17

- i 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

- 2
17.2.2 Assumptions Regarding Non

- Regulatory Policies

................................ ................. 17

- 3
17.2.3 Policy Interactions

................................ ................................ ................................ 17

- 4
17.3 ASSUMPTIONS REGARDIN G NON

- REGULATORY POLICIES

.................... 17

- 4
17.3.1 No New Regul atory Action

................................ ................................ ................... 17

- 4
17.3.2 Consumer Rebates

................................ ................................ ................................ 17

- 4
17.3.2.1 Methodology

................................ ................................ ...................... 17

- 5
17.3.2.2 Analysis

................................ ................................ ............................. 17

- 6
17.3.3 Consumer Tax Credits

................................ ................................ .......................... 17

- 9
17.3.4 Manufacturer Tax Credits

................................ ................................ ................... 17

- 10
17.3.5 Voluntary Energy Efficiency Targets

................................ ................................ .. 17

- 11
17.3.6 Early Replacement

................................ ................................ .............................. 17

- 12
17.3.7 Bulk Government Purchases

................................ ................................ ............... 17

- 14
17.4 IMPACTS OF NON

- REGULATORY ALTERNATI VES

................................ .. 17

- 15

LIST OF TABLES

Table 17.1.1 Non

- Regulatory Alternatives to National Standards

................................ ..... 17

- 1
Table 17.2.1 Efficiency Levels in Proposed Standards for Residential Clothes
Washers

................................ ................................ ................................ ....... 17

- 4
Table 17.3.1 Benefit/Cost Ratios Witho ut and With Rebates for Residential Clothes Washers (2010$)

................................ ................................ .......................... 17

- 7
Table 17.3.2 Market Penetrations in 2015 Attributable to Rebates for Residential
Clothes Washers

................................ ................................ .......................... 17

- 8
Table 17.3.3 Market Penetrations in 2015 Attributable to Consumer Tax Credits for
Residential Clothes Washers

................................ ................................ ...... 17

- 10
Table 17.3.4 Market Penetrations in 2015 Attributable to Manufacturer Tax Credits
for Residential Clothes Wash ers

................................ ................................ . 17

- 11
Table 17.4.1 Impacts of Non

- Regulatory Alternatives for Residential Front

- Loading Clothes Washers that Meet the Proposed C onsensus Standards (TSL 3)

..... 17

- 17
Table 17.4.2 Impacts of Non

- Regulatory Alternatives for Residential Top

- Loading Clothes Washers that Meet the Proposed Consensus Standards (TSL 3)

..... 17

- 18
Table 17.4.3 Impacts of Non

- Regulatory Alternatives for All Residential Clothes Washers that Meet the Proposed Consensus Standard (TSL 3)

................... 17

- 19

LIST OF FIGURES

Figure 17.3.1 Market Penetration Curve for Front

- Loading Clothes Washers

..................... 17

- 7 Figure 17.3.2 Market Penetration Curve for Top

- Loading Clothes Washers

....................... 17

- 817

- ii Figure 17.4.1 Market Penetration of Front

- Loading Clothes Washers Meeting Target Efficiency Levels in Various Policy Cases

................................................. 17-16 Figure 17.4.2 Market Penetration of Top

- Loading Clothes Washers Meeting Target Efficiency Levels in Various Policy Cases

................................................. 17-1617

- 1 CHAPTER 17. REGULATORY IMPACT AN ALYSIS

17.1 INTRODUCTION

The U.S. Department of Energy (DOE) has determined that energy conservation
standards for consumers of residential clothes washers constitute an “economically significant regulatory action” under Executive Order (E.O.) 12866

, Regulatory Planning and Review . 58 FR 51735 (October 4, 1993). Under 10 CFR part 430, subpart C, appendix A, section III.12, DOE committed to evaluating non

- regulatory alternatives to proposed standard s by performing a regulatory impact analysis (RIA). 61 FR 36978 ( November 15, 1996)

. 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 standard s. 58 FR 51735, 51741. As noted in E.O. 12866, t his RIA is subject to review by the Office of Management and Budget’s Office of Information and Regulatory Affairs. 58 FR 51735, 51740.

For this RIA , DOE used an integrated model built on the national impacts analysis ( NIA )
model discussed in chapter 10 . DOE studied the impacts of non

- regulatory policies for the two product classe s that are the subject of this rulemaking : front

- loading and top

- loading clothes
washers

. DOE identified six non

- regulatory policy alternatives that po tentially could achieve the

same energy efficiency leve ls as the proposed consensus standard s . The non

- regulatory policy
alternatives are listed in Table 17 .1.1. 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 s

.

