought to be a second refrigerator is modeled as being converted from first to second 

immediately at purchase; the offset parameter δ represents those units. Refrigerators commonly 

are bought to be second units, as indicated by the relatively large number of young second 

refrigerators reported by in RECS surveys. 

DOE fit the conversion function using results from the 1990, 1993, 1997, 2001, and 2005 

RECS. The RECS micro-data again enabled removing refrigerators that are not standard size, 

which has a significant effect given that many compact refrigerators are used as second units. In 

Table 8.2.12 the fifth column shows the RECS-derived stock of second refrigerators by age bin, 

and the sixth column shows the best fit from a Weibull distribution. Figure 8.2.4 shows the 

Weibull distribution. The best-fit Weibull parameters for the conversion function are α = 38.12, β

= 2.03, and θ = 0.0, with an offset of 5.6 percent (meaning that 5.6 percent of shipments are sold 

as new second refrigerators). Roughly 1.5 percent of surviving refrigerators are converted from 

first to second refrigerator status each year, and roughly 20 percent of surviving refrigerators are 

converted to second refrigerators before they reach 15 years of age. 

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EERE-2008-BT-STD-0012 COMMENT 20
0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

Fraction converted to 2nd refrigerator

Conversion function 

0 10 20 30 40 50 

Age (years) 

Figure 8.2.4 Function for Conversion of First to Second Refrigerator-Freezers 

8.2.3.3 Standard-Size Freezers 

DOE assumed relatively simple consumer behavior related to freezers. DOE did not 

model the conversion from first to second freezer for households having more than one freezer, 

but simply used all freezer data from RECS. Standard-sized freezers were assumed to have a 

capacity greater than 10 cubic feet. As with refrigerators, RECS bins were adjusted for units 

replaced in the second half of a year to synchronize the RECS and shipments data. RECS did not 

collect freezer lifetime data in 1990, so DOE used results from only the 1993, 1997, 2001, and 

2005 surveys. The U.S. Census AHS survey does not report data on freezers, so the RECS bins 

were not scaled by the AHS total as for refrigerators. Before 2005, RECS reported the age 

distribution only for a household’s first freezer, so DOE assumed that second and third freezers 

have the same age distribution as first freezers. 

The best-fit Weibull parameters for freezer lifetime are α = 19.49, β = 2.40, and θ = 5.0. 

The resulting calculated mean freezer lifetime is 22.28 years; the median is 21.73 years. Table 

8.2.13 lists the (adjusted) number of freezers reported in each RECS age bin, along with the 

modeled stock based on the best-fit Weibull survival function and the manufacturer-provided 

shipments history. Figure 8.2.5 shows the survival function used for standard-size freezers in the 

LCC and national impact analyses. 

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EERE-2008-BT-STD-0012 COMMENT 20
Table 8.2.13 Standard-Size Freezers: Comparison of Survey and Shipments Stock to 

Modeled Stock 

RECS 2005 

Age Bin years Shipments RECS Stock Modeled Stock 

0–4 12,003,000 9,378,328 12,003,000 

5–9 8,617,000 8,118,709 8,557,502 

10–19 13,571,000 9,886,011 11,269,325 

20 or more 47,672,000 7,607,227 6,973,305 

RECS 2001 

Age Bin years Shipments RECS Stock Modeled Stock 

0–4 9,284,000 8,462,128 9,284,000 

5–9 7,615,000 6,939,187 7,557,289 

10–19 12,648,000 12,144,649 10,366,534 

20 or more 42,528,000 7,494,606 7,817,703 

RECS 1997 

Age Bin years Shipments RECS Stock Modeled Stock 

0–4 7,580,000 7,192,449 7,580,000 

5–9 6,578,000 7,527,447 6,529,381 

10–19 13,920,000 12,591,552 11,241,688 

20 or more 36,203,000 6,561,157 8,045,004 

RECS 1993 

Age Bin years Shipments RECS Stock Modeled Stock 

0–4 6,700,000 6,018,630 6,700,000 

5–9 6,250,000 6,924,204 6,202,243 

10–19 17,801,000 13,279,168 14,110,780 

20 or more 27,388,000 8,277,900 6,374,921 

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EERE-2008-BT-STD-0012 COMMENT 20
21.73 

