CHAPTER 10. SHIPMENTS ANALYSIS

TABLE OF CONTENTS
10.1 INTRODUCTION

......................................................................................................... 10-1 10.2 SHIPMENTS MODEL METHODOLOGY

.................................................................. 10-2 10.3 DATA INPUTS AND MODEL CALIBRATION

........................................................ 10-4 10.3.1 Cooktops and Ovens

...................................................................................................... 10-5 10.3.1.1 Historical Shipments

.................................................................................... 10-8 10.3.1.2 Markets and Model Calibration

................................................................... 10-9 10.3.1.3 Base Case Shipments

................................................................................. 10-15 10.3.2 Microwave Ovens

........................................................................................................ 1 0-18 10.3.2.1 Historical Shipments

.................................................................................. 10-18 10.3.2.2 Markets and Model Calibration

................................................................. 10-18 10.3.2.3 Base Case Shipments

................................................................................. 10-22 10.4 PURCHASE PRICE, OPERATING COST, AND HOUSEHOLD INCOME IMPACTS

.................................................................................................................... 10-2 3 10.5 AFFECTED STOCK

................................................................................................... 10-25 10.6 RESULTS

.................................................................................................................... 10-26 10.6.1 Cooktops and Ovens

.................................................................................................... 10 -26 10.6.2 Microwave Ovens

........................................................................................................ 1 0-26

LIST OF TABLES
Table 10.3.1 Cooktops and Ovens: Product Categories, Product Types, and Product Classes

................................................................................................................ 10-5 Table 10.3.2 Electric Cooktops and Ovens: Historical Shipment Market Shares by Product Type

...................................................................................................... 10-6 Table 10.3.3 Gas Cooktops and Ovens: Histor ical Shipment Market Shares by Product Type

................................................................................................................... 10-8 Table 10.3.4 Cooktops and Ovens including Ranges and Built-Ins: Historical Shipments

........................................................................................................... 10-9 Table 10.3.5 Historical and Forecaste d Housing Starts (millions)

....................................... 10-11 Table 10.3.6 Electric Cooking Products: Historical Market Saturations

............................. 10-12 Table 10.3.7 Gas Cooking Products: Hist orical Market Saturations

................................... 10-13 Table 10.3.8 Microwave Ovens: Historical Shipments, Domestic plus Imports

................. 10-18 Table 10.3.9 Microwave Ovens: Hist orical Market Saturations

.......................................... 10-20 Table 10.4.1 Change in Relative Price Elasticity following a Purchase Price Change

........ 10-25 Table 10.6.1 Microwave Ovens: Cumulative Shipments Impacts Caused by EF Standards over the Period 2012–2042

............................................................. 10-27

10-iLIST OF FIGURE Figure 10.3.1 Electric and Gas Cooking Pr oducts: Retirement Functions

............................ 10-14 Figure 10.3.2 Electric Cooking Products: Historic al and Base Case Shipments Forecast

.... 10-15 Figure 10.3.3 Gas Cooking Products: Historical and Base Case Shipments Forecast

.......... 10-16 Figure 10.3.4 Electric Cooking Products: Disaggre gated Base Case Shipments Forecast

... 10-17 Figure 10.3.5 Gas Cooking Products: Disaggregat ed Base Case Shipments Forecast

......... 10-17 Figure 10.3.6 Microwave Ovens: Surv ival and Retirement Functions

................................. 10-21 Figure 10.3.7 Microwave Ovens: Historical and Base Case Shipments Forecast

................ 10-22 Figure 10.3.8 Microwave Ovens: Disaggregated Base Case Shipments Forecast

................ 10-23 Figure 10.6.1 Microwave Ovens: Base Case and TSL Shipments Forecasts for EF Standard Levels

................................................................................................ 10-27