Table 17.1.1 Non

- Regulatory Alternatives to National Standa rds No New Regulatory Action

Consumer Rebates

Consumer Tax Credits

Manufacturer Tax Credits Voluntary Energy Efficiency Targets Early Replacement

Bulk Government Purchases

Sections 17 .2 and 17 .3 d e sc ribe DOE’s analysis of the six policies listed above. Sections
17 .4 and 17 .5 present the results of the analysis

.

17.2 NON

- REGULATORY POLICIES

This section describes the method s DOE used to analyz e the energy savings and cost

effectiveness of the six non

- regulatory policy alternatives (excluding the alternative of no new regulatory action) for residential clothes washers

. This section also describes the assumptions underlying the analysis.17

- 2 17.2.1 Methodology

DOE used its integrated NIA

- RIA spreadsheet model t o calculate the national energy savings (NES) and net present value (NPV) associated with each non

- regulatory policy
alternative . Chapter 10 of the technical support document (TSD) describes the NIA spreadsheet
model . Appendix 17

- A , section 17

- A .3

, documen t s DOE’s us e of the integrated NIA

- RIA model.

DOE quantified the effect of each alternative on the purchase of products that meet target levels , which are defined as the efficiency levels in the proposed consensus standard s. After establishing the assumptions underlying each alternative, DOE revised inputs to the NIA

- RIA
model . The primary revised inputs were market shares of prod ucts meeting target efficiency
levels and produc t replacement rates. The shipments of products for any given year reflect a distribution of efficiency levels. DOE assumed that the proposed standard s would affect 100 percent of the shipments of products that d o not meet target levels 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
residential clothes washers attributable to each policy alternative.

Increasing the efficiency of a product often increases its average installed cost. O perating costs generally decrease , however, because energy consumption declines. DOE therefore
calculated an NP V for each non

- regulatory alternative in the same way it did for the proposed
standard s. In some scenarios, increases in total installed cost are mitigated by government
rebates or tax credits. Because DOE assumed that consumers would re

- pay credits and re bates in some way (such as additional taxes) , DOE did not include rebates or tax credits as a consumer 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.

a T he base case for the NIA is a market

- weighted average of units that operate at several efficiency levels.17

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

**•** National energy savings (NES) , given in quadrillion British thermal units (quads), describes the cumulative national primary energy savings for products bought from the effective date of the policy ( 2015 ) through the end of the analysis period ( 2044 ).

**•** Net present value (NPV) represents the value in 20 1 0$ (discounted to 2011 ) of net monetary savings from products bought from the effective date of the policy ( 2015 ) through the end of the analysis period ( 2044 ).

**•** DOE calculated the NPV as the difference between the present value of installed product cost s and operating expendit ures in the base case and the present value of
th o se 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 consumers’ responses to a program. Because the projected effects depend on assumptions regarding the rate of consumer partici pation, they are subject to more uncertainty than are the impacts of mandatory standards, which DOE assumes will meet with full compliance. To increase the robustness of the analysis, DOE conducted a literature review regarding each non

- regulatory policy a nd consulted with recognized experts to gather information on similar incentive programs that have been implemented in the United States. By studying experienc es with various programs, DOE sought to make credible assumptions regarding potential market impa cts. 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 modeling of each policy.

Each non

- regulatory policy that DOE considered would improve the aver age efficiency
of new residential clothes washers relative to their base

- case efficiency scenarios (which involve no new regulatory action). The analysis considered that each alternative policy would induce consumers to purchase units having the same (targ et) efficiency levels as required by the proposed standard s

. As opposed to the standards case, however, the policy cases may not lead to 100 percent market penetration of units that meet target levels.

Table 17 .2. 1 show s the efficiency levels stipulated in the proposed standard s for
residential clothes washers

.17

- 4 Table 17.2.1 Efficiency Levels in Proposed Standard s for Residential Clothes Washers

Front

- Loading Top

- Loading

TSL I MEF * IWF † I MEF IWF

Consensus (3) 1.84 4.73 1/1/2015 1.29 1/1/2015 8.44

1/1/2018 1.57 1/1/2018 6.47

* I MEF = integrated modified energy factor

. † IWF = integrated water factor

.

DOE assumed that the effects of non

- regulatory policies would last from the effective
date of standards

— 2015

— through the end of the analysis period, which is 2044

.

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 early replacement implemented with consumer rebates, or early replacement implemented with bulk government purchases. However, DOE made conservative assumptions
to avoid double

- counting policy impacts. The resulting impacts may not be added ; the combined effect of several or all policies cannot be inferred from summing their results.

