CHAPTER 17. REGULATORY IMPACT ANALYSIS 

TABLE OF CONTENTS

17.1 INTRODUCTION ......................................................................................................... 17-1

17.2 NON-REGULATORY POLICIES ................................................................................ 17-1

17.2.1 Methodology ...................................................................................................... 17-1

17.2.2 Assumptions Regarding Non-Regulatory Policies ............................................ 17-2

17.2.3 Policy Interactions ............................................................................................. 17-3

17.3 NON-REGULATORY POLICY ASSUMPTIONS ...................................................... 17-4

17.3.1 No New Regulatory Action ............................................................................... 17-4

17.3.2 Consumer Rebates ............................................................................................. 17-4

17.3.2.1 Methodology ............................................................................................ 17-4

17.3.2.2 Analysis .................................................................................................... 17-5

17.3.3 Consumer Tax Credits ....................................................................................... 17-9

17.3.4 Manufacturer Tax Credits ................................................................................ 17-11

17.3.5 Voluntary Energy Efficiency Targets .............................................................. 17-12

17.3.6 Bulk Government Purchases ............................................................................ 17-14

17.4 IMPACTS OF NON-REGULATORY ALTERNATIVES ......................................... 17-16

REFERENCES ........................................................................................................................ 17-20

LIST OF TABLES

Table 17.1.1 Non-Regulatory Alternatives to National Standards ................................... 17-1

Table 17.2.1 Proposed Efficiency Levels for CUACs and CUHPs .................................. 17-3

Table 17.3.1 Effect of Consumer Rebates on Benefit/Cost Ratios of CUACs ................. 17-6

Table 17.3.2 Effect of Consumer Rebates on Benefit/Cost Ratios of CUHPs ................. 17-6

Table 17.3.3 Market Penetrations in 2019 Attributable to Consumer Rebates for 

CUACs (TSL 3) ........................................................................................... 17-9

Table 17.3.4 Market Penetrations in 2019 Attributable to Consumer Rebates for 

CUHPs (TSL 3)............................................................................................ 17-9

Table 17.3.5 Market Penetrations in 2019 Attributable to Consumer Tax Credits for 

CUACs (TSL 3) ......................................................................................... 17-11

Table 17.3.6 Market Penetrations in 2019 Attributable to Consumer Tax Credits for 

CUHPs (TSL 3).......................................................................................... 17-11

Table 17.3.7 Market Penetrations in 2019 Attributable to Manufacturer Tax Credits 

for CUACs (TSL 3) ................................................................................... 17-12

Table 17.3.8 Market Penetrations in 2019 Attributable to Manufacturer Tax Credits 

for CUHPs (TSL 3) .................................................................................... 17-12

17-i 
Table 17.3.9 Market Penetrations in 2019 Attributable to Voluntary Energy 

Efficiency Targets for CUACs (TSL 3) ..................................................... 17-13

Table 17.3.10 Market Penetrations in 2019 Attributable to Voluntary Energy 

Efficiency Targets for CUHPs (TSL 3) ..................................................... 17-13

Table 17.3.11 Market Penetrations in 2019 Attributable to Bulk Government 

Purchases for CUACs (TSL 3) .................................................................. 17-15

Table 17.3.12 Market Penetrations in 2019 Attributable to Bulk Government 

Purchases for CUHPs (TSL 3) ................................................................... 17-15

Table 17.4.1 Impacts of Non-Regulatory Alternatives for CUACs (TSL 3) .................. 17-19

Table 17.4.2 Impacts of Non-Regulatory Alternatives for CUHPs (TSL 3) .................. 17-19

LIST OF FIGURES

Figure 17.3.1 Market Penetration Curves for CUACs [Top to down: 65,000-135,000 

Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h] ............................. 17-7

Figure 17.3.2 Market Penetration Curves for CUHPs [Top to down: 65,000-135,000 

Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h] ............................. 17-8

Figure 17.4.1 Market Penetration of CUACs in Policy Cases [Top to down: 65,000-

135,000 Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h] ............. 17-17

Figure 17.4.2 Market Penetration of CUHPs in Policy Cases [Top to down: 65,000-

135,000 Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h] ............. 17-18

17-ii
CHAPTER 17. REGULATORY IMPACT ANALYSIS

17.1 INTRODUCTION

 The U.S. Department of Energy (DOE) has determined that energy conservation 

standards for consumers of commercial unitary air conditioners (CUAC) and heat pumps 

(CUHP) constitute an “economically significant regulatory action” under Executive Order (E.O.) 

12866, Regulatory Planning and Review. 58 FR 51735 (October 4, 1993). This RIA, which DOE 

has prepared pursuant to E.O. 12866, evaluates potential non-regulatory alternatives, comparing 

the costs and benefits of each to those of the proposed standards. 58 FR 51735, 51741. 

 For this analysis, DOE used an integrated National Impact Analysis (NIA)-RIA model 

built on the NIA model discussed in Chapter 10 for its analysis. DOE studied the impacts of the 

non-regulatory policies on all CUAC and CUHP equipment classes. 