22.28 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

Fraction surviving 

Survival function 

Median lifetime 

Mean lifetime 

0 5 10 15 20 25 30 35 40 45 50 

Age (years) 

Figure 8.2.5 Survival Function for Standard-Size Freezers 

8.2.3.4 Compact Refrigeration Products 

As mentioned previously, compact refrigeration products are used in the residential and 

commercial sectors. RECS micro-data identify households that have refrigerators that are “halfheight” and less than 10 cubic feet in capacity. DOE considered those households as potentially 

using compact refrigerators. EIA’s Commercial Building Energy Consumption Survey (CBECS) 

survey of 20037

 notes the presence of a residential-style refrigerator in an establishment. 

However, CBECS provides no further detail regarding the size of the refrigerator. Thus, RECS 

and CBECS data together do not provide enough detail on compact refrigerators to develop a 

survival function similar to the ones developed for standard-sized refrigerator-freezers and 

freezers. 

DOE assumed that a Weibull distribution remains the appropriate functional form to 

represent retirement rates of compact refrigeration products. DOE initially used the average 

value of lifetime and historical shipments data from Appliance magazine to estimate Weibull 

parameters for compact refrigerators. When DOE applied the average lifetime of 10 years, given 

in Appliance magazine, to historical shipments, the model yielded a stock of compact 

refrigerators that was more than double the stock indicated by RECS and CBECS. DOE 

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EERE-2008-BT-STD-0012 COMMENT 20
 

 

 

therefore calibrated the average lifetime to match the stock of compact refrigerators as reported 

by the surveys. 

The estimated Weibull parameters for compact refrigerator lifetime are α = 5.75 and β = 

1.75. The resulting calculated mean lifetime is 5.62 years. For determining the lifetime of 

compact freezers, DOE used a scaling factor proportional to the ratio of the lifetimes of standardsized refrigerators and standard-sized freezers. The calculated mean lifetime of a compact freezer 

is 7.46 years. 

8.2.4 Discount Rates 

The discount rate is the rate at which DOE discounts future expenditures to establish their 

present value. DOE derived discount rates for the LCC and PBP analyses from estimates of the 

cost to finance the purchase of the considered products. Following financial theory, the financal 

cost of raising funds to purchase appliances can be interpreted as: (1) the financial cost of any 

debt incurred to purchase a product, or (2) the opportunity cost of any equity used to purchase a 

product. In addition to estimating discount rates for appliances bought directly by consumers, 

DOE also estimated discount rates for purchasers of compact refrigerators and freezers in the 

commercial sector. 

8.2.4.1 Discount Rates for Residential Consumers 

Households use various methods to finance the purchase of major appliances. In 

principle, one could estimate the interest rates on the actual financing vehicles used to purchase 

appliances. The frequency with which each financing vehicle is used to purchase an appliance is 

unknown, however. 

DOE’s approach involved identifying all possible debt or asset classes that might be used 

to purchase the considered appliances, including household assets that might be affected 

indirectly.d

 DOE excluded debt from primary mortgages and the equity of assets considered 

non-liquid (such as retirement accounts), because those are unlikely to be used to purchase 

appliances. DOE estimated the average percentage shares of the various types of debt and equity 

in the average U.S. household using data from the Federal Reserve Board’s Survey of Consumer 

Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007.8

 Table 8.2.15 shows the 

average percentages of each considered type of debt or equity. DOE derived the mean 

percentages of each source of financing throughout the 7 years surveyed. 

d An indirect effect would arise if a household sold assets in order to pay off a loan or credit card debt that might 

have been used to finance the appliance purchase. 