10-iiCHAPTER 10. SHIPMENTS ANALYSIS

10.1 INTRODUCTION Product shipments estimates are a necessary input to the national energy savings (NES) and net present value (NPV) calculations. Sh ipments are also a necessary input to the manufacturer impact analysis (MIA), whic h DOE conducts for its notices of proposed rulemaking (NOPRs). This chapter desc ribes DOE’s methodology for projecting annual shipments and presents results for cooking products. DOE estimated shipments for each product with a separate Shipments Model. DOE developed two separate Shipments Models: one for cooktops and ovens and another for microwave ovens. It calibrated each Shipment s Model against historical shipments. For purposes of estimating the impacts of prosp ective trial standard levels (TSL) on product shipments, each Shipments Model accounts for th e 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. DOE accounted for three market segments: (1) new construction; (2) existing buildings (i .e., replacing failed equipment); and early replacements. The Shipments Models are Microsoft Excelspreadsheets that are accessible on the Internet ( http://www.eere.energy.gov/buildings/appliance_standards/). Appendix 11A 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 10.2 presents the Sh ipments Model methodology for each product; section 10.3 describes the data inputs and the model calibration; section 10.4 discusses impacts on shipments from changes in equipment purchase price, operating cost, and household income; section 10.5 discusses the affected stock; and section 10.6 presents the results for different TSL scenarios. The technical support document (TSD) for DOE’s notice of proposed rulemaking (NOPR) covered conventional cooking products (i.e., cooktops and ovens), microwave oven energy factor (EF), microwave oven standby power consumption, and commercial clothes washers (CCW). 1 This chapter presents information and results pertaining solely to conventional cooking products and microwave oven EF. Th e impact of more-efficient equipment on microwave oven standby power and CCWs w ill be addressed in subsequent TSDs.

10-110.2 SHIPMENTS MODEL METHODOLOGY DOE developed a national stock model fo r 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 ar e new installations and replacements. Ship p ( j ) = Rpl p ( j ) + NI p ( j )

where: Ship p (j) = Total shipments of product p in year j , Rpl p (j) = Units of product p retired and replaced in year j , and NI p (j) = Number of new in stallations of product p in year j

. As the product-specific sections below di scuss, 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 trends aare dynamic and can vary among product classes. Rather than simply extrapolating a current shipments trend, the base case shipments analysis (i.e., the cas e without new standards) uses dr iver 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 produ ct shipments from the new construction market segment are equal to the number of new housi ng 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 existi ng stock, and expected co nstruction 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 estimate how long the appliance is likely to remain in stock. The following equation represents how DOE estimated replacement shipments.

aEfficiency trends affect sh ipments only in the standards case. A changein 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 10.4.

10-2_ _ _ ageMax j 1 Rpl p ( j ) = Stock p ( j 1 ) 

## ∑ ∑Ship j × prob Rtr ( age )
age =0 j = N where:
Stock p (j-1) = Total stock of in-servi ce appliances in year j-1 , prob Rtr (age) = Probability that an ap pliance of a particular age will be retired, and N

= Start year for when the model begi ns 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 provide s 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 ope rating costs for any year depe nd on the age distribution of the stock. The dependence of operating cost on the equipment age distribution occurs under a TSL that produces increasing efficiency over ti me, 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 e quipment by integrating historical shipments data starting from a specific year. The start ye ar 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 deve loped a series of equations that define the dynamics and accounting of in-service stoc ks. 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-servi ce 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 ye ar. The slightly more complicated equations (e.g., the following equation) are those that de scribe the accounting of the existing in-service stock of units: Stock( j +1 ,age +1 ) = Stock( j,age ) × 

# [ 1 _ prob Rtr ( age ) 

# ]
In the above equation, as the year is incremented from jto 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, prob Rtr (age) , which is described

10-3in section 10.3. Because the pr oducts 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.

10.3 DATA INPUTS AND MODEL CALIBRATION As discussed above, shipments are drivenprimarily by two market segments: new construction and replacements. DOE estimated new construction shipments us ing two inputs: new housing forecasts and market saturation data. New housing includes ne wly 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 2006, and adopted the projections from the DOE Energy In formation Administration (EIA)’s Annual Energy Outlook 2009 Early Release ( AEO2009 Early Release ) for the period of 2007–2030. 2 To determine new construction shipments for each product, DOE used forecasts of market saturations, combined with forecasts of housing starts. DOE estimated replacements using product reti rement functions that it developed from product lifetimes. For all produc ts, with the exception of mi crowave ovens, DOE based the retirement function on a Weibull probability distribution for the product lifetime. The Shipments Models assume that no units are retired belo w 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: prob Rtr ( age ) = 0 for age < AgeMin 1 prob ( age ) = f o r AgeMin ≤ age ≤ AgeMax Rtr AgeMax _ AgeMin prob Rtr ( age ) = 1 for age > AgeMax
where: prob Rtr (age) = Probability of retirement at the age of the product, 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.