DOE identified five non-regulatory policy alternatives that possibly could provide 

incentives for the same energy efficiency levels as the proposed standards for the equipment that 

are the subject of this rulemaking. The non-regulatory policy alternatives are listed in 0. DOE 

evaluated each alternative in terms of its ability to achieve significant energy savings at a 

reasonable cost, and compared the effectiveness of each to the effectiveness of the proposed 

standard. 

Table 17.1.1 Non-Regulatory Alternatives to National Standards 

No New Regulatory Action

Consumer Rebates

Consumer Tax Credits

Manufacturer Tax Credits

Voluntary Energy Efficiency Targets

Bulk Government Purchases

 

Sections 17.2 and 17.3 discuss the analysis of five selected policies listed above

(excluding the alternative of no new regulatory action). Section 17.4 presents the results of the 

policy alternatives. 

17.2 NON-REGULATORY POLICIES

 This section describes the method DOE used to analyze the energy savings and cost 

effectiveness of the five non-regulatory policy alternatives for CUACs and CUHPs. This section 

also describes the assumptions underlying the analysis. 

17.2.1 Methodology 

DOE used its integrated NIA-RIA spreadsheet model to calculate the national energy 

savings (NES) and net present value (NPV) associated with each non-regulatory policy 

17-1 
alternative. Chapter 10 of the technical support document (TSD) describes the NIA spreadsheet 

model. Appendix 17-A, Section 17-A.3, discusses the NIA-RIA integrated model approach. 

DOE quantified the effect of each alternative on the purchase of equipment that meet the 

target efficiency level, which is defined as the efficiency level in the proposed standards. After 

establishing the quantitative assumptions underlying each alternative, DOE appropriately revised 

inputs to the NIA-RIA spreadsheet model. The primary model inputs revised were market shares 

of equipment meeting the target efficiency level of each equipment class. The shipments of 

equipment for any given year reflect a distribution of efficiency levels. DOE assumed that the 

proposed standards would affect 100 percent of the shipments of equipment that did not meet the 

target level in the base case,a whereas the non-regulatory policies would affect a smaller 

percentage of those shipments. DOE made certain assumptions about the percentage of 

shipments affected by each alternative policy. DOE used those percentages to calculate the 

shipment-weighted average energy consumption and costs of CUACs and CUHPs attributable to 

each policy alternative. 

Increasing the efficiency of a product often increases its average installed cost. However, 

operating costs generally decrease because energy consumption declines. DOE therefore 

calculated an NPV for each non-regulatory alternative in the same way it did for the proposed 

standards. In some policy scenarios, increases in total installed cost are mitigated by government 

rebates or tax credits. Because DOE assumed that rebates and tax credits would be re-paid in 

some way (such as additional taxes) DOE did not include the total national amount of rebates or 

tax credits as a benefit when calculating national NPV. DOE’s analysis also excluded any 

administrative costs for the non-regulatory policies; including such costs would decrease the 

NPVs slightly.

 

The following are key measures for evaluating the impact of each alternative. 

• National Energy Savings, given in quadrillion Btus (quads), describes the cumulative 

national primary energy savings for equipment purchased during the 30-year analysis 

period starting from the effective date of the policy (2019-2048). 

• Net-Present Value, represents the value of net monetary savings in 2013, expressed in 

2012$, from equipment purchased during the 30-year analysis period starting from

the effective date of the policy (2019-2048). DOE calculated the NPV as the 

difference between the present value of installed product cost and operating 

expenditures in the base case and the present value of those costs in each policy case. 

DOE calculated operating expenses (including energy costs) for the life of the 

product. 

17.2.2 Assumptions Regarding Non-Regulatory Policies

The effects of non-regulatory policies are by nature uncertain, because they depend on 

program implementation, marketing efforts, and on consumers’ responses to a program. Because 

the projected effects depend on assumptions regarding the rate of consumer participation, they 

a

 The base case for the NIA is a market-weighted average of units at several efficiency levels.

17-2 

 
are subject to more uncertainty than are the impacts of mandatory standards, which DOE 

assumes will be met with full compliance. To increase the robustness of the analysis, DOE 

conducted a literature review regarding each non-regulatory policy and consulted with 

recognized experts to gather information on similar incentive programs that have been 

implemented in the United States. By studying experiences with the various types of programs,

DOE sought to make credible assumptions regarding potential market impacts. Section 17.3

presents the sources DOE relied on in developing assumptions about each alternative policy and 

reports DOE’s conclusions as they affected the assumptions that underlie the modeling of each 

policy. 

 Each non-regulatory policy that DOE considered would improve the average efficiency 

of CUACs and CUHPs marketed relative to their base case efficiency scenario (which involves 

no new regulatory action). The analysis considered that each alternative policy would induce 

consumers to purchase units having the same efficiency level as required by the proposed 

standards (the target level). As opposed to the standards case, however, the alternative policy 

cases may not lead to 100 percent market penetration of units that meet the target level. 

