The work described in this technical brief was funded by the National Electricity Delivery Division of the U.S. 

Department of Energy’s Office of Electricity Delivery and Energy Reliability and the U.S. Department of Energy’s Office 

of Energy Policy and Systems Analysis under Lawrence Berkeley National Laboratory Contract No. DE-AC02-

05CH11231. Any questions or feedback may be directed to Ian Hoffman, project lead, ihoffman@lbl.gov. Reviewers 

who provided valuable comments on this report are too numerous to thank by name, but we are deeply grateful for 

their time and improvements to this paper. If you would like to receive notifications of similar energy policy 

publications, join the LBNL Electricity Markets and Policy mailing list here.

T E C H N I C A L B R I E F

April 2015

The Total Cost of Saving Electricity through Utility 

Customer-Funded Energy Efficiency Programs:

Estimates at the National, State, Sector and Program Level

Ian M. Hoffman, Gregory Rybka, Greg Leventis, Charles A. Goldman, Lisa Schwartz, Megan Billingsley, 

and Steven Schiller

Overview

This brief presents the most comprehensive estimates to date of the full cost of saving electricity through 

efficiency programs funded by customers of investor-owned utilities.1,2The total cost of the electricity 

efficiency resource includes the investment by both the program administrator and program participants in 

saving a kilowatt-hour (kWh). It is a valuable metric that resource planners, regulators and stakeholders can use 

to assess and compare the relative costs among efficiency programs and between efficiency and energy supply 

investments.

A previous report (Billingsley et al. 2014) drew upon the Lawrence Berkeley National Laboratory (LBNL) 

Demand-Side Management (DSM) Program Database3to assess the costs to program administrators of saving 

electricity. For this brief, we updated the database with information from 20 states4 where one or more 

program administrators reported sufficient data for analysis of total costs. Based on more than 2,100 program 

years5of data, we compare the total cost versus the program administrator cost of saved electricity at the 

national and state levels, for market sectors and for the most prevalent program types.

The U.S. average total cost of saved electricity, weighted by energy savings, was $0.046 per kWh for the period 

2009 to 2013 for our dataset (see Table 1).

The median value for programs with claimed energy savings across all sectors was $0.069 per kWh. This 

difference between the average and median reflects the fact that some programs delivered a large share of 

overall savings at a low total cost.

 

1

This brief focuses on the cost of saved electricity; we will explore the total costs of natural gas efficiency programs as more data become 

available.

2

Data collected for this analysis came from state regulatory filings or similar documents filed by investor-owned utilities (or third-party 

program administrators). We did not include data on efficiency programs funded by customers of rural cooperatives, municipal utilities, 

tribal utilities, or other publicly owned utilities—except in the few instances where those entities contributed to the budgets of thirdparty program administrators. 

3

The LBNL DSM Program Database is an ongoing collection of spending, savings and other data for utility customer-funded electric and 

natural gas efficiency programs. The database contains more than 6,000 program years of data, which represents about 1,700 programs 

across multiple years from 34 states.

4

Data are from the following states: AR, AZ, CA, HI, IA, ID, MA, MD, ME, MN, NC, NM, OK, OR, PA, RI, SC, UT, VT, and WA. 

5

A program year (PY) is a year’s worth of data for each program in the LBNL DSM Program Database. For example, data covering four 

years of spending and impacts for a particular program represent four program years.
T E C H N I C A L B R I E F 2

Table 1. Savings-weighted average total cost of saved electricity at the national level by market sector

Sector

Total Cost of Saved 

Electricity 

(2012$/kWh)*

Program Administrator 

Cost of Saved Electricity 

(2012$/kWh)

Participant Cost of 

Saved Electricity 

(2012$/kWh)

All Sectors $0.046 $0.023 $0.022

Residential $0.033 $0.019 $0.014

Commercial, Industrial, and Agricultural $0.055 $0.025 $0.030

Low Income $0.142 $0.134 $0.008

*Note: Totals may differ from sum of component values due to rounding.

Program participants paid widely varying shares of the costs of efficiency activities, depending on the design of 

individual programs (e.g., no direct cost contribution for certain behavioral feedback, direct-install,

6

and lowincome programs, and higher participant cost shares for commercial/industrial custom rebate programs). 7,8

Overall, program administrators and participants split the costs of saving electricity almost exactly in half in our 

program sample, such that total costs were about twice what utilities and other efficiency program 

administrators on average paid for those energy savings ($0.023/kWh).

We also found that program administrators in fewer than half of states with efficiency programs funded by 

electric utility customers report total costs and savings. More complete reporting of program-level results 

would result in a larger study sample and increase representation from regions where efficiency programs are 

ramping up. Inconsistent data reporting practices also pose challenges. For example, where full costs are 

reported, differing definitions and interpretations of the components of total costs can make aggregating and 

comparing data challenging. We identify key data inputs (e.g., lifetime savings, incremental measure costs) for 

which more consistent reporting would improve insights into efficiency programs, policies and system needs.

Introduction 

The cost of saved energy is a useful metric for assessing what efficiency costs across different program 

types, among program administrators and over time (Billingsley et al. 2014).9 The cost of saved energy is 

expressed as dollars or cents per kilowatt-hour of electricity or per therm of natural gas. It is not directly 

affected by differences in energy prices or other benefits across markets and utility territories.10 This 

simplicity makes the cost of saved energy valuable as a standard yardstick across territories and states and 

different efficiency activities.

The program administrator cost of saved energy enables assessments of efficiency resources from the 

economic perspective of the utility, and so is useful to program administrators, regulators, and other 

stakeholders. Resource planners and grid operators often rely on the program administrator cost of saved 

 

6

Direct-install programs typically deliver a set of prescribed or pre-approved high-efficiency equipment or measures that are installed 

under contract to the program administrator and typically do not involve a cost contribution from participants.

7 We define participant costs as the out-of-pocket funds paid by participants for measures and their installation, exclusive of any 

incentives paid to the customer by the program administrator. Indirect or softer costs, such as customers’ transaction cost of 

investigating energy efficiency investments or waiting at home for a contractor, are not reported and thus are not included.

8

Custom rebate programs allow customers to propose efficiency measures that are tailored to their facility; the administrator typically 

reviews and validates modeled or calculated estimates of energy savings and incentives are often capped at a percentage of total project 

costs (e.g. 50%).

9

Variation in program design, delivery, market conditions, program maturity, and other factors also may have bearing on differences in 

the cost of saved energy from one program administrator to the next. 