10-4The 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.

10.3.1 Cooktops and Ovens DOE designed its Shipments Model for cookt ops and ovens by di viding these products into two general fuel categories: electric and ga s. 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 estim ated the electric cooking product shipments while the other Model estimated gas cooking product shipments. After DOE estimated shipments for each fuel category, it then disaggr egated 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 10.3.1 shows the product types and product classes under each general fuel category (i.e., electric and gas c ooking products). For electric cooking products there are eight product types and four product cla sses; for gas cooking products th ere are five product types and three product classes. Because ranges are co mprised of cooktop and oven product classes, DOE needed to disaggregate range shipments into the appropriate cooktop an d oven product classes and then combine those shipments with the a ppropriate built-in cooktop and oven shipments to obtain the total shipments for each product class.
Table 10.3.1 Cooktops and Ovens: Product Cate gories, 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 10.3.2 shows the historical market shar es 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 2003–2005 3 and (2) data from DOE’s supplemental analysis to its 1996 technical support document (TSD) on cooking products covering the period 1989– 1996. 4 For the time periods for which no data wereavailable, DOE either applied the market share percentages from the above two data source s or interpolated from the two available data

10-5sources. The notes in Table 10.3.2 provide further details. To estimate forecasted market shares of each product type, DOE decided to freeze the per centages 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.
Table 10.3.2 Electric Cooktops and Ovens: Hist orical Shipment Market Shares by Product Type

Year Percent of Total Shipments Ranges Built-In Cooktops Built-In OvensCoilStandard 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 10.3.3 shows the historical market shar es of the five product types that comprise total gas cooking product shipments. For any gi ven 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, 3 (2) data from DOE’s supplemental analysis to its 1996 TSD on cooking produc ts covering the period 1989–1996, 4and (3) data from the Appliance Recycling Information Center (ARIC) for the year 2004. 5 For the time periods for which no data were available, DOE either applie d the market share percentages from the above

10-6AHAM and DOE data sources or interpolated between the data from these two sources. The notes in Table 10.3.3 provide further details. Note that in Table 10.3.3, 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, LifeCycle 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 estimat e the national impacts of elimin ating pilot lights for gas cooking pilots. DOE’s method for estimating the national im pacts is discussed in detail in Chapter 10, National Impact Analysis. To estimate the futu re percentages of each product type (with the exception of gas standard ranges with standing p ilots), 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 th e five gas cooking product types for the period 2006–2042. Section 10.2.3 of Chapter 10, Natio nal Impact Analysis, discusses how DOE forecasted the market share of gas standard ranges with standing pilots.

10-7Table 10.3.3 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.

10.3.1.1 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, 3 (2) data from the 2000 AHAM Factbook for the period 1989–2002, 6 and (3) data from Appliance Magazine 7,8,9 for the period 1972–1988. b Table 10.3.4 summarizes the historical cooking product shipme nts data. DOE built up a total stock of cooking products by integrating hist orical shipments starting in the year 1972. Over time, some units are retired and, therefore, removed from stoc k, thus triggering the shipment of a new unit.

bShipments 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.

