9-i

CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

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

9.1.1 Definition of Market Segments for the Shipments Analysis........................................... 9-1

9.1.2 Fundamental Model Equations........................................................................................ 9-4

9.2 DATA INPUTS AND SUPPORTING CALCULATIONS ............................................ 9-5

9.2.1 Historical Shipments and the Calculation of Replacement Shipments............................ 9-5

9.2.1.1 Historical Shipments...................................................................................... 9-5

9.2.1.2 Calculation of Replacement Shipments......................................................... 9-9

9.2.2 Shipments to New Construction .................................................................................... 9-10

9.2.2.1 Central Air Conditioners and Heat Pumps................................................... 9-11

9.2.2.2 Furnaces....................................................................................................... 9-13

9.2.3 Model Calibration and New Owners ............................................................................. 9-13

9.2.3.1 Central Air Conditioners and Heat Pumps................................................... 9-14

9.2.3.2 Furnaces....................................................................................................... 9-15

9.3 DECISION MODEL FOR REPLACEMENTS AND EQUIPMENT 

SWITCHING ................................................................................................................. 9-15

9.3.1 Decision Model for Replacements................................................................................. 9-15

9.3.1.1 Purchase Price Elasticity.............................................................................. 9-16

9.3.1.2 Impact from Increase in Relative Price........................................................ 9-17

9.3.1.3 Replacement Shipment Impacts................................................................... 9-18

9.3.2 Equipment Switching..................................................................................................... 9-19

9.3.2.1 Split System Heat Pumps: Switch to Combination Split System 

Central Air Conditioner and Electric Furnace ............................................. 9-19

9.3.2.2 Gas Furnace Equipment Switching.............................................................. 9-20

9.3.2.3 Other Equipment Switching......................................................................... 9-20

9.4 REGIONAL SHIPMENTS MODEL............................................................................. 9-20

9.4.1 Central Air Conditioners and Heat Pumps..................................................................... 9-21

9.4.1.1 Allocation of Historical Shipments to Regions ........................................... 9-21

9.4.1.2 Regional New Construction and New Construction Saturations................. 9-25

9.4.2 Furnaces......................................................................................................................... 9-29

9.4.2.1 Allocation of Historical Shipments to Regions ........................................... 9-29

9.4.2.2 Regional New Construction and New Construction Saturations................. 9-30

9.5 RESULTS ...................................................................................................................... 9-33

9.5.1 Base Case Shipments..................................................................................................... 9-33

9.5.1.1 Central Air Conditioners.............................................................................. 9-33

9.5.1.2 Heat Pumps.................................................................................................. 9-35

9.5.1.3 Furnaces....................................................................................................... 9-36

9.5.2 Shipments Impacts due to Standards ............................................................................. 9-38

`
9-ii

LIST OF TABLES

Table 9.1.1 Central Air Conditioner, Heat Pump and Furnace Product Classes .................... 9-2

Table 9.1.2 Stock Categories, Input Data, Decisions, and Resulting Actions used in the 

Shipments Model ................................................................................................. 9-3

Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments*......................... 9-7

Table 9.2.2 Furnace Historical Shipments.............................................................................. 9-9

Table 9.2.3 Historical New Owner Market Shares of Central Air Conditioner and Heat 

Pump Equipment................................................................................................ 9-15

Table 9.3.1 Change in Relative Price Elasticity following a Purchase Price Change .......... 9-17

Table 9.4.1 CAC Residential Regional Stock Saturations.................................................... 9-21

Table 9.4.2 HP Residential Regional Stock Saturations....................................................... 9-22

Table 9.4.3 CAC Shipment Regional Allocation Factors..................................................... 9-22

Table 9.4.4 HP Shipment Regional Allocation Factors........................................................ 9-22

Table 9.4.5 Central Air Conditioner and Heat Pump Regional Shipment Market 

Shares*............................................................................................................... 9-23

Table 9.4.6 CAC Shipment Regional Allocation Factors by Product Class......................... 9-23

Table 9.4.7 HP Shipment Regional Allocation Factors by Product Class............................ 9-24

Table 9.4.8 Population Projected for 2020 for Areas defined by the Overlap of Census 

Divisions with Climate Regions ........................................................................ 9-26

Table 9.4.9 Furnace Regional Shipment Market Shares*..................................................... 9-30

Table 9.5.1 Trial Standard Levels for Central Air Conditioners and Heat Pumps and 

Furnaces (Energy Efficiency) ............................................................................ 9-39

Table 9.5.2 Base Case Cumulative Shipments and Shipments Impacts due to TSLs........... 9-40

LIST OF FIGURES

Figure 9.2.1 Central Air Conditioner and Heat Pump Saturations in Residential New 

Construction....................................................................................................... 9-11

Figure 9.2.2 Central Air Conditioner and Heat Pump Saturation in Commercial New 

Construction....................................................................................................... 9-12

Figure 9.2.3 Furnace Saturations in Residential New Construction ...................................... 9-13

Figure 9.4.1 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: 

American Housing Survey (AHS) vs. Shipments Model (Calculated).............. 9-25

Figure 9.4.2 Central Air Conditioner National and Regional Saturations in Residential 

New Construction .............................................................................................. 9-27

Figure 9.4.3 Heat Pump National and Regional Saturations in Residential New 

Construction....................................................................................................... 9-28

Figure 9.4.4 Central Air Conditioner and Heat Pump National and Regional Saturations 

in Commercial New Construction ..................................................................... 9-29

Figure 9.4.5 Non-Weatherized Gas Furnace National and Regional Saturations in 

Residential New Construction ........................................................................... 9-31

Figure 9.4.6 Mobile Home Gas National and Regional Saturations in Residential New 

Construction....................................................................................................... 9-32
9-iii

Figure 9.4.7 Oil Furnace National and Regional Saturations in Residential New 

Construction....................................................................................................... 9-32

Figure 9.5.1 Central Air Conditioners: Base Case Shipments by Product Class and 

Product Type...................................................................................................... 9-33

Figure 9.5.2 Central Air Conditioners: Base Case Shipments by Product Channel ............. 9-34

Figure 9.5.3 Central Air Conditioners: Base Case Shipments by Region............................. 9-34

Figure 9.5.4 Heat Pumps: Base Case Shipments by Product Class ....................................... 9-35

Figure 9.5.5 Heat Pumps: Base Case Shipments by Product Channel................................... 9-35

Figure 9.5.6 Heat Pumps: Base Case Shipments by Region.................................................. 9-36

Figure 9.5.7 Furnaces: Base Case Shipments by Product Class ............................................ 9-36

Figure 9.5.8 Furnaces: Base Case Shipments by Product Channel........................................ 9-37

Figure 9.5.9 Furnaces: Base Case Shipments by Region....................................................... 9-37
9-1

CHAPTER 9. SHIPMENTS ANALYSIS

9.1 INTRODUCTION

Estimates of future product shipments are a necessary input to calculations of the national 

energy savings (NES) and net present value (NPV), as well as to the manufacturer impact 

analysis (MIA). This chapter describes the data and methods the U.S. Department of Energy 

(DOE) used to forecast annual product shipments, and presents results for each of the central air 

conditioner (CAC), heat pump (HP), and furnace product classes being considered in this 

analysis. The shipments model divides the population of appliance users into specific market 

segments and estimates the shipment of new equipment to each of these segments under each 

candidate standard level (CSL). The model starts from a historical base year and calculates, for 

each year of the analysis period, both shipments and retirements by market segment. This 

approach produces an estimate of the total equipment stock, broken down by age or vintage, in 

each year of the analysis period. The product stock distribution is calculated for the base case 

and for each efficiency level for each product class. The stock distribution is used in the national 

impact analysis (NIA) to estimate the total dollar and energy costs and benefits associated with 

each efficiency level.

The shipments model was developed as a Microsoft Excel spreadsheet that is accessible 

on DOE’s Appliance and Commercial Equipment Standards website 

(http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp.html). 

Appendix 10-A discusses how to access and utilize the shipments model spreadsheet, which is

integrated into the spreadsheet for the National Impact Analysis (NIA). This chapter explains 

how the shipments model is constructed and provides some summary output. The rest of section 

9.1 describes the methodological approach. The analysis incorporates a large number of 

components or market segments, describing different product classes, market sectors and 

geographic regions; for simplicity, the methodology is explained for a single product class for 

residential consumers for the country as a whole. Section 9.2 defines the input data, preprocessing and calibration steps that are used in the model. Section 9.3 defines the decision 

models used to differentiate between the base case and efficiency levels. Section 9.4 presents the 

modifications to the input data that were used to develop shipments models specific to the 

regions used in the analysis: hot-humid, hot-dry and rest-of-country for central air conditioners 

and heat pumps and North and South regions for furnaces. Although regional standards were not 

considered for single package central air conditioners and heat pumps, the shipments models 

which were developed still analyzed this equipment on a regional basis in order to properly track 

shipments to the different regions of the country. Section 9.5 presents summary output from the 

shipments model for the base cases. 