Section 17

. 4 presents graphs that illustrate the market penetration estimated under each

non

- regulatory policy , along wit h tables that summarize the i mpacts of the non

- r egulatory policy

a lternatives for residential clothes washers

.

17.3 ASSUMPTIONS REGARDING NON

- REGULATORY POLIC IES

The following subsections describe DOE’s analysis of the impacts of the six non

regulatory policy alternatives. Because the alternative of No New Regulatory Action does not
affect energy use or NPV, but essentially represent s the NIA base case, DOE did not analyze that
alternative further

. DOE developed estimate s of the market pe netration of high

- efficiency products both with and without each of the non

- regulatory policy alternatives

.

17.3.1 No New Regulatory Action

The case in which no new re gulatory action is taken with regard to the energy efficiency
of residential clothes washers constitutes the base case, as described in C hapter 10, National Impact Analysis. The base case provides the basis of comparison for all other policies. By
definiti on, no new regulatory action yields zero energy savings and an NPV of zero dollars.

17.3.2 Consumer Rebates

DOE considered th e scenario in which the Federal government would provide consumers with financial incentives , in the form of rebate s, for purchasing energy

- efficient appliances

. This policy provides a consumer rebate for purchasing clothes washers that operate at (or above) the
target efficiencies stipulated in the proposed standard s

.17

- 5 17.3.2.1 Methodology

To inform its estimate of the market im pacts of consumer rebates, DOE re search ed utility and agency rebate programs for residential clothes washers nationwide . DOE also reviewed the current State Energy Efficient Appliance Rebate Program (SEEARP) funded by the American Recovery and Reinvestment Act (ARRA)

. 1 , b SEEARP may be considered a combination of a consumer rebate and an early replacement program, with intention to induce appliance sales during the economic recession. DOE analyzed summary material from DOE on SEEARP rebates
for clothes washers

. 2

DOE also incorporated previous research that disaggregated the effe ct of rebates into a direct price effect , which deriv es from the savings in purchase price

, and an announcement effect , which is independent of the amount of the incentive

. 3 , 4 T he 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 policy would encompass both dire ct price effect s and announcement effect s, and that half the increase in market penetration associated with the policy would be due to the direct price effect and ha lf to the announcement effect.

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., c summarize d experience s with various utility rebate programs. 5 3 XENE RGY’s analytical
method utilized penetration c urves 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, 6 , 7 , 8 , 9 , 10 , 11

9 used different economic parameters ( e.g. , payback period), expert surveys,

or model calibration based on specific utility program data rather than multi

- utility data

. Some
models use d in evaluating programs were so client

- specific that generic relationships between economic parameters and consumer res ponse could not be established. DOE decided that the
most appropr iate method for this RIA 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 prima rily 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 exte rnal information diffusion.

b SEEARP provide s Federal funding for State

- run rebate programs for purchases of new ENERGY STAR

- qualified home appliances. SEEARP was implemented in late 2009 by the 50 States and six U.S. territories, each selecting its own appliances, rebate levels, efficiency levels, appliance recycling requirements, and eligible populations.

c XENERGY is now owned by KEMA, Inc. ( www.kema.com ).17

- 6 XENERGY’s model 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 p enetration (or implementation) curves for a measure. XENERGY then 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 rebate programs that change the B/C ratio. The penetration curves depict various diffusion patterns based on perceived barriers (from
no barriers to extremely high barriers ) to consumer purchase of high

- efficiency products.

DOE adjusted the XENERGY penetration curves based on expert advice founded on more recent utility program experience. 9

, 12

17.3.2.2 Analysis DOE also devised an interpo lation method to create penetration curves based on relati onships between the actual base

- case market penetrations and
B/C ratios for each product class. Appendix 17

- A , section s 17

- A .4 .2 and 17

- A .4 .3, discu ss DOE’s method for adjusting and interpolating th e curves. DOE modeled the effects of a consumer rebate policy for residential clothes washers by determining the increase s in market penetration of products meeting the target level relative to their market penetration s in the base case. It did this using t he interpolated penetration curve s created for each product class based on
the XENERGY methodology to reflect the market barrier levels faced by that product class.

DOE estimated the effect of increasing the B/ C ratio of each product class via a rebate
that would pay part or all of the incr eased installed cost of a unit me e t ing the target efficiency level compared to one meeting the baseline efficiency l evel

. d DOE based the rebate amount s on a large sample of 163 rebates for residential clot hes washers initiated by 119 utilities or agencies in
various States

. Appendix 17

- A, section 17

- A.5 .1, identifies and provides details regarding utility rebate programs. DOE calculated t he simple average of the rebate amounts for units meeting or exceeding the target levels in the various programs. DOE assumed that t h ose average rebate

amounts would apply to all units that meet or exceed the target efficiency level for each product
class. DOE assumed th at rebates would remain in effect at the sa me levels throughout the forecast period ( 2015

– 2044 ).

