Behavioral Insights

What is Behavioral Economics?

Behavioral economics is a field that combines insights from psychology and economics to understand how individuals actually make decisions, often deviating from the purely rational models traditionally assumed in economics. It examines how factors like cognitive biases, emotions, social influences, and heuristics impact economic choices.

How Can Behavioral Economics Increase Effectiveness in Public Policy?

By acknowledging and leveraging the ways in which real people make decisions, behavioral economics can enhance public policy effectiveness. Policies designed with behavioral insights can “nudge” individuals toward beneficial behaviors without restricting freedom of choice.

What Are Behavioral Insights?

Behavioral insights refer to the application of behavioral economics principles to the design and implementation of policies and programs. These insights help policymakers understand and predict human behavior, allowing for the creation of interventions that guide people toward better choices while preserving autonomy.

The Economist as Plumber

In her essay “The Economist as Plumber,” Esther Duflo (AER, 2017) emphasizes the importance of economists engaging with the practical details of policy implementation. She argues that economists should not only design policies but also understand the intricacies of how they are executed, much like a plumber understands the workings of pipes to fix a leak. This hands-on approach ensures that policies function effectively in real-world settings.

Examples of Behavioral Insights Units Around the Globe

– United Kingdom: The Behavioural Insights Team (BIT), also known as the “Nudge Unit”.

– United States: The Social and Behavioral Sciences Team (SBST)

– Australia: The Behavioural Economics Team of the Australian Government (BETA).

– OECD – Behavioural Insights Knowledge Hub

– World Bank – Mind, Behavior, and Development Unit (eMBeD)

– United Nations – Behavioural Science Group

– European Commission – Competence Centre on Behavioural Insights (CCBI)

– World Health Organization (WHO) – Behavioural Sciences for Better Health

Note: These organizations offer excellent opportunities for PhD graduates in behavioral economics to apply their expertise in public policy

Basic Tools in Public Policy:

1) Regulation: Establishing rules or laws that mandate or prohibit certain behaviors (e.g., smoking bans).

2) Information: Providing data or education to inform choices (e.g., nutritional labels).

3) Incentives: Offering financial or other rewards/punishments to encourage or discourage behaviors (e.g., tax credits for renewable energy use).

Behavioral insights complement these tools by addressing the psychological factors that influence how people respond to regulations, information, and incentives.

Choice architecture refers to the way in which choices are structured and presented to individuals. The concept, introduced by Thaler and Sunstein, emphasizes that the design of the decision environment—even when seemingly neutral—has a strong impact on the choices people make. Behavioral public policy uses this insight to design environments that nudge people toward better choices without restricting freedom.

I. Execution Aids

These behavioral tools can help individuals follow through on their intentions. While people often know what they want (e.g., save more, exercise, vaccinate), they fail to act due to forgetfulness, procrastination, cognitive overload, or competing short-term temptations.

– Defaults: Setting pre-selected options to guide choices. Default tends to be selected disproportionately: not necessarily because it is the best option, but because it reduces cognitive effort, signals a recommended choice, and avoids friction.

Thaler, R. H., & Benartzi, S. (2004). Save More Tomorrow™: Using Behavioral Economics to Increase Employee Saving. Journal of Political Economy, 112(S1), S164–S187.

– Active Choice: Requiring individuals to make an explicit choice to prompt action. The person must say yes or no—they cannot ignore the decision or passively continue.

Carroll, G. D., Choi, J. J., Laibson, D., Madrian, B. C., & Metrick, A. (2009). Optimal Defaults and Active Decisions. Quarterly Journal of Economics, 124(4), 1639–1674.

– Simplification: Removing sludge and reducing complexity to facilitate access and comprehension. It is especially effective in situations where cognitive overload, limited time, or low familiarity may prevent individuals from making beneficial choices.

Bettinger, E. P., Long, B. T., Oreopoulos, P., & Sanbonmatsu, L. (2012). The Role of Application Assistance and Information in College Decisions: Results from the H&R Block FAFSA Experiment. Quarterly Journal of Economics, 127(3), 1205–1242.

Bhargava, S., & Manoli, D. (2015). Psychological Frictions and the Incomplete Take-Up of Social Benefits: Evidence from an IRS Field Experiment. American Economic Review, 105(11), 3489–3529.

Abaluck & Gruber (2011) Choice Inconsistencies Among the Elderly American Economic Review, 101(4), 1180–1210.

– Decision Aids: Tools designed to help individuals make more informed, deliberate, and confident decisions—especially when facing complex or high-stakes choices.

Hastings, J. S., & Weinstein, J. M. (2008). Information, School Choice, and Academic Achievement: Evidence from Two Experiments. Quarterly Journal of Economics, 123(4), 1373–1414.

– Feedback/Reminders: Providing individuals with timely and relevant information about the outcomes of their actions. The goal is to help people adjust their behavior based on real or perceived consequences, especially when those consequences are delayed, invisible, or abstract.

