Bringing Behavioral Economics to Development

In recent years, it has been exciting to see policymakers in rich countries begin to take seriously what has long been known in the private sector: Paying attention to seemingly trivial details of policy design can powerfully affect how individuals respond.

Take the example of organ donation in Europe (Figure 1). What explains the vast differences in rates of consent? None of these countries provide incentives—no rewards for consent, nor any tax or fine for refusal. Differences in culture and information do not explain the gap either. For example, Germany and Austria have remarkably similar cultures, yet their consent rates differ by 88 percentage points. And the Netherlands ran an extensive educational campaign and mass mailing asking citizens to register as organ donors, but the campaign failed to change the effective consent rate.

Figure 1. Effective consent rates of becoming an organ donor in select European countries, 2003

Source:  Johnson and Goldstein, 2003.

What then can explain the large differences in the consent rates? The answer turns out to be the default option—whether a person has to choose to be an organ donor (“opt-in”) or choose not to be one (“opt-out”). A person has to opt-in to be an organ donor in the gold countries in the figure, whereas in the blue countries there is presumed consent from which a person can opt-out.

Traditional policymaking would not predict the default option to have a large effect. Standard “rational actor” models assume people behave based on pre-formed preferences. They know what they want and if it is not the default option, they will opt out of the option.

A new wave of public policymaking informed by behavioral economics and psychology submits the assumptions of the rational actor to empirical scrutiny. Public debates are now assessing the introduction of behavioral interventions (interventions based on a non-rational or non-selfish actor) in many domains, including organ donation, taxes, retirement savings, and employment schemes.

Applying behavioral insights in developing countries

In the spirit of such innovative programming, the World Development Report 2015:  Mind, Society, and Behavior examined hundreds of studies, and organized the many strikingly successful interventions they found around three ways that people think:

  1. We think automatically, as well as deliberatively. We don’t always have the mental bandwidth to make careful decisions. Thus we might not make the best use of government programs. The global availability of antiretroviral therapy has improved the health of people living with HIV/AIDS in poor countries, but its impact is severely limited by poor regimen adherence. In Kenya, when patients received a weekly text reminding them to take their drugs, adherence rose by 13 percentage points (from 40-53 percent).
  2. We think socially. Thinking is conditioned by social context and the salience of social identities. We may look at other people’s behavior—for example, whether or not they use a government service—in deciding our own. When eligible female community leaders were made beneficiaries of grants to promote businesses in Nicaragua, program participants became more active and their incomes went up by 40 percent. The community leaders’ involvement in the program increased communication and motivation.
  3. We think with mental models. We rely on a cultural toolkit of categories, concepts, worldviews, and other mental models to filter, process, and interpret information and guide action. If policy goals are inconsistent with widely shared mental models, interventions may not be effective or may even make things worse. When a civic education intervention was run in communities in Mali, female political participation declined. The program increased the salience of civic activity, which in turn increased men’s resistance to women’s civic participation. Threats of sanctions against their participation discouraged women from engaging in civic life.

To see how powerful insights into human psychology can be for policy, consider an intervention in Kenya aimed at preventing traffic accidents. As shown in the graph from The Economist, traffic accidents in poor and middle-income countries have become a major public health problem. They kill more people than tuberculosis and malaria and are forecast to kill as many as HIV/AIDS by 2030.

Figure 2. Global deaths by selected cause (millions)

Source:  The Economist, based on WHO data.

What can be done? Traditional interventions—harsher penalties for reckless driving, stronger enforcement mechanisms—can be costly and often have little independent effect. In Kenya, practitioners and researchers collaborated to place stickers in accident-prone buses. The stickers urged passengers to speak up against reckless driving.

Figure 3. Bumper sticker in Kenya

Source: Habyarimana and Jack, 2011.

Accident rates in buses that had stickers plummeted. Why? People knew that buses were dangerous before the intervention. In a passenger survey before the intervention, one-third of respondents reported having felt that their lives were in danger on a recent trip. But the bus stickers changed something in the environment. The seemingly trivial change of posting a sticker transformed the behavior of the drivers. It saved lives at a cost per year of a life saved—$5.80—that was even lower than the cost of saving lives through vaccines.

Examples like this demonstrate that behavioral economics has the potential to revolutionize development policy. Many interventions documented in the WDR can be scaled up. The new field of behavioral development economics should be expanded with care, however. To list just three considerations:

