Assessing the Energy-Efficiency Gap

Global energy consumption is on a path to grow 30-50 percent over the next 25 years, bringing with it, in many countries, increased local air pollution, greenhouse gas (GHG) emissions, and oil consumption, as well as higher energy prices.  Energy-efficient technologies offer considerable promise for reducing the costs and environmental damages associated with energy use, but these technologies appear not to be used by consumers and businesses to the degree that would apparently be justified, even on the basis of their own (private) financial net benefits.

For some thirty years, there have been discussions and debates about this phenomenon among researchers and others in academia, government, non-profits, and private industry, typically couched in terms of potential explanations of the so-called “energy efficiency gap” or “energy paradox.”

Thinking About the Energy-Efficiency Gap

I wrote about this some two years ago at this blog ().  I  noted then that Professor Richard Newell of Duke University and I had just launched an initiative – sponsored by the Alfred P. Sloan Foundation — to synthesize past work on potential explanations of the energy paradox and identify key gaps in knowledge. We subsequently conducted a comprehensive review and assessment of social-science research on the adoption of energy-efficient technologies.

We worked with leading social scientists — including scholars from economics, psychology, and other disciplines, at a workshop held at Harvard — to examine the various possible explanations of the energy paradox and thereby to help identify the frontiers of knowledge on the diffusion of energy-efficient technologies.  As materials became available, we posted them at the project’s Harvard website and the project’s Duke website.

Releasing a New Monograph

I’m pleased to inform readers of this blog that we have now released a major monograph, Assessing the Energy Efficiency Gap, co-authored with Todd Gerarden, a Harvard Ph.D. student in Public Policy and a Pre-Doctoral Fellow of the Harvard Environmental Economics Program (HEEP).  The monograph draws in part from the research workshop held at Harvard (in October 2013), in which most of the U.S.-based scholars (primarily, but not exclusively, economists) then conducting research on the energy-efficiency gap participated. HEEP co-sponsored a second such research workshop with the Centre for European Economic Research (ZEW) in Mannheim, Germany in March 2014, where European economists explored the same topic. Closely-related research was presented by panelists at the annual conference of the Allied Social Science Association in January 2015.

In the new monograph, Gerarden, Newell, and I examine both the “energy paradox,” the apparent reality that some energy-efficiency technologies that would pay off for adopters are nevertheless not adopted, and the broader phenomenon we characterize as the “energy-efficiency gap,” the apparent reality that some energy-efficiency technologies that would be socially efficient are not adopted. The contrast is between private and social optimality, which ultimately has important implications for the role of various policies, as well as their expected net benefits.

Four Key Questions

We begin by decomposing cost-minimizing energy-efficiency decisions into their fundamental elements, which allows us to identify four major questions, the answers to which are germane to sorting out the causes (and reality or lack thereof) of the paradox and gap.

First, we ask whether the energy efficiency and associated pricing of products on the market are economically efficient. To answer this question, we examine the variety of energy-efficient products on the market, their energy-efficiency levels, and their pricing. Although the theory is clear, empirical evidence is—in general—quite limited. More data that could facilitate potential future empirical research are becoming available, although firm-level data are much less plentiful than data on consumers. We do not see this area as meriting high priority for future research, however, with the exception of research that evaluates the effectiveness and efficiency of existing energy-efficiency information policies and examines options for improving these policies.

Second, we ask whether energy operating costs are inefficiently priced and/or understood. Even if consumers make privately optimal decisions, energy-saving technology may diffuse more slowly than the socially optimal rate, because of negative externalities. So, even if the energy paradox is not present, the energy-efficiency gap may be. As in the first realm, the theoretical arguments are strong. Empirical evidence is considerable, and in many cases data are likely to be available for additional research. Existing policies appear not to be sufficient from an economic perspective, suggesting that further research is warranted. Indeed, we ascribe high priority to the pursuit of research in this realm.