10 The cost of saved energy can be evaluated for the first year or lifetime of an energy efficiency action, program, or portfolio, and it can 

be levelized, with the costs spread over the lifetime, as in this brief. 
T E C H N I C A L B R I E F 3

electricity for projecting energy efficiency impacts 

on load forecasts. For example, the regional 

transmission operator for New England (ISO-NE) 

calculates a cost of saved electricity for each 

program administrator in its territory and uses 

those values, with adjustments, to translate future 

efficiency program budgets into savings projections 

that can be used to refine the ISO-NE’s load 

forecast.

What program administrators alone pay for 

efficiency has been the focus of most empirical 

research to date. The program administrator cost of 

saved energy is nonetheless subject to criticism 

that it underestimates the full costs of energy 

efficiency (Joskow and Marron 1992).11,12,13 The 

total cost of saved energy captures the full cost—

that is, the full, system-wide investment in the 

efficiency resource by all parties. The total cost of saved energy provides a way of measuring cost 

performance and screening programs on a consistent basis that accounts for all costs borne by both the 

program administrator and participants. In this brief, the primary metric is the levelized total cost of saved 

energy (Equation 1), which is the total cost of the energy saved, spread in equal payments over the 

economic lifetime of the actions taken through a program (or sector or portfolio), then divided by the 

annual energy saved.

Equation 1.

 = 

 14 

 

With the = [ (1 + )^ ]/[(1 + )^ − 1] 

Where:

A = Discount rate

B = Estimated program lifetime in years and calculated as the savings-weighted life of measures or actions 

promoted by a program

 

11 Joskow and Marron reviewed costs and estimated savings for 12 utility commercial lighting efficiency programs and concluded that 

“computations based on utility expectations could be underestimating the actual societal cost (of efficiency programs) by a factor of two 

or more on average.” Eto et al. (1994, 1996) confirmed that the reported data for those programs understated the total costs for those 

programs and made efforts to capture as many costs as possible for the same programs. The researchers concluded that, when all costs 

were accounted for using Joskow and Marron’s method, the monetized benefits of those programs exceeded their total costs.

12 When the program administrator pays the full cost of an energy efficiency action, the program administrator and total costs of saved 

energy are identical. This circumstance is typical of programs for low-income households and a number of direct-install programs that 

typically do not involve a cost contribution from participants. The total cost of saved energy, with both the program administrator and 

participant cost contributions, enables more meaningful comparisons among these many types of efficiency programs than the program 

administrator cost of saved energy.

13 For additional information on the various cost performance metrics and the LBNL DSM Program Database, see Billingsley et al. (2014). 

14 Total program administrator costs include all costs of administering, marketing, implementing and evaluating the program, as well as 

any incentives paid to any party.

The Cost of Saved Energy and CostEffectiveness Screening

The program administrator and total costs of saved 

energy are neither synonymous with, nor should be 

confused with, the Program Administrator Cost Test, 

the Total Resource Cost Test or the Societal Cost Test. 

These tests are the primary screening tools for 

comparing the costs and benefits of energy efficiency 

programs and often decisions about whether utility 

customers should fund a program. The total cost of 

saved energy is denominated solely in physical energy 

savings and is not intended to define and capture all 

the benefits of energy efficiency or assign values to 

them. The total cost of saved energy for the electricity 

sector answers a simple question: What does it cost to 

save a kilowatt-hour?
T E C H N I C A L B R I E F 4

We used a 6 percent real discount rate as an approximation of the weighted average cost of capital15 for an 

investor-owned electric utility (IOU). We use gross energy savings primarily because net savings are not 

widely reported. When net savings are reported, inconsistencies in the definition and estimation of net-togross ratios add considerably to the uncertainties already embedded in estimates of energy savings.16

Similarly, since many program administrators do not report evaluated or verified savings, we use claimed 

savings. To calculate claimed savings, program administrators often multiply per-unit savings estimates for 

individual measures by the number of measures installed or efficiency actions taken.17 States and program 

administrators vary widely in the level of rigor that they apply in estimating these ex-ante savings values 

and the frequency with which they update those assumptions as impact evaluations are completed.18

The levelized total cost of saved energy treats energy efficiency much like an investment, with costs spread 

over the lifetime of the efficiency actions. It is comparable to the levelized cost of energy supply (LCOE),19

which is similarly calculated by spreading generator capital costs over the economic life of the power 

plant(s). The total cost of saved energy therefore is valuable to resource planners, regulators, and other 

stakeholders as an initial screening tool for weighing alternative investment options. Utility resource 

planners can readily use the total cost of saved energy to determine what efficiency resources are the 

likeliest candidates for consideration in an integrated resource plan. Similarly, efficiency program 

administrators can use the total cost of saved energy for planning and designing efficiency programs and 

portfolios, as well as improving program efficacy.

In the next section, we describe our approach for collecting, standardizing and validating the data analyzed. 

We then highlight several challenges: (1) incomplete reporting of total cost data; (2) varying approaches 

used by program administrators to define and report participant costs; and (3) certain costs that were 

excluded from our analysis. We then present the total cost of saved electricity for the period 2009 to 2013 

at the national, market sector, program type, and state level. 

Data Collection and Analysis Approach

For this study, we identified program administrators that report total costs at the program level and 

collected program-level cost and impacts data from regulatory reporting, testimony, or similar sources.20

We found one or more program administrators reporting at this level in 20 states21 (Figure 1). 

 

15 We use a real discount rate because inflation already is accounted for in the use of constant dollars. The 6 percent real discount rate is 

intended to be a proxy for a nominal rate in the range of 7.5 percent to 9 percent, typical values for a utility weighted average cost of 

capital (WACC). A utility WACC is the average of the cost of payments on the utility’s debt (bonds) and its equity (stock), weighted by the 

relative share of each in the utility’s funds available for capital investment. The utility WACC is often used by investor-owned utilities in 

their economic screening of efficiency programs.

16 See Billingsley et al. (2014) for a discussion of this methodological choice.

17 For some programs, claimed savings may be based on analysis of utility billing data before and after installation of measures or on 

results from building simulation models (e.g., new construction programs).

18 Estimates also differ widely in the assumed baseline—whether the level of energy performance assumed prior to installing a measure 

or taking another efficiency action is based on current practice, building energy code, or even a tiered or dual baseline that changes over 

the savings lifetime of a measure.

19 The comparison has some limitations. For example, the cost of saved energy usually is calculated at the meter of the end-use customer,

while the levelized cost of energy supply is calculated at the busbar of the power plant, which typically does not reflect energy lost in 

transmission and distribution (i.e., line losses) between the generator and end-use customer. Line losses vary by geography and sector 

but average about 6 percent nationally, according to surveys by the U.S. Energy Information Administration 

(http://www.eia.gov/tools/faqs/faq.cfm?id=105&t=3), though other sources report higher values.

