CHAPTER 9. SHIPMENTS ANALYSIS 

TABLE OF CONTENTS 

9.1 INTRODUCTION ........................................................................................................... 9-1 

9.2 SHIPMENTS MODEL METHODOLOGY.................................................................... 9-2 

9.3 DATA INPUTS AND MODEL CALIBRATION .......................................................... 9-4 

9.3.1 Dishwashers ..................................................................................................................... 9-5 

9.3.1.1 Historical Shipments...................................................................................... 9-5 

9.3.1.2 Markets and Model Calibration ..................................................................... 9-6 

9.3.1.3 Base Case Shipments................................................................................... 9-10 

9.3.2 Dehumidifiers ................................................................................................................ 9-12 

9.3.2.1 Historical Shipments.................................................................................... 9-12 

9.3.2.2 Markets and Model Calibration ................................................................... 9-13 

9.3.2.3 Base Case Shipments................................................................................... 9-16 

9.3.3 Cooktops and Ovens ...................................................................................................... 9-17 

9.3.3.1 Historical Shipments.................................................................................... 9-21 

9.3.3.2 Markets and Model Calibration ................................................................... 9-22 

9.3.3.3 Base Case Shipments................................................................................... 9-27 

9.3.4 Microwave Ovens .......................................................................................................... 9-30 

9.3.4.1 Historical Shipments.................................................................................... 9-30 

9.3.4.2 Markets and Model Calibration ................................................................... 9-30 

9.3.4.3 Base Case Shipments................................................................................... 9-34 

9.3.5 Commercial Clothes Washers........................................................................................ 9-35 

9.3.5.1 Historical Shipments.................................................................................... 9-36 

9.3.5.2 Markets and Model Calibration ................................................................... 9-38 

9.3.5.3 Base Case Shipments................................................................................... 9-43 

9.4 PURCHASE PRICE, OPERATING COST, AND HOUSEHOLD INCOME 

IMPACTS ...................................................................................................................... 9-45 

9.5 AFFECTED STOCK ..................................................................................................... 9-47 

9.6 RESULTS ...................................................................................................................... 9-48 

9.6.1 Dishwashers ................................................................................................................... 9-48 

9.6.2 Dehumidifiers ................................................................................................................ 9-49 

9.6.3 Cooktops and Ovens ...................................................................................................... 9-50 

9.6.4 Microwave Ovens .......................................................................................................... 9-51 

9.6.5 Commercial Clothes Washers........................................................................................ 9-52 

LIST OF TABLES 

Table 9.3.1 Dishwashers: Historical Shipments, Domestic plus Imports.............................. 9-6 

Table 9.3.2 Historical and Forecasted Housing Starts (millions) ........................................... 9-8 

Table 9.3.3 Dishwashers: Historical Market Saturations....................................................... 9-9 

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EE-2006-STD-0127 COMMENT 39.2
Table 9.3.4 Product Class Market Share of Dehumidifiers .................................................. 9-12 

Table 9.3.5 Dehumidifiers: Historical Shipments, Domestic plus Imports .......................... 9-13 

Table 9.3.6 Dehumidifiers: Historical Market Saturations................................................... 9-14 

Table 9.3.7 Cooktops and Ovens: Product Categories, Product Types, and Product 

Classes................................................................................................................ 9-18 

Table 9.3.8 Electric Cooktops and Ovens: Historical Shipment Market Shares by 

Product Type...................................................................................................... 9-19 

Table 9.3.9 Gas Cooktops and Ovens: Historical Shipment Market Shares by Product 

Type ................................................................................................................... 9-20 

Table 9.3.10 Cooktops and Ovens including Ranges and Built-Ins: Historical 

Shipments........................................................................................................... 9-21 

Table 9.3.11 Electric Cooking Products: Historical Market Saturations............................... 9-24 

Table 9.3.12 Gas Cooking Products: Historical Market Saturations ..................................... 9-25 

Table 9.3.13 Microwave Ovens: Historical Shipments, Domestic plus Imports................... 9-30 

Table 9.3.14 Microwave Ovens: Historical Market Saturations............................................ 9-32 

Table 9.3.15 Commercial Clothes Washers: Historical Shipments, Domestic plus 

Imports ............................................................................................................... 9-37 

Table 9.3.16 Historical and Forecasted Multi-Family Housing Starts (millions)................... 9-39 

Table 9.3.17 Commercial Clothes Washers: Historical New Multi-Family Building 

Saturations.......................................................................................................... 9-40 

Table 9.4.1 Change in Relative Price Elasticity following a Purchase Price Change .......... 9-47 

Table 9.6.1 Dishwashers: Cumulative Shipments Impacts Caused by Standards over 

the Period 2012–2042 ........................................................................................ 9-49 

Table 9.6.2 Dehumidifiers: Cumulative Shipments Impacts to all Product Classes 

caused by Standards over the period 2012–2042............................................... 9-50 

Table 9.6.3 Microwave Ovens: Cumulative Shipments Impacts Caused by Standards 

over the Period 2012–2042 ................................................................................ 9-51 

Table 9.6.4 Commercial Clothes Washers: Cumulative Shipments Impacts Caused by 

Standards over the Period 2012–2042 ............................................................... 9-53 

LIST OF FIGURES 

Figure 9.3.1 Dishwashers: Survival and Retirement Functions ............................................ 9-10 

Figure 9.3.2 Dishwashers: Historical and Base Case Shipments Forecast ............................ 9-11 

Figure 9.3.3 Dishwashers: Disaggregated Base Case Shipments Forecast........................... 9-11 

Figure 9.3.4 Dehumidifiers: Survival and Retirement Functions ......................................... 9-15 

Figure 9.3.5 Dehumidifiers: Historical and Base Case Shipments Forecast......................... 9-16 

Figure 9.3.6 Dehumidifiers: Disaggregated Base Case Shipments Forecast ........................ 9-17 

Figure 9.3.7 Electric and Gas Cooking Products: Retirement Functions.............................. 9-26 

Figure 9.3.8 Electric Cooking Products: Historical and Base Case Shipments Forecast...... 9-27 

Figure 9.3.9 Gas Cooking Products: Historical and Base Case Shipments Forecast............ 9-28 

Figure 9.3.10 Electric Cooking Products: Disaggregated Base Case Shipments Forecast ..... 9-29 

Figure 9.3.11 Gas Cooking Products: Disaggregated Base Case Shipments Forecast ........... 9-29 

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EE-2006-STD-0127 COMMENT 39.2
Figure 9.3.12 Microwave Ovens: Survival and Retirement Functions ................................... 9-33 

Figure 9.3.13 Microwave Ovens: Historical and Base Case Shipments Forecast .................. 9-34 

Figure 9.3.14 Microwave Ovens: Disaggregated Base Case Shipments Forecast.................. 9-35 

Figure 9.3.15 Commercial Clothes Washer Shipments and Trend in Quantity Index............. 9-38 

Figure 9.3.16 Commercial Laundry Saturation in New Multi-Family Housing...................... 9-41 

Figure 9.3.17 Commercial Clothes Washers: Survival and Retirement Functions................. 9-42 

Figure 9.3.18 Commercial Clothes Washers: Percent of Retired Units not Replaced over 

the period 1998─2013........................................................................................ 9-43 

Figure 9.3.19 Commercial Clothes Washers: Historical and Base Case Shipments 

Forecast.............................................................................................................. 9-44 

Figure 9.3.20 Commercial Clothes Washers: Disaggregated Base Case Shipments 

Forecast.............................................................................................................. 9-45 

Figure 9.6.1 Standard-Sized Dishwashers: Base Case and Standards Case Shipments 

Forecasts ............................................................................................................ 9-49 

Figure 9.6.2 Dehumidifiers: Base Case and Standards Case Shipments Forecasts .............. 9-50 

Figure 9.6.3 Microwave Ovens: Base Case and Standards Case Shipments Forecasts ........ 9-52 

Figure 9.6.4 Commercial Clothes Washers: Base Case and Standards Level 6 

Shipments Forecasts........................................................................................... 9-53 

9-iii 

EE-2006-STD-0127 COMMENT 39.2
CHAPTER 9. SHIPMENTS ANALYSIS 

9.1 INTRODUCTION 

Product shipments estimates are a necessary input to the national energy savings (NES) 

and net present value (NPV) calculations. Shipments are also a necessary input to the 

manufacturer impact analysis (MIA), which DOE conducts for its notices of proposed 

rulemaking (NOPRs). This chapter describes DOE’s methodology for projecting annual 

shipments and presents results for each of the four sets of products being considered for this 

standards rulemaking (i.e., cooking products, dishwashers, dehumidifiers, and commercial 

clothes washers). 

DOE estimated shipments for each product with a separate Shipments Model. In the case 

of cooking products, DOE developed two separate Shipments Models: one for cooktops and 

ovens and another for microwave ovens. Therefore, DOE developed a total of five separate 

Shipments Models; two for cooking products and one each for dishwashers, dehumidifiers, and 

commercial clothes washers. It calibrated each Shipments Model against historical shipments. 

For purposes of estimating the impacts of prospective standard levels on product shipments, each 

Shipments Model accounts for the combined effects of changes in purchase price, annual 

operating cost, and household income on the consumer purchase decision. 

Each Shipments Model considers specific market segments to estimate shipments, the 

results for which are then aggregated to estimate total product shipments. In the case of all of the 

considered products, with the exception of dehumidifiers, DOE accounted for at least two market 

segments: (1) new construction and (2) existing buildings (i.e., replacing failed equipment). For 

dehumidifiers, DOE did not consider the new construction market since this product, unlike most 

major household appliances, is not standard equipment for new households. For dehumidifiers, 

rather than a new construction market, DOE accounted for the market of existing households 

acquiring new dehumidifiers for the first time, in addition to accounting for replacements. In 

addition, for the following products, DOE accounted for a third market segment: cooking 

products—early replacements; dishwashers—existing households acquiring the equipment for 

the first time; and commercial clothes washers—retired units not replaced. 

The Shipments Models are Microsoft Excel spreadsheets that are accessible on the 

Internet (http://www.eere.energy.gov/buildings/appliance_standards/). Appendix 10A discusses 

how to access the Shipments Model spreadsheet and other related spreadsheets, and provides 

basic instructions for using them. The rest of this chapter explains the Shipments Models in 

more detail. Section 9.2 presents the Shipments Model methodology for each product; section 

9.3 describes the data inputs and the model calibration; section 9.4 discusses impacts on 

shipments from changes in equipment purchase price, operating cost, and household income; 

section 9.5 discusses the affected stock; and section 9.6 presents the results for different energyefficiency standard-level scenarios. 

9-1 

EE-2006-STD-0127 COMMENT 39.2
9.2 SHIPMENTS MODEL METHODOLOGY 

DOE developed a national stock model for estimating annual shipments for the four 

product categories considered for this standards rulemaking. The model considers market 

segmentation as a distinct input to the shipments forecast. As represented by the following 

equation, the two primary market segments (which are common to all products except 

dehumidifiers) are new installations and replacements.a 

Ship p ( j ) = Rpl p ( j ) + NI p ( j ) 

where: 

Shipp(j) = Total shipments of product p in year j, 

Rplp(j) = Units of product p retired and replaced in year j, and 

NIp(j) = Number of new installations of product p in year j. 

As the product-specific sections below discuss, DOE also considered a third market 

segment for most of the products to calibrate its Shipments Models to historical shipments data. 

In principle, each market segment and each product class responds differently to both the 

base case demographic and economic trends and to the implementation of standards. 

Furthermore, retirements, early replacements, and efficiency trendsb

 are dynamic and can vary 

among product classes. Rather than simply extrapolating a current shipments trend, the base 

case shipments analysis (i.e., the case without new standards) uses driver input variables, such as 

construction forecasts and product lifetime distributions, to forecast sales in each market 

segment. Thus, DOE’s Shipments Models assume that construction, i.e., new housing units, 

drives new installations. In each year, the product shipments from the new construction market 

segment are equal to the number of new housing units built times the purchase rate, which is 

determined by the product class market share and the market saturation of the product under 

consideration. 

DOE’s Shipments Models take an accounting approach, tracking market shares of each 

product class, the vintage of units in the existing stock, and expected construction trends. The 

models estimate shipments due to replacements using sales in previous years and assumptions 

about the lifetime of the equipment. Therefore, estimated sales due to replacements in a given 

year are equal to the total stock of the appliance minus the sum of the appliances sold in previous 

years that still remain in the stock. DOE determined the useful service life of each appliance to 

a

 For dehumidifiers, DOE accounts for shipments to existing households that do not own the product, since 

dehumidifiers are not typically purchased with a new home. 

b

 Efficiency trends affect shipments only in the standards case. A change in the efficiency distribution of the stock 

results in a change in the purchase price and operating cost and, therefore, produces a purchase price and operating 

cost impact on the shipments. This is discussed later in the chapter in section 9.4. 