Third, we ask whether product choices are cost-minimizing in present-value terms, or whether various market failures and/or behavioral phenomena inhibit such cost-minimization. We find that the empirical evidence ranges from strong (split incentives/agency issues and inattention/salience phenomena) to moderate (heuristic decision-making/bounded rationality, systematic risk, and option value) to weak (learning-by-using, loss aversion, myopia, and capital market failures). Importantly, here, as elsewhere in our review, the bulk of previous work has focused on the residential sector and much less attention has been given to the commercial and industrial sectors. Some areas merit priority for future research, such as empirical analysis of split incentives/agency issues in areas where efficiency standards are not present, and much more work can be done in the behavioral realm.

Fourth, we ask whether other unobserved costs may inhibit energy-efficient decisions. We find that the empirical evidence is generally sound, and that data needed for more research are available. We assign a relatively high priority to future research, particularly to aid understanding of consumer demand for product attributes that are correlated with energy efficiency, thereby informing policy and product development decisions.

Three Categories of Potential Explanations of the Gap

Finally, we ask what these findings have to say about the three categories of explanations (reviewed in detail in my 2013 essay at this blog) for the apparent underinvestment in energy-efficient technologies relative to the predictions of some engineering and economic models: (1) market failures, (2) behavioral effects, and (3) modeling flaws.  In brief, potential market-failure explanations include information problems, energy market failures, capital market failures, and innovation market failures. Potential behavioral explanations include inattentiveness and salience, myopia and short sightedness, bounded rationality and heuristic decision-making, prospect theory and reference-point phenomena, and systematically biased beliefs. Finally, potential modeling flaws include unobserved or understated costs of adoption; ignored product attributes; heterogeneity in benefits and costs of adoption across potential adopters; use of incorrect discount rates; and uncertainty, irreversibility, and option value.

It turns out that all three categories of explanations are theoretically sound and that limited empirical evidence exists for every category as well, although the empirical research is by no means consistently strong across all of the specific explanations.  The validity of each of these explanations—and the degree to which each contributes to the energy-efficiency gap—are relevant for crafting sensible policies, so Gerarden, Newell, and I hope that our new monograph can help inform both future research and policy.  Given the many energy-efficiency policies and programs that are already in place, high priority should be given to research that evaluates the effectiveness, cost-effectiveness, and overall economic efficiency of existing energy-efficiency policies, as well as options for their improvement.


Thinking About the Energy-Efficiency Gap

Adoption of energy-efficient technologies could reap both private and social rewards, in the form of economic, environmental, and other social benefits from reduced energy consumption. Social benefits include improvements in air quality, reduced greenhouse-gas emissions, and increased energy security. In response, governments around the world have adopted policies to increase energy efficiency.  Still, there is a broadly held view that various barriers to the adoption of energy-efficient technologies have prevented the realization of a substantial portion of these benefits.

For some thirty years, there have been discussions and debates among researchers and others in academia, government, non-profits, and private industry regarding the so-called “energy efficiency gap” (or “energy paradox”) — the apparent reality that many energy-efficiency technologies are not adopted even when it makes sense for consumers and businesses to do so, based on their private costs and benefits. That is, decision makers appear to “under-invest” in energy-efficient technologies, relative to the predictions of some engineering and economic models.

What causes this gap?  The answer to that question could presumably help inform the development of better public policy in this realm.

Possible Explanations for the Energy-Efficiency Gap

Potential explanations for the energy efficiency gap tend to fall into three broad categories: (1) market failures, such as lack of information or misplaced incentives; (2) behavioral effects, such as inattentiveness to future energy savings when purchasing energy-consuming products; and (3) modeling flaws, such as assumptions that understate the costs or overstate the benefits of energy efficiency.  In this essay, I simply want to outline the types of hypothetical explanations of the gap that have been posited within these three broad categories.