9.1.1 Definition of Market Segments for the Shipments Analysis 

The shipments model disaggregates the total stock according to the following 

characteristics:
9-2

1. Product class: there are two central air conditioner product classes, two heat pump

product classes and three furnace product classes as summarized in Table 9.1.1. DOE 

further disaggregated the split system central air conditioner product class into two unit 

types: coil-only and blower coil units. Although not considered as separate product 

classes, DOE structured the shipments model to analyze both split central air conditioner

coil-only and split central air conditioner blower coil systems separately. 

2. Market sector: For central air conditioners and heat pumps, residential and commercial

building sectors; approximately 93 percent of shipments are to the residential sector with 

the balance going to the commercial sector.1 This ratio is held constant over the analysis 

period. For furnaces, 100 percent of shipments are to the residential sector. 

3. Repair status: this is defined as default (i.e., normal repairs and maintenance as accounted 

for in the lifetime of the equipment) or extended repair (ER). The shipments model 

allows for the price increase associated with a CSL to influence the consumer decision to 

repair, rather than replace, broken equipment. The extended repair stock category 

represents equipment that has been repaired after failure. This component of the stock is 

accounted for separately because it is further assumed that equipment that has undergone 

one extended repair will last another six years and then be replaced. This category is 

referred to as extended repair because it models major equipment failures; minor repairs 

are accounted for in the annual maintenance costs and determination of equipment 

lifetimes.

Table 9.1.1 Central Air Conditioner, Heat Pump and Furnace Product Classes

Product Type Product Class Unit Type

Central Air Conditioner (CAC) Split System Coil-OnlyBlower Coil

Single Package NA

Heat Pump (HP) Split System NA

Single Package NA

Furnaces

Non-Weatherized Gas Furnaces NA

Mobile Home Furnaces NA

Oil Furnaces NA

Each market sector (i.e., residential and commercial) is further disaggregated into three 

product placement channels (hereafter referred to as “channels”) as follows:

1. New construction: a certain fraction of new buildings are assumed to acquire central air 

conditioners, heat pumps, and furnaces in the year of construction. This fraction is

defined as the new construction saturation, which varies by year, by region, and by

product type.

2. Existing owners: these are defined as existing buildings with central air conditioner, heat 

pump, and furnaces installed. This category receives new shipments when existing 

equipment is replaced.
9-3

3. New owners: these are defined as existing buildings that acquire central air conditioner, 

heat pump, and furnaces for the first time during the analysis period. The fraction of new 

owners is estimated from trends in overall market saturation. As described later in this 

chapter, the new owner channel is necessary for calibrating the shipments model to 

historical shipments.

These three channels are treated differently in the way that the consumer decision is 

modeled. For new construction, the placement of equipment is automatic, in line with observed 

trends in the data. For new owners, DOE also estimated the placement of equipment is 

automatic. For existing owners, the repair versus replace decision is affected by the change in 

ownership cost associated with higher efficiency. In those cases where existing owners have 

been modeled as being affected by higher ownership costs, DOE assumed they would perform an 

extended repair which prolongs the life of the equipment by six years, after which the equipment 

would be replaced. The three channels and related decisions modeled in the spreadsheet are 

summarized in Table 9.1.2.

Table 9.1.2 Stock Categories, Input Data, Decisions, and Resulting Actions used in the 

Shipments Model

Category Input data Decision Action

Equipment Stock 

= 

+ new 

construction

nc_starts (year) buy => add to equip_stock, age=0 nc_saturation(year)

- demolitions housing demolitions(year) remove => subtract from equip_stock Equip_stock(age, year)

+ existing owners

Equip_stock(age, year) does not break => stays in equip_stock; increment 

age

survival_function(age) breaks: replace => add to equip_stock, age=0

Repair_probability(year) breaks: repair => convert to ER_equip_stock, 

a2=0

Extended Repair ER_equip_stock(year,a2)

a2 < 6 years => stays in ER_equip_stock; 

increment a2

a2=6 years, replace 

=> add to equip_stock, age=0

New owners

(no CAC, HP, or 

Furnaces)

housing_stock(year) buy => add to equip_stock, age=0 Equip_stock(age, year)

max_saturation(year) do not buy => stays in no cooling stock purchase_probability(year)

One decision not reflected in Table 9.1.2 is the potential equipment switching for split 

system heat pump consumers to combination split system central air conditioning and electric 

furnace systems. DOE specifically modeled such equipment switching because of the potential 
9-4

of high efficiency standards for heat pumps to drive consumers into using more energy intensive 

electric-resistance heating systems. Equipment switching is discussed in section 9.3.3.

9.1.2 Fundamental Model Equations

The fundamental dependent variable in the shipments model is the equipment stock 

which is represented as a function of analysis year (indexed by j), and equipment vintage or age 

(the equipment age is noted as a, and is equal to the analysis year minus the vintage). The stock 

function is adjusted in each year of the analysis period by new shipments coming in and broken 

or demolished equipment being taken out.

For existing stock:

Stock (j,a) Stock (j ,a ) Rem (j,a) p = p − − − p 1 1

and for new units:

Stock (j,a ) Ship (j ). p p = 1 = − 1

Where: 

Stockp (j, a) = number of units of product class p and age a in analysis year j,

Remp (j, a) = number of units of product class p and age a removed in analysis year j, 

and

Shipp(j) = number of units of product class p shipped in year j.

Shipments are directed to one of the three channels:

Ship (j) Rpl (j) NC (j) NO (j) p = p + p + p

Where:

Rplp(j) = number of units of product p replaced in year j; it depends on removals,

NCp(j) = number of units installed in new construction of product p in year j, and

NOp(j) = number of units shipped to “new owners” of product p in year j.

Removals due to equipment breakage contains two terms. In the first, a survival function 

fp(a) is used to represent the probability that a unit of age a will survive in a given year; 

equivalently the probability that this unit will fail is 1- fp(a). The second term is the extended 

repair stock that has been in use for six years following the repair date. Total removals in the 

base case are then:

Rem (j,a) = [1 − f (a)]× Stock (j,a)+ ER _Stock (j,a2 = 6) p p p p
9-5

Where:

a2 = number of years since the equipment was repaired, and

ER_Stockp(j, a2) = number of extended-repair units of product p replaced in year j.

The new construction and new owner markets depend on changes to the building stock, 

which is included as a component of the shipments model. This is discussed in the next section. 

9.2 DATA INPUTS AND SUPPORTING CALCULATIONS

Data inputs and supporting calculations that are necessary for the shipments model are 

explained in detail in the following sections. Data inputs are discussed separately for central air 

conditioner and heat pump and furnaces. 

9.2.1 Historical Shipments and the Calculation of Replacement Shipments

9.2.1.1 Historical Shipments

Central Air Conditioners and Heat Pumps

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

shipments model for central air conditioner and heat pump equipment. As part of its data 

submittal to the DOE standards rulemaking, the Air-Conditioning, Heating, and Refrigeration 

Institute (AHRI) provided historical shipments data over 1990-2009 disaggregated into the four 

primary product classes.2 Historical shipments from 1972-1989 were also provided by AHRI 

from previous data submittals to the Lawrence Berkeley National Laboratory (LBNL).3

 The data 

for 1972-1989 included some shipments of 3-phase as well as single-phase central air 

conditioner and heat pump, whereas the data for 1990-2009 included only single-phase central 

air conditioner. DOE disaggregated the shipments for single-phase and 3-phase central air 

conditioner and heat pump equipment in the earlier data and included only single phase units in 

the analysis.

DOE further broke down split system central air conditioner historical shipments into 

coil-only and blower coil unit shipments. Because DOE believes that a majority of split central 

air conditioner shipments are coil-only units, it estimated that coil-only units account for 90 

percent of annual split system shipments.

As discussed earlier in section 9.1.1, DOE divided all historical shipments for all product 

classes into two market segments, i.e., the residential and commercial building sectors. DOE 

allocated 93 percent of historical shipments to the residential building sector and the remaining 

seven percent to the commercial building sector. 

0 summarizes the historical shipments data. DOE developed a total stock estimate for 

each product class and market segment by integrating historical shipments. Over time, units are 

retired and removed from the stock based on a survival function as discussed in section 9.1.1, 
9-6

triggering the purchase 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 

conservation standards.
9-7

Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments*

Year

Split CAC** Single Package CAC Split HP Single Package HP

thousands thousands thousands thousands

1972 1,489 257 28 52

1973 1,742 318 35 52

1974 1,503 289 49 48

1975 888 159 83 45

1976 1,219 231 177 74

1977 1,364 218 329 89

1978 1,546 253 389 97

1979 1,428 248 376 107

1980 1,233 134 293 61

1981 1,293 122 348 66

1982 1,037 111 267 49

1983 1,558 192 455 82

1984 1,857 189 535 98

1985 1,784 203 619 107

1986 1,876 203 680 106

1987 2,204 237 714 103

1988 2,334 247 649 91

1989 2,516 267 650 91

1990 2,241 334 643 104

1991 2,388 306 615 96

1992 2,254 330 647 101

1993 2,474 346 718 107

1994 3,087 387 825 118

1995 3,221 384 834 120

1996 3,635 418 936 139

1997 3,364 395 917 142

1998 4,010 406 1,019 148

1999 4,317 429 1,044 147

2000 4,280 437 1,073 159

2001 3,931 361 1,180 165

2002 4,381 380 1,229 165

2003 4,281 390 1,350 174

2004 4,561 414 1,584 190

2005 5,461 455 1,810 213

2006 4,038 330 1,807 190

2007 3,582 338 1,570 199

2008 3,171 274 1,566 189

2009 2,887 234 1,389 162

Source: AHRI

* For each product class, 93 percent of annual shipments are allocated to the residential building sector and the 

remaining seven percent are allocated to the commercial building sector.