For each product class, DOE first calculated the B/C ratio without a rebate using the difference in total installed costs and lifetime operating cost savings between the unit meeting the target leve l 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 l arger B/C ratio. Table 17 .3.1 shows the effects of con sumer rebates
on B/C ratios for both product classes. Each B/C value for units given rebates represen ts a

d 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

- 7 weighted average e of the values for the efficiency levels at or above the target level to which the rebate would apply.

Table 17.3.1 Benefit/Cost Ratios Without and W ith Rebates for Residential Clothes
Washers ( 20 10$ )

Front

- Loading Top

- Loading

B/C Ratio Without Rebate 33.8 36 .6

Rebate Amount $ 82 $ 61

B/C Ratio w ith Rebate Inf. * Inf.

Calculated Market Barrier Curve Low

– Moderate X

– high

* Inf. = infinite B/C ratio, which occurs when the rebate pays the full incremental cost.

DOE used the B/C ratios along with the penetration curve s shown in Figures 17 .3.1 and
17 .3. 2 to estimate the percentage of consumers who would purchase clothes washers that meet the target levels both with and without a rebate incentive. The curve calculated by DOE to represent the market behavior for front

- loading clothes washers was between t he low and
moderate barriers penetration curve s . For top

- loading clothes washers the curve was close to the extremely high barriers curve

.

Figure 17.3.1 Market Penetration Curve for Front

- Loading Clothes Washers

e The weighting factor is the 2015 base

- case market share of each corresponding efficiency level. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 10 20 30 40 50 60 70 80 90 100Penetration Rate

Benefit/Cost Ratio

Low Estimated Moderate No Rebate With Rebate17

- 8 Figure 17.3.2 Market Penetration Curve for Top

- Loading Clothes Washers

For each product class, DOE next estimated the percent increase represented by the change in penetration rate shown by the penetration curve s . It then added that percent increase to

t he 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 case. Table 17.3.2 summarizes the market shares for
the two product classes in 2015 . DOE used the resulting increase s in market shares as inputs t o represent the policy

- case scenari os in its NIA

- RIA model. Appendix 17

- A, section 17

- A.2

, shows the annual market share increases attributable to this policy. Section 17.4 below presents the resulting efficiency trends for the policy case of consumer rebates for residential clothes
washers

.

Table 17.3.2 Market Penetrations in 2015 Attributable to Rebates for Residential Clothes
Washers

Front

- Loading Top

- Loading
%

Base

- Case Market Share of Units that Meet Target Levels %

72 13 Market Share of Units that Meet Target
Levels w ith Rebates 77 33
Increased Market Share of Units that Meet Target Level w ith Rebates 5 20 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 10 20 30 40 50 60 70 80 90 100Penetration Rate

Benefit/Cost Ratio

High Estimated xHigh No Rebate With Rebate17

- 9 17.3.3 Consumer Tax Credits

DOE used its previous analysis of consumer participation in tax credits to estimate the
effects of tax credits on consumer purchases of target

- level clothes washers

. In estimat ing the effects, DOE assumed the amount of the tax credit s for each product class would be the same as the corresponding rebate amounts described above

. As with rebates, DOE incorporated previous

resear ch that disaggregated the effect of 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. 3

, 4 The announcement effect derives from the credibility that a technology
receives fro m being included in an incentive program, as well as changes in product marketing and modifications in markup and pricing. DOE assumed that the consumer tax credit polic y, like the rebate policy, would encompass both direct price effects and announcement effects, and that half the increase in market penetration associated with the policy would be due to the direct price
effect and half to the announcement effect.

DOE estimated that fewer consumer s 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
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. 13

In develop ing its assumptions , DOE reviewe d other Federal and State tax credit programs offered for energy efficient appliances. The Energy Policy Act of 2005 (EPACT 2005) included Federal tax credits for consumers who purchase d energy efficient produc t s , including water heaters, furnaces, and fur nace fans for new or existing homes. 14

1 Those tax credits were in effect in 2006 and 2007, expired in 2008, and were r einstated for 2009

– 2010 by ARRA. , 15 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 from the 1980s. DOE did not find data specific enough to
residential clothes washers to warrant adjusting its analysis method for the policy case of

c onsumer t ax c redits. Appendix 17

- A, section 17

- A.6 .1

, contains more information on Federal
consumer tax credits.