Market-Failure Explanations

First, various Innovation Market Failures have been posited, including:  research and development (R&D) and learning-by-doing spillovers; inefficient product quality and differentiation due to market power; and inefficient introduction of new products due to consumer taste spillovers (for example, consumers becoming comfortable with a new technology).

Second, another set of potential market-failure explanations for the gap may be characterized as Information Problems.  These include:  lack of information on the part of consumers (learning-by-using or so-called experience goods; energy prices; energy consumption of products; and available substitutes); asymmetric information (the “lemons problem”); and split incentives and principal-agent issues (such as the frequently-discussed renter/owner dichotomy).

Third, there are Capital Market Failures and Liquidity Constraints, which may be a particularly significant issue in developing-country contexts.

Fourth, there are Energy Market Failures, including various externalities (environmental, energy security, congestion, and accident risk), as well as average-cost pricing of electricity.

Behavioral Explanations

The rise of behavioral economics has brought to the fore another well-defined set of potential explanations of the energy efficiency gap.  A variety of alternative taxonomies could be employed to separate these explanations, but one such taxonomy would categorize the explanations as:

Model and Measurement Explanations

The third category of possible explanations of the energy efficiency gap consists essentially of a set of reasons why observed levels of diffusion of energy-efficiency technologies may actually be privately optimal.

First, there is the possibility of unobserved or understated adoption costs, including unaccounted for product characteristics.

Second, there may be overstated benefits of adoption, due to inferior project execution relative to assumptions, and/or poor policy design.

Third, an incorrect discount rate may be employed in an analysis, when the correct consumer and firm discount rates should vary with:

  • opportunity cost of and access to capital
  • income
  • buying versus retrofitting equipment
  • systematic risk
  • option value (see below)

Fourth, there is frequently heterogeneity across end users in the benefits and costs of employing energy-efficiency technologies, so that what is privately optimal on average will not be privately optimal for all.  This can refer either to static (cross-sectional) heterogeneity or to dynamic (intertemporal) heterogeneity, that is, technology improvements over time, which raises two possibilities:  the reality of some potential adopters being short of the frontier, and the presence of option value to waiting.

Fifth and finally, there is the possibility of uncertainty (real, not informational, as above), irreversibility, and option value.  This could be due to uncertainty regarding future energy prices, or can be linked with option value that arises for delaying investments that have only minimal if any salvage value.

Public Policy and Next Steps

Determining the validity of each of these possible explanations — and the degree to which each contributes to the energy efficiency gap — are crucial steps in crafting the most appropriate public policy responses.

To inform future research and policy, Professor Richard Newell of Duke University and I have launched an initiative – sponsored by the Alfred P. Sloan Foundation — to synthesize past work on these potential explanations of the energy paradox and identify key gaps in knowledge.  We are conducting a comprehensive review and assessment of published and ongoing social-science research on the adoption of energy-efficient technologies, including scholarly literature, industry case studies, reports from national and sub-national governments, and, to the extent possible, consulting reports evaluating specific programs.

We are working with leading social scientists — including scholars from economics, psychology, and other disciplines — to examine the various possible explanations of the energy paradox and thereby to help identify the frontiers of knowledge on the diffusion of energy-efficient technologies.  We hope the products of this initiative will help decision makers in industry and government better understand the energy efficiency gap, and will thereby contribute to decisions that maximize the potential economic, environmental, and other social benefits associated with optimal adoption of energy-efficient technologies.  As materials become available, we will post them at the project’s Harvard website and the project’s Duke website, and I will alert readers of this blog.  In the meantime, please stay tuned.


Does economic analysis shortchange the future?

Decisions made today usually have impacts both now and in the future. In the environmental realm, many of the future impacts are benefits, and such future benefits — as well as costs — are typically discounted by economists in their analyses.  Why do economists do this, and does it give insufficient weight to future benefits and thus to the well-being of future generations?