Table 17.2.1shows the efficiency level stipulated in the proposed Trial Standard Level 

(TSL) for CUACs and CUHPs. 

Table 17.2.1 Proposed Efficiency Levels for CUACs and CUHPs

Equipment Class Efficiency Levels (IEER) 

for Trial Standard Level 3 

Commercial Unitary Air Conditioners

CUAC ≥65,000 Btu/h and <135,000 Btu/h 14.8

CUAC ≥135,000 Btu/h and <240,000 Btu/h 14.2

CUAC ≥240,000 Btu/h and <760,000 Btu/h 13.5

Commercial Unitary Heat Pumps

CUHP ≥65,000 Btu/h and <135,000 Btu/h 14.6

CUHP ≥135,000 Btu/h and <240,000 Btu/h 13.7

CUHP ≥240,000 Btu/h and <760,000 Btu/h 13.0

 DOE assumed that the effects of non-regulatory policies would last from the effective 

date of standards—2019—through the end of the analysis period, which is 2048. 

17.2.3 Policy Interactions 

DOE calculated the effects of each non-regulatory policy separately from those of the 

other policies. In practice, some policies are most effective when implemented in combination, 

such as voluntary efficiency targets implemented with consumer rebates or tax credits. However, 

DOE attempted to make conservative assumptions to avoid double-counting policy impacts. The 

resulting policy impacts are not additive, and the combined effect of several or all policies cannot 

be inferred from summing their results. 

17-3 
Section 17.4 presents graphs that show the market penetration estimated under each nonregulatory policy for each CUAC and CUHP equipment class. 

17.3 NON-REGULATORY POLICY ASSUMPTIONS

 The following subsections describe DOE’s analysis of the impacts of the five nonregulatory policy alternatives to proposed standards for CUACs and CUHPs. (Because the 

alternative of No New Regulatory Action has no energy or economic impacts, essentially 

representing the NIA base case, DOE did not perform any additional analysis for that 

alternative.) DOE developed estimates of the market penetration of high-efficiency equipment 

both with and without each of the non-regulatory policy alternatives. 

17.3.1 No New Regulatory Action 

 The case in which no new regulatory action is taken with regard to the energy efficiency 

of CUACs and CUHPs constitutes the base case, as described in Chapter 10, National Impact 

Analysis. The base case provides the basis of comparison for all other policies. By definition, no 

new regulatory action yields zero NES and an NPV of zero dollars. 

17.3.2 Consumer Rebates

DOE considered the scenario in which the Federal government would provide financial 

incentives in the form of rebates to consumers for purchasing energy-efficient appliances. This 

policy provides a consumer rebate for purchasing a CUAC or CUHP that operates at (or above) 

the same efficiency level as the one stipulated for the proposed TSL (target level).

17.3.2.1 Methodology 

 To inform its estimate of the market impacts of consumer rebates, DOE performed a 

thorough nationwide search for existing rebate programs for air-cooled unitary air conditioners 

and heat pumps with cooling capacity between 65,000 Btu/h and 760,000 Btu/h. It gathered data 

on utility and agency rebates throughout the nation. 

DOE based its evaluation methodology for consumer rebates on a comprehensive study 

of California’s potential for achieving energy efficiency. This study, performed by XENERGY, 

Inc.,b summarized experiences with various utility rebate programs.

1 XENERGY’s analytical 

method utilized graphs, or penetration curves, that estimate the market penetration of a 

technology based on its benefit/cost (B/C) ratio. DOE consulted with experts and reviewed other 

methods of estimating the effect of consumer rebate programs on the market penetration of 

efficient technologies. The other methods, developed after the referenced XENERGY report was 

published,2, 3, 4, 5, 6, 7 used different approaches: other economic parameters (e.g., payback 

period), expert surveys, or model calibration based on specific utility program data rather than 

multi-utility data. Some models in use by energy efficiency program evaluation experts were so 

client-specific that generic relationships between economic parameters and consumer response 

could not be established.5DOE decided that the most appropriate available method for this RIA 

b XENERGY is now owned by KEMA, Inc. (www.kema.com) 

17-4 

 
analysis was the XENERGY approach of penetration curves based on B/C ratio, which 

incorporates lifetime operating cost savings. 

XENERGY’s model estimates market impacts induced by financial incentives based on 

the premise that two types of information diffusion drive the adoption of new technologies. 

Internal sources of information encourage consumers to purchase new products primarily 

through word-of-mouth from early adopters. External sources affect consumer purchase 

decisions through marketing efforts and information from outside the consumer group. Appendix 

17-A, Section 17-A.4.1, contains additional details on internal and external information 

diffusion. 

XENERGY’s model equation accounts for the influences of both internal and external 

sources of information by superimposing the two components. Combining the two mechanisms 

for information diffusion, XENERGY’s model generates a set of penetration (or implementation) 

curves for a policy measure. XENERGY calibrated the curves based on participation data from 

utility rebate programs. The curves illustrate the increased penetration (i.e., increased market 

share) of efficient products driven by consumer response to changes in B/C ratio induced by 

rebate programs. The penetration curves depict various diffusion patterns based on perceived 

barriers (from “no barriers” to “extremely high barriers”) to consumer purchase of highefficiency products. 