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EE-2006-STD-0127 COMMENT 39.2
_ _ 

estimate how long the appliance is likely to remain in stock. The following equation represents 

how DOE estimated replacement shipments. 

_ ageMax j 1 

Rpl p ( j ) = Stock p ( j 1) ∑ ∑Ship j × probRtr ( age ) 

age=0 j= N 

where: 

Stockp (j-1) = Total stock of in-service appliances in year j-1, 

probRtr (age) = Probability that an appliance of a particular age will be retired, and 

N = Start year for when the model begins its stock accounting (start year is 

specific to each product based on available historical shipments data). 

Stock accounting takes product shipments, a retirement function, and initial in-service 

product stock as inputs and provides an estimate of the age distribution of in-service product 

stocks for all years. The age distribution of in-service product stocks is a key input to both the 

NES and NPV calculations—the operating costs for any year depend on the age distribution of 

the stock. The dependence of operating cost on the equipment age distribution occurs under a 

standards case scenario that produces increasing efficiency over time, where older, less efficient 

units may have higher operating costs, while younger, more-efficient units will have lower 

operating costs. Furthermore, in the case of an early replacement scenario, retirements due to 

early replacement will depend on the age of the units that are subject to early replacement. 

DOE calculated total in-service stock of equipment by integrating historical shipments 

data starting from a specific year. The start year depended on the historical data available for 

the product. As units are added to the in-service stock, some of the older ones retire and exit the 

stock. To estimate future shipments, DOE developed a series of equations that define the 

dynamics and accounting of in-service stocks. For new units, the equation is: 

_ Stock( j,age = 1) = Ship( j 1) 

where: 

Stock(j, age) = The population of in-service units of a particular age, 

j = Year for which the in-service stock is being estimated, and 

Ship (j) = Number of units purchased in year j. 

The above equation states that the number of one-year-old units is simply equal to the 

number of new units purchased the previous year. The slightly more complicated equations 

(e.g., the following equation) are those that describe the accounting of the existing in-service 

stock of units: 

Stock( j +1,age +1) = Stock( j,age )×[1 _ prob Rtr ( age )] 

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EE-2006-STD-0127 COMMENT 39.2
In the above equation, as the year is incremented from j to j+1, the age is also 

incremented from age to age+1. With time, a fraction of the in-service stock is removed, and 

that fraction is determined by a retirement probability function, probRtr(age), which is described 

in section 9.3. Because the products considered in this rulemaking are common appliances that 

have been used by U.S. consumers for a long time, replacements typically constitute the majority 

of shipments. Most replacements are made when equipment wears out and fails. 

9.3 DATA INPUTS AND MODEL CALIBRATION 

As discussed above, shipments are driven primarily by two market segments: new 

construction and replacements. 

DOE estimated new construction shipments using two inputs: new housing forecasts and 

market saturation data. New housing includes newly constructed single- and multi-family units, 

referred to as “new housing completions,” and mobile home placements. For new housing 

completions and mobile home placements, DOE used actual data through 2005, and adopted the 

projections from the DOE Energy Information Administration (EIA)’s Annual Energy Outlook 

2007 (AEO2007) for the period of 2006–2030.1

 To determine new construction shipments for 

each product (except dehumidifiersc

), DOE used forecasts of market saturations, combined with 

forecasts of housing starts. 

DOE estimated replacements using product retirement functions that it developed from 

product lifetimes. For all products, with the exception of microwave ovens, DOE based the 

retirement function on a uniform probability distribution for the product lifetime.d The 

Shipments Models assume that no units are retired below a minimum product lifetime and all 

units are retired before exceeding a maximum product lifetime. The models determine the 

probability of retirement at a certain age for all products using the following equations: 

probRtr ( age ) = 0 for age < AgeMin 

1

probRtr ( age ) = _ for AgeMin ≤ age ≤ AgeMax AgeMax AgeMin 

probRtr ( age ) = 1 for age > AgeMax 

where: 

probRtr(age) = Probability of retirement at the age of the product, 

c

 For dehumidifiers, because they are not typically installed at the time of new construction, DOE did not account 

for shipments to new construction. 

d

 As described in section 8.2.3.2 in Chapter 8, in the case of microwave ovens, DOE assumed a triangular retirement 

function. 

9-4 

EE-2006-STD-0127 COMMENT 39.2
AgeMin = Minimum retirement age, and 

AgeMax = Maximum retirement age. 

DOE used historical shipments as the basis for calibrating its Shipments Models. For all 

products, because new construction shipments and replacements were not enough to account for 

all product shipments, DOE developed another market segment to calibrate its Shipments 

Models. This additional market segment represented a small share of total shipments. 

The sections below explain in detail each of the data inputs for each product, including 

the third market segment that DOE developed to calibrate its Shipments Model for each product. 

9.3.1 Dishwashers 

DOE divided residential dishwashers into two product classes: standard-sized and 

compact-sized units. However, because DOE did not conduct an engineering analysis or a lifecycle cost and payback period analysis specific to compact dishwashers, it conducted the 

shipments analysis without disaggregating dishwasher shipments into its two product classes. 

DOE included only built-in units (not portable units) in its analysis. 

9.3.1.1 Historical Shipments 

DOE used historical shipments data (i.e., data on both domestic shipments and imports) 

to calibrate its Shipments Model for dishwashers. It used three sources to establish historical 

shipments: (1) data provided by the Association of Home Appliance Manufacturers (AHAM) for 

the period 1995–2005,2

 (2) data from the 2000 AHAM Factbook for the period 1989–1994,3 and 

(3) data from Appliance Magazine4,5,6 for the period 1972–1988. e Table 9.3.1 summarizes the 

historical dishwasher shipments data. DOE built up a total stock of dishwashers by integrating 

historical shipments starting in the year 1972. Over time, some of the units will be retired and 

removed from the stock, thus triggering the shipment of a new unit. Because of the relationship 

between retirements and total stock, there is a strong correlation between past and future 

shipments, independent of efficiency standards. 

e

 Shipments estimates from Appliance Magazine included exports. Thus, DOE reduced total shipments by 4.1 

percent (the average percentage of exports for the years 1989–1993 based on the five-year average difference 

between the AHAM Fact Book 2000 and Appliance Magazine data) to estimate total domestic shipments plus 

imports. 

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EE-2006-STD-0127 COMMENT 39.2
Table 9.3.1 Dishwashers: Historical Shipments, Domestic plus Imports 

Year Shipments (thousands) Year Shipments (thousands) 

1972 2,756 1989 3,390 

1973 3,189 1990 3,291 

1974 2,860 1991 3,195 

1975 2,328 1992 3,424 

1976 2,705 1993 3,722 

1977 2,891 1994 4,125 

1978 3,064 1995 4,254 

1979 3,005 1996 4,317 

1980 2,258 1997 4,655 

1981 2,104 1998 5,073 

1982 1,876 1999 5,425 

1983 2,743 2000 5,834 

1984 3,113 2001 5,752 

1985 3,192 2002 5,906 

1986 3,514 2003 6,467 

1987 3,610 2004 6,868 

1988 3,499 2005 7,280 

Sources: 1995–2005: AHAM Data Submittal, 2006; 1989–1994: AHAM Factbook 2000; 1972–1988: Appliance 

Magazine, “Statistical Review,” 1982, 1990, and 1993. 

9.3.1.2 Markets and Model Calibration 

The shipments market for dishwashers primarily comprises the following: units for new 

construction, and replacement units for equipment that has been retired. DOE’s Shipments 

Model also assumes that some existing households without dishwashers will purchase the 

equipment (i.e., become first time owners (FTOs)). Total dishwasher shipments are represented 

by the following equation: 

ShipDW ( j ) = Rpl DW ( j ) + NI DW ( j ) + FTODW ( j ) 

where: 

ShipDW (j) = Total shipments of dishwashers in year j, 

RplDW (j) = Replacement shipments in year j, 

NIDW (j) = Shipments to new households in year j, and 

FTODW (j)= Shipments to existing households without dishwashers in year j. 

The sections below discuss all three of these markets in further detail. 

9-6 

EE-2006-STD-0127 COMMENT 39.2
New Construction. To estimate shipments to new construction, DOE used forecasts of 

housing starts coupled with dishwasher saturation data. In other words, to forecast the shipments 

for new construction for any given year, DOE multiplied the housing starts forecasts by the 

forecasted saturation of dishwashers for new housing. 

Table 9.3.2 presents historical and forecasted new housing starts based on EIA’s 

AEO2007 for the period 1990–2030.1 AEO2007 provides three sets of housing starts: the 

Reference case, the High Economic Growth case, and the Low Economic Growth case. All three 

housing starts forecasts are presented in Table 9.3.2. DOE used the forecasts from the Reference 

case to estimate its shipments to new construction. 

New housing is comprised of single- and multi-family units (also referred to as “new 

housing completions”) and mobile home placements. For new housing completions and mobile 

home placements, the AEO2007 data are based on actual completions through the year 2005. 

For the Reference case, the forecast shows a decline in housing completions from 2.22 million in 

2005 to 1.8 million by 2030. For the period 2031−2042, DOE froze completions at the level in 

the year 2030 for all three economic forecasts. 

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EE-2006-STD-0127 COMMENT 39.2
Table 9.3.2 Historical and Forecasted Housing Starts (millions) 

Year Reference High Low Year Reference High Low 

1990 1.38 1.38 1.38 2017 1.91 2.30 1.53 

1991 1.18 1.18 1.18 2018 1.91 2.30 1.53 

1992 1.41 1.41 1.41 2019 1.90 2.31 1.50 

1993 1.54 1.54 1.54 2020 1.90 2.33 1.48 

1994 1.76 1.76 1.76 2021 1.88 2.32 1.44 

1995 1.69 1.69 1.69 2022 1.85 2.31 1.40 

1996 1.82 1.82 1.82 2023 1.83 2.30 1.37 

1997 1.49 1.49 1.49 2024 1.83 2.32 1.35 

1998 1.54 1.54 1.54 2025 1.85 2.37 1.32 

1999 1.64 1.64 1.64 2026 1.86 2.41 1.31 

2000 1.70 1.70 1.70 2027 1.85 2.41 1.28 

2001 1.72 1.72 1.72 2028 1.81 2.38 1.24 

2002 1.75 1.75 1.75 2029 1.80 2.36 1.23 

2003 1.79 1.79 1.79 2030 1.80 2.41 1.20 

2004 1.80 1.80 1.80 2031 1.80 2.41 1.20 

2005 2.22 2.22 2.22 2032 1.80 2.41 1.20 

2006 2.03 2.03 2.03 2033 1.80 2.41 1.20 

2007 1.91 2.11 1.71 2034 1.80 2.41 1.20 

2008 1.93 2.20 1.66 2035 1.80 2.41 1.20 

2009 1.92 2.21 1.63 2036 1.80 2.41 1.20 

2010 1.94 2.26 1.62 2037 1.80 2.41 1.20 

2011 1.94 2.27 1.62 2038 1.80 2.41 1.20 

2012 1.90 2.23 1.57 2039 1.80 2.41 1.20 

2013 1.88 2.21 1.55 2040 1.80 2.41 1.20 

2014 1.88 2.25 1.52 2041 1.80 2.41 1.20 

2015 1.91 2.28 1.53 2042 1.80 2.41 1.20 

2016 1.92 2.30 1.55 

Source: EIA, AEO2007. 

Table 9.3.3 presents historical market saturations of dishwashers based on various 

sources, including the AHAM 2005 Fact Book,

7 Appliance Magazine,8

 NFO World Group,9 and 

EIA’s Residential Energy Consumption Survey (RECS) for the years 1993,10 1997,11 and 2001.12 

The table presents market saturations for the overall housing stock and for new households. 

Because the forecast of shipments for the new housing market depends on the saturation of 

dishwashers in new housing, DOE focused its attention on the market saturations for new 

housing. According to RECS, dishwasher saturation in new housing for 1993, 1997, and 2001 

was 74.9 percent, 74.1 percent, and 73.2 percent, respectively. Because the downward trend in 

new household dishwasher saturation is statistically insignificant, DOE decided to freeze the 

saturation at 73.2 percent to estimate the shipments to new construction for future years. 

