For more than a decade, governments have been using evidence from behavioral science to make more informed policy decisions. Still, policymakers have struggled to put these research insights into practice on a large scale.
According to Elizabeth Linos, the Emma Bloomberg Associate Professor of Public Policy and Management, policymakers need to overcome three barriers:
- knowing and valuing the evidence from behavioral economics
- translating the correct insight into a new context
- acting on the evidence by implementing the correct insight at scale
Linos expands on these barriers, and possible steps to address them, in “Translating Behavioral Economics Evidence into Policy and Practice,” a report for the National Academies of Sciences, Engineering, and Medicine.*
Knowing and valuing evidence
“The first barrier in translating evidence to practice is informational: Political actors need to know that evidence exists, understand its findings and level of rigor, and value it as useful,” Linos writes.
The way evidence is presented is also important, she says. To maximize uptake, the researchers should explain their work concisely and in accessible language rather than complicated jargon. Who is sharing the evidence is important too: Factors like political affiliation or whether policymakers see the messenger as credible may influence the decision to use evidence.
In addition, not all policymakers value research to the same extent, Linos writes, and some may be discouraged or lose trust if they find that insights from behavioral economics have “a lower-than-expected effect.”
To help them, Linos says that organizations such as think tanks can “play the role of translator, aiming to help policymakers parse through the evidence, weigh more rigorous studies more heavily, and consume the results of those studies in a manageable way.”
Translating evidence into a new context
A second problem is that it can be very difficult to translate research findings into different contexts with different populations. Policymakers, Linos writes, often have to “to produce a ‘conceptual replication’—parsing out the mechanism behind why something works, making an educated guess about whether the same mechanism would apply to a new population or context, potentially testing their educated guess, and using that new information to bring behavioral evidence to a new policy context.”
In addition to the challenge of translating evidence to different contexts, governments may have a hard time conducting randomized controlled trials (RCTs)—the gold standard in behavioral research—for several reasons. Governments may have ethical concerns about running RCTs; they might have logistical and political challenges in collecting data; and they may not feel they have the time to design and implement RCTs. All these factors contribute to a barrier in using evidence.
Linos also sees room for more direct involvement with people who will be affected by the tested policies. “Future work on translation of mechanisms to new contexts should focus primarily on reimagining how new interventions are designed, and by whom,” she writes. “This could include ensuring that those who are most impacted by the policy are involved in designing the adaptation, and the RCT, alongside behavioral researchers.”
According to Linos, “Replicating existing findings in new and more diverse contexts also provides an opportunity to both understand mechanisms more fully and scale ideas that work for more types of populations.”
Scaling up evidence
Linos explains that it can be hard to scale research evidence. For example, the population that academics study might not represent the population at large, meaning that an intervention might only work well with a smaller segment. “Policymakers cannot—and should not—assume similar effects when they try to scale up behavioral interventions, especially if some part of the delivery of the intervention or the target population is fundamentally different than those of the original study,” Linos says.
In addition, governments may not be set up well to bring experiments to scale. Larger and wealthier organizations might do better, along with ones that have a culture of organizational learning. Turnover in government could also be a barrier: Linos says that “efforts to retain innovative career civil servants within government may increase the likelihood of an agency acting on the evidence it has produced.” And logistical challenges may mean that incremental improvements might be easier to make than large-scale ones—something that behavioral scientists should consider when working with practitioners.
Paths for future work
All these barriers suggest a good question for future research: “How do we make it easier for policy practitioners to implement evidence when they know about it, value it, and it is readily applicable to their contexts?”
Linos says that we are still in the early stages of understanding how evidence can inform practice and how this evidence can be successfully translated. “In order for many of the barriers cited here to be addressed, academics, policymakers, and the larger evidence-based policymaking ecosystem may have to shift their behaviors,” she writes.
More interdisciplinary work—and collaborations between researchers and practitioners—may help in designing interventions that will be most valuable to policymakers. So may greater and more thoughtful investment in the people and processes needed to adopt evidence-based policies, as well as improved transparency.
Linos writes that researchers and policymakers should be mindful not only of the outcomes that matter but of the people affected. “Actively expanding who is involved in the production of evidence, both by including more voices in the co-design of interventions and in the selection of outcome metrics, is critical,” she says.
“Ultimately, viewing the process of understanding, translating, and adopting evidence as a series of behavioral pain points allows the research community and the policy community to come together to address a common goal: better policy outcomes through research.”
*Opinions and statements included in the paper are solely those of the individual author(s), and are not necessarily adopted, endorsed, or verified as accurate by the Committee on Future Directions for Applying Behavioral Economics to Policy or the National Academies of Sciences, Engineering, and Medicine.
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