10-8Because of the relationship between retirements and total stock, there is a strong correlation between past and future shipments, i ndependent of efficiency standards. Table 10.3.4 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

10.3.1.2 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 a ddition to normal replacements, DOE’s Shipments Model for each general category also assumed th at a certain fraction of the stock would be replaced early. Total electric cooktop and oven shipments are represented by the following equation: Ship ELEC ( j ) = Rpl ELEC ( j ) + NI ELEC ( j ) + ER ELEC ( j )
where: Ship ELEC (j) = Total shipments of electric cooking products in yearj , RplELEC (j) = Replacement shipments in year j ,

10-9NI ELEC (j) = Shipments to new households in year j , and ER ELEC (j) = Early replacement shipments in year j

. Total gas cooktop and oven shipments are represented by the same basic equation: Ship GAS ( j ) = Rpl GAS ( j ) + NI GAS ( j ) + ER GAS ( j )
where: Ship GAS (j) = Total shipments of ga s cooking products in year j , Rpl GAS (j) = Replacement shipments in year j , NI GAS (j) = Shipments to new households in year j , and ER GAS (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 c onstruction, 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 ye ar, DOE multiplied the housing forecasts by the forecasted saturation of cooking pr oducts for new housing. Table 10.3.5 presents historical and forecas ted new housing starts for the Reference cast based on EIA’s AEO2009 Early Release for the period 1990–2030. 2 Because the AEO2009 Early Release does not provide High Economic Growthand Low Economic Growth case, DOE relied on the AEO2008 10 to estimate housing starts for th e High Economic Growth case and the Low Economic Growth case. DOE scaled the AEO 2008high-growth case and low-growth forecasts by the ratio of AEO 2009 Early Release and AEO 2008reference case forecasts to estimate high-growth and low-growth price tren ds. All three housing starts forecasts are presented in Table 10.3.5. 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 AEO2009 Early Release and AEO2008data are based on actual completions through the year 2005. For the Refe rence case, the forecast shows a decline in housing completions from 2.22 million in 2005 to 1.74 million by 2030. For the period 2031

− 2042, DOE froze completions at the level in the year 2030 for all three economic forecasts.

10-10Table 10.3.5 Historical and Forecasted Housing Starts (millions) Year Reference High Low Year Reference High Low 1990 1.38 1.38 1.38 2017 2.00 2.40 1.60 1991 1.18 1.18 1.18 2018 2.00 2.42 1.59 1992 1.41 1.41 1.41 2019 1.93 2.34 1.53 1993 1.54 1.54 1.54 2020 1.77 2.16 1.39 1994 1.76 1.76 1.76 2021 1.72 2.11 1.33 1995 1.69 1.69 1.69 2022 1.70 2.10 1.30 1996 1.82 1.82 1.82 2023 1.69 2.11 1.27 1997 1.49 1.49 1.49 2024 1.71 2.15 1.26 1998 1.54 1.54 1.54 2025 1.74 2.21 1.27 1999 1.64 1.64 1.64 2026 1.76 2.27 1.25 2000 1.70 1.70 1.70 2027 1.75 2.28 1.22 2001 1.72 1.72 1.72 2028 1.73 2.26 1.19 2002 1.75 1.75 1.75 2029 1.72 2.27 1.17 2003 1.79 1.79 1.79 2030 1.74 2.30 1.18 2004 1.80 1.80 1.80 2031 1.74 2.30 1.18 2005 2.22 2.22 2.22 2032 1.74 2.30 1.18 2006 1.92 1.92 1.92 2033 1.74 2.30 1.18 2007 1.75 1.75 1.75 2034 1.74 2.30 1.18 2008 1.45 1.61 1.28 2035 1.74 2.30 1.18 2009 1.49 1.70 1.28 2036 1.74 2.30 1.18 2010 1.20 1.38 1.02 2037 1.74 2.30 1.18 2011 1.56 1.82 1.31 2038 1.74 2.30 1.18 2012 1.77 2.06 1.47 2039 1.74 2.30 1.18 2013 1.90 2.23 1.56 2040 1.74 2.30 1.18 2014 1.94 2.30 1.59 2041 1.74 2.30 1.18 2015 1.99 2.39 1.59 2042 1.74 2.30 1.18 2016 2.01 2.42 1.60 Source: EIA, AEO2009 Early Release and AEO2008. Table 10.3.6 presents historical market saturations of electric c ooking products based on various sources, including AHAM’s 2005 Fact Book , 11 Appliance Magazine , 12 NFO World Group, 13 and EIA’s RECS for the years 1997 14and 2001. 15 The table presents market saturations for the overall housing stock and for new housing. Note that the overall electric 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 prev ious two sources. Because the forecast of shipments for the new housing market depends on the saturation of elect ric 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