9-8 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.3 Dishwashers: Historical Market Saturations 

Year 

Overall Household New 

Households 

AHAM* Appl** NFO*** RECS†

 RECS† 

1970 18.9% 

1978 41.9% 

1982 44.5% 

1983 45.0% 

1987 47.7% 

1990 53.9% 45.4% 

1991 47.7% 

1992 50.0% 

1993 51.0% 45.4% 74.9% 

1994 52.2% 

1995 54.4% 

1996 54.9% 49.9% 

1997 55.6% 50.3% 74.1% 

1998 56.3% 

1999 56.5% 

2000 59.0% 

2001 59.3% 59.3% 53.6% 53.0% 73.2% 

2002 59.5% 

2003 59.5% 

2004 60.0% 

2005 73.7% 

* Source: AHAM, Fact Book, 2005; ** Source: Appliance Magazine, “The Saturation Picture,” September 

issues; *** Source: NFO World Group, 2001; † Source: DOE-EIA, RECS, 1993, 1997, and 2001. 

 Replacements. DOE determined shipments to the replacement market using an 

accounting method that tracks the total stock of units by vintage. DOE estimated a stock of 

dishwashers by vintage by integrating historical shipments starting from the year 1972. Over 

time, some units will be retired and removed from stock, thereby triggering the shipment of a 

replacement unit. Depending on the vintage, a certain percentage of each type of unit will fail 

and need to be replaced. To determine when a unit fails, DOE used a survival function based on 

a product lifetime distribution with an average value of 12.3 years, and minimum and maximum 

values of 5.3 years and 17.6 years, respectively. For a more complete discussion of dishwasher 

lifetimes, refer back to section 8.2.3.3 of Chapter 8. Figure 9.3.1 shows the survival and 

retirement functions that DOE used to estimate replacement shipments. 

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EE-2006-STD-0127 COMMENT 39.2
0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percent Surviving 

Percent Retiring 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 

Age (years) 

Figure 9.3.1 Dishwashers: Survival and Retirement Functions 

Model Calibration—Existing Households Without Dishwashers. To calibrate the 

estimated shipments with the historical data, DOE introduced into the model a new market 

segment corresponding to existing households without dishwashers, also referred to as FTOs. 

DOE estimated that three percent of existing households without a dishwasher would annually 

purchase this product over the period 2005─2042. 

9.3.1.3 Base Case Shipments 

Figure 9.3.2 shows the forecasted shipments in the base case (i.e., the case without new 

energy efficiency standards) and the historical shipments DOE used to calibrate the forecast. 

9-10 

EE-2006-STD-0127 COMMENT 39.2
0.00 

2.00 

4.00 

6.00 

8.00 

10.00 

12.00 

14.00 

1985 1995 2005 2015 2025 2035 

Year 

Shipments (million units)

Historical Shipments 

modelled Shipments 

Figure 9.3.2 Dishwashers: Historical and Base Case Shipments 

Forecast 

Figure 9.3.3 presents forecasted dishwasher shipments in the base case, disaggregated 

into the following market segments: shipments due to retirements, shipments to new housing, 

and shipments for FTOs. DOE determined that replacements due to retirements range from 60 

percent to 85 percent of total dishwasher shipments over the period 2006–2042. 

0.0 

2.5 

5.0 

7.5 

10.0 

12.5 

15.0 

1990

1993

1996

1999

2002

2005

2008

2011

2014

2017

2020

2023

2026

2029

2032

2035

2038

2041 

Year 

Shipments (million units) 

First Time Ow ners 

New Units 

Repl. Units 

Total Shipments 

Figure 9.3.3 Dishwashers: Disaggregated Base Case Shipments 

Forecast 

9-11 

EE-2006-STD-0127 COMMENT 39.2
9.3.2 Dehumidifiers 

DOE considered six product classes of dehumidifiers for the current analysis. It based 

the six product classes on the following size categories: ≤25.00, 25.01─35.00, 35.01−45.00, 

45.01−54.00, 54.01−74.99, and ≥75.00 pints/day. DOE’s Shipments Model for dehumidifiers 

used the aggregate shipments, i.e., the shipments for all six product classes, as the basis for its 

forecasts. In other words, DOE did not develop a separate Shipments Model for each 

dehumidifier product class. As provided in Table 9.3.4, DOE based the market shares for each 

of the six product classes on data AHAM provided for the years 2003–2005.13 DOE used the 

average market shares over the period 2003–2005 to disaggregate forecasted shipments into each 

of the six dehumidifier product classes. 

Table 9.3.4 Product Class Market Share of Dehumidifiers 

Year Product Class (pints/day) 

≤25.00 25.01-35.00 35.01-45.00 45.01-54.00 54.01-74.99 ≥75.00 

2003 13.4% 21.3% 23.2% 21.8% 19.3% 1.0% 

2005 10.0% 23.0% 23.4% 20.3% 22.3% 1.0% 

2005 6.4% 25.7% 23.0% 20.5% 23.3% 1.0% 

Average 10.0% 23.4% 23.2% 20.9% 21.6% 1.0% 

Source: AHAM Data Submittal, 2006. 

9.3.2.1 Historical Shipments 

DOE used historical shipments data (i.e., data on domestic shipments and imports) to 

calibrate its Shipments Model. It used three sources to establish historical shipments: (1) data 

provided by AHAM for the period 2003–2005,13 (2) data from the 20003

 and 200314 AHAM 

Factbooks for the period 1989–2002, and (3) data from Appliance Magazine4,5,6 for the period 

1972–1988. f Table 9.3.5 summarizes the historical dehumidifier shipments data. DOE built up 

a total stock of dehumidifiers by integrating historical shipments starting in the year 1972. Over 

time, some of the units will be retired and removed from the stock, triggering the shipment of a 

new unit. Because of the relationship between retirements and total stock, there is a strong 

correlation between past and future shipments, independent of efficiency standards. 

f

 Shipments estimates from Appliance Magazine included exports. However, DOE saw no difference between 

shipments in the AHAM Fact Book 2000, which exclude exports, and those reported in Appliance Magazine for 

almost all years. Thus, DOE made no adjustments to the Appliance Magazine shipments. 

9-12 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.5 Dehumidifiers: Historical Shipments, Domestic plus Imports 

Year Shipments (thousands) Year Shipments (thousands) 

1972 461 1989 605 

1973 646 1990 743 

1974 586 1991 745 

1975 392 1992 803 

1976 440 1993 983 

1977 314 1994 1,059 

1978 442 1995 1,003 

1979 685 1996 977 

1980 673 1997 820 

1981 536 1998 1,031 

1982 440 1999 950 

1983 437 2000 975 

1984 591 2001 806 

1985 588 2002 799 

1986 555 2003 1,311 

1987 704 2004 1,672 

1988 673 2005 1,957 

Sources: 2003–2005: AHAM Data Submittal, 2006; 1989–2002: AHAM Factbooks 2000, 2003; 1972–1988: 

Appliance Magazine, “Statistical Review,” 1982, 1990, and 1993. 

9.3.2.2 Markets and Model Calibration 

Table 9.3.6 presents historical market saturations of dehumidifiers based on various 

sources, including the AHAM 2005 Fact Book,

6 Appliance Magazine,7

 NFO World Group,8 and 

EIA’s 2001 RECS.11 

9-13 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.6 Dehumidifiers: Historical Market Saturations 

Year 

Overall Housing 

AHAM* Appl** NFO*** RECS† 

1970 

1978 8.5% 

1982 11.0% 

1983 11.0% 

1987 11.4% 

1990 16.7% 16.3% 

1991 12.0% 

1992 15.5% 

1993 16.5% 

1994 17.0% 

1995 18.0% 

1996 18.0% 14.8% 

1997 18.0% 

1998 18.4% 

1999 10.5% 

2000 14.0% 

2001 14.1% 14.5% 14.2% 11.3% 

2002 16.0% 

2003 19.0% 

2004 20.0% 

2005 18.9% 

* Source: AHAM, Fact Book, 2005; ** Source: Appliance Magazine, “The Saturation Picture,” September 

issues; *** Source: NFO World Group, 2001; † Source: DOE-EIA, RECS, 2001. 

The shipments market for dehumidifiers primarily comprises replacement units for 

equipment that has been retired. DOE’s Shipments Model also assumes that some existing 

households without dehumidifiers will purchase the equipment (i.e., become FTOs). Total 

dehumidifiers shipments are represented by the following equation: 

ShipDEH ( j ) = Rpl DEH ( j ) + FTODEH ( j ) 

where: 

ShipDEH (j) = Total shipments of dehumidifiers in year j, 

RplDEH (j) = Replacement shipments in year j, and 

FTODEH (j)= Shipments to existing households without dehumidifiers in year j. 

9-14 

EE-2006-STD-0127 COMMENT 39.2
DOE discusses the two markets for dehumidifiers in further detail below.

 Replacements. DOE determined shipments to the replacement market using an 

accounting method that tracks the total stock of units by vintage. DOE estimated a stock of 

dehumidifiers by vintage by integrating historical shipments starting from the year 1972. Over 

time, some units will be retired and removed from the stock, thereby triggering the shipment of a 

replacement unit. Depending on the vintage, a certain percentage of each type of unit will fail 

and need to be replaced. To determine when a unit fails, DOE used a survival function based on 

a product lifetime distribution with an average value of 11 years, and minimum and maximum 

values of 5 years and 17 years, respectively. For a more complete discussion of dehumidifier 

lifetimes, refer back to section 8.2.3.4 of Chapter 8. Figure 9.3.4 shows the survival and 

retirement functions that DOE used to estimate replacement shipments. 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percent Surviving 

Percent Retiring 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 

Age (years) 

Figure 9.3.4 Dehumidifiers: Survival and Retirement Functions 

Model Calibration—Existing Households Without Appliance. To calibrate the 

estimated shipments with the historical data, DOE introduced into the model a market segment 

identified as existing households without dehumidifiers, also referred to as FTOs. DOE 

estimated that 0.6 percent of existing households without a dehumidifier would annually 

purchase this product over the period 2005─2042. 

9-15

EE-2006-STD-0127 COMMENT 39.2
9.3.2.3 Base Case Shipments 

Figure 9.3.5 shows the forecasted shipments in the base case (i.e., the case without new 

energy efficiency standards) and the historical shipments DOE used to calibrate the forecast. As 

stated above, DOE used the average market shares of the six dehumidifier product classes over 

the period 2003–2005 to disaggregate forecasted base case shipments into each of the six 

dehumidifier product classes. 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

3.00 

3.50 

4.00 

1980 1990 2000 2010 2020 2030 2040 

Year 

Shipments (million units)

Shipments 

Modeled Shipments 

Figure 9.3.5 Dehumidifiers: Historical and Base Case Shipments 

Forecast 

Figure 9.3.6 presents forecasted dehumidifier shipments in the base case, disaggregated 

into the following market segments: shipments due to retirements and shipments for FTOs. 

DOE determined that replacements due to retirements range from 68 percent to 80 percent of 

total dehumidifier shipments over the period 2006–2042. 

9-16 

EE-2006-STD-0127 COMMENT 39.2
1991 

1995 

1999 

2003 

2007 

2011 

2015 

2019 

2023 

2027 

2031 

2035 

2039 

Shipments (million units) 

4.0 

3.5 

3.0 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

M odel ed F i r s t T i m e O w n e r s 

R epl . U n i t s 

A ggr egate S h i p m ent s 

Year 

Figure 9.3.6 Dehumidifiers: Disaggregated Base Case Shipments 

Forecast 

9.3.3 Cooktops and Ovens 

DOE designed its Shipments Model for cooktops and ovens by dividing these products 

into two general fuel categories: electric and gas. Both the electric and gas categories comprised 

the following product configurations: ranges, built-in cooktops, and built-in ovens. DOE 

developed two Shipments Models; one Model estimated the electric cooking product shipments 

while the other Model estimated gas cooking product shipments. After DOE estimated 

shipments for each fuel category, it then disaggregated the shipments into product types—eight 

product types for electric cooking products and five types for gas cooking products. Since each 

product type (except gas cooktops) consists of two or more product classes, DOE then 

disaggregated shipments for each product type into their appropriate product classes. 

Table 9.3.7 shows the product types and product classes under each general fuel category 

(i.e., electric and gas cooking products). For electric cooking products there are eight product 

types and four product classes; for gas cooking products there are five product types and three 

product classes. Because ranges are comprised of cooktop and oven product classes, DOE 

needed to disaggregate range shipments into the appropriate cooktop and oven product classes 

and then combine those shipments with the appropriate built-in cooktop and oven shipments to 

obtain the total shipments for each product class. 

9-17 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.7 Cooktops and Ovens: Product Categories, Product Types, and Product 

Classes 

Product 

Categories Electric Gas 

Product 

Types: 

8 electric, 

5 gas 

Ranges Built-In 

Cooktop Built-In Oven Ranges Built-In Cooktop Built-In Oven 

1. 