DOE supported its approach using data from Oregon State’s tax credit program for energy efficient appliances. DOE reviewed its previous analysis o f Oregon’s tax credits for
clothes washers. 16 In the 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 efficiencies . This finding supports DOE’ s 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 is in Appendix 17

- A, section 17

- A.6 .3

.17

- 10 DOE applied the assumed 60

- percent participation rate to the penetration rates estimated
for the r ebate 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 selected for each product class. Table 17 .3. 3 summarize s DOE’s assumptions

r egarding the market penetration in 2015 of residential clothes washers tha t meet target efficiency levels given a consumer tax credit.

Table 17.3.3 Market Penetrations in 2015 Attributable to Consumer Tax Credits for
Residential Clothes Washers

Front

- Loading
% Top

- Loading

Base

- Case Market Share of Units that Meet Target Levels %

72 13 Market Share of Units that Meet Target
Levels w ith Consumer Tax Credits 75 25
Increased Market Share of Units that Meet Target Level w ith Consumer Tax Credits 3 12

DOE assumed that this policy would transform the market permanently, so that the
increase s in market share s seen in the first year of the program would be maintained throughout the forecast period. The increased market shares attributable to consumer tax credit s shown in
Table 17 .3. 3 were used as inputs in the NIA

- RIA model. Appendix 17

- A, section 17

- A.2 , shows
the annual increas es in market share s attributable to this policy. Section 17 .4 below presents the resulting efficiency trends for the policy case of consumer tax credits for residential clothes
washers that meet target efficiency levels

.

17.3.4 Manufacturer Tax Credits

To analyze the potential effects of a policy that offers tax credits to manufacturers that produce residential clothes washers that meet target efficiency levels, DOE assumed that such a tax credit would lower the consumer’s purchase cost by an amount equivalent to that provided by
the consumer rebate or tax credit described above. DOE further assumed that manufacturers
would pass on some of their reduced costs to consumers, causing a di rect price effect. DOE assumed that no announcement effect would occur, because the program would not be visible to

consumers. f

3 Because the direct price effect is approximately equiva lent to the announcement
effect

, 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 products. This assum ed participation rate is equal to 30 percent of the number of consumers who would participate in a rebate program. DOE applied the assumption of 30

- percent participation

f This is a conservative assumption, because manufacturers or utility/agency efficiency programs might promote those models for which manufacturers increase production because of the tax credits, which in turn might induce

some announcement effect. DOE, ho wever, 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 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 selected for each product class.

DOE attempted to in vestigate manufacturer response to the Energy Efficient Appliance
Credits for manufacturers , which were mandated by EPACT 2005. 17 Those tax credits were in
effect for clothes washer models produced in 2006 and 2007 a nd then reinstated for 2009 and
2010 . DOE was unable to locate data from the In ternal Revenue Service or other sources on manufacturer response to the Federal credits. Appendix 17

- A , section 17

- A.6 .2 presents details

o f Federal manufacturer tax credits.

Table 17 .3.4 summarize s DOE’s assumptions regarding the market penetration in 2015 of
residential clothes washers meeting target efficiency levels given a manufacturer tax credit.

Table 17.3.4 Market Penetrations in 2015 Attributable to Manufacturer Tax Credits for
Residential Clothes Washers

Front

Loading
% Top

Loading

Base

- Case Market Share of Units that Meet Target Levels %

72 13 Market Share of Units that Meet Target Levels

w ith Manufacturer Tax Credits 73 19 Increased Market Share of Units that Meet Target
Level w ith Manufacturer Tax Credits 2 6

DOE assumed that th e manufacturer tax credit policy would transform the market permanently, so that the increase s in market share seen in the first year of the program would be maintained throughout the forecast period. The increased market shares attributab le to a
manufacturer tax credit shown in Table 17 .3. 4 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 below presents the resulting efficiency trends for the policy case of manufacturer
tax credits for residential clothes washers

.

