The science of manipulation

Classical economic theory assumes people act rationally and strive to maximise their gains. Yet a strand of scholarship disputes this, pointing out that people often act irrationally, swayed by emotions, biases and cognitive limits.

In this ForkLog article, we examine how behavioural economics has changed the way we think about human action, why it became influential, and the challenges it has encountered.

Origins: from classical theory to psychology

For a long time, economic theory rested on the assumption that people act rationally, weighing every decision and assessing benefits. In classical models, the value of a good depends on how much of it a person has: the first unit is highly desired, the second less so, and subsequent ones barely matter.

Armed with such ideas and mathematical methods, scholars sought to explain how the economy works. This approach, known as the ‘economic man’ concept, underpinned much research. In practice, however, people often behave otherwise. Behavioural economics emerged to account for these deviations, showing that decisions are frequently shaped by incidental, independent factors such as emotions, social pressure and cognitive biases.

Psychological aspects of behaviour were addressed as early as Adam Smith’s “The Theory of Moral Sentiments” (1759). In the 20th century, cognitive psychology developed and showed that departures from rationality are systematic and predictable. Behavioural economics took clearer shape as a bridge between individual behaviour and economic processes, offering a new perspective on markets, investment and public policy.

One of the field’s key contributions is the idea of bounded rationality, developed by the American scholar Herbert Simon. He showed that people rarely have all the information and cognitive resources needed to make ideal decisions. Instead they rely on simplified rules that help them navigate complexity more quickly. His ideas laid the groundwork for analysing real human behaviour and for further research in behavioural economics.

In 1979, psychologists Daniel Kahneman and Amos Tversky published Prospect Theory: An Analysis of Decision under Risk, which founded prospect theory. It describes how people choose between alternatives with known outcome probabilities. Individuals evaluate gains and losses relative to a reference point, overweighting low-probability events and underweighting high-probability ones.

Kahneman and Tversky showed that losses loom larger than equivalent gains: losing $100 hurts more than gaining $100 pleases. Choices also depend on framing — the way information is presented. For example, people are more likely to opt for an operation with a “90% success rate” than one with a “10% risk”, though both are identical. Prospect theory reshaped notions of rationality and became a cornerstone of behavioural economics.

The American economist Richard Thaler — one of the field’s leading popularisers — made major contributions by showing how small changes in the environment can strongly influence behaviour. His “nudge” concept posits that well-designed prompts — for example, automatic enrolment in a pension programme or putting healthy food at eye level in a canteen — can steer people towards better choices without infringing their freedom to choose.

Thaler also studied bounded rationality, social preferences and self-control, stressing that people often act against their long-term interests. In 2017 he received the Nobel prize and joked that he would spend the prize money “as irrationally as possible”, neatly illustrating the human nature he had studied for decades.

Another important strand applies behavioural principles to financial markets, where irrationality is especially vivid. The 2013 Nobel laureate Robert Shiller showed how psychological factors such as over-optimism or panic foster bubbles and crises. His analysis of the late-1990s dotcom bubble and the 2008 mortgage crisis demonstrated that markets are far from always efficient. Shiller highlighted the role of “narrative economics” — stories and expectations that shape investor behaviour and generate waves of hype or fear.

Irrationality at work: how we err

From a behavioural-economics perspective, human decisions often diverge from rational models because of psychological, emotional and social factors. These deviations are not random but systematic and predictable, allowing their impact on economic behaviour to be analysed.

The field rests on several key ideas that explain why people act irrationally and how this shows up in everyday choices, from shopping to investing:

• bounded rationality. People do not always make optimal choices because of limits on information, time or cognitive ability. They use heuristics (simplified decision rules) that can lead to errors. For example, in his research Kahneman posed this riddle to students: “A baseball bat and a ball together cost $1.10. The bat costs $1 more than the ball. How much does the ball cost?” Most quickly answered “10 cents”, though the correct answer is 5 cents. This shows that people often decide intuitively and only then check correctness. Heuristics often give rise to cognitive biases — systematic errors in thinking such as overconfidence, status quo bias or anchoring — which also matter for decision-making;
• emotions and social factors. Feelings, social norms and peer pressure shape choices. For example, an experiment at Western Electric showed that workers’ productivity rose with changes in lighting (up, down or back to the starting level) not because of the light itself but because workers felt observed by researchers who asked questions and tracked results;
• market inefficiency. Irrational behaviour by market participants leads to mispricing, poor investment choices and anomalies. Thaler showed that phenomena such as the January effect or the momentum effect arise from cognitive biases — overconfidence or herding. Such anomalies contradict the efficient-market hypothesis, which holds that prices always reflect all available information.