CoilStd 

2. 

CoilSC 

3. 

SmthStd 

4. 

SmthSC 

5. 

Coil 

6. 

Smooth 

7. 

Std 

8. 

SC 

1. 

GasStd 

2. 

GasSC 

3. 

Gas 

4. 

Std 

5. 

SC 

Product 

Classes: 

4 electric, 

3 gas 

Ovens Cooktops Ovens 3. 

Cooktops 

1. 

Standard 

2. 

Self-Clean 

3. 

Coil 

4. 

Smooth 

1. 

Standard 

2. 

Self-Clean 

Std = standard; SC = self cleaning; Smth = smooth 

Table 9.3.8 shows the historical market shares of the eight product types that comprise 

total electric cooking product shipments. For any given year, the sum of the product type market 

shares equals 100 percent. DOE used two sources to establish historical market shares: (1) data 

that AHAM provided for the period 2003–200515 and (2) data from DOE’s supplemental 

analysis to its 1996 technical support document (TSD) on cooking products covering the period 

1989–1996.16 For the time periods for which no data were available, DOE either applied the 

market share percentages from the above two data sources or interpolated from the two available 

data sources. The notes in Table 9.3.8 provide further details. To estimate forecasted market 

shares of each product type, DOE decided to freeze the percentages at the levels for the year 

2005, i.e., DOE used the market shares in the year 2005 to disaggregate forecasted shipments 

into each of the eight electric cooking product types for the period 2006–2042. 

9-18 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.8 Electric Cooktops and Ovens: Historical Shipment Market Shares by 

Product Type 

Year 

Percent of Total Shipments 

Ranges Built-In Cooktops Built-In Ovens 

CoilStandard CoilSelf-Clean SmoothStandard SmoothSelf-Clean Coil Smooth Standard Self-Clean 

1970–1989 26% 13% 9% 21% 4% 9% 6% 13% 

1990 22% 15% 8% 23% 4% 9% 7% 12% 

1991 25% 14% 9% 22% 4% 8% 4% 14% 

1992 26% 14% 9% 22% 4% 8% 4% 14% 

1993 26% 14% 9% 22% 4% 8% 3% 14% 

1994 22% 17% 8% 26% 3% 7% 5% 11% 

1995 24% 16% 9% 26% 3% 7% 3% 12% 

1996 22% 18% 8% 27% 3% 7% 3% 12% 

1997 21% 18% 7% 28% 3% 7% 3% 12% 

1998 20% 19% 7% 29% 3% 8% 2% 12% 

1999 19% 20% 7% 30% 3% 7% 2% 12% 

2000 19% 20% 7% 31% 3% 7% 2% 12% 

2001 18% 20% 6% 31% 3% 7% 2% 12% 

2002 17% 21% 6% 32% 3% 7% 2% 13% 

2003 14% 22% 5% 34% 3% 6% 2% 13% 

2004 14% 22% 5% 34% 3% 6% 2% 14% 

2005 15% 21% 6% 34% 3% 6% 1% 14% 

Source: 2003–2005: AHAM Data Submittal, 2006; 

1989–1996, Standard and Self-Clean Range and Built-In Oven percentages: DOE, Supplemental Analysis, 

1996; 

1997–2002, Standard and Self-Clean Range and Built-In Oven percentages: interpolated between 1996 and 

2003 data; 

1989–2002, Smooth and Coil Range and Built-In Cooktop percentages: 3-year average from AHAM Data 

Submittal for the period 2003–2005; 

1970-1988: Set equal to percentages for 1989. 

Table 9.3.9 shows the historical market shares of the five product types that comprise 

total gas cooking product shipments. For any given year, the sum of the product type market 

shares equals 100 percent. DOE used three sources to establish historical market shares: (1) 

data provided by AHAM for the period 2003–2005,15 (2) data from DOE’s supplemental analysis 

to its 1996 TSD on cooking products covering the period 1989–1996,16 and (3) data from the 

Appliance Recycling Information Center (ARIC) for the year 2004.17 For the time periods for 

which no data were available, DOE either applied the market share percentages from the above 

AHAM and DOE data sources or interpolated between the data from these two sources. The 

notes in Table 9.3.9 provide further details. 

Note that in Table 9.3.9, gas standard range market shares are broken down into 

equipment with and without standing pilots. As discussed in section 8.2.6 of Chapter 8, Life9-19 

EE-2006-STD-0127 COMMENT 39.2
Cycle Cost and Payback Period Analysis, only gas standard ranges are still being produced with 

standing pilot lights. As a result, DOE used the ARIC data to track the percentage of gas ranges 

with pilots, to accurately estimate the national impacts of eliminating pilot lights for gas cooking 

pilots. DOE’s method for estimating the national impacts is discussed in detail in Chapter 10, 

National Impact Analysis. To estimate the future percentages of each product type (with the 

exception of gas standard ranges with standing pilots), DOE decided to freeze the percentages at 

the levels shown for the year 2005, i.e., DOE used the market shares in the year 2005 to 

disaggregate forecasted shipments into each of the five gas cooking product types for the period 

2006–2042. Section 10.2.3 of Chapter 10, National Impact Analysis, discusses how DOE 

forecasted the market share of gas standard ranges with standing pilots. 

Table 9.3.9 Gas Cooktops and Ovens: Historical Shipment Market Shares by Product 

Type 

Year 

Percent of Total Shipments 

Ranges Built-In 

Cooktop 

Built-In Ovens 

Std w/ Pilot Std no Pilot Self-Clean Standard Self-Clean 

1970–1988 33% 30% 22% 10% 4% 1% 

1989 35% 28% 22% 10% 4% 1% 

1990 36% 27% 22% 11% 4% 1% 

1991 37% 25% 23% 11% 3% 1% 

1992 38% 24% 24% 12% 3% 1% 

1993 37% 21% 27% 12% 2% 1% 

1994 40% 21% 25% 11% 3% 0% 

1995 39% 19% 30% 9% 2% 1% 

1996 38% 18% 31% 10% 2% 1% 

1997 38% 16% 34% 10% 2% 1% 

1998 36% 14% 36% 11% 2% 1% 

1999 35% 13% 38% 12% 2% 1% 

2000 34% 12% 40% 12% 2% 1% 

2001 33% 10% 42% 13% 2% 1% 

2002 32% 10% 44% 13% 2% 1% 

2003 32% 9% 44% 13% 1% 1% 

2004 29% 8% 47% 14% 1% 0% 

2005 30% 7% 47% 15% 1% 0% 

Source: 2003–2005: AHAM Data Submittal, 2006 (with the exception of Standard Ranges with pilot); 

1989–1996, Standard and Self-Clean Range and Built-In Oven percentages: DOE, TSD, 1996; 

1997–2002, Standard and Self-Clean Range and Built-In Oven percentages: interpolated between 1996 and 

2003 data; 

1989–1996, Standard Range with pilot percentages: DOE, Supplemental Analysis, 1998; 

2004, Standard Ranges with pilot percentage: ARIC, 2005; 

1997–2003, 2005, Standard Range with pilot percentages: based on interpolation between 1996 and 2004 

data; 

1970-1988: Set equal to percentages for 1989. 

9-20 

EE-2006-STD-0127 COMMENT 39.2
9.3.3.1 Historical Shipments 

DOE used data on historical shipments (i.e., domestic shipments and imports) to calibrate 

its Shipments Model. It obtained historical shipments data from three sources: (1) data provided 

by AHAM for the period 2003–2005,15 (2) data from the 2000 AHAM Factbook for the period 

1989–2002,3

 and (3) data from Appliance Magazine4,5,6 for the period 1972–1988.g Table 9.3.10 

summarizes the historical cooking product shipments data. DOE built up a total stock of 

cooking products by integrating historical shipments starting in the year 1972. Over time, some 

units are retired and, therefore, removed from stock, thus triggering the shipment of a new unit. 

Because of the relationship between retirements and total stock, there is a strong correlation 

between past and future shipments, independent of efficiency standards. 

Table 9.3.10 Cooktops and Ovens including Ranges and Built-Ins: Historical Shipments 

Year 

Shipments (thousands) 

Year 

Shipments (thousands) 

Electric Gas Electric Gas 

1972 2,871 2,366 1989 3,411 2,326 

1973 3,532 2,381 1990 3,349 2,354 

1974 3,126 1,871 1991 3,206 2,301 

1975 2,281 1,553 1992 3,450 2,492 

1976 2,355 1,750 1993 3,725 2,631 

1977 3,183 1,683 1994 4,047 2,840 

1978 3,361 1,725 1995 3,917 2,715 

1979 3,123 1,726 1996 4,155 2,710 

1980 2,606 1,476 1997 4,240 2,744 

1981 2,389 1,435 1998 4,639 2,950 

1982 2,077 1,312 1999 4,983 3,137 

1983 3,033 1,509 2000 5,026 3,176 

1984 3,348 1,662 2001 5,066 3,036 

1985 3,440 1,740 2002 5,338 3,268 

1986 3,620 2,006 2003 5,620 3,419 

1987 3,719 2,249 2004 6,144 3,719 

1988 3,589 2,359 2005 6,195 3,763 

Sources: 2003–2005: AHAM Data Submittal, 2006; 1989–2002: AHAM Fact Books, 2000, 2003, 2005; 1972– 

1988: Appliance Magazine, “Statistical Review,” 1990, 1993 

g

 Shipments estimates from Appliance Magazine included exports. Thus, DOE reduced total electric and gas 

cooking product shipments by 3.2 and 4.0 percent, respectively (the average percentage of exports for the years 

1989–1993 based on the five-year average difference between the AHAM Fact Book 2000 and Appliance Magazine) 

to estimate total domestic shipments plus imports. 

9-21 

EE-2006-STD-0127 COMMENT 39.2
9.3.3.2 Markets and Model Calibration 

For each general fuel category of cooktops and ovens, i.e., electric and gas, the market is 

primarily comprised of the following: replacement units for equipment that has been retired 

from service and units for new housing. In addition to normal replacements, DOE’s Shipments 

Model for each general category also assumed that a certain fraction of the stock would be 

replaced early. Total electric cooktop and oven shipments are represented by the following 

equation: 

ShipELEC ( j ) = Rpl ELEC ( j ) + NI ELEC ( j ) + ERELEC ( j ) 

where: 

ShipELEC (j) = Total shipments of electric cooking products in year j, 

RplELEC (j) = Replacement shipments in year j, 

NIELEC (j) = Shipments to new households in year j, and 

ERELEC (j)= Early replacement shipments in year j. 

Total gas cooktop and oven shipments are represented by the same basic equation: 

ShipGAS ( j ) = RplGAS ( j ) + NIGAS ( j ) + ERGAS ( j ) 

where: 

ShipGAS (j) = Total shipments of gas cooking products in year j, 

RplGAS (j) = Replacement shipments in year j, 

NIGAS (j) = Shipments to new households in year j, and 

ERGAS (j)= Early replacement shipments in year j. 

The sections below discuss in further detail all three of these markets for each general 

cooking product category. 

New Construction. To estimate shipments to new construction, DOE used forecasts of 

housing starts coupled with cooking product saturation data. In other words, to forecast the 

shipments for new construction for any given year, DOE multiplied the housing forecasts by the 

forecasted saturation of cooking products for new housing. 

Historical and forecasted new housing starts were presented earlier for cooking products. 

Refer back to Table 9.3.2 for the housing starts data. 

Table 9.3.11 presents historical market saturations of electric cooking products based on 

various sources, including AHAM’s 2005 Fact Book,

7 Appliance Magazine,8

 NFO World 

Group,9

 and EIA’s RECS for the years 199711 and 2001.12 The table presents market saturations 

for the overall housing stock and for new housing. Note that the overall electric cooking product 

9-22 

EE-2006-STD-0127 COMMENT 39.2
saturations provided by AHAM and Appliance Magazine are roughly the same. NFO breaks out 

the saturations of ranges, built-in ovens, and built-in cooktops but does not indicate which 

households have multiple cooking appliances. Thus, it is not possible to directly compare the 

saturations from NFO to the previous two sources. Because the forecast of shipments for the 

new housing market depends on the saturation of electric cooking products in new housing, DOE 

focused its attention on the market saturations for new housing that RECS provided for the years 

1997 and 2001. DOE decided to use only the saturations for the year 2001 to estimate the 

shipments to new construction for future years. Because DOE conducted its shipments analysis 

by first forecasting overall electric cooking product shipments and then disaggregating the total 

shipments using the historical market share data in Table 9.3.8, it used the overall saturation of 

electric cooking products to estimate shipments to new construction. DOE based the saturation 

on the sum of the values for ranges, built-in ovens, and built-in cooktops, which is 77.5 percent. 