20 See Billingsley et al. (2014) for more discussion on the types and sources of data in the LBNL DSM Program Database, as well as quality 

assurance and quality control efforts undertaken by LBNL to increase consistency in program data across program administrators. 
T E C H N I C A L B R I E F 5

Figure 1. Geographic location of energy efficiency program administrators included in this study

Sources: LBNL DSM Program Database; U.S. Energy Information Administration, Form 861

The states are shaded by the degree of data coverage (i.e., the percent of retail electricity sales of IOUs 

represented by those program administrators in that state). Dark shading denotes states with data 

collected from program administrators serving customers of IOUs that account for more than 75 percent of 

2012 IOU retail electricity sales in that state; light shading represents states with data collected from 

program administrators serving customers of IOUs accounting for 50 percent to 75 percent of 2012 IOU 

retail sales in that state. 

We rely almost exclusively on annual reports filed by program administrators because they are the most 

comprehensive, consolidated repository of efficiency program data. For California, we also drew upon 

program implementation plans filed by utilities and a program reporting database maintained by the 

California Public Utilities Commission. For Oregon, the Energy Trust of Oregon provided values directly to 

LBNL. In several states, we augmented data collection with clarifying questions to the program 

administrator or regulator, or we requested additional data. We characterized programs by market sector, 

program implementation type, and technology to enable benchmarking of program results on a more 

consistent basis and to better define program savings lifetimes, which are a critical input to the cost of 

saved energy.22

 

21 In other states, program administrators only reported efficiency program results at the portfolio level, only reported program 

administrator costs and savings (and not participant costs), or were not required to file annual reports.

22 Some program administrators include costs at the portfolio level for specified activities (e.g., statewide brand marketing, regulatory 

compliance costs) and do not allocate those costs to individual programs. In these cases, we use a method employed by many program 

administrators, treating each of these activities as a “program” so that all program administrator costs are fully captured and included at 

the portfolio level. Non-resource programs are typically characterized by sector, except when they are non-sector specific (e.g., emerging 

technologies programs or work on building codes in an unspecified sector). 
T E C H N I C A L B R I E F 6

In general, we treated all savings and cost data reported by program administrators as given. In many 

cases, we do not have insight into what methods and assumptions underlie the estimation of those values, 

nor a reliable way to reverse engineer them if desired. The results of LBNL’s calculations are therefore 

highly dependent on values as reported by program administrators. 

We report the savings-weighted average total cost of saved electricity for the aggregate national portfolio 

of efficiency programs for which all components of total costs are available, totaling more than 2,100 

program years. The weighted average is calculated using all costs for all programs, levelized over the 

average lifetime of savings at the national, state, and sector levels of analysis, including activities for which 

no savings are claimed.23 Programs that produce large energy savings have greater influence over the 

savings-weighted averages than do smaller programs. 

We also report savings-weighted averages and median values for the total cost of saved electricity for 

individual program types. Both costs and savings are required for this calculation, and therefore we derive 

these values from the ~1,600 program years of data that include both program-level cost and savings 

information.24

Every energy efficiency program is different. Each has its own design and implementation characteristics. 

While some programs are enormously successful, other programs struggle to get customer participation. 

Thus, we report the interquartile ranges of the total cost of saved electricity for various types of 

programs—that is, the middle 50 percent of cost of saved electricity values for each program type or 

market sector.25

Defining and Reporting the Total Cost of Saved Electricity: Issues and 

Challenges

Data inconsistencies on program spending and savings have been a persistent problem for utility energy 

efficiency programs (see Hirst and Goldman 1990; Joskow and Marron 1992; Eto et al. 1994). Billingsley et 

al. (2014) described varying practices of program administrators in reporting costs and savings, 

differences in definitions of input values (e.g., net savings, cost categories reported by program 

administrators), issues that arise in defining gross and net savings, and varying estimates of key input 

values (e.g., measure lifetime), and illustrated how these differences can affect the program administrator’s 

cost of saved electricity.

In this section, we highlight issues that arise specifically in reporting and analyzing the total cost of saved 

electricity, focusing on issues related to costs incurred by program participants in implementing efficiency 

projects.

 

23 Many program administrators report costs for certain activities that do not have explicit savings reported. These activities may support 

a broad array of programs (e.g., portfolio-wide marketing, outreach and planning; financing; residential audits), so savings cannot be 

assigned to individual programs. We found no obvious consensus method for allocating these costs. We include costs reported for those 

activities at the portfolio or “all sectors” level for the nation, each sector and each state, but not at the program level. Thus, when 

analyzing results at the program level, some differences in cost allocation and reporting practices among program administrators persist. 

24 The median is the exact middle value (i.e., 50 percent of values lie above the median and 50 percent below the median) for a set of 

similarly classified programs.

25 The highest and lowest 25 percent of total cost of saved energy values for individual programs are not depicted in these figures. 

However, all program results for a given program type, sector, or state are included in determining savings-weighted averages and 

median values. 
T E C H N I C A L B R I E F 7

Incomplete Reporting of Data on the Total Cost of Saved Electricity

The data needed to calculate the total cost of saved electricity are typically inputs that program 

administrators use for cost-effectiveness analyses of their program portfolio, specifically the Total 

Resource Cost (TRC) or Societal Cost Test (SCT). Twenty-eight states use the TRC test as their primary costeffectiveness screen26 for utility customer-funded efficiency programs. Thirteen additional states either 

require reporting of TRC results or rely upon the SCT as their primary test (Kushler, Nowak and Witte 

2012). Thus, as part of efficiency program planning in those 41 states, program administrators must collect 

or derive all data needed to calculate a total cost of saved electricity at the program level. However, in 

about half of these states, program administrators do not report program-level total cost data or 

participant costs to state regulators, or they only report these costs at the portfolio level. In these cases, it is 

not possible to calculate a program-level total cost of saved electricity. Our study sample is therefore 

limited to 20 states in which one or more program administrators report total costs (i.e., program 

administrator costs plus net participant costs) or values from which total costs at the program level can be 

derived.

Program administrators use different definitions and reporting practices for the components of total costs.

LBNL took steps to standardize the cost data and addressed those diverse practices in the following ways:

 Total costs reported by the program administrator included participant incentives. Cost data 

were entered “as is.”

 Total costs reported by the program administrator did not include participant incentives, 

but incentives were reported elsewhere. Values for incentives were collected or derived and 

added to generate total costs.

 Total costs reported by the program administrator were discounted values. Values were 

restored to non-discounted costs and added to the database.

 Participant costs were available, but total costs were not reported. Net participant costs 

(excluding rebates, program-paid installation costs, or discounts for audits) were added to the 

program administrator cost in order to estimate total cost.