DOE adjusted the XENERGY penetration curves based on expert advice founded on 

more recent utility program experience.5, 8 DOE also used the interpolation method presented in

Blum et al (2011)9 to create penetration curves based on relationships between the actual base 

case market penetrations and actual B/C ratios. 

 DOE modeled the effects of a consumer rebate policy for CUACs and CUHPs by 

determining the increase in market penetration of equipment meeting the target level relative to 

their market penetration in the base case. It did this using the interpolated penetration curve 

created for each CUAC and CUHP based on the methodology presented in Blum et al (2011)9 to 

best reflect the market barrier level faced by each equipment class. Section 17.3.2.2 shows the 

interpolated curves used in the analysis. 

17.3.2.2 Analysis 

For each CUAC and CUHP equipment class it analyzed, DOE estimated the effect of 

increasing its B/C ratio via a rebate that would pay part of the increased installed cost of a unit 

that met the target efficiency level compared to one meeting the baseline efficiency level.

c DOE 

based the rebate amounts on a sample of utility and agency rebate programs for air-cooled 

unitary air conditioners and heat pumps with cooling capacity between 65,000 Btu/h and 760,000 

Btu/h. DOE gathered data on 602 rebates initiated by 86 utilities or agencies in various States.

(Appendix 17-A, Section 17-A.5, identifies the rebate programs.) The rebate programs cover a 

c The baseline technology for each product class is defined in the engineering analysis, Chapter 5, as the technology 

that represents the basic characteristics of products in that class. A baseline unit typically is one that just meets 

current Federal energy conservation standards and provides basic consumer utility. 

17-5 

 
wide range of tonnage and efficiency levels. To represent the rebate level for each CUAC and 

CUHP equipment class, DOE performed statistical analysis on the data it collected. Appendix 

17-A, Section 17-A.5, describes the regression model DOE used and the corresponding results 

for each equipment class. DOE assumed that rebates would remain in effect at the same levels 

throughout the analysis period (2019–2048). 

For each equipment class, DOE first calculated the B/C ratio without a rebate using the 

difference in total incremental installed costs (C) and lifetime operating cost savings (B) between 

the unit meeting the target level and the baseline unit. It then calculated the B/C ratio given a 

rebate for the unit meeting the target efficiency level. Because the rebate reduced the incremental 

cost, the unit receiving the rebate had a larger B/C ratio. Table 17.3.1 and Table 17.3.2 show 

respectively the effect of consumer rebates on the B/C ratios for CUACs and CUHPs. The B/C 

values for units given rebates refer to the efficiency level to which the rebate would apply. 

Table 17.3.1 Effect of Consumer Rebates on Benefit/Cost Ratios of CUACs

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h 

and <240,000 

Btu/h

≥240,000 Btu/h 

and <760,000 

Btu/h

B/C Ratio Without Rebate 84.4 45.8 116.9

Rebate Amount (2012$) 657.92 1245.84 2328.33

B/C Ratio With Rebate 121.3 66.6 217.2

Calculated Market Barrier Curve xHigh xHigh xHigh

Table 17.3.2 Effect of Consumer Rebates on Benefit/Cost Ratios of CUHPs

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h 

and <240,000 

Btu/h

≥240,000 Btu/h 

and <760,000 

Btu/h

B/C Ratio Without Rebate 4.0 1.9 5.9

Rebate Amount (2012$) 628.92 1152.83 2142.30

B/C Ratio With Rebate 5.7 2.6 10.3

Calculated Market Barrier Curve xHigh xHigh xHigh

 DOE used these B/C ratios along with the penetration curves shown in and to estimate 

the percentage of consumers who would purchase CUACs and CUHPs that meet the target level

both with and without a rebate incentive. The penetration curves calculated by DOE to represent 

the market behavior for CUACs and CUHPs are indicated in Figure 17.3.1 and Figure 17.3.2

respectively. 

17-6 
Figure 17.3.1 Market Penetration Curves for CUACs [Top to down: 65,000-135,000 Btu/h; 

135,000-240,000 Btu/h; 240,000-760,000 Btu/h] 

17-7 
Figure 17.3.2 Market Penetration Curves for CUHPs [Top to down: 65,000-135,000 Btu/h; 

135,000-240,000 Btu/h; 240,000-760,000 Btu/h]

 

For each equipment class, DOE next estimated the percent increases represented by the 

change in penetration rate shown on the corresponding penetration curve. It then added this

17-8 
percent increase to the market share of units that meet the target level in the base case to obtain 

the market share of units that meet the target level in the rebate policy case. Table 17.3.3 and 

Table 17.3.4 summarize the market shares in 2019 for CUACs and CUHPs respectively. DOE

used the resulting annual increases in market shares as inputs to represent the rebate policy case 

scenario in its NIA-RIA model. Appendix 17-A, Section 17-A.2, shows the annual market share 

increases due to this policy. Section 17.4 presents the resulting market penetration trends for the 

policy case of consumer rebates for CUACs and CUHPs. 