10-11shipments analysis by first forecasting overall electric cooking product shipments and then disaggregating the total shipments using the historical market shar e data in Table 10.3.6, it used the overall saturation of electric cooking products to estimate shipments to new construction. DOE based the saturation on the sum of the va lues for ranges, built-in ovens, and built-in cooktops, which is 77.5 percent.
Table 10.3.6 Electric Cooking Products: Hi storical Market Saturations

Year 1970 1978 1982 Overall Housing New Housing AHAM* Appl** NFO*** RECS † All Elec Products

40.6%

58.0% 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

51.0%

1983

62.6%

66.3%

65.3% 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% 60.0%

61.0%

62.0% 9.4%

9.2%

9.6% 9.2%

10.1%

9.4% 26.6% 39.7%

30.1% 32.5% 8.1%

3.5% 4.0%

1.7% 6.5%

9.6% 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 10.3.7 presents historical market saturations of gas cooking products based on various sources, including AHAM’s 2005 Fact Book , 11 Appliance Magazine , 12 NFO World Group, 13 and EIA’s RECS for the years 1997 14and 2001. 15 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 range s, built-in ovens, and built-in cook tops but does not indicate which

10-12households have multiple cooking appliances. Thus , it is not possible to directly compare the saturations from NFO to the previous two source s. 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 by first forecasting overall gas cooking product sh ipments and then disaggregating the total shipments using the historical market share data in Table 10.3.7, it used the overall saturation of gas cooking products to estimate sh ipments to new construction. So as not to overstate the overall saturation, DOE based the saturation on th e sum of the values for ranges, built-in ovens, and built-in cooktops, which is 30.1 percent.
Table 10.3.7 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.

10-13Replacements. DOE determined shipments to the replacement market using an accounting method that tracks the to tal stock of units by vintage. DOE estimated stocks of electric and gas cooking products by vintage by integrating histori cal 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 stock, there is a strong correlati on between past and future shipme nts, 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 co oking product fails, DOE used a product survival function based on a lifetime distribution with anaverage value of 19 years, and minimum and maximum values of 10 years and 28 years, resp ectively. 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 Ch apter 8. Figure 10.3.1 shows the survival functions that DOE used to estimate replacement shipments.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 Age (years)Percent Surviving Electric Gas

Figure 10.3.1 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 atthe 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 fo r electric cooking products and 12 to 26 years

10-14for gas cooking products; DOE weighted these e quipment by their respec tive population in the surviving stock. The following equation illustrates the calculations:

AgeMax 1
_ ER MWO ( j ) = 

# ∑ _ Stock( j 1 ,age ) × ERRate × Stock( j

_ 1 )

_ age =4 

# ∑Stock( j 1 ,age )
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.

10.3.1.3 Base Case Shipments Figures 10.3.2 and 10.3.3 show the forecas ted shipments of electric and gas cooking products, respectively, in the basecase (i.e., the case without ne w 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 YearShipments (million) Historical Shipments Modeled Shipments

Figure 10.3.2 Electric Cooking Products: Histor ical and Base Case Shipments Forecast

10-150.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 YearShipments (million) Historical Shipments Modeled Shipments

Figure 10.3.3 Gas Cooking Products: Histori cal and Base Case Shipments Forecast

Figures 10.3.4 and 10.3.5 present forecasted base case electric and gas cooking product shipments, respectively, disaggregated into th e following market segments: shipments due to retirements, shipments to new housing, and ship ments due to early replacements. Note that replacement shipments comprised 85–92 percent of total gas and elec tric 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.

10-160.0 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 YearShipments (million)

Figure 10.3.4 Electric Cooking Products: Disaggregated Base Case Shipments Forecast

5.5 New Units Early Repl Units Normal Repl

5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0

2000 2005 2010 2015 2020 2025 2030 2035 2040 Year New Units Early Repl Units Normal ReplShipments (million)

Figure 10.3.5 Gas Cooking Products: Disaggregated Base Case Shipments Forecast

10-1710.3.2 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), DOErepresented microwave ovens as a single product class.