9-23 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.11 Electric Cooking Products: Historical Market Saturations 

Year 

1970 

1978 

1982

1983 

Overall Housing New Housing 

AHAM* Appl** NFO*** RECS† 

All Elec 

Products 

40.6% 

 58.0% 

 62.6% 

66.3% 

 65.3% 

All Elec 

Products Ranges 

60.0% 

61.0% 

62.0% 

Built-In 

Oven 

9.4% 

9.2% 

9.6% 

Built-In 

Cooktop 

9.2% 

10.1% 

9.4% 

Range 

SC 

26.6% 

30.1% 

Range 

Standard 

39.7% 

32.5% 

Built-In 

SC Oven 

8.1% 

3.5% 

Built-In 

Std Oven 

4.0% 

1.7% 

Built-In 

Cooktop 

6.5% 

9.6% 

51.0% 

58.0% 

59.4% 

56.7% 

56.4% 

57.5% 

58.5% 

61.0% 

60.2% 

60.0% 

60.5% 

60.0% 

60.0% 

61.0% 

62.0% 

61.0% 

61.0% 

1987 

1990

1991 

1992 

1993 

1994 

1995 

1996 

1997 

1998 

1999 

2000 

2001 

2002 

2003 

2004 

2005

Source: AHAM, Fact Book 2005; ** Source: Appliance Magazine, “The Saturation Picture,” September issues; 

*** Source: NFO World Group; † Source: DOE-EIA, RECS, 1997, 2001. 

Table 9.3.12 presents historical market saturations of gas cooking products based on 

various sources, including AHAM’s 2005 Fact Book,

6 Appliance Magazine,7

 NFO World 

Group,8

 and EIA’s RECS for the years 199710 and 2001.11 The table presents market saturations 

for the overall housing stock and for new households. Note that the overall gas cooking product 

saturations provided by AHAM and Appliance Magazine are roughly the same. NFO breaks out 

the saturations of ranges, built-in ovens, and built-in cooktops but does not indicate which 

households have multiple cooking appliances. Thus, it is not possible to directly compare the 

saturations from NFO to the previous two sources. Because the forecast of shipments for the 

new housing market depends on the saturation of gas cooking products in new housing, DOE 

focused its attention on the market saturations for new housing that RECS provided for the years 

1997 and 2001. DOE decided to use only the saturations for the year 2001 to estimate the 

shipments to new construction for future years. Because DOE conducted its shipments analysis 

9-24 

EE-2006-STD-0127 COMMENT 39.2
by first forecasting overall gas cooking product shipments and then disaggregating the total 

shipments using the historical market share data in Table 9.3.9, it used the overall saturation of 

gas cooking products to estimate shipments to new construction. So as not to overstate the 

overall saturation, DOE based the saturation on the sum of the values for ranges, built-in ovens, 

and built-in cooktops, which is 30.1 percent. 

Table 9.3.12 Gas Cooking Products: Historical Market Saturations 

Year 

Overall Housing New Housing 

AHAM* Appl** NFO*** RECS† 

All Elec 

Products 

All Elec 

Products Ranges 

Built-In 

Oven 

Built-In 

Cooktop 

Range 

SC 

Range 

Standard 

Built-In 

SC Oven 

Built-In 

Std Oven 

Built-In 

Cooktop 

1970 57.7% 

1978 48.0% 

1982 42.7% 

1983 42.7% 

1987 42.2% 

1990 38.7% 40.0% 3.1% 

1991 45.7% 

1992 46.0% 

1993 44.8% 

1994 45.0% 

1995 42.0% 

1996 39.0% 39.0% 2.9% 4.3% 

1997 39.4% 8.2% 11.0% 1.0% 0.8% 7.0% 

1998 40.2% 

1999 40.1% 

2000 40.0% 

2001 37.8% 40.0% 38.0% 2.5% 4.8% 8.3% 12.4% 0.8% 2.4% 6.2% 

2002 38.0% 

2003 39.0% 

2004 39.0% 

2005 39.0% 

Source: AHAM, Fact Book 2005; ** Source: Appliance Magazine, “The Saturation Picture,” September issues; 

*** Source: NFO World Group; † Source: DOE-EIA, RECS, 1993, 1997, 2001. 

 Replacements. DOE determined shipments to the replacement market using an 

accounting method that tracks the total stock of units by vintage. DOE estimated stocks of 

electric and gas cooking products by vintage by integrating historical shipments starting from the 

year 1972. Over time, some of the units will be retired and removed from the stock, thus 

triggering the shipment of a new unit. Because of the relationship between retirements and total 

9-25

EE-2006-STD-0127 COMMENT 39.2
stock, there is a strong correlation between past and future shipments, independent of efficiency 

standards. 

Depending on the vintage, a certain percentage of each type of unit will fail and need to 

be replaced. To determine when an electric cooking product fails, DOE used a product survival 

function based on a lifetime distribution with an average value of 19 years, and minimum and 

maximum values of 10 years and 28 years, respectively. For gas cooking products, DOE used a 

product survival function based on a lifetime distribution with an average value of 19 years, and 

minimum and maximum values of 12 years and 26 years, respectively. For a more complete 

discussion of cooking product lifetimes, refer back to section 8.2.3.1 of Chapter 8. Figure 9.3.7 

shows the survival and retirement functions that DOE used to estimate replacement shipments. 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Gas - Percent Surviving 

Elec - Percent Surviving 

Gas - Percent Retiring 

Elec - Percent Retiring 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 

Age (years) 

Figure 9.3.7 Electric and Gas Cooking Products: Retirement Functions 

Model Calibration—Early Replacements. To calibrate estimated shipments with the 

historical data, DOE introduced into the model an early replacement market function. DOE 

assumed that replacements in this category occur at the rate of two percent of the surviving stock 

per annum over the time period 2005–2042. The early replacement rate is distributed among 

equipment of ages ranging from 10 to 28 years for electric cooking products and 12 to 26 years 

for gas cooking products; DOE weighted these equipment by their respective population in the 

surviving stock. The following equation illustrates the calculations: 

9-26 

EE-2006-STD-0127 COMMENT 39.2
_ AgeMax 1 Stock( j _

1,age ) _ ERMWO ( j ) = 

age 

∑

=4 ∑Stock( j 1,age ) 

× ERRate × Stock( j 1) _ 

age 

where: 

ERMWO (j) = Number of cooking products replaced early in year j, 

Stock (j-1, age) = Population of in-service units of a particular age in year j-1, 

ERRate = Early replacement rate, and 

AgeMax = Maximum age of the unit before it retires. 

9.3.3.3 Base Case Shipments 

Figures 9.3.8 and 9.3.9 show the forecasted shipments of electric and gas cooking 

products, respectively, in the base case (i.e., the case without new energy efficiency standards) 

and the historical shipments DOE used to calibrate the forecast. 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

Shipments (millons) 

Historical Shipments 

Modeled Shipments 

Figure 9.3.8 Electric Cooking Products: Historical and Base Case Shipments 

Forecast 

9-27 

EE-2006-STD-0127 COMMENT 39.2
0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

Shipments (millons) 

Historical Shipments 

Modeled Shipments 

Figure 9.3.9 Gas Cooking Products: Historical and Base Case Shipments 

Forecast 

Figures 9.3.10 and 9.3.11 present forecasted base case electric and gas cooking product 

shipments, respectively, disaggregated into the following market segments: shipments due to 

retirements, shipments to new housing, and shipments due to early replacements. Note that 

replacement shipments comprised 85–92 percent of total gas and electric cooking product 

shipments over the period 2006–2042. The percentage of total shipments represented by 

replacements is high because the gas and electric cooking product market is fairly mature. 

9-28 

EE-2006-STD-0127 COMMENT 39.2
0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

8.0 

9.0 

10.0 

2000 2005 2010 2015 2020 2025 2030 2035 2040 

Year 

Shipments (million) 

New Units 

Early Repl Units 

Normal Repl 

Figure 9.3.10 Electric Cooking Products: Disaggregated Base Case 

Shipments Forecast 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

5.0 

5.5 

2000 2005 2010 2015 2020 2025 2030 2035 2040 

Year 

Shipments (million) 

New Units 

Early Repl Units 

Normal Repl 

Figure 9.3.11 Gas Cooking Products: Disaggregated Base Case 

Shipments Forecast 

9-29 

EE-2006-STD-0127 COMMENT 39.2
9.3.4 Microwave Ovens 

Microwave ovens are a specific product category of the cooking products that DOE 

considered for this rulemaking. Although microwave oven shipments are tracked by 

configuration (i.e., countertop, convection, over-the-range), DOE represented microwave ovens 

as a single product class. 

9.3.4.1 Historical Shipments 

DOE used data on historical shipments (i.e., domestic shipments and imports) to calibrate 

its Shipments Model for microwave ovens. DOE’s sources for historical shipments data were: 

(1) AHAM Factbooks for the years 2000,3

 200314, and 20057 covering the period 1989−2005 and 

(2) Appliance Magazine4,5,6 for the period 1981−1988.h

 Table 9.3.13 summarizes the historical 

microwave oven shipments data. 

Table 9.3.13 Microwave Ovens: Historical Shipments, Domestic plus Imports 

Year Shipments (thousands) Year Shipments (thousands) 

1980 3,144 1993 7,240 

1981 3,864 1994 8,574 

1982 3,469 1995 8,162 

1983 5,012 1996 8,771 

1984 7,638 1997 8,883 

1985 9,543 1998 10,365 

1986 10,912 1999 11,422 

1987 10,891 2000 12,644 

1988 9,479 2001 13,446 

1989 9,778 2002 13,311 

1990 7,693 2003 14,274 

1991 6,623 2004 15,526 

1992 7,190 2005 13,862 

Source: 1989–2005: AHAM Fact Books, 2000, 2003, 2005; 1981–1988: Appliance Magazine, “Statistical 

Review,” 1990, 1993. 

9.3.4.2 Markets and Model Calibration 

The market for microwave ovens is primarily comprised of the following: replacement 

units for equipment that has been retired from service and units for new housing. In addition to 

normal replacements, DOE’s Shipments Model also assumed that a certain fraction of the stock 

h

 Shipments estimates from Appliance Magazine included exports. Thus, DOE reduced total shipments by 12.3 

percent (the average percentage of exports for the years 1989–1993 based on the five-year average difference 

between the AHAM Fact Book 2000 and Appliance Magazine) to estimate total domestic shipments plus imports. 

9-30 

EE-2006-STD-0127 COMMENT 39.2
would be replaced early. Total microwave oven shipments are represented by the following 

equation: 

ShipMWO ( j ) = Rpl MWO ( j ) + NI MWO ( j ) + ERMWO ( j ) 

where: 

ShipMWO (j) = Total shipments of microwave ovens in year j, 

RplMWO (j) = Replacement shipments in year j, 

NIMWO (j) = Shipments to new households in year j, and 

ERMWO (j)= Early replacement shipments in year j. 

The sections below discuss all three of these markets in further detail. 

 New Construction. To estimate shipments to new construction, DOE used forecasts of 

housing starts coupled with microwave oven saturation data. In other words, to forecast the 

shipments for new construction for any given year, DOE multiplied the housing forecasts by the 

forecasted saturation of microwave ovens for new housing. 

Historical and forecasted new housing starts were presented earlier for cooking products. 

Refer back to Table 9.3.2 for the housing starts data. 

Table 9.3.14 presents historical market saturations of microwave ovens based on various 

sources, including AHAM’s 2005 Fact Book,

7 Appliance Magazine,8

 NFO World Group,9 and 

EIA’s RECS for the years 1993,10 1997,11 and 2001.12 The table presents market saturations for 

the overall housing stock, new households only, and households with two or more microwave 

ovens. Because the forecast of shipments for the new housing market depends on the saturation 

of microwave ovens in new housing, DOE focused its attention on the market saturations for new 

housing as well as the saturations of housing with multiple microwave ovens. According to 

RECS, microwave oven saturation in new housing for 1993, 1997, and 2001 was 92 percent, 

87.5 percent, and 93.3 percent, respectively. According to NFO, households with more than one 

microwave oven represented 3.7 percent, 4.9 percent, and 4.1 percent of the housing market for 

the years 1990, 1996, and 2001, respectively. Therefore, DOE incremented the saturation levels 

for new housing estimated by RECS by the amounts provided by NFO to estimate the new 

housing saturations. As a result, DOE determined the effective saturation of microwave ovens in 

new housing to be 95.7 percent, 92.4 percent, and 97.4 percent for 1993, 1997, and 2001, 

respectively. Because 2001 is the most recent year in which data are available, DOE decided to 

freeze the saturation at 97.4 percent to estimate the shipments to new construction for future 

years. 