17.3.5 Voluntary Energy Efficiency Targets

F or this scenario , DOE assumed that voluntary energy efficiency targets would be achieved as manufacturers gradually stopped producing units that operated below target levels. DOE assumed that the impetus for phasing out production of low

- efficiency units w ould be a program similar to the ENERGY STAR labeling program conducted by the Envir onmental Protection Agency and DOE. The program specifie s the minimum energy efficienc ies that various products, including residential clothes washers , must have to receive the 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 qual ifying appliances.17

- 12 Program efforts generally involve a combination of information dissemination and utility or agency rebates. Researchers have analyzed the ENERGY STAR program’s effects on sales of several consumer products based on State

- specific data on percentages of shipments of appliances that meet ENERGY STAR specifications. The analyses generally have concluded that the market penetration of ENERGY STAR

- qualifying appliances is higher in regions or States where ancillary promotional programs have be en active. 18 , 19 , 20

ENERGY STAR projects market penetration of compliant appliances and estimates the percentage of sales of compliant appliances that are attributable to the program. DOE estimated the percentage of market shares attributable to the ENERGY STAR program for residential
clothes washers for 1997

– 2025. 21 DOE then assumed that

, beginning in 2015, an enhanced ENERGY STAR program for each product class would add 50 percent to the annual increases in

ma rket penetration shown by existing program s

. From this forecast DOE calculated the annual percent increases in market share represented by the shipments attributed to ENERGY STAR

. DOE added those percent increases to the market share s of residential clothes washers that me et target level s in the RIA base case , starting in 2015 , to obtain the annual market share s of units meeting the target efficiency level in the voluntary efficiency targets case

.

DOE estimated that the programs developed in support of voluntary efficiency targets would increase mar ket shares of ef ficient units

. Appendix 17

- A, section 17

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

- RIA model. Section
17 .4 below presents the resulting efficiency trends for the policy case of voluntary energy efficiency targets for clothes washers that meet target efficiency levels.

17.3.6 Early Replacement

The non

- regulatory policy of early replacement refers to a program to replace residential appliances before the ends of their useful lives. The purpose of such a policy is to replace old, inefficient units with higher efficiency units. The economic feasibility of early replacement depends on the vintage of the unit being replaced, the installed cost of the new unit , and th e energy cost savings. DOE examin ed several resources to inform its analysis of th e policy. One report detailed the Connecticut Appliance Retirement Program (ARP) , which was conducted in
2004. 22 Another was a 2006 study of the potentials for electric energy efficiency performed for
the State of Vermont. 23

The Connecticut ARP was conducted from June through December 2004 by Nexus Market Research, Inc., and RLW Analytics, Inc., for Northeast Utilities

– Connecticut Light and Power and the United Illuminating Company’s State programs. The purpose of the ARP was to help Connecticut utility customers overcome barriers to recycling room air conditioners (RACs), secondary refrigerators, and freezers. The program picked up used appliances at customers’
homes or at turn

- in events, paid participants to retire their unit s, and educated customers about the costs of operating older appliances. In addition, the program provided consumers with financial incentives to replace inefficient RACs with ENERGY STAR

- qualified units. DOE
consider s the RAC program to most closely resem ble the early replacement policy scenario for
residential clothes washers , because consumers replaced primary units rather than retiring second17

- 13 units. Nexus/RLW used program data and surveys to estimate the number of RACs retired by ARP participants, the p ercentage of retired units that were replaced with an ENERGY STAR model, and the number of RACs replaced by non

- participants during the program. According to the Nexus/RLW analysis, about 7 percent of all RACs retired during the program were retired throug h the ARP, and 63 percent of those were replaced with ENERGY STAR models. Thus the program resulted directly in about 4 percent of total eligible RAC consumers deciding on early replacement of inefficient units.

In 2006, GDS Associates, Inc., conducted a study for the State of Vermont of the potential for reducing electricity use and peak demand through energy efficiency and fuel conversion measures. The study took an aggressive, multi

- program approach, one aspect of which was early replacement of appli ances. GDS considered that under the program residential appliances, including RACs, would be replaced during 4 years (2006

– 2009). GDS estimated achievable market penetrations assuming that consumers would receive a financial incentive equal to 50 percent of the incremental cost of each program measure. GDS assumed a maximum
80

- percent penetration. For early replacement of RACs, GDS estimated a maximum achievable participation of 5 percent of eligible single

- family or multi

- family homes in the year before t he program began (2005).

DOE also reviewed a study it had conducted in the 1990s, under EPACT 1992, which analyzed the effectiveness of Federal programs that support ed early retirement of appliances

. 24

Th e study identified policy options for early replace ment that included a direct national program ; replacement of Federally owned appliances ; and promotion through equipment manufacturers, consumer incentives, incentives to utilities, and building regulations. g

For this RIA analysis, DOE analyzed a program to target installed units having efficiency levels lower than target level s and encourag e their early replacement with products that perform at target level s

. For each product class , DOE modeled th e effects of the early replacement policy by increasing by 4 percent per year the retirement rate of units that were in the stock in the first year of the analysis period (2015 ) . DOE used the 4