10.3.2.1 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 Factbooksfor the years 2000, 6 2003 16 , and 2005 11 covering the period 1989

− 2005 and (2) Appliance Magazine 7,8,9 for the period 1981

− 1988. cTable 10.3.8 summarizes the historical microwave oven shipments data.
Table 10.3.8 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.

10.3.2.2 Markets and Model Calibration The market for microwave ovens is primarily comprised of the following: replacement units for equipment that has been retired from se rvice and units for new housing. In addition to normal replacements, DOE’s Shipments Model also assumed that a certain fraction of the stock

cShipments 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.

10-18would be replaced early. Total microwave ove n shipments are represented by the following equation: Ship MWO ( j ) = Rpl MWO ( j ) + NI MWO ( j ) + ER MWO ( j )
where: Ship MWO (j) = Total shipments of microwave ovens in year j , Rpl MWO (j) = Replacement shipments in year j , NI MWO(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 c onstruction, 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 microwav e ovens for new housing.
Historical and forecasted new housing starts were presented earlier for cooking products. Refer back to Table 10.3.5 for the housing starts data. Table 10.3.9 presents historical market saturations of microwave ovens based on various sources, including AHAM’s 2005 Fact Book , 11 Appliance Magazine , 12 NFO World Group, 13 and EIA’s RECS for the years 1993, 17 1997, 14 and 2001. 15 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 mark et saturations for new housing as well as the saturations of housing wi th multiple microwave ovens. According to RECS, microwave oven saturation in new hous ing for 1993, 1997, and 2001 was 92 percent, 87.5 percent, and 93.3 percent, respectively. Ac cording to NFO, households with more than one microwave oven represented 3.7 percent, 4.9 per cent, and 4.1 percent of the housing market for the years 1990, 1996, and 2001, resp ectively. Therefore, DOE incr emented 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 y ear 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.

10-19Table 10.3.9 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 to tal stock of units by vintage. DOE estimated a stock of microwave ovens by vintage by integrating histor ical shipments starting from the year 1981. Over time, some units will be retired and re moved from the stock, thereby triggering the shipment of a replacement unit. Depending on the vi ntage, a certain percenta ge of each type of unit will fail and need to be replaced. To de termine 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 year s and 10 years, respec tively. For a more complete discussion of microwave lifetimes, refer back to section 8.2.3.2 of Chapter 8. Figure 10.3.6 shows the survival function that DOE us ed to estimate replacement shipments.

10-200% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Avge (years)Percent Surviving

Figure 10.3.6 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. Th e early replacement rate is distributed among equipment of ages ranging from four through 10 years; DOE weighted these equipment by their respective populati on in the surviving stock. The following equation illustrates the calculations:

_ AgeMax 1 Stock( j

_ 1 ,age )

_ ER MWO ( j ) = 

# ∑ × ERRate × Stock( j 1 )

_ age =4 

# ∑Stock( j 1 ,age )
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.

10-2110.3.2.3 Base Case Shipments Figure 10.3.7 shows the forecasted shipments in the base case (i.e., the case without new energy efficiency standards) and the historical sh ipments DOE used to calibrate the forecast.

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

1985 1995 2005 2015 2025 2035 2045 YearShipments (million)

Figure 10.3.7 Microwave Ovens: Historical and Base Case Shipments Forecast Figure 10.3.8 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. No te 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 ove n market is fairly mature. Historical Shipments modelled Shipments

10-220.0 5.0 10.0 15.0 20.0 25.0

2000 2005 2010 2015 2020 2025 2030 2035 2040 YearShipments (million units) New Units Early Repl Normal Repl

Figure 10.3.8 Microwave Ovens: Disaggregated Base Case Shipments Forecast

10.4 PURCHASE PRICE, OPERATING COST, AND HOUSEHOLD INCOME IMPACTS DOE conducted a literature review and an analysis of appliance pri ce 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 10A 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, su ch that rising incomes increase the demand for appliances. Finally, the literature suggests that consumers us e relatively high implicit discount rates dwhen comparing appliance prices and appliance operating costs. DOE did not find enough equipment purchase price and operating cost data to perform a complex analysis of dynamic changes in the appl iance market. Rather, it used purchase price

d 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.