8-28 

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Table 8.2.14 Types of Household Debt and Equity by Percentage Shares 

Type of Debt or Equity 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % 

Home equity loan 4.3 4.5 2.7 2.8 2.8 4.4 4.6 3.7 

Credit card 1.6 2.1 2.6 2.2 1.7 2.0 2.4 2.1 

Other installment loan 2.8 1.7 1.4 1.7 1.1 1.3 1.1 1.6 

Other residential loan 4.4 6.9 5.2 4.3 3.1 5.8 7.1 5.3 

Other line of credit 1.1 0.6 0.4 0.2 0.3 0.5 0.3 0.5 

Checking account 5.8 4.7 4.9 3.9 3.6 4.2 3.4 4.4 

Savings or money market 

account 19.2 18.8 14.0 12.8 14.2 15.1 13.0 15.3 

Certificate of deposit 14.5 11.7 9.4 7.0 5.4 5.9 6.5 8.6 

Savings bond 2.2 1.7 2.2 1.1 1.2 0.9 0.7 1.4 

Bonds 13.8 12.3 10.5 7.0 7.9 8.4 6.7 9.5 

Stocks 22.4 24.0 25.9 36.9 37.5 28.0 28.6 29.0 

Mutual funds 8.0 11.1 20.9 20.1 21.3 23.4 25.5 18.6 

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 

2007. 

DOE estimated interest or return rates associated with each type of equity and debt. The 

source for interest rates for loans, credit cards, and lines of credit was the Federal Reserve 

Board’s SCF for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Table 8.2.16 shows the average 

nominal rates in each year and the inflation factors used to calculate real rates. DOE calculated 

effective interest rates for home equity loans in a similar manner as for mortgage rates, because 

interest on both such loans is tax deductible. Table 8.2.17 shows the average effective real rates 

in each year and the mean rate across years. Because the interest rates for each type of household 

debt reflect economic conditions throughout numerous years, they are expected to be 

representative of rates that may be in effect in 2014. 

Table 8.2.15 Average Nominal Interest Rates for Household Debt 

Type of Debt 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % 

Home equity loan 11.5 9.6 9.6 9.8 8.7 5.7 6.3 7.9 

Credit card* - - 14.2 14.5 14.2 11.7 7.9 9.0 

Other installment loan 9.0 7.8 9.3 7.8 8.7 7.4 12.6 13.4 

Other residential loan 8.8 7.6 7.7 7.7 7.5 6.0 10.4 8.6 

Other line of credit 14.8 12.7 12.4 11.9 14.7 8.8 6.3 7.4 

Inflation rate 4.82 3.01 2.83 1.56 2.85 2.66 2.85 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 

2007. 

* No data on interest rates available for credit cards in 1989 or 1992. 

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Table 8.2.16 Average Real Effective Interest Rates for Household Debt 

Type of Debt 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % 

Home equity loan 3.8 4.3 4.4 5.8 3.8 1.9 2.1 3.0 

Credit card* - - 11.0 12.7 11.1 9.1 3.3 3.9 

Other installment loan 4.9 5.8 7.0 6.6 6.1 5.4 9.7 10.7 

Other residential loan 4.0 4.7 4.8 6.0 4.6 3.3 5.8 6.0 

Other line of credit 9.6 9.4 9.3 10.2 7.3 6.0 3.4 4.4 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 

2004, and 2007. 

* No data on interest rates available for credit cards in 1989 or 1992. 