**Annual split central air conditioner shipments are disaggregated into coil-only and blower coil unit shipments. 

Coil-only unit shipments estimated to comprise 90 percent of annual split central air conditioner shipments.

Furnaces
9-8

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

shipments model for furnace equipment. As part of its data submittal to the DOE standards 

rulemaking, the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) provided 

historical shipments data over the 1988-2009 time-period disaggregated into two categories: (1) 

the non-weatherized gas and mobile home gas furnaces and (2) oil furnaces.2 Historical 

shipments from 1972-1988 were also provided by the Gas Appliance Manufacturers Association 

(GAMA) from previous data submittals to the Lawrence Berkeley National Laboratory (LBNL).4 

For non-weatherized gas and mobile home gas furnaces, DOE disaggregated mobile home gas 

furnace shipments from the gas furnace total by using a combination of data from U.S. Census5

and American Housing Survey (AHS).6

Table 9.1.2 summarizes the historical shipments data. DOE developed a total stock 

estimate for each product class and market segment by integrating historical shipments. Over 

time, units are retired and removed from the stock based on a survival function as discussed in 

section 9.1.1, triggering the purchase 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 conservation standards.
9-9

Table 9.2.2 Furnace Historical Shipments

Year

Non-weatherized Gas Mobile Home Gas Oil-fired

thousands thousands thousands

1972 1,855 211 311

1973 1,504 215 328

1974 1,337 139 209

1975 1,085 101 213

1976 1,439 115 236

1977 1,384 124 228

1978 1,506 130 263

1979 1,730 133 158

1980 1,328 118 64

1981 1,291 126 81

1982 1,028 128 104

1983 1,513 149 127

1984 1,698 151 148

1985 1,673 150 147

1986 1,966 139 201

1987 1,936 137 206

1988 1,958 134 204

1989 2,033 129 179

1990 1,823 127 138

1991 1,934 123 131

1992 1,969 137 141

1993 2,431 153 149

1994 2,526 171 164

1995 2,419 182 135

1996 2,683 188 152

1997 2,593 186 124

1998 2,785 192 128

1999 2,937 189 125

2000 2,940 164 121

2001 2,915 148 123

2002 3,060 142 117

2003 3,134 131 127

2004 3,388 131 130

2005 3,378 134 111

2006 3,071 125 93

2007 2,665 117 84

2008 2,169 111 59

2009 2,073 101 56

Source: AHRI

9.2.1.2 Calculation of Replacement Shipments

When an equipment unit is broken, it is removed from the stock. The following

retirement function rp(a) is used to represent the probability that a unit will be broken at age a.
9-10

Re m (j) r (a) Stock (j,a) p a p = ∑ a ×

Retirement functions and product lifetimes are discussed in more detail in Chapter 8. The 

average lifetimes are 19.5 years for split and single package central air conditioner equipment, 

16.7 years for split and single package heat pumps, 24.0 years for non-weatherized gas furnaces, 

19.1 years for mobile home gas furnaces, and 27.0 years for oil furnaces.

In each year, equipment are removed with demolished buildings. As represented by the 

following expression, the shipments model assumes that the saturation of the equipment in the 

demolished buildings is the same of that of the overall population.

D(j) = H _ Stock(j −1)+ H _ Starts(j)− H _ Stock(j)

Dem( j) = D( j)× sat(p, j −1)

Where: 

H_Stock (j) = number of housing units in analysis year j,

H_Starts(j) = number of new housing units in year j,

D(j) = number of demolished buildings, and

Dem (j) = number of equipment units demolished in analysis year j.

sat(p,j) = saturation of equipment of product class p for all buildings in year j

The shipments model assumes that units that are going away with demolished buildings, 

Dem(j), are included in the mix of broken units Remp (j). Since the demolished units do not need 

to be replaced, they are deducted from Remp(j) when calculating the required replacements, as 

represented by the following expression.

Rpl (j) Re m (j) Dem(j) p = p −

9.2.2 Shipments to New Construction

DOE multiplied new construction market saturations by forecasts of new construction to 

estimate central air conditioner and heat pump shipments to the new construction channel. On a 

product class basis, the determination of shipments to new construction is represented by the 

following expression:

NC (j) NC _ Starts(j) NC _ Sat (j) p = ×

p

Where: 

NC_Starts (j) = number of new construction starts in year j, and

NC_Sat(j) = new construction saturation for product class p and year j.
9-11

9.2.2.1 Central Air Conditioners and Heat Pumps

For the residential market segment, DOE developed new construction market saturations 

from Characteristics of New Housing data from the U.S. Census Bureau.7

Figure 9.2.1

 Central air 

conditioner and heat pump historical and projected saturations are depicted in . DOE 

used historical new construction saturations for all central air conditioner and heat pump

equipment to project future saturations. As evidenced in Figure 9.2.1, DOE used a logistic fit to 

the historical data to estimate future saturations. DOE used product class market shares based on 

historical shipments (as shown in 0) to calculate specific market saturations for each central air 

conditioner and heat pump product class.

Figure 9.2.1 Central Air Conditioner and Heat Pump Saturations in Residential New 

Construction

DOE determined new construction starts to the residential market segment, otherwise 

referred to as housing starts, by using recorded data through 2008 and projections from the DOEEnergy Information Administration (EIA)’s Annual Energy Outlook 2010 (AEO2010) for the 

period 2010–2035.

8

 New housing includes newly constructed single- and multi-family units, 

termed “new housing completions,” and mobile home placements. AEO2010 provides three sets 

of economic growth scenarios: a Reference case, a High Economic Growth case, and a Low 

Economic Growth case. For 2036−2045, DOE froze completions at the 2035 level for all three 

economic scenarios.

Saturation = 0.10Ln(Year-1977) + 0.52

R2 = 0.94

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70

Year - 1977

Residential New Consturciton Saturaitons

CAC + HP

HP

CAC
9-12

For the commercial market segment, DOE developed new construction market 

saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS).9

 

Past CBECS surveys for the years 1992, 1995, 1999, and 2003 provided the saturation of 

residential-type central air conditioners in all new commercial buildings by Census Division. To 

determine nationally representative saturation values, DOE calculated a weighted-average 

saturation based on historical construction commercial starts by Census Division (in millions of 

square feet) from AEO2010. DOE considered residential-type central air conditioners to 

comprise all split system and single package central air conditioner and heat pump equipment. 

DOE used product class market shares based on historical shipments to calculate specific market 

saturations for each central air conditioner and heat pump product class. Figure 9.2.2 depicts the 

new construction saturations for the commercial market segment. Actual data from CBECS are 

shown as “black diamonds” in Figure 9.2.2. Saturations prior to 1992 were fixed by DOE to the 

1992 value. DOE used linear interpolation to develop the saturations for non-CBECS years 

between 1992 and 2003. DOE averaged the saturations for the four CBECS years to forecast 

saturation values after the year 2003.

Figure 9.2.2 Central Air Conditioner and Heat Pump Saturation in 

Commercial New Construction 

As with the residential market segment, DOE determined new construction starts to the 

commercial building market segment by using recorded data through 2008 and projections from 

EIA’s AEO2010 for the period 2010–2035. For 2036−2045, DOE froze completions at the 2035

level for all three economic scenarios. DOE used the same data sources that were used for the 

residential market to estimate new construction starts for a Reference case, a High Economic 

Growth case, and a Low Economic Growth case. 

0%

1%

2%

3%

4%

5%

6%

1990 1995 2000 2005 2010 2015 2020 2025 2030

Year

Saturation (percent sq.ft. cooled 

by CAC and HP)

Sources: DOE-EIA, CBECS; AEO2009
9-13

9.2.2.2 Furnaces

For the residential market segment, DOE developed new construction market saturations 

from Characteristics of New Housing data from the U.S. Census Bureau. Furnace historical and 

projected saturations are depicted in Figure 9.2.3. DOE used historical new construction 

saturations for each furnace product class to project future saturations for each class. Unlike 

central air conditioners and heat pumps, furnace saturations have been relatively unstable. As a 

result, DOE used a ten-year average from 2000-2009 to estimate future saturations for nonweatherized gas (43.9%) and mobile home gas furnaces (30.7%), and a five-year average from 

2005-2009 to estimate future saturations for oil furnaces (0.4%).