10-23and efficiency data specific to residential refrig erators, clothes washers, and dishwashers over the period 1980–2002 to evaluate broad market trends and conduct simple regression analyses. These data indicate that there ha s been a rise in appliance ship ments and a decline in appliance purchase price and operating costs over the time pe riod. Household income has also risen during this time. To simplify the analysis, DOE combin ed the available economic information into one variable, termed the relative price , and used this variable in an an alysis 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 relative ly inelastic (i.e., under 1.0). DOE’s regression analysis suggests that the relative price elasticity of demand, averaged over th e 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. Neve rtheless, 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, operati ng 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 reason able 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 need ed 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 appliances, to indicate how short-run and long-run pr ice elasticities differ. Therefore, to estimate how the relative price elasticity changes over time, DOE relied on a study pertaining to

10-24automobiles. 18 This study shows that the automobile price elasticity of demand changes in the years following a purchase price change. With in creasing 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 10.4.1 shows the re lative change in the price elasticity of demand for automobiles over time. As shown in the table, DOE devel oped 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 10.4.1 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 1 styear 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.

_ Ship STD _ p ( j ) = 

# ( Rpl BASE _ p ( j ) + NI BASE _ p ( j ) + M BASE _ p ( j ) 

# ) × 

# ( 1 e RP ( j ) × Δ RP( j ) 

# )

where: Ship STD_p (j) = Total shipments under the standards case of product p in year j , Rpl BASE_p (j) = Units of product p under the base case retire d and replaced in year j , NI BASE_p (j) = Number of new construction instal lations under the base case of product p in year j , M BASE_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),
e RP (j)= Relative price elasticity in year j(equals -0.34 for year 1), and ΔRP(j)= Change in relative price due to a standard level in year j

.

10.5 AFFECTED STOCK The affected stock is the in-s ervice stock of the appliance or product that is affected by a TSL. In addition to the forecas t of product shipments under both the base case and the standards case, the affected stock (which represents the di fference in the appliance stock for the base case and the standards case) is a key output of DOE ’s Shipments Models. The affected stock quantifies the impact that new product shipments have on the appliance stock due to a TSL. 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:

10-25_ j Std _ yr Aff Stock ( j ) = Ship ( j ) + 

## ∑Stock ( age ) p p p =1 age where: Aff Stock p (j) = Affected stock of units of product p of all vintages that are operational in year j , Ship p (j) = Shipments of product p in year j , Stock p (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 calculat e the affected stock, DOE must define the effective date of the standard. For the NES and NPV results presented in Chapter 11, DOE assumed that new energy efficien cy standards will become effectiv e in the year 2012. Thus, all appliances purchased starting on the first day of the year 2012 are affected by the standard level.

10.6 RESULTS The following sections show the shipments forecasts for the various TSLs that DOE considered for each of the products. The TSLs are identified and described in Chapter 9.

10.6.1 Cooktops and Ovens Because the combined market of electric and gas cooki ng products is completely saturated, DOE assumed that all electric and gas cooking product TSLs 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 co oking products does not incorporate the use of relative price elasticities. As a result, forecasted shipments for all cooking product TSLs are equivalent to the base case shipments forecasts . Refer back to Figures 10.3.2 and 10.3.3 to review the base case shipments forecasts for el ectric and gas cooking products, respectively.