Behavioural economics drew inspiration from psychology but applied its principles to economic processes, analysing how irrationality influences markets, policy and individual decisions.

Heuristics: traps of the mind

Heuristics are simplified mental strategies used to make quick decisions under uncertainty, relying on experience or intuition. They can, however, produce cognitive biases by oversimplifying complex information, ignoring important details or overweighting particular factors — and thus lead to error.

There are many heuristics and biases, and researchers keep identifying new ones. Here are a few:

• anchoring. People lean on the first piece of information they see, even if it is irrelevant. When buying a car, if a dealer first quotes 3m and then “discounts” to 2.5m, the buyer may see it as a bargain even if the market price is 2m;
• reflection effect. People avoid risk in the domain of gains but seek risk in the domain of losses. Most will choose a sure gain of $300 over an 80% chance of $400, yet prefer an 80% chance of losing $400 to a sure loss of $300;
• status quo bias. People prefer to keep things as they are even when change could be better. For fear of the unknown, someone may leave money in a low-yield bank account rather than invest in higher-return assets;
• endowment effect. People ascribe higher value to what they already own. The owner of an old car may refuse to sell it at the market price because he deems it reliable and is used to it;
• framing effect. Wording shapes choice: shoppers are more likely to pick meat described as “95% lean” than “5% fat”, though both are the same;
• availability heuristic. People judge the likelihood of events by how easily examples come to mind. After news of air disasters, more people fear flying;
• representativeness heuristic. People assess probabilities using stereotypes or similarity to a “typical” case, ignoring statistics. In hiring, an employer may pick a candidate who “looks like a successful manager” even if others have more relevant experience;
• gambler’s fallacy. People believe they can influence random events. A casino player thinks his “strategy” for pressing a slot-machine button boosts his odds, though outcomes are random.

Building on these features of thought, behavioural economics shows that economic behaviour is not just about calculating payoffs; it is a complex interplay of psychology, emotions and social norms.

Nudge or manipulation? Ethics and debates

Behavioural economics has not escaped criticism, often from adherents of traditional theory. Scholars such as Milton Friedman, Gary Becker and Eugene Fama argue that in competitive settings with access to knowledge people, while not perfect, gravitate towards rational behaviour.

Friedman stressed that economic models need not describe behaviour perfectly if they predict market outcomes successfully. Fama, known for the efficient-market hypothesis, argued that the anomalies flagged by behavioural economists often have rational explanations or stem from limited data rather than systematic irrationality. In this view, real markets — with their dynamics and learning — push people towards near-optimal choices, making lab-based findings less applicable to complex situations.

Sceptics also target the field’s methods. Experiments and surveys, on which much of the research relies, are prone to systematic distortions. Respondents may display bias or act strategically, and their answers may not reflect true preferences.

Traditional economics emphasises revealed preferences — those manifested in actual behaviour — rather than stated ones. David K. Levine, in Is Behavioral Economics Doomed? (2012), highlights the problem of weak incentives for experimental subjects, which can undermine validity. He also criticises the field for a tendency to craft a new theory for each new fact instead of seeking a unified explanatory model.

Another contentious issue is ethics. The psychologist Nick Chater expressed concern that Thaler’s “nudge” could be seen as a call to manipulation, especially if people are unaware their choices are being steered. This reflects a dilemma between free will and attempts to improve decisions via psychological mechanisms. Despite its successes, behavioural economics remains a field of sharp debate about human nature and how to study it.

An economy with a human face: what next?

Behavioural economics is evolving fast, integrating with other disciplines such as neuroeconomics (the study of the brain during decision-making), behavioural finance and big-data analysis. The use of artificial intelligence makes it possible to study behaviour in real time and build more accurate models.

Many countries have set up dedicated units (for example, the Behavioral Insights Team in Britain) to apply these approaches to social problems: improving tax compliance or environmental behaviour. In marketing, behavioural principles are used to shape demand: anchoring helps set prices (discounts from a “list” price), loss aversion underpins limited-time offers (“Only two places left!”), and social proof drives reviews and ratings (“90% of customers recommend”). Digital design and finance also deploy nudges, simplifying choices (automatic subscriptions, intuitive interfaces) and deepening engagement.

Behavioural economics views the person not as a rational machine but as a complex being whose decisions are formed by psychology, emotions and social factors. It explains why people act irrationally and offers tools to channel their desires and actions.

From nudging in public policy to analysing financial crises, the field’s ideas are applied in the real world, fuelling debate about the balance between freedom of choice and guided behaviour. It remains influential, offering a distinctive view of how people, institutions and the economy interact under uncertainty.

Text: Anastasia O.