Table 17.3.3 Market Penetrations in 2019 Attributable to Consumer Rebates for CUACs 

(TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 3.2% 5.9% 4.7%

Increased Market Share 2.9% 5.8% 2.8%

Table 17.3.4 Market Penetrations in 2019 Attributable to Consumer Rebates for CUHPs 

(TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 1.4% 0.4% 6.0%

Increased Market Share 1.1% 0.2% 4.2%

17.3.3 Consumer Tax Credits

DOE estimated the effects of tax credits on consumer purchases based on its previous 

analysis of consumer participation in tax credits. DOE supported its approach using data from 

Oregon State’s tax credit program for energy-efficient appliances. DOE also incorporated 

previous research that disaggregated the effect of rebates and tax credits into a direct price effect, 

which derives from the savings in purchase price, and an announcement effect, which is 

independent of the amount of the incentive.10, 11 The announcement effect derives from the 

credibility that a technology receives from being included in an incentive program, as well as 

changes in product marketing and modifications in markup and pricing. DOE assumed that the 

rebate and consumer tax credit policies would encompass both direct price effects and 

announcement effects, and that half the increase in market penetration associated with either 

policy would be due to the direct price effect and half to the announcement effect. 

In estimating the effects of a tax credit on purchases of equipment that meet new 

efficiency standards, DOE assumed the amount of the tax credit would be the same as the 

corresponding rebate amount discussed above. 

DOE estimated that fewer consumers would participate in a tax credit program than 

would take advantage of a rebate. Research has shown that the delay required for a consumer to 

receive a tax credit, plus the added time and cost in preparing the tax return, make a tax credit 

17-9 
incentive less effective than a rebate received at the time of purchase. Based on previous 

analyses, DOE assumed that only 60 percent of the consumers who would take advantage of a 

rebate would take advantage of a tax credit.12

In preparing its assumptions, DOE also reviewed other tax credit programs that have been 

offered at both the Federal and State levels for energy-efficient appliances.

 

 The Energy Policy Act of 2005 (EPACT 2005) included Federal tax credits for 

consumers who purchase energy-efficient products, including air-conditioners.13 Those tax 

credits were in effect in 2006 and 2007, expired in 2008, were reinstated for 2009–2010 by the 

American Recovery and Reinvestment Act of 2009 (ARRA), extended by Congress for 2011 

with some modifications, and expired at the end of 2011.14, 15 The American Taxpayer Relief 

Act of 2012 extended, with some modifications, residential tax credits for air conditioners, heat 

pumps, furnaces, and water heaters placed in service between January 1, 2012 and December 31, 

2013.16 DOE reviewed Internal Revenue Service data on the numbers of taxpayers who claimed 

the tax credits during tax years 2006 and 2007. DOE also reviewed data from an earlier Federal 

energy conservation tax credit program in place in the 1980s. However, DOE did not find data 

specific enough to commercial air-conditioners to warrant adjusting its analysis method for the 

Consumer Tax Credits policy case. Appendix 17-A, Section 17-A.6.1, contains more information 

on Federal consumer tax credits. 

DOE also reviewed its previous analysis of Oregon’s tax credits for clothes washers to 

provide support for its assumptions.17 In that previous analysis, DOE compared the market 

shares of ultra-high efficiency (UHE) residential clothes washers in Oregon, which offered both 

State tax credits and utility rebates, with those in Washington State, which offered only utility 

rebates during the same period. Based on this analysis, DOE estimated that in Oregon the impact 

of tax credits was 62 percent of the impact of rebates for UHE clothes washers having equivalent

efficiency. This finding supports its original assumption that participation in a tax credit program 

would be about 60 percent of participation in a rebate program. Additional discussion of State

tax credits for Oregon and other states is in Appendix 17-A, Section 17-A.6.3. 

 

DOE applied the assumed 60 percent participation described above to the penetration 

rates estimated for the rebate policy to estimate penetration rates attributable to consumer tax 

credits. In doing so, DOE incorporated the assumptions for consumer response to financial 

incentives from the penetration curves calculated for CUACs and CUHPs. 

Table 17.3.5 and Table 17.3.6 summarize DOE’s assumptions for CUACs and CUHPs

regarding the market penetration of units in 2019 that meet the target efficiency level given a 

consumer tax credit. 

17-10 
Table 17.3.5 Market Penetrations in 2019 Attributable to Consumer Tax Credits for 

CUACs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 2.0% 3.6% 3.6%

Increased Market Share 1.8% 3.5% 1.7%

Table 17.3.6 Market Penetrations in 2019 Attributable to Consumer Tax Credits for 

CUHPs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 0.9% 0.3% 4.4%

Increased Market Share 0.7% 0.1% 2.5%

 DOE assumed that this policy would transform the market permanently, so that the 

increase in market share seen in the first year of the program would be maintained throughout the 

forecast period. The increased market shares attributable to consumer tax credits shown in Table 

17.3.5 and Table 17.3.6 were used as inputs in the NIA-RIA model. Appendix 17-A, Section 17-

A.2, shows the annual market share increases due to this policy. Section 17.4 presents the 

resulting market penetration trends for the policy case of consumer tax credits for CUACs and 

CUHPs that meet the target efficiency level. 