Defining and Reporting Participant Costs

Participant costs are the costs paid by participants who take actions elicited by an efficiency program (e.g., 

the incremental cost of a high-efficiency refrigerator to the consumer under a refrigerator rebate 

program).27

In an efficiency program, the cost of measures is often split between participating customers and the 

program administrator that may be providing a financial incentive.28The participant cost contribution is 

 

26 Such cost-effectiveness screening can be performed at the measure, program, or portfolio level. Which level of screening is binding 

depends on state policy. Program administrators often perform multiple types of screening to optimize their portfolios, and regulators 

may require reporting for multiple cost tests.

27 Participant costs are important for several reasons. The relative share of measure costs paid by a program administrator versus 

participants is often considered an indicator of program uptake and can suggest a higher degree of leverage (e.g., less direct incentive 

spending elicits a larger participant contribution to acquire the same amount of energy savings).

28 In the Total Resource Cost Test, costs include administrative costs incurred by the program administrator and incremental measure 

costs. Rebates to participants are viewed as a transfer of funds within the utility system, from all utility customers (as a cost) to those 
T E C H N I C A L B R I E F 8

often shown as net participant costs—i.e., participant costs after customer incentives are taken into 

account (Equation 2.). 

Equation 2.

 − 

Some program administrators define incentives narrowly as rebates or other incentives to the end-user or 

participant. Other states recognize a wider array of costs to induce uptake, such as direct-install costs and 

“upstream” payments to manufacturers and distributors. 

Measure cost is the cost to put an efficiency measure in place, including purchase of the more efficient enduse equipment, installation labor, and materials. Many program administrators define measure costs 

simply as the incremental cost—that is, the additional increment of cost of the high efficiency measure 

compared to the cost of a measure of standard energy performance.29 Other program administrators 

differentiate measure costs by program type. Incremental measure costs are used for some program types, 

such as programs that reduce the cost of installing an efficient air conditioner in a new home (rather than a 

standard, less efficient model) or to replace one that is broken beyond economic repair (replace on 

burnout) (Equation 3.). 

Equation 3.

 − 

 

 

Full measure costs may be used for programs in which participants are encouraged to replace end-use 

equipment before the end of its useful lifetime. For example, the full measure cost for an efficient motor in a 

retrofit program might be $1,000 while the incremental cost of that motor compared to a standard 

efficiency motor might be only $200 for a replace-on-burnout program. The cost difference between using 

full versus incremental measure costs flows through to the calculation of net participant costs and, in turn, 

to the total cost of saving electricity.

Participant costs can be determined directly or indirectly:

 Direct Approach. Direct participant costs can be tracked by analyzing receipts, invoices or other 

transaction records of participants, retailers or contractors (see the bottom path of Figure 2), often 

as a precursor to setting and awarding an incentive to the participant. This practice is often used in 

commercial and industrial (C&I) custom rebate programs and in whole-home retrofit programs. 

 

who are program participants (as a benefit), and thus are not regarded as an additional cost to the system. However, in calculating the 

total cost of saved energy, rebates are considered part of the cost of acquiring the energy savings and thus are included. 

29 The incremental cost of an efficient refrigerator or window is limited to the additional cost associated with its energy-saving features 

and does not include other desirable features (e.g., a refrigerator’s stainless steel finish or the window’s attractiveness). Actual 

adherence to this definition may vary for conceptual or pragmatic reasons. Isolating the increment in costs solely associated with what

makes a measure more efficient can be difficult. One accepted method uses statistical regression to separate the efficiency premium 

from other cost components; this method requires large sample sizes given the number of products and diversity of product features in 

the market.
T E C H N I C A L B R I E F 9

Often, the invoiced costs to the participant are costs of the project prior to taking incentives into 

account. However, determining the accuracy of reported participant costs can be quite challenging. 

There is a great deal of heterogeneity among C&I custom rebate projects and variability in the level 

of detail and cost definitions used in participant invoices.30 In some cases, these differences make it 

difficult to accurately determine actual project costs or incremental measure costs. The cost for the 

same measure also may vary by project size (St. John et al. 2014). 

 Indirect Approach. Program administrators and their consultants usually rely upon point-of-sale 

data from retailer records but also can tap a variety of other sources (see the top path of Figure 2). 

Costs not covered by incentives or paid directly by the program administrator are assumed to be 

participant costs. This approach is common, widespread and used for most measures.31 Participant 

invoices may be used for local adjustments to regional or national equipment and labor costs.

32

Figure 2 illustrates these two approaches and their relationship to net participant costs. 

Figure 2. Approaches used by efficiency program administrators to estimate measure and net participant 

costs

Challenges in Measure Cost Estimation

Acquiring accurate and complete data for determining measure costs can be challenging (Ting 2014; Itron 

2014):33

 Comprehensive and reliable measure cost data are often not readily or publicly available. 

Utilities and other program administrators would ideally perform and update measure cost studies 

 

30 While some participants present itemized invoices, many supply only a single cost number (Teng 2014).

31 Program administrators may find that state or regional collection and estimation of measure costs is less costly than if conducted by 

each program administrator alone. These measure costs may be documented in technical reference manuals (TRMs). Thus, two entities 

may be engaged in the quantification of participant costs when using the indirect approach: the organization that is responsible for 

estimating measure costs for the TRM and the program administrator that is setting incentive levels.

32 Program administrators obtain or estimate measure costs through a variety of sources, such as databases that track program rebates 

and projects, onsite collection at local/regional retailers and distributors, contractor price sheets, online retailers, interviews with 

contractors or other market actors, and the program administrator’s own judgment (NW Regional Technical Forum Guidelines for the 

Estimation of Incremental Measure Costs and Benefits 2013; CPUC 2010-2012 WO017 Ex Ante Measure Cost Study Draft Report 2014).

33 Of all values used in establishing cost effectiveness of energy efficiency programs, measure costs receive the least emphasis and 

research investment (St. John et al. 2014). 
T E C H N I C A L B R I E F 10

periodically. Measure-level cost studies often are based on statistical regression analyses of market 

data, yet they can be perceived as difficult or costly and thus are often performed or updated 

infrequently. Borrowing from other jurisdictions is a common practice (Ting 2014; St. John et al. 

2014; LBNL research).

 Translating the prices of many product brands and models into costs of generic efficient 

“measures” and products can be difficult. Determining energy savings impacts of products can 

be performed by grouping the technologies according to their energy performance criteria—e.g., 

SEER, AFUE, R-value.34 Product costs must be assessed at a more granular level, since there is more 

variation in individual products and their costs than in their energy performance. This requires that 

sample sizes of measure cost studies be on the order of hundreds or thousands.

 Measure costs vary across time and geography. Measure cost studies are a snapshot in time and 

place. For example, in commercial prescriptive programs, St. John et al. (2014) found that regional 

differences can have a significant impact on average costs for specific measures, with regional costs 

for a given measure varying 7 percent to 51 percent from the national average. Average costs for 

the same measure varied by up to 24 percent over just a few years. Borrowing of measure cost 

values from other jurisdictions is common, although it is not clear that adjusting those values by 

time and place is as common.35

 Measure costs vary based on the sales channel, the nature of the sales transaction, and the 

scale of the purchase.