No similar rate data are available from the SCF for classes of assets, so the Department 

derived that information from national historical data. The interest rates associated with 

certificates of deposit,9

 savings bonds,10 and bonds (AAA corporate bonds)11 were collected from 

Federal Reserve Board time-series data for 1977–2008. DOE assumed rates on checking 

accounts to be zero. Rates on savings and money market accounts came from Cost of Savings 

Index data covering 1984–2008. 12 The rates for stocks are the annual returns on the Standard and 

Poor’s 500 for 1977–2008. 13 Rates for mutual funds are a weighted average of the stock rates 

(two-thirds weight) and the bond rates (one-third weight) in each year for 1977–2008. DOE 

adjusted the nominal rates to real rates using the annual inflation rate for each year. Average 

nominal and real interest rates for the classes of household assets are listed in Table 8.2.18. 

Because the interest and return rates for each type of asset reflect economic conditions 

throughout numerous years, they are expected to be representative of rates that may be in effect 

in 2014. 

Table 8.2.17 Average Nominal and Real Interest Rates for Household Equity 

Type of Equity Average Nominal Rate % Average Real Rate % 

Checking account - 0.0 

Savings and money market accounts 5.4 2.2 

Certificate of deposit 6.6 2.3 

Savings bond 7.7 3.3 

Bonds 8.5 4.1 

Stocks 11.6 7.1 

Mutual funds 10.3 5.8 

Table 8.2.19 summarizes the mean real effective rates of each type of equity or debt. 

DOE determined the average percentage of each type of debt and asset using SCF data for 1989, 

1992, 1995, 1998, 2001, 2004, and 2007. Each year of SCF data provides the percents of debts 

and assets for U.S. households. DOE averaged those percentages for the 7 years of survey data to 

arrive at the percentages shown in Table 8.2.19. The average rate across all types of household 

debt and equity, weighted by the percentages of each type, is 4.8 percent. 

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Table 8.2.18 Average Interest on Household Debt and Equity 

Type of Debt or Equity 

Average % of Household 

Debt plus Equity* 

Mean Effective Real Rate 

%** 

Home equity loan 3.7 3.9 

Credit card 2.1 10.7 

Other installment loan 1.6 6.0 

Other residential loan 5.3 4.4 

Other line of credit 0.5 8.8 

Checking account 4.4 0.0 

Savings and money market account 15.3 2.2 

Certificate of deposit 8.6 2.3 

Savings bond 1.4 3.3 

Bonds 9.5 4.1 

Stocks 29.0 7.1 

Mutual funds 18.6 5.8 

Total/weighted-average discount rate 100.0 4.8 

* Not including primary mortgage or retirement accounts.
 

** Adjusted for inflation and, for home equity loans, tax deduction of interest.
 

8.2.4.2 Assignment of Discount Rates to Sample Households 

To account for variations among households, DOE assigned each sampled RECS 

household a rate from a distribution of rates for each type of debt and equity. DOE developed a 

probability distribution of interest rates based on SCF data. Appendix 8-C presents the 

probability distribution of interest rates that DOE used in the LCC and PBP analyses. 

8.2.4.3 Discount Rates for Commercial Purchasers 

DOE derived the discount rate for commercial owners of compact refrigeration products 

from the cost of capital of publicly traded firms in the sectors that purchase those products. The 

firms typically finance equipment purchases through debt and/or equity capital. DOE estimated 

the cost of the firms’ capital as the weighted average of the cost of equity financing and the cost 

of debt financing for each year between 2001 and 2008. 

The costs of debt and equity financing usually are publicly available for firms in the 

lodging and other commercial sectorse

 that may purchase compact refrigeration products. 

DOE estimated the cost of equity using the capital asset pricing model (CAPM).14 The 

CAPM assumes that the cost of equity (ke) for a given company is proportional to the systematic 

risk faced by that company, whereby high risk is associated with a high cost of equity and low 

e

 The “other commercial” sector includes financial institutions and all services other than lodging (SIC 6-8). 