- percent rate from the Connecticut study

, because it was based on real

- world experience. DOE assu med that the early replacement program would continue until it had facilitated the replacement of all eligible residential clothes
washers in the stock in the year the program began (2015). S hipments of new units in 2015 and beyond were not affected by th e program , but remained at base

- case efficiency levels. After the
stock of inefficient units was replaced completely

, the policy would produce no additional impacts.

g The analysis concluded that, although cost

- effective opportunities for early replacement exist, a widespread

Fe deral program was not justified economically. Because early retirement means that a unit may be replaced by an appliance less efficient than the eventual replacement would have been, energy savings would be less than anticipated. Early replacement programs also could increase long

- term sales volatility by encouraging a temporary increase in production

, followed by a lull in demand. Early replacement could be economical in localities subject to high energy costs or environmental constraints ; when replacement appliances are much more efficient than existing
stock ; or when a major technology breakthrough has occurred, creating the need for a ready market.17

- 14 An early replacement policy would create a fairly immediate jump in shipments of produc ts that meet target efficiency le vels

, leading to an immediate gain in the market share of efficient units compared to the base case. As opposed to the policy cases discussed previously, however, an early replacement policy results in market shares of effi cient units returning to base

case percentages as the eligible market is depleted. In addition, because units removed early from the stock would have been replaced later (at the ends of their useful lives) without the program, the number of shipments in la ter years drops below the base

- case shipments forecast. Section
17 .4 below presents the resulting efficiency trends for the policy case of early replacement for
residential clothes washers

.

17.3.7 Bulk Government Purchases

DOE assumed that a policy requiring bulk government purchases would lead to Federal, State, and local governments purchasing products that meet target efficiency levels. Combining
the market demands of multiple public sectors would provide a market signal to manufacturers and vendors that some of their largest customers seek products that meet an efficiency target at favorable prices. Such a program also could induce “market pull,” whereby manufacturers and
vendors would achieve economies of scale fo r high efficiency products.

Most of the previous bulk government purchase (procurement) initiatives at the Federal, State, and municipal levels have not tracked data on number s of purchases or degree of compliance with procurement specifications. In ma ny 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 pot ential 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 de monstrated 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 pro grams are feasible. 25 , 26

DOE assumed that government agencies, such as the Department of Housing and Urban Development, would administe r bulk purchasing program s for residential clothes washers . The policy also w ould be incorporated into the FEMP program . The FEMP program currently has procurement guidelines in place for residential clothes washe rs

. 27 Federal construction requirements include the FEMP guidelines for installing or replacing equipment. DOE reviewed
its own previous rese arch 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 purchas es in 2000 already incorporated energy efficiency requirements based

on FEMP guidelines. One scenario in the DOE report showed energy efficient purchasing

ram ping up during 10 years from 20 percent to 80 percent of all Federal purchases. 28 Based on its study, DOE estimated that a bulk government purchas e program instituted within a 10

- year17

- 15 period would result in at least 80 percent of government

- purchased residential clothes washers meeting target efficiency levels.

DOE ass umed that bulk government purchases would affect a subset of housing unit s for which government agencies purchase or influence the purchase of clothes washers . This subset
consist s primari ly of public housing and housing on military bases. DOE defined this subset based on the American Housing Survey (AHS) for 2009, which identified 1.8 million households, or about 1.4 percent of all U.S. households , as publicly owned housing

. 29 ( T he AHS
reports 130.0 million U.S. households

. 30 ) T he 2005 Reside ntial Energy Consumption Survey ( RECS 2005) reported that 0.2 percent of publicly owned househol ds had fron t

- loading clothes
washers and 40.1 percent had top

- loading clothes washers

. 31 RECS 2005 estimated that 0.5 6 percent of U.S. housing units are publicly owned households that use top

- loading clothes
washers ; this constitute s the population to which this policy would apply. DOE estimated that a miniscule percentage of U

. S

. hous ing units represent publicly owned households that us e front

loading clothes washers; for them the potential energy savings are minor

.

DOE estimated that

, starting in 2015, each year of a bulk government purchase policy
would result in an increasing percent of shipments of government

- purchased units beyond t he
base case would meet target efficiency levels. DOE estimated that within 10 years ( by 2024 )

, bulk government purcha s ing programs would result in 80 percent of the top

- loading clothes
washer market for publicly owned housing meeting target levels. DOE modeled the bulk government purchase program assuming that the market share for each product achieved in 2024
would be maintaine d throughout the rest of the forecast 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 efficiency trends for the policy case of bulk government purchase of residential clothes washers

.