Figure 9.2.3 Furnace Saturations in Residential New Construction

DOE determined new construction starts to the residential market segment, otherwise 

referred to as housing starts, by using recorded data through 2008 and projections from the DOEEnergy Information Administration (EIA)’s Annual Energy Outlook 2010 (AEO2010) for the 

period 2010–2035.8

 

9.2.3 Model Calibration and New Owners 

The shipments model begins with an estimate of the building stock and equipment stock 

in the base year, and steps forward adding shipments each year and removing retirements. In 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

Residential New Construction Saturations

Non-Weatherized Gas

Mobile Home Gas

Oil
9-14

principle, only building and market saturation data are needed to allow the shipments model to 

estimate shipments to new construction and replacements. The third product channel, new 

owners, is more difficult to describe based on existing data. 

9.2.3.1 Central Air Conditioners and Heat Pumps

For central air conditioners and heat pumps, the historical shipments data (as described 

above in section 9.2.1.1) can be used to calibrate the shipments model and improve the 

representation of the new owner market. 

To calibrate estimated shipments with the historical data, as represented by the following 

expression, DOE treated the new owner market NOp(j) as a residual after shipments for new 

construction and replacements were subtracted from total shipments.

NO (j) Ship (j) Rpl (j) NC (j) p = p − p − p

The three terms on the left are known quantities (calculation of Rplp(j) and NCp(j) are 

described above).

The results of the historical calibration are shown in Table 9.2.3. The values are 

historical market shares of total central air conditioner and heat pump equipment in the new 

owner channel. The residential market share is the total central air conditioner and heat pump

shipments to the new owner housing market divided by the number of households without either 

central air conditioners or heat pumps. The commercial market share is the number of total 

central air conditioner and heat pump shipments to the new owner commercial building market 

divided by the commercial building stock not conditioned by central air conditioner and heat 

pump equipment. DOE determined the commercial building stock not conditioned by central air 

conditioner and heat pump equipment by dividing the total stock in square feet by 500 square 

feet (i.e., the amount of square feet conditioned by one piece of central air conditioner and heat 

pump equipment). DOE used product class market shares based on historical shipments (as 

shown in 0) to calculate specific new owner market saturations for each central air conditioner

and heat pump product class.
9-15

Table 9.2.3 Historical New Owner Market Shares of Central Air Conditioner and Heat 

Pump Equipment

Year Residential Commercial

1990 2.05% 0.10%

1991 1.78% 0.09%

1992 1.35% 0.08%

1993 1.59% 0.07%

1994 2.25% 0.07%

1995 2.43% 0.06%

1996 3.22% 0.11%

1997 2.53% 0.10%

1998 3.34% 0.15%

1999 3.82% 0.19%

2000 4.04% 0.16%

2001 3.31% 0.12%

2002 4.10% 0.12%

2003 3.93% 0.09%

2004 4.81% 0.14%

2005 7.75% 0.15%

2006 3.51% 0.07%

2007 1.94% 0.02%

To forecast future shipments to the new owner market, DOE calculated the average 

market share over the 1990 to 2007 time-period for the residential and commercial markets, 

3.21% and 0.10%, respectively, and held the market share fixed from 2008-2045. 

9.2.3.2 Furnaces

For furnaces, DOE did not deduce new owner shipments by calibrating to historical 

shipments. For non-weatherized gas furnaces, DOE used data from Decision Analysts’ American 

Home Comfort Survey to estimates the 7.7% of total shipments are to new owner.10

9.3 DECISION MODEL FOR REPLACEMENTS AND EQUIPMENT 

SWITCHING

For mobile 

home gas and oil furnaces, DOE assumed that there were no new owner shipments.

9.3.1 Decision Model for Replacements

In the Shipments Model, replacements are modeled based on two sets of consumer 

purchase decisions. These decisions are influenced by the purchase price and operating cost of 

equipment, and therefore will be different in the base case and different CSLs. These decisions 

are modeled by estimating the purchase price elasticity for cooling and heating equipment. The 

purchase price elasticity is defined as the change in the percentage of consumers acquiring 
9-16

central air conditioner and heat pump equipment divided by a change in the relative price

(defined below) for that equipment. This elasticity and information obtained from the life-cycle 

cost (LCC) and payback period (PBP) analysis on the change in purchase price and operating 

costs under different CSLs are used in the shipments model to estimate the resulting change in 

equipment shipped.

9.3.1.1 Purchase Price Elasticity

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 product purchase price, 

decreases in product operating costs, and changes to household income. Appendix 9-A provides 

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

variables.

Existing studies of appliance markets suggest that the demand for appliances is priceinelastic. Other information in the literature suggests that appliances are a normal good, so that 

rising incomes increase the demand for appliances, and that consumers use relatively high 

implicit discount ratesa when comparing appliance prices and appliance operating costs. 

DOE used the available data for the period 1980-2002 on large appliance purchases 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. Because 

purchase decisions are sensitive to income, and also to potential savings in the operating cost of 

the appliance, DOE combined the available economic information into one variable, termed the 

relative price. This variable was used in a regression analysis to parameterize historical market 

trends. The relative price is defined with the following expression:

Income

PP PVOC

Income

TP RP + = =

Where:

RP = relative price,

TP = total price,

Income = household income,

PP = appliance purchase price, and

PVOC = present value of operating cost, based on an implicit discount rate of 37 

percent.

 

a 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.
9-17

DOE’s regression analysis of the relevant data suggests that the relative price elasticity of 

demand is approximately -0.34; this implies that a relative price increase of 10 percent results in 

a 3 to 4 percent decrease in shipments. Note that the relative price elasticity incorporates the 

impacts from purchase price, operating cost, and household income, so the impact from any 

single effect can be mitigated by changes from the other two effects. The relative price elasticity 

of -0.34 is consistent with estimates in the literature, but is based on a small data set. More 

importantly, 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.

The forecasts of shipments and national impacts due to standards are for a 30-year time 

period, and it is possible that over this time period the numerical value of the relative price

elasticity could change; in particular, it can be affected by a new standard that changes consumer 

expectations about equipment performance. DOE considered the relative price elasticity

provided by the preceding analysis to be a short-run value. No data exists to allow the 

determination of long run price elasticities for appliances, so DOE relied on a study pertaining to 

automobiles.11

Table 9.3.1

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

years following a purchase price change, becoming smaller (more inelastic) until it reaches a 

terminal value around the tenth year after the price change. Table 9.3.1 shows the relative change 

in the price elasticity of demand for automobiles over time. DOE developed a time series of 

relative price elasticities for CAC and CAC-HP based on the relative change in the automobile 

price elasticity of demand. For years not shown in , DOE performed a linear 

interpolation to obtain the relative price elasticity.

Table 9.3.1 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

9.3.1.2 Impact from Increase in Relative Price 

Using the relative price elasticity, DOE was able to estimate the impact of the increase in 

relative price from a particular CSL. The impact, as shown in the equation below, is expressed as 

a percentage drop in market share for each year, dMSp

j , which is applied in the decision for 

replacement versus extended repair. As noted in section 9.1.1, for the new construction and new 

owner market channels, the placement of equipment is automatic. In other words, DOE assumed 

that the new construction and new owner market channels were unaffected by changes in either 

the total installed cost or operating costs of the equipment as well as changes in household 

income. 
9-18

( )

( ) e (j) RP _base j

RP _std j dMS RP

p

p p

j ×































 = 1 −

Where:

dMSp

j = percentage market share drop for class p, year j, 

RP_stdp(j)= relative price in the standards case for product class p, year j, 

RPp(j)= relative price in the base case for product class p, year j, and

eRP(j) = relative price elasticity in year j.

9.3.1.3 Replacement Shipment Impacts

For replacement purchases of central air conditioners, heat pumps, and furnaces, DOE 

assumed consumers affected by an increase in total installed cost would repair their equipment 

rather than replace it, extending the life of the product by six years. When the extended repaired 

units fail after six more years, they will be replaced with new ones. 

The model calculates for each year after the standard, the relative percentage market 

drop, dMSp

j, due to the equipment price increase as described in 9.3.1.1. The extended repair is 

only applicable to broken equipment that are purchased before 2016. For broken equipment that 

are purchased after 2016, extended repair will not be considered since there will be no longer a 

price impact from standards between new units and the broken units.

The number of broken units that will be further repaired instead of being replaced is 

calculated as follows: 

= ∑ ( )× − < a

p

i i XR Re m j,a dMS for( j a ) 2016

( ) = ∑ − + − ( ) −

a

i j Rpl j Re m( j,a ) XR XR Dem j 6

Where:

dMSp

j = percentage market share drop for class p, year j, 

a = age of an equipment

j = year,

Rem(j,a) = retiring units in year j of age a,

XRj = extended repair units, year j,

Rpl(j) = replacement units in year j,

Dem (j) = number of units gone with demolished buildings in analysis year j.
9-19

9.3.2 Equipment Switching

9.3.2.1 Split System Heat Pumps: Switch to Combination Split System Central Air 

Conditioner and Electric Furnace

DOE conducted an analysis of the potential for equipment switching between a split 

system heat pump and the combination of a split system central air conditioner and electric 

furnace. To estimate the likelihood of equipment switching between these two systems, DOE 

utilized proprietary data from Decision Analysts,10 which identified for a representative sample 

of consumers their willingness to purchase more-efficient space-conditioning systems. From 

these data, DOE deduced the payback period that consumers would expect for a more-expensive 

but more-efficient product. For each pairing of split heat pump and split air conditioner 

efficiency levels, DOE applied the payback period criterion to estimate the fraction of consumers 

who would be expected to switch to the other type of equipment. For example, when comparing 

a 15 SEER split system heat pump and a combination of a 14 SEER split air conditioner and an 

electric furnace, DOE calculated the payback period of the more-efficient split system heat pump 

relative to the less-expensive combination of split air conditioner and electric furnace. If the 

resulting payback period for the split system heat pump exceeded the expected payback period 

deduced from the Decision Analysts’ data, DOE forecasted that the consumer would switch to 

the combination of split air conditioner and electric furnace. 