9-31 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.14 Microwave Ovens: Historical Market Saturations 

Year 

Overall Household New 

Households 

Households 

with ≥ 2 ovens 

AHAM* Appl** NFO*** RECS†

 RECS† NFO*** 

1978 7.2% 

1982 25.6% 

1983 33.3% 

1987 65.9% 

1990 82.7% 81.1% 3.9% 

1991 85.2% 

1992 84.5% 

1993 85.5% 84.1% 92.0% 

1994 88.8% 

1995 88.9% 

1996 90.6% 88.7% 4.9% 

1997 91.0% 83.0% 87.5% 

1998 91.3% 

1999 93.1% 

2000 95.6% 

2001 90.7% 95.7% 91.8% 86.1% 93.3% 4.1% 

2002 95.0% 

2003 95.0% 

2004 95.5% 

2005 89.3% 

* Source: AHAM, Fact Book, 2005; ** Source: Appliance Magazine, “The Saturation Picture,” September 

issues; *** Source: NFO World Group, 2001; † Source: DOE-EIA, RECS, 1993, 1997, and 2001. 

 Replacements. DOE determined shipments to the replacement market using an 

accounting method that tracks the total stock of units by vintage. DOE estimated a stock of 

microwave ovens by vintage by integrating historical shipments starting from the year 1981. 

Over time, some units will be retired and removed from the stock, thereby triggering the 

shipment of a replacement unit. Depending on the vintage, a certain percentage of each type of 

unit will fail and need to be replaced. To determine when a microwave oven fails, DOE used a 

product survival function based on a lifetime distribution with an average value of nine years, 

and minimum and maximum values of seven years and 10 years, respectively. For a more 

complete discussion of microwave lifetimes, refer back to section 8.2.3.2 of Chapter 8. Figure 

9.3.12 shows the survival and retirement functions that DOE used to estimate replacement 

shipments. 

9-32 

EE-2006-STD-0127 COMMENT 39.2
100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0% 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 

Percent Surviving 

Percent Retiring 

Age (years) 

Figure 9.3.12 Microwave Ovens: Survival and Retirement Functions 

Model Calibration—Early Replacements. To calibrate estimated shipments with the 

historical data, DOE introduced into the model an early replacement market function. DOE 

determined that replacements in this category occur at the rate of two percent of the surviving 

stock per annum over the time period 2005–2042. The early replacement rate is distributed 

among equipment of ages ranging from four through 10 years; DOE weighted these equipment 

by their respective population in the surviving stock. The following equation illustrates the 

calculations: 

AgeMax_1 Stock( j _

1,age ) _ ERMWO ( j ) = 

age 

∑

=4 ∑Stock( j 1,age ) 

× ERRate × Stock( j 1) _ 

age 

where: 

ERMWO (j) = Number of microwave ovens replaced early in year j, 

Stock (j-1, age) = Population of in-service units of a particular age in year j-1, 

ERRate = Early replacement rate, and 

AgeMax = Maximum age of the unit before it retires. 

9-33 

EE-2006-STD-0127 COMMENT 39.2
9.3.4.3 Base Case Shipments 

Figure 9.3.13 shows the forecasted shipments in the base case (i.e., the case without new 

energy efficiency standards) and the historical shipments DOE used to calibrate the forecast. 

0 

5 

10 

15 

20 

25 

1985 1995 2005 2015 2025 2035 

Year 

Shipments (million units)

Historical Shipments 

modelled Shipments 

Figure 9.3.13 Microwave Ovens: Historical and Base Case Shipments 

Forecast 

Figure 9.3.14 presents forecasted base case microwave oven shipments disaggregated 

into the following market segments: shipments due to retirements, shipments to new housing, 

and shipments due to early replacements. Note that replacement shipments comprised 85–92 

percent of total microwave oven shipments over the period 2006–2035. The percentage of total 

shipments represented by replacements is high because the microwave oven market is fairly 

mature. 

9-34 

EE-2006-STD-0127 COMMENT 39.2
0.0 

5.0 

10.0 

15.0 

20.0 

25.0 

199019931996199920022005200820112014201720202023202620292032203520382041 

Year 

Shipments (million units) 

New Units 

Early Repl 

Normal Repl 

Aggregate Shipments 

Figure 9.3.14 Microwave Ovens: Disaggregated Base Case Shipments 

Forecast 

9.3.5 Commercial Clothes Washers 

DOE’s Shipments Model for commercial clothes washers forecasted shipments to the two 

most predominant product applications: multi-family buildings and laundromats. DOE adopted 

the following approach for estimating shipments. 

The analysis began with aggregate historical shipments data for commercial clothes 

washers. Tracking of product stock and vintage relies on a retirement function, which describes 

the likelihood that equipment installed in a certain year will still be in service in any subsequent 

year. Once a product reaches the end of its useful life it is removed from service. In most cases, 

retirement is followed by replacement, which is a key driver of further shipments. The 

difference between replacements and total shipments for the following year provides the 

shipments going into new construction. The output includes units going into both laundromats 

and multi-family apartment buildings. 

DOE based its Shipments Model on the following three assumptions: (1) All product 

shipments for new construction are driven by the new multi-family housing market, (2) the 

relative market shares of the two product applications, laundromats and common-area laundry 

facilities in multi-family housing, are constant over time, and (3) the U.S. Census Bureau’s 

quantity index data can be used to validate the shipments trend observed in the historical data. 

DOE’s first assumption is based on the premise that multi-family occupants who do not 

have their own personal washers and dryers must either wash their laundry in the common area 

9-35 

EE-2006-STD-0127 COMMENT 39.2
laundry facility within their building or in a laundromat. Because the vast majority of people 

that use laundromats live in multi-family buildings, the construction of any new laundromats 

would seem to be driven by new multi-family customers. Thus, DOE believes it is reasonable to 

expect that new multi-family construction starts capture all new product shipments, regardless of 

whether the units are destined for multi-family buildings or laundromats. 

With regard to the second assumption, i.e., constant market shares, DOE did not have 

sufficient data to forecast whether the market shares of laundromats and multi-family housing 

will vary over time. Therefore, DOE assumed that market shares will remain constant at current 

levels. DOE relied on a report from the Consortium for Energy Efficiency (CEE) to estimate 

current market shares. Based on the CEE report, multi-family buildings and laundromats 

comprise 85 percent and 15 percent of the commercial clothes washer market, respectively.18 

The third assumption pertains to the use of the U.S Bureau of Economic Analysis’ 

quantity index data to validate historical shipments data.19 The Census Bureau’s quantity index 

for commercial laundry equipment includes shipments of commercial laundry products beyond 

those covered by this rulemaking. Because disaggregated quantity index data were not available, 

DOE assumed that the market share of commercial clothes washers covered under this 

rulemaking relative to all commercial laundry was constant over the period 1977–2004. Based 

on this assumption, DOE derived quantity index data specific to the commercial clothes washers 

of interest to this rulemaking and used the data to validate the historical shipments. 

9.3.5.1 Historical Shipments 

DOE used historical shipments data (i.e., domestic shipments and imports) to calibrate its 

Shipments Model. It used two sources to establish historical shipments: (1) data AHAM 

provided for the period 2002–200520 and (2) data from Appliance Magazine21 for the period 

1988–1998. For the period 1999–2001, DOE interpolated between the shipments for 1998 and 

2002. For the period 1979–1987, DOE used the shipments in1989 as the reference point and the 

corresponding Census Bureau’s quantity index data to estimate shipments. Lastly, DOE used a 

five-year moving average to backcast shipments for the period 1972−1978. Table 9.3.15 

summarizes the historical commercial clothes washer shipments data. 

9-36 

EE-2006-STD-0127 COMMENT 39.2
Table 9.3.15 Commercial Clothes Washers: Historical Shipments, Domestic plus Imports 

Year Shipments (thousands) Year Shipments (thousands) 

1972 167 1989 215 

1973 167 1990 225 

1974 166 1991 193 

1975 167 1992 188 

1976 167 1993 190 

1977 167 1994 205 

1978 166 1995 209 

1979 164 1996 232 

1980 170 1997 241 

1981 171 1998 265 

1982 163 1999 239 

1983 163 2000 215 

1984 167 2001 194 

1985 176 2002 175 

1986 186 2003 191 

1987 194 2004 178 

1988 213 2005 177 

Sources: 2002–2005: AHAM Data Submittal, 2006; 1988–1998: Appliance Magazine, “Statistical Review,” 1998 

and 1999. 1972–1987: Based on Census Bureau’s Quantity Index Data. 1999–2001: DOE interpolated values. 

As indicated in Table 9.3.15, there was a significant drop in commercial clothes washer 

shipments between 1998 and 2002. Because DOE used different data sources to estimate the 

shipments in 1998 and 2002, it validated the shipments data through a review of the U.S. Bureau 

of Economic Analysis’ quantity index data. DOE compared the historical shipments data against 

the quantity index for commercial laundry equipment (represented by North American Industry 

Classification System (NAICS) code 333312). The largest product group in this industry is 

washers and extractors, which accounts for almost 40 percent of sales and about 25 percent of 

the shipment value.18 As shown in Figure 9.3.15 below, the commercial laundry quantity index 

tracks the shipments trend closely. Thus, DOE concluded that the downward trend observed in 

the historical shipments between 1998 and 2002 was real. 

9-37 

EE-2006-STD-0127 COMMENT 39.2
0 

20 

40 

60 

80 

100 

120 

140 

160 

1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 

Quantity Index (2000 base) 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

Shipments in millions 

QI Shipments QI-based Shipments 

Pre-1988 shipments 

based on QI 

Extrapolated 

after 2005 

Figure 9.3.15 Commercial Clothes Washer Shipments and Trend in Quantity 

Index 

9.3.5.2 Markets and Model Calibration 

The market for commercial clothes washers primarily comprises replacement units for 

equipment that has been retired and units for new housing. Total commercial clothes washers 

shipments are represented by the following equation: 

ShipCCW ( j ) = RplCCW ( j ) + NICCW ( j ) 

where: 

ShipCCW (j) = Total shipments of commercial clothes washers in year j, 

RplCCW (j) = Replacement shipments in year j, and 

NICCW (j) = Shipments to new households in year j. 

The sections below discuss both of these markets in further detail. 

New Construction. To forecast shipments to the new construction market, DOE assumed 

shipments are driven solely by multi-family construction starts. Implicit in this assumption is the 

fact that a certain percentage of multi-family residents will need to wash their laundry in either a 

common-area laundry facility (within the multi-family building) or a laundromat. 

To estimate shipments to new construction, DOE used forecasts of multi-family housing 

starts coupled with commercial clothes washer saturation data. In other words, to forecast the 

shipments for new construction for any given year, DOE multiplied the multi-housing forecasts 

by the forecasted saturation of commercial clothes washers for new multi-family housing. 

9-38 

EE-2006-STD-0127 COMMENT 39.2
Because DOE used only multi-family housing starts as a driver for new construction shipments, 

the saturation represents washers in both the multi-family housing and laundromat markets. 

Table 9.3.16 presents historical and forecasted new multi-family housing starts based on 

EIA’s AEO2007 for the period 1990–2030.1 AEO2007 provides three scenarios of multi-family 

housing starts: the Reference case, the High Economic Growth case, and the Low Economic 

Growth case. All three housing starts forecasts are presented in Table 9.3.16. DOE used only 

the forecasts from the Reference case to estimate its shipments to new construction. The multifamily housing construction forecast shows an annual 0.5 percent increase in housing 

completions. Therefore, DOE assumed that completions grow at 0.5 percent per year (the 

projected average annual growth rate in the 2004−2030 period) for the 2031−2042 period. 