This is a question my colleague, Lawrence Goulder, a professor of economics at Stanford University, and I addressed in an article in Nature.  We noted that as economists, we often encounter skepticism about discounting, especially from non-economists. Some of the skepticism seems quite valid, yet some reflects misconceptions about the nature and purposes of discounting.  In this post, I hope to clarify the concept and the practice.

It helps to begin with the use of discounting in private investments, where the rationale stems from the fact that capital is productive ­– money earns interest.  Consider a company trying to decide whether to invest $1 million in the purchase of a copper mine, and suppose that the most profitable strategy involves extracting the available copper 3 years from now, yielding revenues (net of extraction costs) of $1,150,000. Would investing in this mine make sense?  Assume the company has the alternative of putting the $1 million in the bank at 5 per cent annual interest. Then, on a purely financial basis, the company would do better by putting the money in the bank, as it will have $1,000,000 x (1.05)3, or $1,157,625, that is, $7,625 more than it would earn from the copper mine investment.

I compared the alternatives by compounding to the future the up-front cost of the project. It is mathematically equivalent to compare the options by discounting to the present the future revenues or benefits from the copper mine. The discounted revenue is $1,150,000 divided by (1.05)3, or $993,413, which is less than the cost of the investment ($1 million).  So the project would not earn as much as the alternative of putting the money in the bank.

Discounting translates future dollars into equivalent current dollars; it undoes the effects of compound interest. It is not aimed at accounting for inflation, as even if there were no inflation, it would still be necessary to discount future revenues to account for the fact that a dollar today translates (via compound interest) into more dollars in the future.

Can this same kind of thinking be applied to investments made by the public sector?  Since my purpose is to clarify a few key issues in the starkest terms, I will use a highly stylized example that abstracts from many of the subtleties.  Suppose that a policy, if introduced today and maintained, would avoid significant damage to the environment and human welfare 100 years from now. The ‘return on investment’ is avoided future damages to the environment and people’s well-being. Suppose that this policy costs $4 billion to implement, and that this cost is completely borne today.  It is anticipated that the benefits – avoided damages to the environment – will be worth $800 billion to people alive 100 years from now.  Should the policy be implemented?

If we adopt the economic efficiency criterion I have described in previous posts, the question becomes whether the future benefits are large enough so that the winners could potentially compensate the losers and still be no worse off?  Here discounting is helpful. If, over the next 100 years, the average rate of interest on ordinary investments is 5 per cent, the gains of $800 billion to people 100 years from now are equivalent to $6.08 billion today.  Equivalently, $6.08 billion today, compounded at an annual interest rate of 5 per cent, will become $800 billion in 100 years. The project satisfies the principle of efficiency if it costs current generations less than $6.08 billion, otherwise not.

Since the $4 billion of up-front costs are less than $6.08 billion, the benefits to future generations are more than enough to offset the costs to current generations. Discounting serves the purpose of converting costs and benefits from various periods into equivalent dollars of some given period.  Applying a discount rate is not giving less weight to future generations’ welfare.  Rather, it is simply converting the (full) impacts that occur at different points of time into common units.

Much skepticism about discounting and, more broadly, the use of benefit-cost analysis, is connected to uncertainties in estimating future impacts. Consider the difficulties of ascertaining, for example, the benefits that future generations would enjoy from a regulation that protects certain endangered species. Some of the gain to future generations might come in the form of pharmaceutical products derived from the protected species. Such benefits are impossible to predict. Benefits also depend on the values future generations would attach to the protected species – the enjoyment of observing them in the wild or just knowing of their existence. But how can we predict future generations’ values?  Economists and other social scientists try to infer them through surveys and by inferring preferences from individuals’ behavior.  But these approaches are far from perfect, and at best they indicate only the values or tastes of people alive today.

The uncertainties are substantial and unavoidable, but they do not invalidate the use of discounting (or benefit-cost analysis).  They do oblige analysts, however, to assess and acknowledge those uncertainties in their policy assessments, a topic I discussed in my last post (“What Baseball Can Teach Policymakers”), and a topic to which I will return in the future.