For every possible pairing of split system heat pump and split system air conditioner 

efficiencies, DOE calculated the fraction of consumers who would be expected to switch from 

split system heat pumps to combination split system air conditioners and electric furnaces. The 

fraction of consumers switching was in turn used by DOE to forecast split system heat pump and 

split system air conditioner shipments in specific standards cases, as well as the increase in 

electric furnace shipments. Including the latter in accounting for the impacts of equipment 

switching is important for proper determination of national energy savings and national 

economic impacts.

For those split system heat pump consumers switching to a combination split system air 

conditioners and electric furnace, DOE determined the space-cooling annual energy use or unit 

energy consumption (UEC) of the air conditioner by multiplying the split system heat pump 

space-cooling UEC by the ratio of the heat pump SEER to the air conditioner SEER. DOE 

determined the space-heating UEC of the electric furnace by multiplying the split system heat 

pump space-heating by the ratio of the heat pump HSPF to the electric furnace efficiency 

(coefficient of performance (COP) of 1.0 which is equivalent to a 3.41 HSPF). DOE determined 

the total installed cost of the combination system based on the SEER level of the split system air 

conditioner plus the cost of an electric furnace.

Appendix 9-B provides a more detailed explanation of the methodology and results DOE 

used to quantify the impacts of equipment switching on split system heat pump consumers.
9-20

9.3.2.2 Gas Furnace Equipment Switching

DOE did not explicitly quantify the potential for fuel switching from gas furnaces to 

electric heating equipment. DOE conducted a thorough review of the 2005 Residential Energy 

Consumption Survey (RECS) to assess the type of space-heating system utilized by consumers 

as a function of house heating load.12 Gas furnaces are primarily utilized in households with high 

heating loads, while electric space heating systems are almost exclusively used in households 

with low heating loads. Generally, this is because the operating costs of electric space heating 

systems are relatively high due to the price of electricity, so using an electric system in a cold 

climate is significantly more expensive than using a gas furnace. Based on the above finding, 

DOE inferred that consumers with high heating loads would be unlikely to switch to electric 

space heating systems as a result of amended standards. 

In addition, for a household with a gas furnace to switch to electric space heating, a 

separate circuit up to 30-amps would need to be installed at a cost of approximately $300 to 

power the electric resistance heater within an electric furnace or heat pump system. On average, 

the electrical circuit cost is approximately 60 percent of the added installation cost of a more 

expensive venting system required for high-efficiency, condensing furnaces, further diminishing 

the likelihood of a consumer switching from gas to electric heating.

Appendix 9-B provides a detailed explanation of the methodology and results DOE used 

to estimate that fuel switching from gas furnaces to electric heating equipment is very unlikely.

9.3.2.3 Other Equipment Switching

DOE did not consider any other equipment switching other than for split system heat 

pumps and gas furnaces. In other words, DOE estimated that consumers of split system and 

single package air conditioners, single package heat pumps, mobile home gas furnaces, and oil 

furnaces would not switch to another type of space-conditioning system regardless of the 

standard level.

9.4 REGIONAL SHIPMENTS MODEL

As described in chapter 7, Energy Use Determination, some of the CSLs involve the 

division of the U.S. into climate regions; hot-humid, hot-dry, and rest-of-country for central air 

conditioners and heat pumps and the North and South for gas furnaces. For the shipments model, 

DOE constructed two variants of the national analysis. In the first, the nation as a whole is 

treated as a single region. In the second, the U.S. is disaggregated into the climate regions, a 

separate shipments model is run for each region, and the results are summed to provide nationallevel output under a regional standard scenario. In the regional standards case, the mechanics of 

the shipments model are identical to the one-region case already described. The only changes 

needed to analyze a specific region are definitions of the various data inputs for the region in 

question. This section describes how these data inputs were disaggregated.
9-21

Not every data input can be or needs to be defined at a regional level. DOE assumed the 

product lifetimes, purchase prices, and relative price elasticities did not vary by region. Product 

operating costs do vary by region and this information is available from the LCC and PBP 

analysis (see chapter 8). For the shipments model, historical shipments, housing starts and 

housing stock, commercial buildings starts and stock (for central air conditioners and heat pump 

only), and market saturations for new construction must be developed for each region. The 

following sections describe the development of regional historical shipments, building starts and 

stock, and market saturations.

9.4.1 Central Air Conditioners and Heat Pumps

9.4.1.1 Allocation of Historical Shipments to Regions

DOE developed regional allocation factors to divide historical shipments into each of the 

three climatic regions. The regional allocation factors were determined by trial and error by 

calibrating to historical residential stock saturations in the American Housing Survey (AHS).13 

Tables 9.4.1 and 9.4.2 provide the historical regional and national stock saturations for CAC and 

HP equipment for every other year between 1991−2007 as specified in the AHS. The stock 

saturations are specific to each region or the nation, i.e., the individual regional stock saturations 

do not add up to the national stock saturation.

Table 9.4.1 CAC Residential Regional Stock Saturations

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S.

1991 32.5% 48.6% 23.8% 30.8%

1993 33.5% 50.0% 25.0% 32.0%

1995 36.6% 50.7% 27.3% 33.9%

1997 42.4% 47.3% 29.2% 36.3%

1999 48.0% 54.0% 33.3% 41.4%

2001 51.5% 58.1% 36.6% 45.0%

2003 53.8% 58.1% 38.5% 46.5%

2005 55.9% 61.5% 43.0% 50.2%

2007 63.5% 62.8% 42.8% 51.8%

Source: AHS
9-22

Table 9.4.2 HP Residential Regional Stock Saturations

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S.

1991 6.3% 18.1% 3.7% 7.8%

1993 7.5% 19.7% 3.9% 8.5%

1995 7.1% 21.6% 4.1% 9.1%

1997 9.9% 28.0% 4.4% 12.0%

1999 8.3% 26.8% 4.2% 11.4%

2001 8.0% 26.2% 4.4% 11.3%

2003 7.8% 27.4% 4.4% 11.7%

2005 8.8% 29.0% 5.4% 12.7%

2007 8.1% 28.8% 5.3% 12.8%

Source: AHS

Tables 9.4.3 and 9.4.4 provide the shipment allocation factors for CAC and HP, 

respectively. 

Table 9.4.3 CAC Shipment Regional Allocation Factors

Year Hot-Dry Hot-Humid Rest U.S.

1983 16.0% 50.0% 34.0%

1987 16.0% 45.0% 39.0%

1990 16.0% 40.0% 44.0%

1993 16.0% 40.0% 44.0%

1997 16.0% 40.0% 44.0%

2001 16.0% 40.0% 44.0%

2003 16.0% 40.0% 44.0%

2005 16.0% 40.0% 44.0%

2007 16.0% 40.0% 44.0%

Table 9.4.4 HP Shipment Regional Allocation Factors

Year Hot-Dry Hot-Humid Rest U.S.

1983 12.0% 70.0% 18.0%

1987 12.0% 70.0% 18.0%

1990 12.0% 70.0% 18.0%

1993 12.0% 70.0% 18.0%

1997 12.0% 70.0% 18.0%

2001 12.0% 70.0% 18.0%

2003 12.0% 70.0% 18.0%

2005 12.0% 70.0% 18.0%

2007 12.0% 70.0% 18.0%

DOE further divided the above allocation factors for CAC and HP into factors specific to 

the split and single package product classes. The regional allocation factors by product class 

were based on regional shipments data submitted by AHRI for the years 2008 and 2009. Table
9-23

9.4.5 provides regional shipment market share data for the three climate regions (hot-dry, hothumid, and rest-of-country). For each product class, the market share values total to 100%.

Table 9.4.5 Central Air Conditioner and Heat Pump Regional Shipment Market Shares*

Year

Product Class

Split System CAC Split System HP Single Package CAC Single Package HP

HotDryHotHumidRest of 

U.S.

HotDryHotHumidRest of 

U.S.

HotDryHotHumidRest of 

U.S.

HotDryHotHumidRest of 

U.S.

2008 10.9% 50.2% 38.9% 7.2% 72.3% 20.5% 25.7% 55.4% 18.9% 24.6% 72.0% 3.4%

2009 11.4% 52.7% 35.9% 6.8% 74.9% 18.3% 23.9% 60.2% 15.9% 25.0% 71.8% 3.2%

Source: AHRI

* Market shares for each product class add up to 100%.