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risk is associated with a low cost of equity. The systematic risk facing a firm is determined by 

several variables: the risk coefficient of the firm (β), the expected return on risk-free assets (Rf), 

and the equity risk premium (ERP). The risk coefficient of a firm describes the risk associated 

with that firm represented by standard deviations in the firm’s stock price. The expected return 

on risk-free assets is defined by the yield on long-term government bonds. The ERP represents 

the difference between the expected stock market return and the risk-free rate. To estimate the 

expected return on risk-free assets and the equity risk premium, DOE used stock and bond data 

from Damodaran Online, a widely used source of information about debt and equity financing 

for most types of firms. 15,16 The Damodaran Online data were adjusted for annual inflation 

using deflator data for the gross domestic product from the Bureau of Economic Analysis’ 

National Income and Product Accounts Tables.

17 

The cost of equity financing is estimated using the following equation: 

ke = Rf + (β× ERP) 

Where: 

ke = cost of equity, 

Rf = inflation-adjusted expected return on risk-free assets,f
 

β = risk coefficient of the firm, and 

ERP = equity risk premium.
 

The cost of debt financing (kd) is the interest rate paid on money a company borrows. The 

cost of debt is estimated by adding a risk adjustment factor (Ra) to the risk-free rate. This risk 

adjustment factor depends on the variability of stock returns represented by standard deviations 

in the firm’s stock price. Thus for firm i, the cost of debt financing is: 

k di f ai = R + R

Where: 

kd = cost of debt financing for firm i, 

Rf = expected return on risk-free assets, and 

Rai = risk adjustment factor to risk-free rate for firm i. 

DOE estimates the weighted-average cost of capital using the following equation. 

WACC = k e e d d × w + k × w

Where: 

WACC = weighted average cost of capital, 

f

 Ibbotson Associates argues that the arithmetic mean equates the expected future value with the present value and 

should be used in calculating the risk-free rate and equity risk premium when using CAPM to estimate discount 

rates (Stocks, Bonds, Bills, and Inflation 2009 Yearbook, Ibbotson Associates, p. 60). 

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we = proportion of equity financing, and 

wd = proportion of debt financing. 

The values of the parameters used in the calculations are shown in Table 8.2.20. 

Table 8.2.19 Data for Calculating Weighted-Average Cost of Capital for Commercial 

Sectors 

Sector Year β Rf 

% 

ERP 

% 

Ra 

% 

we 

% 

wd 

% 

2001 1.18 3.25 5.17 1.50 88 12 

2002 1.27 3.55 3.66 1.50 89 11 

2003 1.71 3.40 4.70 1.25 93 7 

Lodging 2004 0.98 3.43 4.34 1.00 89 11 

2005 1.45 3.36 4.08 1.25 93 7 

2006 1.24 3.36 4.13 1.25 93 7 

2007 1.25 3.54 4.33 1.00 96 4 

2008 1.23 4.10 2.33 2.00 86 14 

2001 0.87 3.25 5.17 3.50 77 23 

2002 0.92 3.55 3.66 3.50 77 23 

2003 0.87 3.40 4.70 1.50 81 19 

Other 

Commercial 

2004 0.90 3.43 4.34 1.25 84 16 

2005 0.88 3.36 4.08 1.50 82 18 

2006 0.91 3.36 4.13 2.00 84 16 

2007 0.87 3.54 4.33 1.25 79 21 

2008 0.93 4.10 2.33 3.00 68 32 

Note: Parameters are defined on the preceding two pages. 

Using the procedure described above and the data in Table 8.2.20, DOE developed the 

real weighted-average cost of capital for the two commercial sectors that purchase compact 

refrigeration products. Those costs are listed in Table 8.2.21. 

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Table 8.2.20 Weighted-Average Cost of Capital for Commercial Sectors 

Year Lodging % Other Commercial % 

2001 5.69 6.75 

2002 5.11 6.21 

2003 5.49 6.64 

2004 5.82 6.62 

2005 5.95 6.24 

2006 6.04 6.46 

2007 6.42 6.40 

2008 5.74 5.60 

Sector average 5.78 6.37 

In calculating the discount rate for companies that typically purchase compact 

refrigeration products, DOE generated a distribution of discount rates within each sector. The 

standard deviation of the distribution for each sector is provided in Table 8.2.22. Weighting each 

sector’s discount rate by its share of compact refrigerator purchases,g

 DOE estimated that the 

average discount rate for companies that purchase compact refrigeration products is 6.20 percent. 