17.3.4 Manufacturer Tax Credits

To analyze the potential effects of a policy that offers tax credits to manufacturers that 

produce CUACs or CUHPs that meet the target efficiency level, DOE assumed that a 

manufacturer tax credit would lower the consumer’s purchase cost by an amount equivalent to 

that provided by the consumer rebates or tax credits described above. DOE further assumed that 

manufacturers would pass on some of their reduced costs to consumers, causing a direct price 

effect. DOE assumed that no announcement effect would occur, because the program would not 

be visible to consumers.d Because the direct price effect is approximately equivalent to the 

announcement effect,

10 DOE estimated that a manufacturer tax credit would induce half the 

number of consumers assumed to take advantage of a consumer tax credit to purchase more 

efficient equipment. Thus the assumed participation rate is equal to 30 percent of the number of 

consumers who would participate in a rebate program. 

DOE attempted to investigate manufacturer response to the Energy Efficient Appliance 

Credits for manufacturers mandated by EPACT 2005.18 Those manufacturer tax credits have 

d Note that this is a conservative assumption, since it is possible that manufacturers or utility/agency efficiency 

programs might promote the models for which manufacturers increase production due to the tax credits, which in 

turn might induce some announcement effect. However, DOE found no data on such programs on which to base an 

estimate of the magnitude of this possible announcement effect on consumer behavior.

17-11 

 
been in effect for dishwashers, clothes washers and refrigerators produced beginning in 2009. 

DOE was unable to locate data from the Internal Revenue Service or other sources on 

manufacturer response to the Federal credits. Appendix 17-A, Section 17-A.6.2, presents details 

on Federal manufacturer tax credits.

DOE applied the assumption of 30 percent participation to the penetration rates predicted 

for the rebate policy to estimate the effects of a manufacturer tax credit policy. In doing so, the 

Department incorporated the assumptions for consumer response to financial incentives from the 

penetration curves calculated for CUACs and CUHPs. 

Table 17.3.7 and Table 17.3.8 summarize DOE’s assumptions for CUACs and CUHPs 

respectively regarding the market penetration of units in 2019 meeting the target efficiency level

given a manufacturer tax credit.

Table 17.3.7 Market Penetrations in 2019 Attributable to Manufacturer Tax Credits for 

CUACs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 1.2% 1.9% 2.7%

Increased Market Share 0.9% 1.7% 0.8%

Table 17.3.8 Market Penetrations in 2019 Attributable to Manufacturer Tax Credits for 

CUHPs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 0.6% 0.2% 3.1%

Increased Market Share 0.3% 0.1% 1.3%

 DOE assumed that this policy would transform the market permanently, so that the 

increases in market share seen in the first year of the program would be maintained throughout 

the forecast period. The increased market shares attributable to a manufacturer tax credit shown 

in Table 17.3.7 and Table 17.3.8 were used as inputs in the NIA-RIA model. Appendix 17-A, 

Section 17-A.2, shows the annual market share increases due to this policy. Section 17.4 presents

the resulting market penetration trends for the policy case of manufacturer tax credits for CUACs 

and CUHPs. 

17.3.5 Voluntary Energy Efficiency Targets 

For each equipment class, DOE assumed that voluntary energy efficiency targets would 

be achieved as manufacturers gradually stop producing units that operate below the target 

efficiency level. DOE assumed that the impetus for phasing out production of low-efficiency 

units would be a program similar to the ENERGY STAR labeling program, conducted by the 

Environmental Protection Agency (EPA) and DOE, and the Better Building Alliance program, 

conducted by DOE in conjunction with industry partners. The ENERGY STAR program 

specifies the minimum energy efficiencies that various products must have to receive the 

17-12 
ENERGY STAR label. ENERGY STAR encourages consumers to purchase efficient products 

via marketing that promotes consumer label recognition, various incentive programs that adopt 

the ENERGY STAR specifications, and manufacturers’ promotion of their qualifying appliances.

The Better Building Alliance introduced in 2011 the High Performance Rooftop Unit Challenge. 