To estimate product class allocation factors for years prior to 2008, DOE first estimated 

single package CAC and HP market shares for 2008 were representative of prior years. With 

this assumption, DOE was able to deduce the markets shares for the split system product classes. 

Tables 9.4.6 and 9.4.7 provide the regional allocation factors for the split and single package 

central air conditioners and heat pumps. 

Table 9.4.6 CAC Shipment Regional Allocation Factors by Product Class

Split System CAC Single Package CAC

Year Hot-Dry Hot-Humid Rest U.S. Hot-Dry Hot-Humid Rest U.S.

1983 14.8% 49.3% 35.9% 25.7% 55.4% 18.9%

1987 15.0% 43.9% 41.2% 25.7% 55.4% 18.9%

1989 15.0% 38.4% 46.7% 25.7% 55.4% 18.9%

1991 14.8% 38.0% 47.2% 25.7% 55.4% 18.9%

1993 14.6% 37.8% 47.5% 25.7% 55.4% 18.9%

1995 14.8% 38.2% 47.0% 25.7% 55.4% 18.9%

1997 14.9% 38.2% 46.9% 25.7% 55.4% 18.9%

1999 15.0% 38.5% 46.5% 25.7% 55.4% 18.9%

2001 15.1% 38.6% 46.3% 25.7% 55.4% 18.9%

2003 15.1% 38.6% 46.3% 25.7% 55.4% 18.9%

2005 15.2% 38.7% 46.1% 25.7% 55.4% 18.9%

2008 10.9% 50.2% 38.9% 25.7% 55.4% 18.9%

2009 11.4% 52.7% 35.9% 23.9% 60.2% 15.9%
9-24

Table 9.4.7 HP Shipment Regional Allocation Factors by Product Class

Split System HP Single Package HP

Year Hot-Dry Hot-Humid Rest U.S. Hot-Dry Hot-Humid Rest U.S.

1983 9.7% 69.6% 20.6% 24.6% 72.0% 3.4%

1987 10.2% 69.7% 20.1% 24.6% 72.0% 3.4%

1989 10.2% 69.7% 20.0% 24.6% 72.0% 3.4%

1991 10.0% 69.7% 20.3% 24.6% 72.0% 3.4%

1993 10.1% 69.7% 20.2% 24.6% 72.0% 3.4%

1995 10.2% 69.7% 20.1% 24.6% 72.0% 3.4%

1997 10.0% 69.7% 20.3% 24.6% 72.0% 3.4%

1999 10.2% 69.7% 20.0% 24.6% 72.0% 3.4%

2001 10.2% 69.7% 20.0% 24.6% 72.0% 3.4%

2003 10.4% 69.7% 19.9% 24.6% 72.0% 3.4%

2005 10.5% 69.8% 19.7% 24.6% 72.0% 3.4%

2008 7.2% 72.3% 20.5% 24.6% 72.0% 3.4%

2009 6.8% 74.9% 18.3% 25.0% 71.8% 3.2%

Figure 9.4.1 provides the resulting comparison between the CAC and HP stock 

saturations by region and the entire U.S. from the AHS and those calculated from the shipments 

model. As shown in the figure below, the calculated values are relatively close to the values 

from the AHS. 
9-25

Figure 9.4.1 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: 

American Housing Survey (AHS) vs. Shipments Model (Calculated)

9.4.1.2 Regional New Construction and New Construction Saturations

Regional New Construction

AEO2010 provides housing forecasts by Census Division. These were converted to the 

three climate regions by using population data to allocate the housing stock. Each state can be 

allocated to both a Census Division and a climate region; hence, a set of overlap regions can

defined at the state level. For example, Florida is in the hot-humid climate region and the South 

Atlantic census division; therefore, the intersection of hot-humid with South Atlantic contains 

the state of Florida. (The list of states included in each climate region is defined in chapter 7).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Saturation

CAC & HP Saturation Hot-Dry

CAC calculated HP calculated

CAC RECS/AHS HP RECS/AHS

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Saturation

CAC & HP Saturation Hot-Humid

CAC calculated HP calculated

CAC RECS/AHS HP RECS/AHS

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Saturation

CAC & HP Saturation Rest of U.S.

CAC calculated HP calculated

CAC RECS/AHS HP RECS/AHS

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Saturation

CAC & HP Saturation Entire U.S.

CAC calculated HP calculated

CAC RECS/AHS HP RECS/AHS
9-26

The U.S. Census provides historical population, and population projections, by state at five-year 

intervals for the years 2005-2030.14 These data were used to define annual populations for each 

of the intersection regions over the same period. First, the Census data were interpolated onto 

one-year intervals by assuming a constant rate of growth within the given five-year period. Next, 

the one-year data were aggregated to provide regional populations. Projections out to 2045 were 

constructed by assuming that the rate of growth in each region would remain constant for the 

years after 2030. The constant in each region was defined as the average of the U.S. Census 

growth rates for 2025 and 2030. Sample output from this calculation is represented in Table 

9.4.2, which shows the population in each area defined by the overlap of a climate region with a 

census division. For example, both the hot-dry and the rest-of-country regions overlap with the 

Mountain and Pacific census divisions, while the West North Central census division is entirely 

in the hot-humid region. 

Table 9.4.8 Population Projected for 2020 for Areas defined by the Overlap of Census 

Divisions with Climate Regions

Region

Census Division Hot-Dry Hot-Humid Rest-of-Country Total 

Northeast - - 15,309,528 15,309,528

Mid-Atlantic - - 41,825,909 41,825,909

East North Central - - 48,208,733 48,208,733

West North Central - - 21,246,442 21,246,442

South Atlantic - 49,782,144 18,659,882 68,442,026

East South Central - 14,554,397 4,424,431 18,978,828

West South Central - 40,149,965 - 40,149,965

Mountain 13,993,072 - 11,563,977 25,557,049

Pacific 42,206,743 - 13,879,323 56,086,066

Total by Region 56,199,815 104,486,506 175,118,225 335,804,546

Using these numbers for each census division, the fraction of its population that belongs 

to a given climate region can be determined. This is used to allocate housing stock to climate 

regions. 

In a similar manner, the year-on-year change in population for each Census Division can 

be disaggregated onto the climate regions that overlap that Census Division. The disaggregation 

of population growth is used to allocate housing starts to climate regions. 

The same coefficients are used to allocate commercial building floor space and 

commercial building starts to the three climate regions.

Regional New Construction Saturations

DOE developed residential regional new construction saturations from Characteristics of 

New Housing data from the U.S. Census Bureau.3

 The data breaks down central air conditioner

and heat pump saturations for single-family and multi-family households into the four Census 

Regions (i.e., northeast, midwest, south, and west). DOE used population allocation factors (as 
9-27

discussed previously) to properly allocate saturations into the three climate regions (i.e., hothumid, hot-dry, and rest-of-country). Figures 9.4.1 and 9.4.2 depict the national and regional 

saturations for central air conditioners and heat pumps, respectively. The regional saturations 

depicted in the figures below were determined using the entire U.S. housing stock. In other 

words, the regional saturations when summed equal the national saturation.

Figure 9.4.2 Central Air Conditioner National and Regional Saturations in 

Residential New Construction

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Year

CAC Residential New Construction Saturations

Entire U.S.

Rest of Country

Hot-Humid

Hot-Dry
9-28

Figure 9.4.3 Heat Pump National and Regional Saturations in Residential New 

Construction

For the commercial market segment, DOE developed new construction market 

saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS).6

 

As noted above in section 9.2.2, DOE developed new construction saturations through the use of 

past CBECS surveys and commercial starts from AEO2009. The assembled data breaks down 

central air conditioner and heat pump saturations into nine Census Divisions. DOE used 

population allocation factors (as discussed previously) to properly allocate saturations into the 

three climate regions (i.e., hot-humid, hot-dry, and rest-of-country). Figures 9.4.3 depicts the 

national and regional saturations for central air conditioner and heat pump equipment. The 

regional saturations depicted in the Figure 9.4.4 below were determined using the entire 

commercial building stock. In other words, the regional saturations when summed equal the 

national saturation.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Year

HP Residential New Construction Saturations

Entire U.S.

Rest of Country

Hot-Humid

Hot-Dry
9-29

Figure 9.4.4 Central Air Conditioner and Heat Pump National and Regional 

Saturations in Commercial New Construction

9.4.2 Furnaces

9.4.2.1 Allocation of Historical Shipments to Regions

DOE developed regional allocation factors to divide historical shipments into each of the 

climatic regions. To maintain consistency with the treatment of central air conditioning and heat 

pump equipment, DOE divided furnace shipments into three regions: hot-humid and hot-dry, 

which comprise the South, and the rest-of-the-country, which comprises the North. The regional 

allocation factors from non-weatherized gas and mobile home gas furnaces were based on 

regional shipments data submitted by AHRI for the years 1992 through 2009. For oil furnaces, 

based the market shares on data from the AHS. Table 9.4.3 provides the regional shipment 

market share data for the three climate regions. For each product class, the market share values 

total to 100%.