Karlan, D., McConnell, M., Mullainathan, S., & Zinman, J. (2016). Getting to the top of mind: How reminders increase saving. Management Science, 62(12), 3393–3411.

Kuan, R., Blagg, K., & Castleman, B. L. (2025). Behavioral nudges prevent loan delinquencies at scale: A 13-million-person field experiment. Proceedings of the National Academy of Sciences, 122(4), e2401234567.

– Implementation Intentions: self-regulatory strategy in which individuals form concrete “if–then” plans that specify when, where, and how they will act toward a goal.

Milkman, K. L., Beshears, J., Choi, J. J., Laibson, D., & Madrian, B. C. (2011). Using implementation intentions prompts to enhance influenza vaccination rates. Proceedings of the National Academy of Sciences, 108(26), 10415–10420.

– Commitment Devices: Mechanisms that bind individuals to future desired behaviors. They help align long-term goals (e.g., saving, exercising, quitting smoking) with short-term behavior by introducing penalties or constraints for not following through.

Ashraf, N., Karlan, D., & Yin, W. (2006). Tying Odysseus to the Mast: Evidence from a Commitment Savings Product in the Philippines. Quarterly Journal of Economics, 121(2), 635–672.

– Digital Nudging: Using digital design elements—such as colors, layout, wording, timing, or interactive features—to influence users’ decisions and behavior in digital environments.

Bhargava, Loewenstein, & Sydnor (2017). Choose to Lose: Health Plan Choices from a Menu with Dominated Options, Quarterly Journal of Economics, 132(3), 1319–1372.

– Gamification: Applying game-like elements—such as points, badges, levels, challenges, leaderboards, rewards, and progress tracking—in non-game contexts to motivate, engage, and influence behavior.

Zhao, Z. (2024). The Effect of Gamification on Employee Boredom and Performance. Accounting Perspectives, 23(3), 375–401.

– Algorithmic Personalization: Use of data-driven algorithms to customize content, recommendations, and decision environments based on an individual’s past behavior, stated preferences, or inferred traits.

II. Cognitive Framing Tools

These behavioral tools can affect how people form their preferences or prioritize among them, often in subtle but powerful ways.

– Framing: Presenting information in different ways to influence decisions.

Hallsworth, M., List, J. A., Metcalfe, R. D., & Vlaev, I. (2017). The behavioralist as tax collector: Using natural field experiments to enhance tax compliance. Journal of Public Economics, 148, 14–31.

– Labeling: Using labels to influence how options are perceived.

Thorndike, A. N., Sonnenberg, L., Riis, J., Barraclough, S., & Levy, D. E. (2012). A 2-phase labeling and choice architecture intervention to improve healthy food and beverage choices. American Journal of Public Health, 102(3), 527–533.

– Ordering: The sequence in which options are presented can affect choices.

Huang, Y., & Hutchinson, J. W. (2022). Order in multi-attribute product choice decisions: Evidence from eye-tracking. Journal of Behavioral Decision Making, 35(1), e2320.

– Social Norms / Proof: Informing individuals about others’ behavior to guide decisions.

Allcott, H. (2011). Social norms and energy conservation. Journal of Public Economics, 95(9–10), 1082–1095.

Allcott, H., & Rogers, T. (2014). The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation. American Economic Review, 104(10), 3003–3037.

Beshears, J., Choi, J. J., Laibson, D., Madrian, B. C., & Milkman, K. L. (2015). The effect of providing peer information on retirement savings decisions. Journal of Finance, 70(3), 1161–1201.

– Saliency / Concreteness: Making relevant aspects more noticeable and tangible to improve comprehension.

Chetty, R., Looney, A., & Kroft, K. (2009). Salience and Taxation: Theory and Evidence. American Economic Review, 99(4), 1145–1177.

Kling, J. R., Mullainathan, S., Shafir, E., Vermeulen, L. C., & Wrobel, M. V. (2012). Comparison friction: Experimental evidence from Medicare drug plans. Quarterly Journal of Economics, 127(1), 199–235.

– Priming: Stimulating responses through exposure to specific cues.

Cohn, A., Fehr, E., & Maréchal, M. A. (2015). Business culture and dishonesty in the banking industry. Nature, 516(7529), 86–89.

– Anchoring: The influence of an initial value on subsequent judgments.

Ariely, D., Loewenstein, G., & Prelec, D. (2003). Coherent Arbitrariness: Stable Demand Curves Without Stable Preferences. Quarterly Journal of Economics, 118(1), 73–105.

– Affect / Emotional Framing: Using emotions to influence decisions.

Lerner, J. S., Small, D. A., & Loewenstein, G. (2004). Heart strings and purse strings: Carry-over effects of emotions on economic decisions. Psychological Science, 15(5), 337–341.