The initiative is based on a design specification for 10-ton capacity commercial air conditioning 

units “expected to reduce energy use by as much as 50 percent compared to the current 

ASHRAE 90.1 standard.” This voluntary energy efficiency target program, similar to the 

ENERGY STAR labeling program, is designed to encourage manufacturers to develop higher 

efficiency commercial air conditioners as a result of commercial buyer’s support for highperformance equipment manufactured in compliance with the aforementioned specification.19 

DOE believes that informational incentive programs – like ENERGY STAR, the High 

Performance Rooftop Unit Challenge, or any other labeling program sponsored by industry or 

other organizations – are likely to reduce the market barriers to more efficient equipment over 

time. During the rebate analysis, when assessing the B/C ratio and market penetration in the base 

case for each equipment class, DOE observed that the market barriers for the six equipment 

classes are extremely high. DOE estimates that voluntary energy efficiency targets could reduce 

these barriers to a moderate level over 10 years, and followed the methodology presented by 

Blum et al (2011)9 to evaluate the effects that such a reduction in market barriers have on the 

market penetration of each equipment class of CUAC and CUHP. The methodology relies on 

interpolated market penetration curves to calculate – given a B/C ratio – how the market 

penetration of more efficient units increases as the market barrier level to those units decreases.

Table 17.3.9 and Table 17.3.10 summarize DOE’s assumptions for CUACs and CUHPs 

respectively regarding the market penetration of units in 2019 meeting the target efficiency level 

under the influence of a voluntary energy efficiency targets program. 

Table 17.3.9 Market Penetrations in 2019 Attributable to Voluntary Energy Efficiency 

Targets for CUACs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 46.7% 40.0% 48.7%

Increased Market Share 46.4% 39.8% 46.8%

Table 17.3.10 Market Penetrations in 2019 Attributable to Voluntary Energy Efficiency 

Targets for CUHPs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 1.9% 0.3% 4.1%

Increased Market Share 1.6% 0.2% 2.2%

DOE estimated that the program developed in support of the voluntary energy efficiency 

targets policy would increase market shares of efficient units. Appendix 17-A, Section 17-A.2, 

shows the annual market share increases due to this policy used as inputs to the NIA-RIA model. 

17-13 
Section 17.4 presents the resulting market penetration trends for the policy case of voluntary 

energy efficiency targets for CUACs and CUHPs.

17.3.6 Bulk Government Purchases 

 Bulk government purchases can lead to Federal, State, and local governments purchasing 

large quantities of equipment that meet the target efficiency level. Combining the market 

demands of multiple public sectors also can provide a market signal to manufacturers and 

vendors that some of their largest customers seek equipment that meet an efficiency target at 

favorable prices. Such a program also can induce “market pull,” whereby manufacturers and 

vendors would achieve economies of scale for high efficiency equipment. 

 Most of the previous bulk government purchase (procurement) initiatives at the Federal, 

State, and municipal levels have not tracked data on numbers of purchases or degree of 

compliance with procurement specifications. In many cases, procurement programs are 

decentralized, being part of larger State or regional initiatives. DOE based its assumptions 

regarding the effects of this policy on studies the Federal Energy Management Program (FEMP) 

performed regarding the savings potential of its procurement specifications for appliances and 

other equipment. FEMP, however, does not track purchasing data, because of the complex range 

of purchasing systems, large number of vendors, and so on. States, counties, and municipalities 

have demonstrated increasing interest and activity in “green purchasing." Although many of the 

programs target office equipment, the growing infrastructure for developing and applying 

efficient purchasing specifications indicates that bulk government purchase programs are 

feasible.

20,21 

 DOE assumed that government agencies would administer bulk purchasing programs for 

CUACs and CUHPs. The policy also would be incorporated into the FEMP program. FEMP 

currently has procurement specifications in place for CUACs and CUHPs based on ENERGY 

STAR requirements. These specifications however do not cover all covered equipment classes.22

DOE assumed the program would be reviewed to meet the efficiency levels corresponding to 

TSL 3 for all covered equipment classes. 

DOE reviewed its own previous research on the potential for market transformation 

through bulk government purchases. Its major study analyzed several scenarios based on the 

assumption that 20 percent of Federal equipment purchases in 2000 already incorporated energy 

efficiency requirements based on FEMP guidelines. One scenario in the DOE report showed 

energy efficient purchasing ramping up during 10 years from 20 percent to 80 percent of all 

Federal purchases.23 Based on this study, DOE estimated that a bulk government purchase 

program instituted within a 10-year period would result in at least 80 percent of governmentpurchased CUACs and CUHPs meeting target efficiency levels. 

 DOE assumed that bulk government purchases would affect the subset of governmentowned commercial buildings cooled by packaged air-conditioners. This subset consists primarily 

of government-owned buildings used for offices, public assembly, education, food service and 

other services. DOE defined this subset based on the primary building activities used for the 

energy use analysis (see Chapter 7). DOE used the 2007 Commercial Buildings Energy 

Consumption Survey (CBECS 2007) to calculate the percentage of the total commercial floor 

space cooled by packaged air-conditioners that corresponds to government-owned buildings. The 

17-14 
calculation resulted in 22 percent. DOE assumed that percentage as the share of the market to 

which this policy would apply. 

DOE estimated that, starting in 2019, each year of a bulk government purchase policy 

would result in an increasing percent of shipments of government-purchased units beyond the 

base case would meet target efficiency levels. DOE estimated that within 10 years (by the end of 

2028), bulk government purchasing programs would result in 80 percent of the CUAC and 

CUHP market for government-owned commercial buildings meeting the target level. DOE 

modeled the bulk government purchase program assuming that the market share for each product 

achieved in 2028 would be maintained throughout the rest of the analysis period. Appendix 17-

A, Section 17-A.2, shows the annual market share increases due to this policy used as inputs to 

the NIA-RIA model. Section 17.4 below presents the resulting market penetration trends for the 

policy case of bulk government purchase of CUACs and CUHPs. 