0%

1%

2%

3%

4%

5%

6%

1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

Year

CAC and HP Commercial New Construction Saturations

Entire U.S.

Hot-Humid

Rest of Country

Hot-Dry
9-30

Table 9.4.9 Furnace Regional Shipment Market Shares*

Year

Product Class

Non-Weatherized Gas Mobile Home Gas Oil

Hot-Dry

HotHumidRest of 

U.S. Hot-Dry

HotHumidRest of 

U.S. Hot-Dry

HotHumidRest of 

U.S.

1992 13.6% 31.8% 54.5% 11.7% 30.0% 58.4% - 19.1% 80.9%

1993 13.2% 35.0% 51.7% 11.7% 30.0% 58.4% - 19.1% 80.9%

1994 11.9% 34.2% 53.9% 11.7% 30.0% 58.4% - 19.1% 80.9%

1995 11.6% 34.2% 54.2% 11.9% 31.4% 56.7% - 19.1% 80.9%

1996 11.0% 35.9% 53.1% 12.9% 33.2% 53.9% - 19.1% 80.9%

1997 12.5% 34.8% 52.6% 13.6% 33.2% 53.2% - 19.1% 80.9%

1998 13.1% 35.6% 51.3% 13.7% 34.1% 52.1% - 19.1% 80.9%

1999 13.0% 35.2% 51.9% 14.3% 32.1% 53.6% - 19.1% 80.9%

2000 13.4% 34.7% 51.8% 15.4% 28.5% 56.1% - 19.1% 80.9%

2001 14.6% 36.7% 48.7% 16.7% 26.8% 56.5% - 19.1% 80.9%

2002 14.1% 36.8% 49.2% 17.3% 25.5% 57.2% - 19.1% 80.9%

2003 15.1% 35.2% 49.8% 20.8% 23.3% 55.9% - 19.1% 80.9%

2004 13.8% 38.0% 48.2% 24.3% 24.8% 50.9% - 19.1% 80.9%

2005 13.6% 37.5% 48.8% 26.0% 29.0% 45.0% - 19.1% 80.9%

2006 13.7% 37.9% 48.4% 26.4% 28.1% 45.5% - 19.1% 80.9%

2007 13.4% 36.5% 50.1% 21.0% 30.9% 48.1% - 19.1% 80.9%

2008 12.2% 32.8% 55.0% 17.4% 35.5% 47.1% - 19.1% 80.9%

2009 12.3% 32.6% 55.1% 15.5% 36.2% 48.3% - 19.1% 80.9%

Sources: Gas Furnaces: AHRI; Oil Furnaces: AHS

* Market shares for each product class add up to 100%.

9.4.2.2 Regional New Construction and New Construction Saturations 

Regional New Construction

For furnaces, residential regional new construction data were based on the same data 

sources and methodology used for central air conditioners and heat pumps. Refer to the 

description in section 9.4.1.2.

Regional New Construction Saturations

DOE developed residential regional new construction saturations from Characteristics of 

New Housing data from the U.S. Census Bureau.3

 The data breaks down furance saturations for 

single-family and multi-family households into the four Census Regions (i.e., northeast, 

midwest, south, and west). DOE used population allocation factors (as discussed previously) to 

properly allocate saturations into the three climate regions (i.e., hot-humid, hot-dry, and rest-ofcountry). Figures 9.4.4 and 9.4.5 depict the national and regional saturations for central air 

conditioners and heat pumps, respectively. The regional saturations depicted in the figures 
9-31

below were determined using the entire U.S. housing stock. In other words, the regional 

saturations when summed equal the national saturation.

Figure 9.4.5 Non-Weatherized Gas Furnace National and Regional Saturations in 

Residential New Construction

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1980 1990 2000 2010 2020 2030 2040 2050

Year

Non-Weatherized Gas Furnace Residential 

New Consturction Saturations

National

North

South - Hot Humid

South - Hot Dry

`
9-32

Figure 9.4.6 Mobile Home Gas National and Regional Saturations in Residential New 

Construction

Figure 9.4.7 Oil Furnace National and Regional Saturations in Residential New 

Construction

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1980 1990 2000 2010 2020 2030 2040 2050

Year

Mobile Home Gas Furnace Residential New 

Consturction Saturations

National

North

South - Hot Humid

South - Hot Dry

`

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

1.80%

2.00%

1980 1990 2000 2010 2020 2030 2040 2050

Year

Oil Furnace Residential New Consturction 

Saturations

National

North

South - Hot Humid

`
9-33

9.5 RESULTS

This section presents the shipments forecasts for the base case for central air conditioners, 

heat pumps, and furnaces. For each major product category, figures are presented showing base 

case shipments by product class, product channel (new construction, replacements, and new 

owners), and region (hot-dry, hot-humid, and rest-of-country for central air conditioners and heat 

pumps, and North and South for furnaces).

Also presented are the cumulative impacts to central air conditioner, heat pump, and 

furnace shipments due to various standard levels.

9.5.1 Base Case Shipments 

9.5.1.1 Central Air Conditioners

Figure 9.5.1 shows the base case shipments for central air conditioners by product class. 

Because split central air conditioner shipments are divided into coil-only and blower coil units, 

shipments for split systems are shown by product type. Figure 9.5.2 shows the base case 

shipments for central air conditioners by product channel while Figure 9.5.3 shows the base case 

shipments for central air conditioners by region. 

Figure 9.5.1 Central Air Conditioners: Base Case Shipments by Product Class and 

Product Type

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Single Package

Split System Blower Coil

Split System - Coil Only
9-34

Figure 9.5.2 Central Air Conditioners: Base Case Shipments by Product Channel

Figure 9.5.3 Central Air Conditioners: Base Case Shipments by Region

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Replacement and New Owners

New Construction

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Rest of Country

Hot Humid

Hot Dry
9-35

9.5.1.2 Heat Pumps

Figure 9.5.4 shows the base case shipments for heat pumps by product class. Figure 9.5.5 

shows the base case shipments for central air conditioners by product channel while Figure 9.5.6 

shows the base case shipments for central air conditioners by region. 

Figure 9.5.4 Heat Pumps: Base Case Shipments by Product Class

Figure 9.5.5 Heat Pumps: Base Case Shipments by Product Channel

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Single Package

Split System

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Replacements and New 

Owners

New Construction
9-36

Figure 9.5.6 Heat Pumps: Base Case Shipments by Region

9.5.1.3 Furnaces

Figure 9.5.7 shows the base case shipments for heat pumps by product class. Figure 9.5.8 

shows the base case shipments for central air conditioners by product channel while Figure 9.5.9 

shows the base case shipments for central air conditioners by region. 

Figure 9.5.7 Furnaces: Base Case Shipments by Product Class

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Rest of Country

Hot Dry

Hot Humid

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Mobile Home Furnaces

Oil Furnaces

Non-Weatherized Gas 

Furnaces
9-37

Figure 9.5.8 Furnaces: Base Case Shipments by Product Channel

Figure 9.5.9 Furnaces: Base Case Shipments by Region

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

Replacements and New 

Owners

New Construction

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

2010 2015 2020 2025 2030 2035 2040 2045

Shipments (millions)

South

North
9-38

9.5.2 Shipments Impacts due to Standards

As detailed in chapter 10, DOE created trial standard levels (TSLs) that combine specific 

efficiency levels across product classes. DOE analyzed the benefits and burdens of a number of 

TSLs for the products considered in this rulemaking. 

Table 9.5.1 shows the TSLs DOE analyzed for furnaces and central air conditioners and 

heat pumps. In the table SAC means split system central air conditioners, SHP means split 

system heat pumps, PAC means single package central air conditioners, PHP means single 

package heat pumps, SDHV means small duct high velocity systems, NWGF means nonweatherized gas furnaces, OF means oil furnaces, and MHF means mobile home furnaces. 