Table 9.3.16 Historical and Forecasted Multi-Family Housing Starts (millions) 

Year Reference High Low Year Reference High Low 

1990 0.30 0.30 0.30 2017 0.33 0.28 0.39 

1991 0.17 0.17 0.17 2018 0.34 0.29 0.39 

1992 0.17 0.17 0.17 2019 0.33 0.28 0.39 

1993 0.16 0.16 0.16 2020 0.32 0.27 0.38 

1994 0.26 0.26 0.26 2021 0.31 0.26 0.36 

1995 0.28 0.28 0.28 2022 0.31 0.25 0.37 

1996 0.32 0.32 0.32 2023 0.31 0.25 0.37 

1997 0.34 0.34 0.34 2024 0.31 0.25 0.38 

1998 0.35 0.35 0.35 2025 0.32 0.25 0.38 

1999 0.34 0.34 0.34 2026 0.32 0.25 0.40 

2000 0.34 0.34 0.34 2027 0.34 0.26 0.41 

2001 0.33 0.33 0.33 2028 0.34 0.27 0.42 

2002 0.35 0.35 0.35 2029 0.35 0.27 0.43 

2003 0.35 0.35 0.35 2030 0.36 0.28 0.43 

2004 0.34 0.34 0.34 2031 0.36 0.28 0.43 

2005 0.34 0.34 0.34 2032 0.36 0.28 0.43 

2006 0.32 0.25 0.39 2033 0.36 0.28 0.43 

2007 0.34 0.27 0.42 2034 0.36 0.28 0.43 

2008 0.34 0.27 0.42 2035 0.36 0.28 0.43 

2009 0.33 0.25 0.41 2036 0.36 0.28 0.43 

2010 0.32 0.25 0.40 2037 0.36 0.28 0.43 

2011 0.31 0.24 0.39 2038 0.36 0.28 0.43 

2012 0.31 0.24 0.38 2039 0.36 0.28 0.43 

2013 0.31 0.24 0.37 2040 0.36 0.28 0.43 

2014 0.31 0.25 0.37 2041 0.36 0.28 0.43 

2015 0.31 0.25 0.37 2042 0.36 0.28 0.43 

2016 0.32 0.26 0.37 

Source: EIA, AEO2007. 

9-39 

EE-2006-STD-0127 COMMENT 39.2
DOE deduced historical commercial laundry saturations for the new construction market 

based on the remaining portion of historical shipments that did not serve as replacement units. 

(The determination of replacement shipments is discussed below.) Table 9.3.17 shows the 

historical saturation of commercial clothes washers in new multi-family buildings. 

Table 9.3.17 Commercial Clothes Washers: Historical New Multi-Family Building 

Saturations 

Year Saturation 

1990 19.7% 

1991 14.9% 

1992 11.4% 

1993 11.9% 

1994 11.7% 

1995 10.5% 

1996 14.7% 

1997 14.8% 

1998 20.7% 

Average 14.5% 

DOE assumed that the average saturation over the period 1990−1998 of 14.5 percent 

would remain constant over the period 1999−2042. CEE’s report on the commercial laundry 

industry estimates a 14 percent saturation (i.e., approximately 14 percent of total domestic 

laundry is done in non-residential washers). CEE’s 14 percent figure is close to the 14.5 percent 

saturation value that DOE determined. Thus, DOE has confidence that its calculated saturation 

is representative of the commercial clothes washer market. Figure 9.3.16 shows the historical 

variation in the new construction saturation as well as the forecasted saturation for the years after 

1998. 

9-40 

EE-2006-STD-0127 COMMENT 39.2
0. 0% 

5. 0% 

10 . 0 % 

15 . 0 % 

20 . 0 % 

25 . 0 % 

1984 

1988 

1992 

1996 

2000 

2004 

2008 

2012 

2016 

2020 

2024 

2028 

2032 

2036 

2040 

Year 

Commercial Laundry Saturation in new MF

Housing 

Figure 9.3.16 Commercial Laundry Saturation in New Multi-Family 

Housing 

 Replacements. DOE determined shipments to the replacement market using an 

accounting method that tracks the total stock of units by vintage. DOE estimated a stock of 

commercial clothes washers by vintage by integrating historical shipments starting from the year 

1972. Over time, some units will be retired and removed from stock, thereby triggering the 

shipment of a replacement unit. Depending on the vintage, a certain percentage of each type of 

unit will fail and need to be replaced. To determine when a unit fails, DOE used a survival 

function based on the product lifetime distributions of the two product applications considered in 

the analysis—laundromats and multi-family buildings. For the commercial clothes washer 

Shipments Model, DOE combined the average values for the two product applications based on 

the market share of each application (85 percent for multi-family housing and 15 percent for 

laundromats). The survival function that DOE used had an average lifetime of 10.6 years with 

minimum and maximum values of 6.7 years and 14.6 years, respectively. For a more complete 

discussion of commercial clothes washer lifetimes, refer back to section 8.2.3.5 of Chapter 8. 

Figure 9.3.17 shows the survival and retirement functions that DOE used to estimate replacement 

shipments. 

9-41 

EE-2006-STD-0127 COMMENT 39.2
0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percent Surviving 

Percent Retiring 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 

Age (years) 

Figure 9.3.17 Commercial Clothes Washers: Survival and Retirement 

Functions 

 Model Calibration—Non-Replacements. To account for the significant drop in 

shipments after 1998, and to reconcile the historical shipments with the accounting model, DOE 

assumed every retired unit is not replaced immediately. The market share of retired units not 

replaced was relatively large due to the significant drop in shipments after 1998 (as discussed 

above in section 9.3.5.1). Staring in 1999 and extending to 2005, DOE estimated an evergrowing share of retired units that were not replaced. DOE gradually reduced the percentage of 

retired units not replaced to zero over the period 2006─2013. Figure 9.3.18 shows the 

percentage of retired units not replaced over the period 1998─2013. 

9-42 

EE-2006-STD-0127 COMMENT 39.2
0% 

5% 

10% 

15% 

20% 

25% 

30% 

35% 

40% 

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 

Year 

Percent 

Figure 9.3.18 Commercial Clothes Washers: Percent of Retired Units not 

Replaced over the period 1998─2013 

9.3.5.3 Base Case Shipments 

Figure 9.3.19 shows the forecasted commercial clothes washer shipments in the base case 

(i.e., the case without new energy efficiency standards) and the historical shipments DOE used to 

calibrate the forecast. In the figure below, note that the replacement shipments for the period 

1998─2013 are lower than the actual retired units. The area between the two lines showing 

retired units and replacement shipments represents the retired units that were not replaced. 

9-43 

EE-2006-STD-0127 COMMENT 39.2
0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

1985 1995 2005 2015 2025 2035 

Year 

Shipments (million units) 

Historical Shipments 

Total Shipments 

Retired Units 

Replacement Shipments 

Figure 9.3.19 Commercial Clothes Washers: Historical and Base Case 

Shipments Forecast 

Figure 9.3.20 presents forecasted base case commercial clothes washer shipments 

disaggregated into shipments due to retirements and shipments for new construction. DOE 

determined that replacements accruing from retirements range from 80 percent to 85 percent of 

total commercial clothes washer shipments over the period 2006–2042. 

9-44 

EE-2006-STD-0127 COMMENT 39.2
1986

1990

1994

1998

2002

2006

2010

2014

2018

2022

2026

2030

2034

2038

2042 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

Shipments (million units) 

Shipments due to New cons 

Replacements 

Aggregate Shipments 

Year 

Figure 9.3.20 Commercial Clothes Washers: Disaggregated Base 

Case Shipments Forecast 

9.4 PURCHASE PRICE, OPERATING COST, AND HOUSEHOLD INCOME 

IMPACTS 

DOE conducted a literature review and an analysis of appliance price and efficiency data 

to estimate the combined effects on product shipments from increases in equipment purchase 

price, decreases in equipment operating costs, and changes to household income. Appendix 9A 

provides a detailed explanation of the methodology DOE used to quantify the impacts from the 

above variables. 

In the literature, DOE found only a few studies of appliance markets that are relevant to 

this rulemaking analysis, and identified no studies that use time-series data of equipment price 

and shipments data after 1980. The information that can be summarized from the literature 

suggests that the demand for appliances is price inelastic. Other information in the literature 

suggests that appliances are a normal good, such that rising incomes increase the demand for 

appliances. Finally, the literature suggests that consumers use relatively high implicit discount 

ratesi

 when comparing appliance prices and appliance operating costs. 

i

 A high implicit discount rate with regard to operating costs means that consumers do not put much economic value 

on the operating cost savings realized from more-efficient appliances. In other words, consumers are much more 

concerned with higher purchase prices. 

9-45 

EE-2006-STD-0127 COMMENT 39.2
DOE did not find enough equipment purchase price and operating cost data to perform a 

complex analysis of dynamic changes in the appliance market. Rather, it used purchase price 

and efficiency data specific to residential refrigerators, clothes washers, and dishwashers over the 

period 1980–2002 to evaluate broad market trends and conduct simple regression analyses. 

These data indicate that there has been a rise in appliance shipments and a decline in appliance 

purchase price and operating costs over the time period. Household income has also risen during 

this time. To simplify the analysis, DOE combined the available economic information into one 

variable, termed the relative price, and used this variable in an analysis of market trends, as well 

as to conduct a regression analysis. The relative price is defined with the following expression: 

TP PP + PVOC

RP = = 

Income Income 

where: 

RP = Relative price, 

TP = Total price, 

Income = Household income, 

PP = Appliance purchase price, and 

PVOC = Present value of operating cost. 

In the above equation, DOE used an implicit discount rate of 37 percent to determine the 

present value of operating costs. 

DOE’s analysis of market trends suggests that the relative price elasticity of demand for 

the three appliances is relatively inelastic (i.e., under 1.0). DOE’s regression analysis suggests 

that the relative price elasticity of demand, averaged over the three appliances, is -0.34. For 

example, a relative price increase of 10 percent results in a shipments decrease of 3.4 percent. 

Note that, because the relative price elasticity incorporates the impacts from three effects (i.e., 

purchase price, operating cost, and household income), the impact from any single effect is 

mitigated by changes from the other two effects. The relative price elasticity of -0.34 is 

consistent with estimates in the literature. Nevertheless, DOE stresses that the measure is based 

on a small data set, using simple statistical analysis. More important, the measure is based on an 

assumption that economic variables, including purchase price, operating costs, and household 

income, explain most of the trend in appliances per household in the United States since 1980. 

Changes in appliance quality and consumer preferences may have occurred during this period, 

but DOE did not account for them in this analysis. Despite these uncertainties, DOE believes 

that its estimate of the relative price elasticity of demand provides a reasonable assessment of the 

impact that purchase price, operating cost, and household income have on product shipments. 

Because DOE’s forecasts of shipments and national impacts due to standards is over a 

30-year time period, it needed to consider how the relative price elasticity is affected once a new 

standard takes effect. DOE considered the relative price elasticitiy provided above to be a shortrun value. It was unable to identify sources specific to household durable goods, such as 

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appliances, to indicate how short-run and long-run price elasticities differ. Therefore, to estimate 

how the relative price elasticity changes over time, DOE relied on a study pertaining to 

automobiles.22 This study shows that the automobile price elasticity of demand changes in the 

years following a purchase price change. With increasing years after the purchase price change, 

the price elasticity becomes more inelastic until it reaches a terminal value around the tenth year 

after the price change. Table 9.4.1 shows the relative change in the price elasticity of demand for 

automobiles over time. As shown in the table, DOE developed a time series of relative price 

elasticities for home appliances based on the relative change in the automobile price elasticity of 

demand. For years not shown in the table below, DOE performed a linear interpolation to obtain 

the relative price elasticity. 

Table 9.4.1 Change in Relative Price Elasticity following a Purchase Price Change 

Years Following Price Change 

1 2 3 5 10 20 

Relative Change in 

Elasticity to 1st year 

1.00 0.78 0.63 0.46 0.35 0.33 

Relative Price Elasticity -0.34 -0.26 -0.21 -0.16 -0.12 -0.11 

Based on the following equation, DOE estimated standards case shipments by 

incorporating the impact of the relative price into the base case shipments forecast. Note that in 

the equation below, the relative price and the relative price elasticity are functions of the year 

because both change with time. 

_ ShipSTD _ p ( j ) = (RplBASE _ p ( j ) + NI BASE _ p ( j ) + MBASE _ p ( j ))× (1 eRP ( j )× ∆RP( j )) 

where: 

ShipSTD_p(j) = Total shipments under the standards case of product p in year j, 

RplBASE_p(j) = Units of product p under the base case retired and replaced in year j, 

NIBASE_p(j) = Number of new construction installations under the base case of product p 

in year j (not applicable to dehumidifiers), 

MBASE_p(j) = Units installed in Market M under the base case of product p in year j (M 

represents early replacements for cooking products and microwave ovens, 

and first time owners for dishwashers and dehumidifiers), 

eRP(j)= Relative price elasticity in year j (equals -0.34 for year 1), and 

∆RP(j)= Change in relative price due to a standard level in year j. 