Other Costs Excluded from the Analysis

A number of other costs should in theory be included 

in the total cost of saved energy, but these types of 

costs generally are not included as a matter of practice 

or are not available at the time that program 

administrators submit their annual reports. Examples 

include:

 Lost Revenue Recovery and Performance 

Incentives for the Program Administrator.

Recovery of “lost revenues” and performance 

incentives for utility shareholders or other 

program administrators are often regarded as a 

component in the total cost of saved energy. 

However, the awarding of lost revenue 

recovery and performance incentives tends to 

substantially lag annual program reporting. 

 

34 Seasonal Energy Efficiency Ratio (SEER) is the ratio of output cooling energy in British thermal units (Btus) to the input electric energy 

consumed in watt-hours. Annual Fuel Utilization Efficiency (AFUE) is a thermal efficiency of combustion equipment. R-value is a measure 

of thermal resistance typically used in building insulation. 

35 Escalation rates can be applied to correct for temporal changes, and different calibrations for installation labor, materials, and 

contractor markup can be applied to adjust by geography or market.

Non-Energy Benefits

Investments in high-efficiency products and 

equipment often result in benefits to customers 

beyond energy savings. For example, a home with 

better insulation and higher-efficiency windows is 

more comfortable. The cost of saved electricity 

does not include the enhanced comfort of 

homeowners who retrofit their homes, the water 

saved with energy-efficient clothes washers, or the 

adverse health impacts that are mitigated by 

reducing emissions from fossil-fuel power plants. 

Values for most of these non-energy benefits also 

are rarely reported as program-level outcomes and 

thus are not readily available.
T E C H N I C A L B R I E F 11

Thus, LBNL did not include these costs in our calculation of the total cost of saved electricity.36

 Participant Transaction Costs. Program participants typically incur costs in analyzing potential 

efficiency investments and getting the work done. For example, homeowners may have to take time 

off from work to meet contractors and have measures installed. Businesses must devote time to 

securing budgets, getting and reviewing contractor bids, obtaining financing, and interacting with 

program staff and contractors. Industrial facilities may slow or stop production to make efficiency 

improvements. These costs are rarely included in regulatory reporting as a matter of practice and 

as a practical matter. However, it can be difficult to establish a counterfactual: Would the time and 

attention invested have been different for purchase and installation of less efficient insulation, 

lighting, or equipment?

 Tax Credits. Four states in our sample (OR, SC, NM, OK) offer some form of tax credits, most 

commonly for new construction. These forms of tax relief result in reductions in a government’s 

treasury akin to a societal cost.37 Information is not readily available on whether efficiency program 

participants claimed a tax credit, nor is it clear that accounting for tax credits would change the 

total cost of saved electricity so we did not account for tax credits in this analysis.

Results: The Total Cost of Saved Electricity

The National and Sector-Level Total Cost of Saved Electricity

The total cost of saved electricity, weighted by the reported energy saved, was $0.046 per kWh across all 

sectors and programs in our 2009–2013 data collection (see leftmost bar in Figure 3).38 For comparison, 

the American Council for an Energy Efficient Economy (Molina 2014) reported a savings-weighted average 

of $0.054 per kWh (in 2011 dollars) for a smaller sample of program administrators in seven states.39

Figure 3 shows the level of participant spending leveraged by program administrator spending. The 

average total cost of saved electricity was about twice the program administrator cost of saved electricity

($0.023/kWh) in our 2009–2013 dataset. 

The average total cost for all residential sector programs was $0.033 per kWh (see Figure 3), about 

40 percent lower than the average cost of saved electricity in the commercial, industrial and agricultural 

sector ($0.055 per kWh). Programs in the C&I sector nonetheless had a larger influence over the savingsweighted average than residential programs because of greater energy savings (51 percent vs. 38 percent 

of total savings).

 

36 See footnote 39, however, for an estimate of what the total cost of saved electricity would be if performance incentives were included.

37 At the federal level, tax credits often are forecasted and reported as a form of expenditure. 

38 We also calculated the cost of saved electricity using a lower discount rate (3 percent real) that could be a proxy for a societal discount 

rate. At this lower rate, the savings-weighted average total cost of saved electricity is $0.038/kWh for all programs in oursample.

39 Differences in assumptions and key inputs account for some of the difference in results. For example, Molina et al. (2014) used a 

slightly lower discount rate (5 percent vs. 6 percent real), included performance incentives for program administrators, reported all costs 

in 2011 dollars, and used net rather than gross energy savings. LBNL did not include performance incentives because they usually are not 

available at the time that spending and savings are reported. If a 12% estimated national average for performance incentives (Hayes et al 

2011) were applied to all program years for the program administrators in this analysis that receive performance incentives, the U.S. 

average total cost of saved electricity would be $0.048/kWh. If we adjusted our analysis to account for all of ACEEE’s methodological 

differences for our sample of programs, then the levelized total cost of saved energy would increase to $0.051/kWh (compared to our 

estimate of $0.046/kWh).
T E C H N I C A L B R I E F 12

Figure 3.Total cost of saved electricity for all market sectors. The total cost consists of program administrator and 

participant costs.

Low-income programs had a significantly higher cost per unit of energy saved with an average of about 

$0.142 per kWh. Low-income programs had only a modest impact on the savings-weighted average value 

for all sectors, however, because they only accounted for about 1 percent of total savings for our sample of 

programs. For this reason, we focus our discussion on other types of programs. But we note that, in many 

states, program administrators are required to look beyond strict cost-effectiveness criteria for low-income 

programs and consider other policy objectives (e.g., equitable access to efficiency programs among all 

customer classes, safety and health issues), which influence the cost, design and relative size of low-income 

programs. 

The cost contribution from participating low-income customers tends to be modest in these programs 

(~10 percent of project cost), with program administrators most often paying the full cost of 

comprehensive retrofits of older, lower-quality housing, in which basic repairs may be a prerequisite for 

efficiency improvements.40

The Total Cost of Saved Electricity for Efficiency Programs with Claimed Savings

Thus far, we have reported average values for all programs in our dataset, using all savings and spending, 

regardless of whether a specific program or expenditure is associated with a claim of energy savings. We 

take this approach to ensure that all costs are counted, even those not directly tied to saving electricity. 

From here onward, however, all reported values are reported solely for programs with a claim of energy 

savings.