SDHV systems are not explicitly addressed in the shipments analysis due to their very low 

shipments.
9-39

Table 9.5.1 Trial Standard Levels for Central Air Conditioners and Heat Pumps and 

Furnaces (Energy Efficiency)

SAC SHP PAC PHP SDHV NWGF OF MHF

TSL Region Applicable SEER SEER/HSPF SEER SEER/HSPF SEER/HSPF AFUE AFUE AFUE

7

Rest of Country* 22** 20 / 9.9† 16.5 16.5 / 9.0 14.5 / 8.6 98% 97% 96%

North (Furnace) 98% 96%

Hot Humid (CAC-HP) 22** 20 / 9.9† 16.5 16.5 / 9.0 14.5 / 8.6

Hot Dry (CAC-HP) 22** 20 / 9.9† 16.5 16.5 / 9.0 14.5 / 8.6

6

Rest of Country* 14 15 / 8.5 15 15 / 8.4 14 / 8.5 80% 85% 80%

North (Furnace) 95% 96%

Hot Humid (CAC-HP) 15 15 / 8.5 15 15 / 8.4 14 / 8.5

Hot Dry (CAC-HP) 15 15 / 8.5 15 15 / 8.4 14 / 8.5

5

Rest of Country* 13 14 / 8.2 14 14 / 8.0 13 / 7.7 80% 85% 80%

North (Furnace) 95% 96%

Hot Humid (CAC-HP) 14 14 / 8.2 14 14 / 8.0 13 / 7.7

Hot Dry (CAC-HP) 14 14 / 8.2 14 14 / 8.0 13 / 7.7

4††

Rest of Country* 13 14 / 8.2 14 14 / 8.0 13 / 7.7 80% 83% 80%

North (Furnace) 90% 90%

Hot Humid (CAC-HP) 14 14 / 8.2 14 14 / 8.0 13 / 7.7

Hot Dry (CAC-HP)

14 /

12.2 & 

11.7 EER

14 / 8.2 14 /

11 EER 14 / 8.0 13 / 7.7

3

Rest of Country* 13 14 / 8.2 14 14 / 8.0 13 / 7.7 80% 83% 80%

North (Furnace) 90% 90%

Hot Humid (CAC-HP) 14 14 / 8.2 14 14 / 8.0 13 / 7.7

Hot Dry (CAC-HP) 14 14 / 8.2 14 14 / 8.0 13 / 7.7

2

Rest of Country* 13.5 13.5 / 8.1 13 13 / 7.7 13 / 7.7 80% 82% 80%

North (Furnace) 92% 80%

Hot Humid (CAC-HP) 13.5‡ 13.5 / 8.1‡ 13‡ 13 / 7.7‡ 13 / 7.7

Hot Dry (CAC-HP) 13.5‡ 13.5 / 8.1‡ 13‡ 13 / 7.7‡ 13 / 7.7

1 Nation 13.5 13.5 / 8.1 13 13 / 7.7 13 / 7.7 80% 82% 80%

*The values presented under “Rest of Country” are the national standards, but they effectively apply to those States not 

subject to regional standards. Rest of Country refers to the Northern region for air conditioners and heat pumps and to the 

Southern region for NWGF and MHF. For OF, the value refers to the entire Nation.

** Max-tech of 22 SEER pertains to 3-ton blower-coil units only, which is the most common cooling capacity of products on 

the market. Max-tech efficiencies vary by tonnage and type. See chapter 5 of the TSD for more information on the max-tech 

efficiency levels.

† Max- tech of 20 SEER / 9.9 HSPF pertains to 3-ton units only, which is the most common cooling capacity of products on 

the market. Max-tech efficiencies vary by tonnage. See chapter 5 of the TSD for more information on the max-tech efficiency 

levels.

†† Compliance date is 1/1/2015 for central air conditioners and heat pumps and 5/1/2013 for furnaces. For SAC, TSL 4 has 

separate EER levels based on capacity (see section III.B.2).

‡ Largest market share unknown; assumed to be equal to the market share for entire Nation.

 Table 9.5.2 shows the base case cumulative shipments and the impacts to cumulative 

shipments due to the various TSLs. Decreases in shipments are represented as positive values 

while increases in shipments are represented by negative values. Shipments impacts for the 

various product classes are for the most part small. The most significant impact on product 

shipments is due to equipment switching between split system coil-only central air conditioners 
9-40

(SAC-CO) and split system heat pumps (SHP). For TSLs 3, 4, 5, and 6 where there is a 

difference in the efficiency standards between SAC-CO and SHP for the ‘rest of country’ region, 

the impact from the TSLs is to increase SAC-CO shipments and to decrease SHP shipments.

Table 9.5.2 Base Case Cumulative Shipments and Shipments Impacts due to TSLs

Region

SAC-CO SAC-BC PAC SHP PHP NWGF MHF OF

Base Case Shipments (millions)

Hot-Dry 24.203 2.689 3.930 6.723 3.307 16.920 0.892 0.000

Hot-Humid 47.717 5.302 6.407 44.365 5.632 32.335 0.989 0.291

Rest of U.S. 73.507 8.167 4.410 13.715 2.381 55.228 1.966 1.493

U.S. 145.427 16.159 14.747 64.803 11.319 104.483 3.846 1.784

TSL 1 Shipments Impacts* (millions)

Hot-Dry 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Hot-Humid 0.001 0.000 0.000 0.001 0.000 0.000 0.000 0.000

Rest of U.S. 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000

U.S. 0.004 0.001 0.000 0.001 0.000 0.000 0.000 0.000

TSL 2 Shipments Impacts* (millions)

Hot-Dry 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Hot-Humid 0.001 0.000 0.000 0.001 0.000 0.000 0.000 0.000

Rest of U.S. 0.002 0.000 0.000 0.000 0.000 0.040 0.000 0.000

U.S. 0.004 0.001 0.000 0.001 0.000 0.040 0.000 0.000

TSL 3 Shipments Impacts* (millions)

Hot-Dry 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Hot-Humid 0.005 0.001 0.000 0.003 0.000 0.000 0.000 0.000

Rest of U.S. -0.046 0.000 0.000 0.052 0.000 0.035 0.006 0.000

U.S. -0.040 0.001 0.000 0.056 0.000 0.035 0.006 0.000

TSL 4 Shipments Impacts* (millions)

Hot-Dry 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Hot-Humid 0.001 0.000 0.000 0.002 0.000 0.000 0.000 0.000

Rest of U.S. -0.048 0.000 0.000 0.054 0.000 -0.001 0.000 0.000

U.S. -0.047 0.000 0.000 0.055 0.000 -0.001 0.000 0.000

TSL 5 Shipments Impacts* (millions)

Hot-Dry 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Hot-Humid 0.005 0.001 0.000 0.003 0.000 0.000 0.000 0.000

Rest of U.S. -0.046 0.000 0.000 0.052 0.000 0.061 0.012 0.002

U.S. -0.040 0.001 0.000 0.056 0.000 0.061 0.012 0.002

TSL 6 Shipments Impacts* (millions)

Hot-Dry 0.065 0.001 0.000 0.001 0.000 0.000 0.000 0.000

Hot-Humid 0.166 0.002 0.000 0.012 0.000 0.000 0.000 0.000

Rest of U.S. -0.038 0.001 0.000 0.058 0.000 0.061 0.012 0.002

U.S. 0.193 0.004 0.000 0.071 0.000 0.061 0.012 0.002

TSL 7 Shipments Impacts* (millions)

Hot-Dry 0.172 0.009 0.000 0.012 0.000 0.116 0.008 0.000

Hot-Humid 0.433 0.022 0.000 0.104 0.000 0.172 0.006 0.002

Rest of U.S. 0.632 0.034 0.000 0.039 0.000 0.083 0.012 0.006

U.S. 1.237 0.065 0.000 0.155 0.000 0.372 0.026 0.007

*Positive values represent decreases in shipments; negative values represent increases in shipments.

DOE also created trial standard levels (TSLs) for specific efficiency levels that limit offmode power consumption across product classes. Although the TSLs for off-mode power 
9-41

consumption did increase product cost, DOE estimated the cost increase was so small as to not 

impact product shipments.
9-42

REFERENCES

 1 Letter to Mrs. Rachel Schmeltz, Energy Star Program Manager, Environmental Protection 

Agency from Karim Amrane, Vice President, Regulatory & Research, Air-Conditioning, 

Heating, and Refrigeration Institute (AHRI), “EPA Proposed Draft Energy Star Specification 

for Light Commercial HVAC Equipment,” Jan. 30, 2009.

2 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008.

3 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments data, 1972-1989 

– provided to Lawrence Berkeley National Laboratory. 

4 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments data, 1972-1989 

– provided to Lawrence Berkeley National Laboratory. 

5

 U.S. Census Bureau. Characteristics of New Housing, History Tables, 2008. Washington, 

DC. < http://www.census.gov/const/C25Ann/c25ann2008.pdf> 

6 U.S. Census Bureau, Housing and Household Economic Statistics Division. American 

Housing Survey. Washington, DC. 

<http://www.census.gov/hhes/www/housing/ahs/ahs.html>

7 U.S. Census Bureau. Characteristics of New Housing, History Tables, 2008. Washington, 

DC. < http://www.census.gov/const/C25Ann/c25ann2008.pdf> 

8

 U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2010, May, 2010. Washington, DC. DOE/EIA-0383(2010). 

<http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2010).pdf>

9 U.S. Department of Energy–Energy Information Administration. Commercial Building 

Energy Consumption Survey. Washington, D.C. Surveys for 1992, 1995, 1999 and 2003. 

<http://www.eia.doe.gov/emeu/cbecs/>

10 Decision Analyst. 2008 American Home Comfort Survey: Online Database Tool. 2009. 

Arlington, Texas. (URL: http://www.decisionanalyst.com/Syndicated/HomeComfort.dai)

11 S. Hymans. Consumer Durable Spending: Explanation and Prediction, Brookings Papers on 

Economic Activity, 1971. Vol. 1971, No. 1, pp. 234-239.

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

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

Washington, D.C. <www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html>
9-43

 13 U.S. Census Bureau, Housing and Household Economic Statistics Division. American 

Housing Survey. Washington, DC. 

<http://www.census.gov/hhes/www/housing/ahs/ahs.html>

14 U.S. Census Bureau, National Population Projections Released 2008. 

http://www.census.gov/population/www/projections/summarytables.html