9.5 AFFECTED STOCK 

The affected stock is the in-service stock of the appliance or product that is affected by a 

standard level. In addition to the forecast of product shipments under both the base case and the 

standards case, the affected stock (which represents the difference in the appliance stock for the 

base case and the standards case) is a key output of DOE’s Shipments Models. The affected 

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EE-2006-STD-0127 COMMENT 39.2
stock quantifies the impact that new product shipments have on the appliance stock due to a 

standard level. Therefore, the affected stock consists of those in-service units that are purchased 

in or after the year the standard has taken effect, as described by the following equation: 

_ j Std _ yr 

Aff Stock ( j ) = Ship ( j ) + ∑Stock ( age ) p p p 

age =1

where: 

Aff Stockp(j) = Affected stock of units of product p of all vintages that are operational in 

year j, 

Shipp(j) = Shipments of product p in year j, 

Stockp(j) = Stock of units of product p of all vintages that are operational in year j, 

age = Age of the units (years), and 

Std_yr = Effective date of the standard . 

As noted in the above equation, to calculate the affected stock, DOE must define the 

effective date of the standard. For the NES and NPV results presented in Chapter 10, DOE 

assumed that new energy efficiency standards will become effective in the year 2012. Thus, all 

appliances purchased starting on the first day of the year 2012 are affected by the standard level. 

9.6 RESULTS 

The following sections show the shipments forecasts for the various standard levels that 

DOE considered for each of the four sets of products. 

9.6.1 Dishwashers 

Table 9.6.1 shows the cumulative shipments impacts over the period 2012–2042 caused 

by each of the seven standards cases considered for standard-sized dishwashers. For standard 

level 1, shipments are forecasted to increase slightly—the decrease in operating costs due to the 

efficiency standard offsets the increase in purchase prices, resulting in a net increase in 

shipments. For standard levels 2 through 7, the effect due to the increase in product purchase 

prices exceeds the effects from decreased operating costs, resulting in a net decrease in 

shipments. Figure 9.6.1 compares the shipments forecasts for the base case and standard levels 4 

through 7 (annual shipments forecasts for standard levels 1 through 3 are not appreciably 

different from the base case). In Figure 9.6.1, the difference between the base case and standard 

level shipments forecasts depicts the annual shipments reductions caused by the standard levels. 

As can be seen in this figure, the decrease in forecasted shipments is significant for standard 

levels 5 through 7. 

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EE-2006-STD-0127 COMMENT 39.2
2008 

2010 

2012 

2014 

2016 

2018 

2020 

2022 

2024 

2026 

2028 

2030 

2032 

2034 

2036 

2038 

2040 

2042 

Table 9.6.1 Dishwashers: Cumulative Shipments Impacts Caused by Standards over the 

Period 2012–2042 

Standard Level Energy Factor Cumulative Impacts (million) 

1 0.58 +0.056 

2 0.62 -0.002 

3 0.65 -0.676 

4 0.68 -2.925 

5 0.72 -9.010 

6 0.80 -17.413 

7 1.11 -23.936 

13 

12 

11 

10 

9 

8 

7 

Ba s e C a s e 

S t d Le v e l 4 

S t d Le v e l 5 

S t d Le v e l 6 

S t d Le v e l 7

Shipments (million) 

Year 

Figure 9.6.1 Standard-Sized Dishwashers: Base Case and Standards Case 

Shipments Forecasts 

9.6.2 Dehumidifiers 

Table 9.6.2 shows the cumulative shipments impacts over the period 2012–2042 caused 

by each of the five standards cases considered for dehumidifiers. For all standard levels, 

shipments are forecasted to decrease—the effects from the increase in product purchase prices 

offset the effects from decreased operating costs, resulting in a net decrease in shipments. Figure 

9.6.2 compares the shipments forecasts for the base case and standard levels 3 through 5 (annual 

shipments forecasts for standard levels 1 and 2 are not appreciably different from the base case). 

In Figure 9.6.2, the difference between the base case and standard level shipments forecasts 

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EE-2006-STD-0127 COMMENT 39.2
2008 

2010 

2012 

2014 

2016 

2018 

2020 

2022 

2024 

2026 

2028 

2030 

2032 

2034 

2036 

2038 

2040 

2042 

depicts the annual shipments reductions caused by the standard levels. As can be seen in the 

figure, the decrease in forecasted shipments is significant for standard levels 4 and 5. 

Table 9.6.2 Dehumidifiers: Cumulative Shipments Impacts to all Product Classes caused 

by Standards over the period 2012–2042 

Standard Level Cumulative Impacts (million) 

1 -0.251 

2 -0.810 

3 -1.635 

4 -2.957 

5 -7.179 

1. 5 

2. 0 

2. 5 

3. 0 

3. 5 

4. 0 

Shipments (million) 

B a se C a se 

S t d Lev e l 3 

S t d Lev e l 4 

S t d Lev e l 5 

Year 

Figure 9.6.2 Dehumidifiers: Base Case and Standards Case Shipments Forecasts 

9.6.3 Cooktops and Ovens 

 Because the combined market of electric and gas cooking products is completely 

saturated, DOE assumed that all electric and gas cooking product standard levels would neither 

impact base case shipments nor cause shifts in electric and gas cooking product market shares. 

Thus, DOE’s Shipments Model for electric and gas cooking products does not incorporate the 

use of relative price elasticities. As a result, forecasted shipments for all cooking product 

standard levels are equivalent to the base case shipments forecasts. Refer back to Figures 9.3.8 

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EE-2006-STD-0127 COMMENT 39.2
and 9.3.9 to review the base case shipments forecasts for electric and gas cooking products, 

respectively. 

9.6.4 Microwave Ovens 

Table 9.6.3 shows the cumulative shipments impacts over the period 2012–2042 caused 

by each of the four standards cases considered for microwave ovens. For all standard levels, 

shipments are forecasted to decrease—the effects from the increase in product purchase prices 

offset the effects from decreased operating costs, resulting in a net decrease in shipments. Figure 

9.6.3 compares the shipments forecasts for the base case and standard levels 1 through 4. In 

Figure 9.6.3, the difference between the base case and standard level shipments forecasts depicts 

the annual shipments reductions caused by the standard levels. As can be seen in the figure, the 

decrease in forecasted shipments is significant for all standard levels. 

Table 9.6.3 Microwave Ovens: Cumulative Shipments Impacts Caused by Standards 

over the Period 2012–2042 

Standard Level Energy Factor Cumulative Impacts (million) 

1 0.586 -10.978 

2 0.588 -22.550 

3 0.597 -40.406 

4 0.602 -62.567 

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EE-2006-STD-0127 COMMENT 39.2
2008 

2010 

2012 

2014 

2016 

2018 

2020 

2022 

2024 

2026 

2028 

2030 

2032 

2034 

2036 

2038 

2040 

2042 

Shipments (million) 

22 

21 

20 

19 

18 

17 

16 

15 

14 

B a se C a se 

S t d L e v el 1 

S t d L e v el 2 

S t d L e v el 3 

S t d L e v el 4 

Year 

Figure 9.6.3 Microwave Ovens: Base Case and Standards Case Shipments 

Forecasts 

9.6.5 Commercial Clothes Washers 

Table 9.6.4 shows the cumulative shipments impacts over the period 2012–2042 caused 

by each of the six standards cases considered for commercial clothes washers. For all standard 

levels, shipments are forecasted to decrease—the effects from the increase in product purchase 

prices offset the effects from decreased operating costs, resulting in a net decrease in shipments. 

Figure 9.6.4 compares the shipments forecasts for the base case and standard level 6. Standard 

levels 2 through 6 have very similar impacts because the purchase price increase associated with 

each of the standard levels is the same. In Figure 9.6.4, the difference between the base case and 

standard level shipments forecasts depicts the annual shipments reductions caused by the 

standard levels. 

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EE-2006-STD-0127 COMMENT 39.2
2008 

2010 

2012 

2014 

2016 

2018 

2020 

2022 

2024 

2026 

2028 

2030 

2032 

2034 

2036 

2038 

2040 

2042 

Table 9.6.4 Commercial Clothes Washers: Cumulative Shipments Impacts Caused by 

Standards over the Period 2012–2042 

Standard Level 

Modified Energy Factor/ 

Water Factor 

Cumulative Impacts 

(thousands) 

1 1.42/9.5 -0.141 

2 1.60/8.5 -0.596 

3 1.72/8.0 -0.595 

4 1.80/7.5 -0.595 

5 2.00/5.5 -0.593 

6 2.20/5.1 -0.592 

0. 1 5 

0. 2 0 

0. 2 5 

0. 3 0 

0. 3 5 

0. 4 0 

Shipments (million) 

Ba s e C a s e 

St d L e v e l 6 

Year 

Figure 9.6.4 Commercial Clothes Washers: Base Case and Standards Level 6 

Shipments Forecasts 

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REFERENCES 

1 U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2007 with Projections to 2030, February, 2007. Washington, DC. DOE/EIA-0383(2007). 

2 Association of Home Appliance Manufacturers. AHAM Data on Dishwashers for Efficiency 

Standards Rulemaking, September 7, 2006. Letter to Building Technologies Program, U.S. 

Department of Energy. 

3 Association of Home Appliance Manufacturers. AHAM 2000 Fact Book, 2000. Washington, 

DC. 

4 Statistical Review. Appliance Magazine, April, 1993. 

5 Statistical Review. Appliance Magazine, April, 1990. 

6 Statistical Review. Appliance Magazine, April, 1982. 

7 Association of Home Appliance Manufacturers. AHAM 2005 Fact Book, 2005. Washington, 

DC. 

8 The Saturation Picture. Appliance Magazine, September, 1993, 1995, 2004, 2005. 

9 NFO World Group. Final Report: Home Appliance Saturation and Length of First 

Ownership Study, May, 2001. Prepared for Association of Home Appliance Manufacturers 

by NFO World Group, Boston, MA. 

10 U.S. Department of Energy-Energy Information Administration. Residential Energy 

Consumption Survey, 1993 Public Use Data Files, 1993. Washington, DC. 

<http://www.eia.doe.gov/emeu/recs/93publicuse.html> 

11 U.S. Department of Energy-Energy Information Administration. Residential Energy 

Consumption Survey, 1997 Public Use Data Files, 1997. Washington, DC. 

<http://www.eia.doe.gov/emeu/recs/public.html> 

12 U.S. Department of Energy-Energy Information Administration. Residential Energy 

Consumption Survey, 2001 Public Use Data Files, 2001. Washington, DC. 

<http://www.eia.doe.gov/emeu/recs/recs2001/publicuse2001.html> 

13 Association of Home Appliance Manufacturers. AHAM Data on Dehumidifiers for

Efficiency Standards Rulemaking, August 23, 2006. Letter to Building Technologies 

Program, U.S. Department of Energy. 

14 Association of Home Appliance Manufacturers. AHAM 2003 Fact Book, 2003. Washington, 

DC. 

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EE-2006-STD-0127 COMMENT 39.2
15 Association of Home Appliance Manufacturers. AHAM Data on Cooking Products for 

Efficiency Standards Rulemaking, August 23, 2006. Letter to Building Technologies 

Program, U.S. Department of Energy. 

16 U.S. Department of Energy-Office of Codes and Standards. Supplemental Analysis for 

Ranges and Ovens, Supplemental Chapter 3 – Projected National Impacts of Standard 

Levels, 1998. Washington, DC. 

<http://www.eere.energy.gov/buildings/appliance_standards/residential/pdfs/chap3_sup.pdf> 

17 Appliance Recycling Information Center. INFOBulletin #8, Applications in Appliances, 

March 2005. Washington, DC. 

<http://www.aham.org/industry/ht/action/GetDocumentAction/id/5370> 

18 Consortium for Energy Efficiency. Commercial Family-Sized Washers: An Initiative

Description of the Consortium for Energy Efficiency, 1998. Boston, MA. 

19 U.S. Department of Commerce-Bureau of Economic Analysis. Industry Economic Accounts, 

Gross-Domestic-Product-(GDP)-by-Industry-Data, 1998-2005 NAICS Data: 

GDPbyInd_SHIP_NAICS and SIC Data: GDPbyInd_SHIP_SIC, Commercial Laundry 

Quantity Index Data, NAICS code 333312. Washington, DC. 

<http://preview.bea.gov/industry/gdpbyind_data.htm> 

20 Association of Home Appliance Manufacturers. AHAM Data on Commercial Clothes 

Washers for DOE Efficiency Standards Rulemaking, October 12, 2006. Letter to Building 

Technologies Program, U.S. Department of Energy. 

21 Statistical Review. Appliance Magazine, April, 1998, 1999. 

22 S. Hymans. Consumer Durable Spending: Explanation and Prediction, Brookings Papers on 

Economic Activity, 1971. Vol. 1971, No. 1, pp. 234-239. 

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