  1. Behaviorally informed interventions must be introduced with care for the dignity and autonomy of the individuals and communities affected. Just as, for example, the United Kingdom is publicly debating whether and how to change their laws on consent for organ donation, the use of behavioral interventions in poor countries must be transparent and subject to local public deliberation. This means that some behavioral interventions might not be desirable even if they would promote globally recognized development outcomes.
  2. Development practitioners are far from having a clear picture as to when evidence from one context is generalizable to others. There is increasing evidence that institutions have deep effects on how people think. Thus individuals in societies with different institutions may process information in systematically different ways. In China, people who grew up in areas that historically farmed rice (a relatively collective activity) think more interdependently than those who grew up in wheat-growing regions (a relatively individualistic activity). When making associations, people in rice cultures are drawn to relationships rather than categories. And they are more likely to display loyalty (or nepotism) and less likely to divorce. The WDR and the work that elaborates on it offer proofs of concept—demonstrations that taking a richer notion of how people think can improve development interventions in ways that standard models would not predict. But we are still far from a general and parsimonious theory of human behavior. Ethically designed experiments can help identify the social and psychological factors of importance in a particular context. A recent experiment in Kenya showed that when people were given a lockable metal box, padlock, and passbook, they increased their investment in health products by 66-75 percent. This could only have been hypothesized beforehand and cannot be generalized to other settings. It has to be tested, and in many cases, randomized control trials can be both cheap and quick.
  3. Behavioral interventions, like all other interventions, can have unanticipated effects—for example, by eroding valued institutions. An intervention that helps poor households to save more by adopting formal commitment devices (such as having a fixed amount of your income taken out during harvest season) may do so by enabling them to avoid commitments under informal insurance schemes, making society as a whole worse off. Many interventions need to be piloted at small levels first, before considered for broad testing and application.

With these and other considerations in mind, there is a large potential for behavioral interventions to enhance the effectiveness of development institutions. The WDR provides a new framework for the subfield of behavioral development economics. It will be exciting to see what progress is made in this field in coming years.

This article originally appeared in [https://www.brookings.edu/blog/future-development/2015/05/19/bringing-behavioral-economics-to-development/] and belongs to the creators.

What Behavioral Science Has to Say About Energy Conservation

Energy efficiency depends not only on the availability of energy efficient technologies, but also whether people adopt them and how they are used. New research shows that energy conservation programs motivated by behavioral science are relatively cost effective.

To combat climate change, many economists and policymakers advocate price-based approaches, such as greenhouse gas emissions taxes and emissions trading programs, or technology-based approaches, such as R&D subsidies and public-private R&D partnerships.  In the end, however, both types of approaches rely on consumers and firms to make different choices: they will need to change what they do and what they buy in response to increases in the relative prices of carbon-intensive goods. A growing body of research in psychology and behavioral economics suggests that non-price interventions can be just as powerful as prices in changing consumer choices.

Historically, energy efficiency has been a leading example of the difficulties in inducing people to change behaviors and adopt new technologies, even when it appears to be in their own financial interest. The great potential for energy efficiency has been detailed in consistently optimistic language over the past 30 years. Investments in fluorescent light bulbs and new insulation appear to pay for themselves very quickly. For example, a recent consulting report concluded that many households and businesses in the United States have yet to take such relatively straightforward measures, even though doing so could reduce energy consumption by 23 percent from the baseline and earn $1.2 trillion, more than double the up-front cost of $520 billion.

Compared to these possibilities, however, the actual penetration of energy-efficient technologies and behaviors has been strikingly low. Although there are many reasons for this, prices and technology are certainly not the only barriers to increased energy efficiency.

In the past 15 years, a series of hundreds of partnerships between behavioral scientists and partner organizations—including governments, NGOs, and private-sector businesses—have generated non-price interventions with increasingly compelling results. These partnerships have arisen in a variety of domains, including retirement savings, microfinance, economic development, and health—as well as in energy use and environmental behaviors. Some programs have proven remarkably powerful: in one case, a company worried about its employees’ retirement savings, introduced a behaviorally motivated program that increased employees’ average savings rate by 400 percent. Crucially, behavioral interventions are often much less costly to implement than other common approaches to greenhouse gas emissions abatement, such as R&D for energy technologies or replacement of fossil-fuel based electricity generation with renewables. 

The Power of Non-Price Interventions in Energy Conservation

Energy conservation programs based on approaches other than changing relative prices have been studied in a large body of ongoing research on social approval, consumption feedback, goal setting, commitment, and other mechanisms. Although many of these were small-scale, short-term pilot studies on nonrepresentative populations, they do show proof of concept.

Recent work by OPOWER, an energy-efficiency software and consulting firm, shows this concept can be realized at scale. During the past two years, OPOWER has partnered with utilities in Northern and Southern California, Washington, Minnesota, Illinois, Colorado, Virginia, and other states to send energy use reports to residential electricity and natural gas consumers. The reports display the household’s energy consumption, compare it to similar households over time, and provide energy conservation tips. The social comparisons are based on research that showed that descriptive social norms are better at reducing energy use than appeals to saving the environment and to social responsibility (despite the fact that many households claim that social norms have little influence on their behavior).

OPOWER’s pilot programs were designed for rigorous evaluation: from a population of households in the utility’s service territory, some are randomly selected to receive the report letters, while the rest remain as a control group. Comparing the electricity bills of the treatment and control groups gives a clean estimate of the actual energy conservation caused by the reports. Such analysis shows that OPOWER’s reports prompt households to reduce energy use by about two percent, depending on the program’s location, frequency, and duration.