 

40 During the 2008 to 2010 recession, program administrators in a number of states raised the income eligibility of their low-income 

programs or added offerings to serve households on the margins of poverty guidelines. In some cases, program administrators asked for 

a modest contribution from these customers. For our sample of low-income programs, costs incurred by participating low-income 

customers were about $0.014/kWh.
T E C H N I C A L B R I E F 13

The total cost of saved energy ranged fairly widely in all sectors (Figure 4). The third quartile value across 

all sectors was 250 percent higher than the first quartile value, with particularly wide ranges among lowincome and residential programs. The breadth of these ranges is a product of many factors, including but 

not limited to the contexts in which the programs operate, diversity in measure mixes and program 

designs, and the program administrators’ assumptions regarding measure lifetimes and unit savings.

Figure 4. Savings-weighted average, median and interquartile range of total cost of saved electricity values for all sectors. 

Only programs with claimed savings are included.

The median value of the total cost of saved electricity for programs in all sectors was much higher than the 

savings weighted average, at $0.069 per kWh. This difference reflects the fact that some programs that 

account for a large share of the overall savings in our sample have low total costs of saved electricity values, 

thus keeping the overall savings-weighted average low compared to the middle value of the dataset.

Efficiency Programs in the Residential Sector

The comparatively low cost of savings in the residential sector was influenced significantly by one type of 

program (Figure 5).41Consumer product rebates include programs that provide incentives for lighting, 

appliances and consumer electronics. These programs were a key driver for the relatively low cost of saved 

electricity in the residential sector, delivering energy savings in 2009–2013 at an average of $0.021 per 

kWh (Figure 5). Of these programs, lighting rebate programs had the largest influence on cost performance 

for the residential sector overall. They accounted for nearly 60 percent of the savings in the residential 

sector, with a savings-weighted average total cost of $0.018 per kWh. Historically, compact fluorescent 

lighting programs have accounted for a large share of savings and helped bolster the cost effectiveness of 

the rest of the portfolio. Excluding residential lighting-only rebate programs—an extremely unlikely but 

illustrative scenario—the total savings-weighted cost of saved electricity would have been $0.055/kWh for 

the residential sector (~ 70 percent higher) and $0.054 per kWh for all sectors (nearly 20 percent higher). 

 

41 See Billingsley et al. (2014) for details on the multi-level typology used to characterize programs nationally.
T E C H N I C A L B R I E F 14

Residential prescriptive programs typically provide incentives for more efficient heating, ventilation and 

air conditioning (HVAC) systems; water heaters; and shell improvements (e.g., additional insulation, highefficiency windows). Their savings-weighted average cost of saved electricity is $0.054 per kWh. Multifamily retrofit and whole-home retrofit programs tend to promote more comprehensive retrofits (i.e., 

several different measures are installed) and are more costly on average ($0.071 and $0.094 per kWh, 

respectively). Residential new construction programs tend to have high cost of saved electricity values on 

average ($0.111 per kWh), in part because building efficiency standards have captured some of the lowercost efficiency opportunities.42

The relative cost contributions provided by program participants also varies widely for different types of 

residential programs. For example, participants usually incur no costs in behavioral feedback programs but 

contribute more to multi-family retrofit programs (28 percent of total costs), whole-home retrofit 

programs (36 percent), and prescriptive programs (59 percent) (see Figure 5).

Figure 5. Total cost of saved electricity for various types of residential programs. The total cost consists of program 

administrator and participant costs.

It is also important to understand the range in performance among types of programs. Figure 6 shows 

median values and the interquartile range in the cost of saved electricity values. The interquartile ranges

vary by a factor of three to five among residential program types. The large range for whole-home retrofit

and new home construction programs may reflect variability in the mix of measures, program maturity, 

knowledge and state of the market, and program design. For example, many of the whole-home retrofit 

programs (i.e., home energy upgrade) are relatively new programs, and thus may have significant start-up 

 

42 In assessing the effectiveness of new construction programs, program administrators and policymakers should also consider market 

barriers (e.g., split incentives) and “lost opportunity” costs (e.g., from a societal perspective, it still may be less expensive to construct a 

high efficiency building initially, rather than retrofitting that building later).
T E C H N I C A L B R I E F 15

costs or be early in developing the necessary relationships with local contractors. Some new construction 

programs attempt to drive higher energy performance throughout the home, while other new construction 

programs are limited primarily to promoting certain high-efficiency equipment or appliances. 

Behavioral feedback, or “home energy report,” programs are increasingly common.43 The savings-weighted 

average total cost was $0.057 per kWh for these programs in our 2009–2013 dataset. These 32 programs 

(excluding pilots and other programs for which no savings are claimed) have an interquartile range of 

$0.038 to $0.092 per kWh. By way of comparison, for three programs sponsored for multiple years by U.S. 

utilities, Allcott and Rogers (2014) reported a range of $0.032 to $0.044 per kWh.

Figure 6. Savings-weighted average, median and interquartile range for the total cost of saved electricity for various 

residential program types

Several factors may account for differences in these results for behavior feedback programs. First, we 

report our results as a savings-weighted average for a larger sample of programs. In addition, some large 

behavior feedback programs in our sample (in terms of enrolled customers and aggregate savings) targeted 

broader groups of residential customers, were located in milder climates, were located in territories where 

efficiency programs have been operating for many years, or all of these. These programs have higher cost of 

saved electricity values and, having produced large savings relative to other behavioral feedback programs, 

have a strong influence on the savings-weighted average values. Second, most savings from behavioral 

feedback programs come from changes in customer behavior (e.g., turning out unneeded lights), with some 

savings resulting from installing more efficient lights or equipment that is discounted or rebated by other 

 

43 These programs send periodic reports that provide the household with a comparison of its energy use relative to similar households 

and offer customized energy-saving tips (e.g., resetting the thermostat). Programs may also provide information on financial incentives 

for purchase of high-efficiency equipment.
T E C H N I C A L B R I E F 16

programs. To avoid double-counting savings, some program administrators allocate those savings to the 

other programs, which tends to increase the cost of saved electricity for the behavioral feedback program.

The duration and persistence of savings are key factors influencing the total cost of saved energy. In our 

dataset, all program administrators estimated savings for behavioral feedback programs are based upon 

the assumption that the savings from actions taken by customers would last about one year.44 A recent 

meta-analysis (Khawaja and Stewart 2014) of studies of the five longest-running behavior feedback 

programs recommends using a measure lifetime of 3.9 years. Using that value, the savings-weighted 

average total cost of saved electricity for behavioral feedback programs with claimed savings would have 

been $0.017 per kWh, compared to the $0.057 per kWh average based on a one-year measure life. 

Behavioral feedback programs did not have much influence on our overall results for total cost of saved 

electricity because they only account for about 6 percent of total residential savings in our 2009–2013 

dataset. 