10.6.2 Microwave Ovens Tables 10.6.1 and 10.6.2 show the cumulative shipments impacts over the period 2012– 2042 caused by each of the TSLs considered fo r microwave ovens. Table 10.6.1 shows the results for the four energy factor (EF) TSLs while Table 10.6.2 shows the results for the four standby power TSLs. For all TSLs, shipments ar e forecasted to decrease—the effects from the increase in product purchase prices offset the eff ects from decreased operating costs, resulting in a net decrease in shipments. Figure 10.6.1 comp ares the shipments forecasts for the base case and the four EF TSLs. Figure 10.6.2 compares th e shipments forecasts for the base case and four standby power TSLs. In Figures 10.6.1 and 10.6. 2, the difference between the base case and

10-262 0 0 8 2010 2012 2 0

1 4 2 0

1 6 2018 2020 2022 2024 2026 2 0 2 8 2 0 3 0 2 0 3 2 2034 2036 2 0 3 8 2040 2042 TSL shipments forecasts depicts the annual shipments reductions caused by the TSLs. As can be seen in Figure 10.6.1, the decrease in forecasted shipments is significant for all four EF TSLs. In Figure 10.6.2, only TSL 4b is shown as the annual shipments forecasts for TSLs 1b through 3b are not dramatically different than the base case.
Table 10.6.1 Microwave Ovens: Cumulative Shipments Impacts Caused by EF Standards over the Period 2012–2042 TSL Energy Factor Cumulative Impacts (million)

1 0.586 -11.11 2 0.588 -22.81 3 0.597 -40.86 4 0.602 -63.24

13 14 15 16 17 18 19 20 21 22Shipments (million) Base Case Std Level 1 Std Level 2 Std Level 3 Std Level 4

Year Figure 10.6.1 Microwave Ovens: Base Case and TSL Shipments Forecasts for EF Standard Levels

10-27REFERENCES

1 U.S. Department of Energy-Office of Energy Efficiency and Renewable Energy. Technical Support Document: Energy Efficiency Program for Consumer Products and Commercial and Industrial Equipment: Residential Dishwa shers, Dehumidifiers, Cooking Products, and Commercial Clothes Washers , September, 2008. Washington, DC. < http://www1.eere.energy.gov/buildings/appliance_ standards/residential/home_appl_tsd.html >

2 U.S. Department of Energy-En ergy Information Administration. Annual Energy Outlook 2009 Early Release , December, 2008. Washington, DC. < http://www.eia.doe.gov/oiaf/aeo/>

3 Association of Home App liance Manufacturers. AHAM Data on Cooking Products for Efficiency Standards Rulemaking , August 23, 2006. Letter to Building Technologies Program, U.S. Department of Energy.

4 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/applianc e_standards/residential/pdfs/chap3_sup.pdf >

5 Appliance Recycling Information Center. INFOBulletin #8, Applications in Appliances , March 2005. Washington, DC. < http://www.aham.org/industry/ht/a ction/GetDocumentAction/id/5370 >

6 Association of Home App liance Manufacturers. AHAM 2000 Fact Book , 2000. Washington, DC.

7 Statistical Review. Appliance Magazine , April, 1993.

8 Statistical Review. Appliance Magazine , April, 1990.

9 Statistical Review. Appliance Magazine , April, 1982.

10 U.S. Department of Energy- Energy Information Administration. Annual Energy Outlook 2007 with Projections to 2030 , February, 2008. Washingt on, DC. DOE/EIA-0383(2008).

11 Association of Home App liance Manufacturers. AHAM 2005 Fact Book , 2005. Washington, DC.

12 The Saturation Picture. Appliance Magazine , September, 1993, 1995, 2004, 2005.

13 NFO World Group. Final Report: Home Appliance Saturation and Length of First Ownership Study , May, 2001. Prepared for Associati on of Home Appliance Manufacturers by NFO World Group, Boston, MA.

10-2814 U.S. Department of Energy-En ergy Information Administration. Residential Energy Consumption Survey, 1997 Public Use Data Files , 1997. Washington, DC. < http ://www.eia.doe.gov/emeu/recs/public.html >

15 U.S. Department of Energy-En ergy Information Administration. Residential Energy Consumption Survey, 2001 Public Use Data Files , 2001. Washington, DC. < http ://www.eia.doe.gov/emeu/recs/recs2001/publicuse2001.html >

16 Association of Home Ap pliance Manufacturers. AHAM 2003 Fact Book , 2003. Washington, DC.

17 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 >

18 S. Hymans. Consumer Durable Sp ending: Explanation and Prediction, Brookings Papers on Economic Activity , 1971. Vol. 1971, No. 1, pp. 234-239.

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