Economists would point to “social learning” and “conditional cooperation” as two reasons why social comparisons could cause people to conserve energy. Social learning means that a homeowner who learns that his or her neighbors are using much less energy might infer that he also has low-cost opportunities to conserve. Conditional cooperation means that people are more likely to contribute to public goods, such as moderating global climate change, when informed that others are contributing.

Results also show that households that were high energy consumers before the OPOWER program conserve substantially more than households whose baseline consumption was low. The heterogeneous treatment effects imply that “profiling,” or targeting future treatment toward high-energy-using households, could markedly improve cost-effectiveness.

Interventions that encourage adoption of energy-saving technology and behaviors can be highly cost effective: a nationally scaled program similar to OPOWER’s program in Minnesota could cause energy conservation at a cost to the utility of 2.5 cents per kilowatt-hour (kWh) saved. This compares very favorably with estimates of the average cost of other energy-efficiency programs, which in two recent studies range from 1.6 to 3.3¢ and 5.5 to 6.4¢ per kWh. If scaled nationwide, a program like this could reduce U.S. carbon dioxide (CO2) emissions from electric power by 0.5 percent, while actually saving $165 per metric ton of reductions. This compares very favorably with other, more traditional strategies to reduce carbon emissions; wind power, carbon capture and storage added to new coal power plants, and plug-in hybrid vehicles are estimated to cost $20, $44, and $15 per metric ton of CO2 abated.

Policy Implications

here are three key policy implications of this discussion. First, governments can provide funding for potentially high impact behavioral programs as part of their broader support for energy innovation. A bill under consideration in the U.S. House of Representatives, HR 3247, would establish a program at the Department of Energy to understand behavioral factors that influence energy conservation and speed the adoption of promising initiatives.

Second, through market incentives, policymakers can encourage—or fail to encourage—private-sector firms to generate and utilize behavioral innovations that “nudge” consumers to make better choices. Historically, economists and policymakers have focused on how regulation affects relative prices—for example, how emissions caps or taxes on pollution-intensive goods affect the prices firms set.

In practice, however, firms interact with consumers in many ways in addition to pricing. Utilities, for example, can give consumers clear or opaque information about energy-efficient goods, can make it easy or difficult to find out about energy-efficiency promotions, and can otherwise nudge consumers in ways that cause them either to increase or decrease consumption. “Decoupling,” a regulatory change that separates electricity retailers’ profits from quantities sold, is one mechanism that could encourage firms to nudge consumers toward reducing energy use. Another policy mechanism, now common in many states, is energy efficiency resource standards (akin to renewable portfolio standards), which require utilities to document that they are inducing energy conservation.

Third, government agencies often provide independent information disclosure, such as vehicle and appliance energy-efficiency ratings. This helps catalyze private-sector innovation by allowing firms to credibly convey the financial value of energy efficiency to consumers. The effect of information on choices, however, depends critically on how the information is conveyed, and government agencies should carefully consider behavioral factors in the disclosures they control. For example, rating fuel economy in miles per gallon (MPG) can mislead consumers. This is because most people reflexively think that annual fuel use and fuel costs increase linearly in miles per gallon, while in reality they do not. For example, increasing a 14 MPG vehicle to 17 MPG saves the same amount of gasoline and money as increasing a 33 MPG vehicle to 50 MPG.

Third, government agencies often provide independent information disclosure, such as vehicle and appliance energy-efficiency ratings. This helps catalyze private-sector innovation by allowing firms to credibly convey the financial value of energy efficiency to consumers. The effect of information on choices, however, depends critically on how the information is conveyed, and government agencies should carefully consider behavioral factors in the disclosures they control. For example, rating fuel economy in miles per gallon (MPG) can mislead consumers. This is because most people reflexively think that annual fuel use and fuel costs increase linearly in miles per gallon, while in reality they do not. For example, increasing a 14 MPG vehicle to 17 MPG saves the same amount of gasoline and money as increasing a 33 MPG vehicle to 50 MPG.

Persuasion vs. Nudging

I’ll conclude by drawing a distinction between “persuasion” and “nudging.” Persuasion is an attempt to influence people to do what the persuader wants—buy a product, conserve energy, reuse hotel towels, and so on. Nudges are attempts to help people to get what they themselves want, but don’t get because of mistakes that all humans make. Utilities marketing energy efficiency programs are rightly focused on persuasion. But policymakers should be careful to remember that the goal is not to minimize society’s energy consumption—we could do that immediately by shutting off all of our power plants. Instead, the goal is to make people as well off as possible overall. While pushing energy efficiency and green energy programs is appealing, I would advocate that policymakers proceed by identifying market failures—potentially including mistakes that consumers make and additional information they would find useful—and introducing policies to address them directly.

This article originally appeared in [https://www.resourcesmag.org/common-resources/what-behavioral-science-has-to-say-about-energy-conservation/] and belongs to the creators.