Commercial, Industrial and Agricultural Sector Efficiency Programs

Non-residential programs that have claimed savings have an average total cost of $0.053 per kWh, with 

average values for most program types in a narrow band between $0.042 per kWh and $0.063 per kWh 

(Figure 7). The most common program types are prescriptive and custom rebate programs, with total costs 

averaging $0.045 and $0.052, respectively. Each of these two program types accounts for about one-third of 

non-residential claimed savings.

Programs that target energy savings opportunities in the government and institutional sector had a higher 

cost of saved electricity on average ($0.085 per kWh). Some program administrators have implemented 

programs that specifically target the so-called “MUSH”45 market that includes state and local government 

facilities, universities and colleges, K-12 schools and hospitals. In the 2009–2013 period, California utilities 

offered more than 80 of these programs, most of them collaborations with local governments. These 

California programs account for more than half of the savings in the MUSH category. If these programs 

were removed from the analysis, the savings-weighted cost of saved electricity for government and 

institutional programs would have been $0.048 per kWh, closer in cost performance to the non-residential 

sector overall ($0.053 kWh).

On average, programs that target non-residential customers appear to leverage more participant 

investment compared to residential sector programs, with program administrators paying on average 

46 percent of total costs and participants paying 54 percent. In custom and prescriptive rebate programs, 

on average, program administrators and participants split total costs 41 percent/59 percent and 

42 percent/58 percent, respectively.

 

44 Program administrators used a measure life of one year for these behavioral programs because it was a condition of regulatory

approval for a pilot or because the programs were new.

45 MUSH is an acronym for Municipalities, Universities, Schools and Hospitals.
T E C H N I C A L B R I E F 17

Figure 7. Total cost of saved electricity for various commercial, industrial and agricultural program types. The total cost 

consists of the program administrator and participant costs.

Figure 8 shows that the range in cost performance among programs in the LBNL dataset tended to be 

narrower for most types of C&I programs, compared to results in our sample of residential sector 

programs. For example, the interquartile range values vary by a factor of two for nearly all types of C&I 

programs (except for programs that target MUSH market customers), compared to a factor of three to five 

among various types of residential programs.

Figure 8. Savings-weighted average, median value and interquartile range for total cost of saved electricity for nonresidential program types
T E C H N I C A L B R I E F 18

Among the States: Total and Program Administrator Cost of Saved Electricity 

Figure 9 summarizes the total cost of saved electricity for each state where one or more program 

administrators report sufficient program data. The total cost across all programs for which data could be 

collected in a given state, weighted by the energy saved, ranged from about $0.03 per kWh for programs in 

New Mexico and Maine to $0.079 per kWh in Massachusetts. The savings-weighted average was $0.046 per 

kWh (denoted by the red dotted line) for all programs in our sample. The ratio of program administrator 

spending to participant spending also varies widely by state (Figure 9). 

Figure 9. Savings-weighted average total cost of saved electricity, by state

Many factors are likely to influence the total cost of saved electricity in a state (Billingsley et al. 2014). 

These factors include but are not limited to the following:

 Policy objectives and context (e.g., acquiring all cost-effective efficiency; rising savings targets 

required by an Energy Efficiency Resource Standard)

 Program planning requirements (e.g., cost-effectiveness screening practices, avoided supply costs)

 Technical opportunities (e.g., characteristics of the existing building/housing stock and equipment)

 Program administrator performance and motivation

 Program scale

 Technical resources and approach used to evaluate, measure and verify savings46

 

46 A number of states and regions (e.g., Pacific Northwest, New England, California) that have offered efficiency programs for several 

decades have devoted significant resources to evaluation, measurement and verification (EM&V) activities (e.g., developed

comprehensive EM&V protocols, robust technical reference manuals). Their EM&V practices often include frequent updates to savings 

estimates, measure lifetimes and, to a lesser extent, measure costs. In many cases, these updates result in lower estimates of annual or 
T E C H N I C A L B R I E F 19

 Electricity prices (e.g., impact on economic payback times for efficiency investments) and

 Labor and materials costs.

For example, Hawaii and Massachusetts are at the upper tier for average cost of saved electricity values in 

this study. Retail electricity rates are above the national average in both states. Participating customers in 

Hawaii, with the highest retail electricity rates in the nation, are contributing a larger share of total costs 

than in most states. Program administrators in Massachusetts have implemented efficiency programs for 

more than 25 years, capturing much of the lowest-cost technical opportunities. Massachusetts also has a 

legislative mandate to pursue all cost-effective energy efficiency. The total cost of saved electricity across 

all programs and expenditures was less than $0.06 per kWh in all other states.

Figure 10 illustrates the electricity savings acquired by program administrators in a state and the total cost 

of acquiring those savings. Specifically, we show the program administrators’ reported electricity savings 

as a share of the state’s retail electricity sales by IOUs on the x-axis compared to the savings-weighted 

average total cost of saved electricity value for programs in a state on the y-axis. Squares signify that the 

data are from program administrators serving customers of utilities accounting for more than 75 percent of 

2012 retail electricity sales of IOUs in that state, while diamonds represent data accounting for 50 percent 

to 75 percent of retail electricity sales. 

Vermont, Massachusetts, and Maryland had the highest reported electricity savings of our sample, 

exceeding 2 percent of annual retail electricity sales. Program administrators in 13 states reported 

electricity savings in 2012 between 0.8 percent and 1.8 percent of annual retail sales. Program 

administrators in four states reported saving 0.5 percent or less of annual retail sales. In many cases, these 

program administrators recently ramped up their energy efficiency efforts and may have faced higher 

initial administrative costs, but newer administrators also have more opportunity to offer programs 

targeting lower-cost measures.

If program administrators (and states) pursue higher savings targets, they must achieve greater market 

penetration, deeper savings per project (e.g., install more measures, more comprehensive retrofits), or 

both. These higher savings targets therefore could cost more to achieve as program administrators follow a 

rising “conservation supply curve” of technical efficiency options that are more costly to access or, for 

example, as program administrators spend more money to encourage customers to participate in 

programs. But the actual relationship between the cost of saved electricity and the level of savings is more 

complicated, and some analyses have shown a negative slope (i.e., the cost of saved electricity has declined 

as savings have increased) (Takahashi and Nichols 2008). New high-efficiency technologies and greater 

operational efficiencies in program delivery may reduce the cost of savings. We plan to explore factors that 

influence the total cost of saved electricity in more depth in future work.