Table 17.3.11 and Table 17.3.12 summarize DOE’s assumptions for CUACs and CUHPs 

respectively regarding the market penetration of units in 2019 meeting the target efficiency level 

under the influence of a bulk government purchasing program 

Table 17.3.11 Market Penetrations in 2019 Attributable to Bulk Government Purchases for 

CUACs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 2.0% 1.9% 3.6%

Increased Market Share 1.8% 1.8% 1.7%

Table 17.3.12 Market Penetrations in 2019 Attributable to Bulk Government Purchases for 

CUHPs (TSL 3) 

≥65,000 Btu/h and 

<135,000 Btu/h

≥135,000 Btu/h and 

<240,000 Btu/h

≥240,000 Btu/h and 

<760,000 Btu/h

Base-Case Market Share 0.3% 0.2% 1.9%

Policy Case Market Share 2.0% 1.9% 3.6%

Increased Market Share 1.8% 1.8% 1.7%

DOE estimated that the program developed in support of the bulk government purchases 

policy would increase market shares of efficient units. Appendix 17-A, Section 17-A.2, shows 

the annual market share increases due to this policy used as inputs to the NIA-RIA model. 

Section 17.4 presents the resulting market penetration trends for the policy case of bulk 

government purchases for CUACs and CUHPs.

17-15 
17.4 IMPACTS OF NON-REGULATORY ALTERNATIVES

Figure 17.4.1 and Figure 17.4.2 show the effects of each non-regulatory policy on market 

penetration of CUACs and CUHPs respectively. Relative to the base case, the policy cases 

increase the market share of units that meet the target level. Recall that the proposed standards 

(not shown in the figures) would result in a 100-percent market penetration of units that meet the 

target efficiency level. 

17-16 
Figure 17.4.1 Market Penetration of CUACs in Policy Cases [Top to down: 65,000-135,000 

Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h] 

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

17-17 
Figure 17.4.2 Market Penetration of CUHPs in Policy Cases [Top to down: 65,000-135,000 

Btu/h; 135,000-240,000 Btu/h; 240,000-760,000 Btu/h]

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

0%

10%

20%

30%

40%

50%

60%

70%

201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048

Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Govt Bulk Purchasing

Base Case

17-18 
Table 17.4.1 and Table 17.4.2 show NES and NPV for five non-regulatory policies

analyzed in detail for CUACs and CUHPs. The target level for each policy equals the efficiency

level proposed in TSL 3 for each equipment class. 

The case in which no regulatory action is taken with regard to CUACs and CUHPs

constitutes the base case (or "No New Regulatory Action" scenario), in which energy and 

economic savings are zero by definition. For comparison, the tables include the impacts of the 

proposed standards. Energy savings are given in quadrillion British thermal units (quads). The 

NPVs shown in Table 17.4.1 and Table 17.4.2 are based on two discount rates, 7 percent and 3 

percent. 

The policies with the highest projected cumulative energy and economic savings are 

voluntary energy efficiency targets and bulk government purchases. Market barriers to more 

efficient CUACs and CUHPs have been estimated to be extremely high, and this would prevent 

rebates and tax credits to lead to greater market penetration. Voluntary energy efficiency targets 

were assumed to reduce these barriers and, therefore, to lead to a more significant market 

penetration of energy efficient units. Government bulk purchases are not subject to market

barriers and would affect 22 percent of the market leading to market penetrations that are greater 

than the ones resulting from rebates and tax credits.

Table 17.4.1 Impacts of Non-Regulatory Alternatives for CUACs (TSL 3) 

Policy Alternative Primary Energy

Savings 

quads 

Net Present Value*

billion 2012$

7% Disc. Rate 3% Disc. Rate

Consumer Rebates 0.032 0.032 0.128

Consumer Tax Credits 0.019 0.019 0.077

Manufacturer Tax Credits 0.010 0.010 0.038

Voluntary Energy Efficiency Targets 0.666 0.651 2.635

Bulk Government Purchases 0.136 0.123 0.527

Proposed Standards 10.713 15.095 46.712

Table 17.4.2 Impacts of Non-Regulatory Alternatives for CUHPs (TSL 3) 

Policy Alternative Primary Energy

Savings 

quads 

Net Present Value*

billion 2012$

7% Disc. Rate 3% Disc. Rate

Consumer Rebates 0.001 0.002 0.006

Consumer Tax Credits 0.001 0.001 0.004

Manufacturer Tax Credits 0.000 0.000 0.002

Voluntary Energy Efficiency Targets 0.032 0.033 0.126

Bulk Government Purchases 0.007 0.007 0.028

Proposed Standards 0.951 1.446 4.126

17-19 
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17-21