Table 8.2.21 Discount Rates for Commercial Sectors 

Sector 

Discount Rate 

Average % % of Purchases Max. % Min. % Standard Deviation % 

Lodging 5.78 11.98 2.35 1.26 29 

Other commercial 6.37 15.65 2.48 1.72 71 

Weighted average 6.20 - - - 100 

To account for variations in discount rates within each sector, DOE applied a normal 

probability distribution to the average values and standard deviations in Table 8.2.22. DOE 

truncated the normal distribution using the maximum and minimum values presented in Table 

8.2.22. 

8.2.5 Effective Date of Standard 

The effective date of a potential new standard is the future date when it would become 

operative. Based on DOE’s implementation report for energy conservation standards activities 

submitted pursuant to section 141 of the Energy Policy Act of 2005, a final rule pertaining to the 

appliances being considered for this rulemaking is scheduled for December 2010.18 The effective 

date of any new energy efficiency standards for the products is 3 years after the final rule is 

g

 The approach for estimating the share of total purchases by each of the two commercial sectors is described in 

chapter 9. 

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published, or January 2014. The Department calculated the life-cycle cost (LCC) for all 

consumers as if each would purchase a new appliance in the year the standard is to take effect. 

8.2.6 Base-Case Energy Efficiencies 

To estimate the percentage of consumers who would be affected by a standard at any of 

the potential efficiency levels, in its LCC analysis DOE considered the projected distribution of 

efficiencies for products that consumers purchase under the base case (the case without new 

energy efficiency standards). DOE refers to this distribution of product energy efficiencies as the 

base-case efficiency distribution. Using the projected distribution of efficiencies for each product 

class, DOE randomly assigned a product efficiency to each sample household. If a household 

was assigned a product efficiency that was greater than or equal to the efficiency of the standard 

level under consideration, the LCC calculation would show that this household would not be 

affected by that standard level. 

DOE began with the energy efficiency distribution (market shares) for refrigeration 

products in 2007 based on data provided by AHAM19. In 2007, efficiency level 2 for 

refrigerator-freezers corresponded to the efficiency required for ENERGY STAR certification. In 

2008, the criteria changed so that efficiency level 3 corresponded to the efficiency required for 

ENERGY STAR certification. If the market shares of refrigeration products by efficiency were 

the same in 2008 as in 2007, the ENERGY STAR market share would be 0 percent for topmount refrigerators, 18 percent for bottom-mount refrigerators, and 2 percent for side-by-side 

refrigerators. 

Efforts to promote ENERGY STAR products through various means, including consumer 

rebates, are expected to increase their market shares by 2014. Although it is difficult to predict 

appliance sales in 2014, it is reasonable to assume that the increase in market shares of ENERGY 

STAR products will follow the same pattern as they did between 2001 (the year in which the 

current DOE standards took effect and caused a shift in ENERGY STAR requirements) and 

2007. The projected market shares of efficiency levels are shown in Table 8.2.23. As shown, the 

assumed market share of ENERGY STAR models in 2014 (under current requirements) is equal 

to the market share of ENERGY STAR models in 2007 (under the old requirements). For 

example, because 32 percent of side-by-side refrigerator-freezers qualified for ENERGY STAR 

(efficiency level 2 and higher) under the pre-2008 requirements, DOE assumed that 32 percent 

would meet ENERGY STAR requirements (efficiency level 3) in 2014. DOE also assumed that 

the market shares of lower-efficiency models (i.e., baseline and 10 percent below baseline) 

would stay the same between 2007 and 2014. 

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