 

lifetime savings (e.g., reducing the assumed operating hours or measure life of high-efficiency lighting), which will result in a higher total 

cost of saved electricity, all else being equal. Longer measure lifetimes will result in longer program-average measure lifetime, which 

likewise can lead to a lower cost of saved electricity. Using full versus incremental measure costs for specific measures in a program may 

also result in a higher cost of saved electricity.
T E C H N I C A L B R I E F 20

Figure 10. Total cost of saved electricity compared to electricity savings as a percentage of retail electricity sales by 

investor-owned utilities

Sources: LBNL DSM Program Database; U.S. Energy Information Administration, Form 861; Massachusetts Energy Efficiency Advisory 

Council; Hawaii Energy Annual Report

Conclusion

The average total cost of saved electricity, weighted by energy savings, was $0.046 per kWh of claimed 

savings for program administrators in 20 states that provided sufficient cost information for the 2009 to 

2013 period. This estimate is based on the most expansive collection of total costs to date.

For the subset of residential programs for which savings were claimed, the savings-weighted average total 

cost of saved electricity was $0.030 per kWh. Residential consumer product rebate programs—especially 

lighting programs with an average total cost of $0.018 per kWh—were a primary driver of these results. If 

residential lighting-only programs were excluded to test the effect on the rest of the portfolio, the savingsweighted average total cost would have been $0.055 per kWh in the residential sector (72 percent higher) 

and $0.054 per kWh for all sectors (18 percent higher) for the programs in our dataset. These results 

illustrate the prominent role that lighting programs have played in utility efficiency endeavors to date. 

Non-residential sector programs for which savings were claimed had a savings-weighted average total cost 

of $0.053 per kWh. Prescriptive C&I rebate programs ($0.045/kWh) and custom C&I rebate programs 

($0.052/kWh) account for more than 60 percent of the savings in the non-residential sector. Cost 

performance among program types varied more in the residential sector than in the non-residential 
T E C H N I C A L B R I E F 21

sectors, differing by a factor of three to five among various types of residential programs and by a factor of 

two for most types of non-residential programs.

Program administrators in fewer than half of states with efficiency programs funded by electric utility 

customers report total costs and savings. Where full costs are reported, differing definitions and 

interpretations of the components of total costs can make it challenging to aggregate and compare data. 

Continued efforts to establish more consistent reporting would better establish the cost effectiveness and 

potential of efficiency as an energy resource, as well as provide more accurate insights into programs, 

policies and system needs. This brief highlights varying approaches and practices used by program 

administrators to determine participant costs, including methodological issues (e.g., perceived challenges 

in estimating incremental measure costs).

For future research, we anticipate looking more closely at potential allocation schemes for spreading 

portfolio-level costs among programs not already carrying those costs. We also plan on three key areas of 

inquiry: (1) program reporting issues and establishing linkages between more rigorous, comprehensive 

reporting and the needs of program administrators, regulators and other stakeholders; (2) analyses of 

trends in the cost of saved electricity over time; and (3) analyses of factors that may influence the total cost 

of saved electricity.

References

Allcott, H. and T. Rogers 2014. “The Short-Run and Long-Run Effects of Behavioral Interventions: Experimental 

Evidence from Energy Conservation” American Economic Review 2014, 104(10): 3003–3037 

http://dx.doi.org/10.1257/aer.104.10.3003. 

Billingsley, M., I. M. Hoffman, E. Stuart, S. R. Schiller, C. A. Goldman, and K. Hamachi LaCommare. 2014.“The Program 

Administrator Cost of Saved Energy for Utility Customer-Funded Energy Efficiency Programs.” Lawrence 

Berkeley National Laboratory. LBNL-6595E. April 2014.

Eto, J., E. Vine, L. Shown, R. Sonnenblick, and C. Payne 1996. “The Total Cost and Measured Performance of UtilitySponsored Energy Efficiency Programs.” The Energy Journal 17 (1).

Eto, J., E. Vine, L. Shown, R. Sonnenblick, and C. Payne 1994. “The Cost and Performance of Utility Commercial Lighting 

Programs.” Lawrence Berkeley National Laboratory. May 1994.

Hirst, E. and C. A. Goldman 1990. “Review of Demand-Side Data Needs for Least-Cost Utility Planning.” Energy 15(5): 

403–411. 1990.

Hayes, S., S. Nadel, M. Kushler, and D. York 2011. “Carrots for Utilities: Providing Financial Returns for Utility 

Investments in Energy Efficiency.” American Council for an Energy-Efficient Economy. Report U111. January 

2011.

Itron Consulting 2014. “2010–2012 WO017 Ex Ante Measure Cost Study Final Report.” Submitted to the California 

Public Utilities Commission. May 2014.

Itron 2005. National Energy Efficiency Best Practices Study, prepared for the Pacific Gas & Electric Company on behalf 

of the California Investor-Owned Utilities, California Public Utilities Commission, and California Energy 

Commission. www.eebestpractices.com.

Joskow, P. and D. B. Marron 1992. “What Does a Negawatt Really Cost? Evidence from Utility Conservation Programs.” 

The Energy Journal. 13:4:41–75. 
T E C H N I C A L B R I E F 22

Kushler, M., S. Nowak, and P. Witte 2012.“A National Survey of State Policies and Practices for the Evaluation of 

Ratepayer-Funded Energy Efficiency Programs.” American Council for an Energy-Efficient Economy. Report 

U122. February 2012.

Khawaja, M. S. and J. Stewart 2014. “Long-Run Savings and Cost-Effectiveness of Home Energy Reports Programs” 

Cadmus Group Inc. October 2014. http://www.cadmusgroup.com/wpcontent/uploads/2014/11/Cadmus_Home_Energy_Reports_Winter2014.pdf.

Molina, M. 2014. “The Best Value for America’s Energy Dollar: A National Review of the Cost of Utility Energy 

Efficiency Programs.” American Council for an Energy-Efficient Economy. March 2014. Report Number U1402.

Navigant 2013. “Incremental Cost Study Phase Two Final Report: A Report on 12 Energy Efficiency Measure 

Incremental Costs in Six Northeast and Mid-Atlantic Markets” Prepared for the Northeast Evaluation, 

Measurement and Verification Forum, chaired by the Northeast Energy Efficiency Partnerships. January 2013. 

http://www.neep.org/incremental-cost-study-phase-2-report.

St. John, J., J. Teng, K. Maoz, and A. Stryker 2014. “‘What Will It Cost?’ Exploring Energy Efficiency Measure Costs over 

Time and Across Regions.” Proceedings of the 2014 ACEEE Summer Study of Energy Efficiency in Buildings.

Takahashi, K. and D. Nichols 2008. “The Sustainability and Costs of Increasing Efficiency Impacts: Evidence from 

Experience to Date” Proceedings of the 2008 ACEEE Summer Study of Energy Efficiency in Buildings.

Teng, J. 2014. “‘What Will It Cost?’ Exploring Energy Efficiency Measure Costs over Time and Across Regions.” 

Presentation at the 2014 ACEEE Summer Study of Energy Efficiency in Buildings.

Ting, M. 2014. “California Measure Cost Study.” DOE SEE Action Webinar, September 2014.

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