Deconstructing the Energy-Efficiency Gap:

Conceptual Frameworks and Evidence

By TODD GERARDEN, RICHARD G. NEWELL, AND ROBERT N. STAVINS*

* Gerarden: Harvard Kennedy School, 79 John F. Kennedy St., 

Cambridge, MA 02138 (e-mail: gerarden@fas.harvard.edu); Newell: 

Nicholas School of the Environment, Duke University, 140 Science 

Dr., 101 Gross Hall, Durham, NC 27708 (email: 

richard.newell@duke.edu); Stavins: Harvard Kennedy School, 79 

John F. Kennedy St., Cambridge, MA 02138 (e-mail:

robert_stavins@harvard.edu). This paper draws in part on a workshop 

held at Harvard, as well as on Gerarden, Newell, and Stavins (2014). 

We thank the workshop participants and gratefully acknowledge 

financial support from the Alfred P. Sloan Foundation.

Energy-efficient (EE) technologies offer 

considerable promise for reducing the 

financial costs and environmental damages 

associated with energy use, but these 

technologies appear not to be adopted to the 

degree that appears justified, even on a purely 

private basis.

We present two complementary frameworks 

for understanding the EE gap. First, we build 

upon previous literature (Jaffe and Stavins 

1994; Gillingham, Newell, and Palmer 2009)

by dividing potential explanations for the gap 

into three categories: market failures, 

behavioral explanations, and model and

measurement errors. Second, we examine the 

elements of cost-minimizing EE decisions, the 

typical benchmark used in assessing the gap’s 

magnitude.

I. Potential Explanations

First, potential market-failure explanations 

for the EE gap include information 

asymmetries and imperfections in markets for 

energy, capital, and innovation.

Second, potential behavioral explanations 

include myopia, cognitive limitations,

inattentiveness, loss aversion and reference 

dependence, and systematically biased beliefs.

Third, there are potential model and 

measurement explanations. These feature 

reasons why the adoption rate of EE

technology may not be as paradoxical as it 

first appears. Potential sources of model and 

measurement error include unobserved costs 

or overstated energy savings from adoption, 

ignored product attributes, heterogeneity 

across potential adopters, use of inappropriate 

discount rates, and uncertainty.

Determining the validity of candidate 

explanations—and the degree to which each 

contributes to the EE gap—are crucial for 

crafting sensible public policy responses.

environmental, congestion, and accident 

externalities of gasoline consumption are on 

the order of $2-3 per gallon (Parry, Walls, and 

Harrington 2007), and estimates of the social 

costs of non-climate damages from coalpowered electricity are 3–4 cents per kilowatthour (National Research Council 2010). 

However, many of these externalities are 

regulated, and thereby indirectly or directly

priced.

Other market distortions, such as electricity 

price regulation, make it difficult to judge 

whether electricity prices are too low overall. 

Electricity and natural gas prices may be 

inefficiently high due to pricing that recoups 

fixed costs through marginal fees (Davis and 

Muehlegger 2010).

Another potential explanation for the EE

gap is that consumers’ expectations about 

future energy prices or use are systematically 

biased downward. There is only mixed 

evidence, and a fundamental challenge is to 

identify separately beliefs and preferences.

Further research would be useful to isolate the 

effect of information policies on beliefs.

Analytical assumptions can contribute to the 

EE gap, by overestimating projected energy 

savings or failing to account for consumer 

heterogeneity. Engineering-economic analyses 

typically estimate energy savings that exceed 

savings observed in ex post energy 

consumption data (Davis, Fuchs, and Gertler 

2014). Ignoring heterogeneity can bias energy 

savings estimates upward: systematic 

differences between past and future adopters 

can drive a wedge between observed and 

potential returns for a given investment. There 

are opportunities for more research in this 

area, particularly in the transportation, 

commercial, and industrial sectors.

Are product choices cost-minimizing?—

Product choices may not minimize present 

value costs. Principal-agent conflicts—“split 

incentives”—are among the most widely cited 

market failure explanations for the EE gap. 

Examples include landlord-tenant and builderbuyer conflicts, in which agents make suboptimal capital investment choices from the 

perspective of the principals. Similar agency 

conflicts are possible within firms. Empirical 

studies have compared owner-occupied and 

rental properties and found compelling 

evidence consistent with principal-agent 

conflicts (Gillingham, Harding, and Rapson 

2012), but the economic magnitude of EE

differences due to these principal-agent 

conflicts may be small.

Behavioral phenomena could also explain 

choices that are not cost-minimizing. 

Consumers may be inattentive to energy costs 

when purchasing energy-using products, but 

such lack of attention is not necessarily 
irrational. Costly information acquisition can 

justify decisions that appear privately suboptimal (Sallee 2013), and therefore policies 

that reduce inattention may be warranted, such 

as information provision, which raises the 

salience of EE, or taxes on energy, which raise

the cost of inattention (Allcott, Mullainathan, 

and Taubinsky 2014). But to guide policy, 

further research is needed to isolate inattention 

from imperfect information.

Three other phenomena at the intersection 

of psychology and economics may help 

explain the energy-efficiency gap. First, 

prospect theory, which demonstrates how 

reference points and loss aversion can affect 

economic decisions, is consistent with 

consumer demand for vehicle fuel economy 

(Greene, Evans, and Hiestand 2013) and 

energy use (Goldstein, Cialdini, and 

Griskevicius 2008). Second, cognitive 

limitations (or “bounded rationality”) could 

inhibit consumers from properly balancing 

benefits and costs when comparing energyconsuming products (Allcott 2013). Finally, 

consumer myopia or shortsightedness could 

lead to suboptimal adoption of EE technology. 

Here, very few studies credibly isolate myopia 

from other explanations and the evidence is 

mixed (Allcott and Wozny 2013; Busse, 

Knittel, and Zettelmeyer 2013).

The empirical evidence on whether energyconsuming product choices are costminimizing ranges from strong to weak across 

these candidate explanations, leaving room for 

new research in this realm, particularly 

experiments to isolate and evaluate competing 

explanations.

Do other costs inhibit EE?—If products of 

varying efficiencies differ from each other in 

ways that are omitted by engineering and 

econometric analysis but that are important to 

consumers, this could contribute to the 

misidentification of an energy-efficiency gap. 

In principle, econometric methods can address 

these issues by including data on product 

attributes or subsuming unobserved attributes 

into a product-specific error term. In practice, 

this has been limited by data and 

computational constraints. One solution may 

be to use panel data to eliminate timeinvariant unobserved product attributes. 

Another promising approach is the use of 

geographic variation and an assumption on 

spatial invariance of consumer preferences to 

eliminate product attributes that do not vary 

across markets (Houde 2014).

A second possibility is that analysts fail to 

take sufficient account of the costs of EE

investments. Examples include time spent 

researching product alternatives, unobserved 

implementation costs, and costs of 
reallocating resources within a firm. These 

costs are not easily quantified, but they can be 

real barriers to investment.

These cost issues merit some priority for 

research, including understanding consumer 

demand for relevant product attributes.

III. Conclusions

Debate over the EE gap is not new, but there 

has been a striking increase in policy interest 

and investment in EE over the past decade, 

plus a coincident resurgence of academic 

research. Recent methodological advances 

provide the opportunity for applied 

researchers to evaluate existing and proposed 

policies. Our reframing of key questions and 

our review of recent literature can aid scholars 

in doing this.

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