17.4 IMPACT S OF NON

- REGULATORY ALTERNATI VE S

Figures 17.4.1 and 17.4.2 show the effects of all six non

- regulatory policies on market penetration of the two product classes of residential clothes washers. The mark et share of products that meet the target level in the base case is forecasted to be constant for both product
classes

. Relative to the base case, e very policy case increases the market share of products that
meet target efficiency level s. Recall that the proposed consensus standards (not shown in the figures) would result in a 100

- percent market penetration of products that meet the target efficiency level.1 7

- 16 Figure 17.4.1 Market Penetration of Front

- Loading Clothes Washers Meeting Target Efficiency Level s i n Various Policy Cases

Figure 17.4.2 Market Penetration of Top

- Loading Clothes Washers Meeting Target Efficiency Levels in Various Policy Cases

Tables 17 .4 .1 and 17 .4

. 2 show the national energy saving s and net present value s (NPV s )
of the non

- regulatory polic ies analyzed for residential clothes washers . T he target level for each 65.0% 70.0% 75.0% 80.0% 85.0% 90.0%201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044 Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Early Replacement

Bulk Purchasing

Base Case

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044 Consumer Rebate

Consumer Tax Credit

Manufacturer Tax Credit

Voluntary Efficiency Targets

Early Replacement

Bulk Purchasing

Base Case17

- 17 policy equal s the efficiency level in the proposed standard

. These results correspond to the
market shares in Figures 17.4.1 and 17.4.2. The case in which no regulatory action is taken with regard to residential clothes washers constitute s the base case (or "No New Regulatory Action"
scenario ) , in which energy savings and NPV are zero by definition. For comparison, the tables
in clude the impacts of the proposed consensus standard s. Energy savings are given in quads. The

NPV s shown in Tables 17 .4 .1 and 17 .4 .2 are based on two discount rates, 7 percent and 3
percent

.

Table 17.4.1 Impacts of Non

- Regulatory Alternatives for Residential Front

- Loading
Clothes Washers that Meet the Proposed Consensus Standard s (TSL 3)

Policy Alternative Primary Energy Savings Net Present Value*

quads 7%
discount

rate

billion 20 1 0$

3%
discount

rate

Consumer Rebates

- 0.076

- 1.861

- 3.641

Consumer Tax Credits

- 0.045

- 1.119

- 2.190

Manufacturer Tax Credits

- 0.023

- 0.560

- 1.097 Voluntary Energy Efficiency Targets 0.021 0.467 1.316 Early Replacement

Bulk Government Purchases

- 0.001

- 0.013

- 0.029 Proposed Standards

- 0.172

- 4.137

- 8.276

* For products shipped in 2015

– 2044

.17

- 18 Table 17.4.2 Impacts of Non

- Regulatory Alternatives for Residential Top

- Loading
Clothes Washers that Meet the Proposed Consensus Standard s (TSL 3)

Policy Alternative Primary Energy Savings Net Present Value*

quads 7%
discount

rate

billion 20 1 0$

3%
discount

rate

Consumer Rebates 0.641 5.825 13.487

Consumer Tax Credits 0.388 3.519 8.150

Manufacturer Tax Credits 0.195 1.768 4.096 Voluntary Energy Efficiency Targets 0.183 1.151 2.851 Early Replacement

Bulk Government Purchases 0.006 0.040 0.101 Proposed Standards 2.361 20.200 48.072

* For products shipped in 2015

– 2044

.

Note that the national energy savings for front

- loading clothes washers are negative for
the standards case and for most non

- regulatory policy cases. This effect reflects the cross

- price elasticity for total installed costs assumed in the NIA model, which results in market shifts between the two product classes. (See chapter 10 for more discussion on cross

- price elasticity.) The total national energy savings for both product classes together is positive, however. Table
17.4.3 shows the total NES and NPV fo r residential clothes washers for the non

- regulatory policies and standards. Consumer rebates produce the most national energy savings of the six

non

- regulatory policies , while bulk government purchases provide the least savings

.17

- 19 Table 17.4.3 Impacts of Non

- Regulatory Alternatives for All Residential Clothes Washers
that Meet the Proposed Consensus Standard (TSL 3)

Policy Alternative Primary Energy Savings Net Present Value*

quads 7%
discount

rate

billion 20 1 0$

3%
discount

rate

Consumer Rebates 0.566 3.964 9.846

Consumer Tax Credits 0.342 2.400 5.959

Manufacturer Tax Credits 0.172 1.208 2.999 Voluntary Energy Efficiency Targets 0.204 1.618 4.166 Early Replacement

Bulk Government Purchases 0.006 0.027 0.072 Proposed Standards 2.189 16.063 39.796

* For products shipped in 2015

– 2044

.17

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