– Moral Suasion: Appealing to moral values to encourage desirable behavior.

Ito, K., Ida, T., & Tanaka, M. (2018). Moral Suasion and Economic Incentives: Field Experimental Evidence from Energy Demand. American Economic Journal: Economic Policy, 10(1), 240–267.

Capraro, V., Jagfeld, G., Klein, R., Mul, M., & van de Pol, I. (2017). Increasing altruistic and cooperative behaviour with simple moral nudges. Scientific Reports, 9, 11880.

– Messenger Effect: The effectiveness of a message may depend on who delivers it.

Hafner, R., Elmes, D., & Read, D. (2019). Exploring the role of messenger effects and feedback frames in promoting uptake of energy-efficient technologies. Current Psychology, 38, 1601–1612.

– Ego / Identity Framing: Leveraging a person’s identity to influence decisions.

Bryan, C. J., Walton, G. M., Rogers, T., & Dweck, C. S. (2011). Motivating voter turnout by invoking the self. Proceedings of the National Academy of Sciences, 108(31), 12653–12656.

III. Behaviorally-Informed Incentives

These behavioral tools enhance the effectiveness of incentives by acknowledging that people do not respond to rewards and penalties in purely rational, calculated ways. Instead, their reactions are shaped by psychological biases, emotions, timing, and social context.

– Non-Monetary Incentives: Using non-financial rewards to motivate behavior.

Ashraf, N., Bandiera, O., & Jack, B. K. (2014). No margin, no mission? A field experiment on incentives for public service delivery. Journal of Public Economics, 120, 1–17.

– Lottery-like Incentives: Using lotteries to encourage desirable behaviors.

Volpp, K. G., John, L. K., Troxel, A. B., Norton, L., Fassbender, J., & Loewenstein, G. (2008). Financial incentive–based approaches for weight loss: A randomized trial. JAMA, 300(22), 2631–2637.

Halpern, S. D., Harhay, M. O., Saulsgiver, K., Brophy, C., Troxel, A. B., & Volpp, K. G. (2015). A pragmatic trial of e-cigarettes, incentives, and drugs for smoking cessation. New England Journal of Medicine, 373(13), 1230–1240.

– Loss Framing: Highlighting potential losses to motivate action.

Fryer, R. G., Jr., Levitt, S. D., List, J. A., & Sadoff, S. (2022). Enhancing the Efficacy of Teacher Incentives through Framing: A Field Experiment. American Economic Journal: Economic Policy, 14(4), 269–299.

Levitt, S. D., List, J. A., Neckermann, S., & Sadoff, S. (2016). The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance. American Economic Journal: Economic Policy, 8(4), 183–219.

Hossain, T., & List, J. A. (2012). The Behavioralist Visits the Factory: Increasing Productivity Using Simple Framing Manipulations. Management Science, 58(12), 2151–2167.

– Social Incentives: Rewards based on social recognition.

Butera, L., Metcalfe, R., Morrison, W., & Taubinsky, D. (2019). The Deadweight Loss of Social Recognition. American Economic Association.

Useful references:

Books

Congdon, W. J., Kling, J. R., & Mullainathan, S. (2011). Policy and choice: Public finance through the lens of behavioral economics. Brookings Institution Press.

Hallsworth, M., & Kirkman, E. (2020). Behavioral insights. MIT Press.

Ruggeri, K. (Ed.). (2018). Behavioral insights for public policy: Concepts and cases (1st ed.). Routledge.

Shafir, E. (Ed.). (2013). The behavioral foundations of public policy. Princeton University Press.

Reports

Behavioural Insights Team. (2024). EAST: Four simple ways to apply behavioural insights. Behavioural Insights Ltd.

Dolan, P., Hallsworth, M., Halpern, D., King, D., & Vlaev, I. (2010). MINDSPACE: Influencing behaviour through public policy. Institute for Government.

Organisation for Economic Co-operation and Development. (2017). Behavioural insights and public policy: Lessons from around the world. OECD Publishing.

Applications (examples)

World Health Organization. (2022). Setting up behavioural insights units for improved health outcomes. WHO Regional Office for Europe.

Behavioural Insights Team. (2017). Behavioural insights for education: A practical guide for parents, teachers and school leaders.

European Commission. (n.d.). Behavioural insights for finance. Knowledge for Policy.

World Bank. (2019). Behavioral insights for tax compliance.

Behavioural Insights Team. (2024). Behavioral insights and anti-corruption.

Behavioural Insights Team. (2021). How to improve gender equality in the workplace: Evidence-based actions for employers.

United Nations Environment Programme Copenhagen Climate Centre. (2020). Applying behavioral insights for cost-effective energy efficiency interventions.

Environmental Protection Agency (Ireland). Behavioural insights on climate change.

Gavel, D. (n.d.). How behavioral science can help people get to the polls. Harvard Kennedy School.