Exploring Real-World Phenomena with Behavioral Economics

Traditional economic theory asserts that markets are efficient, or that asset prices accurately reflect their intrinsic value. That is to say, if a piece of land sells for $400,000, that’s because the land is actually worth that much.

This belief is rooted in the assumption that market participants are rational and have access to all relevant information, which then allows them to make optimal economic decisions. In this view, any ‘inefficiencies’ are quickly corrected, as investors take advantage of market errors.

However, real-world observations often contradict the notion of efficient markets. Phenomena such as the stock market and dot-com bubbles suggest that markets can be driven by factors other than fundamental value. These events showed how asset prices can deviate significantly from their intrinsic value, sometimes for extended periods.

One explanation for these deviations is that markets are populated by irrational agents, or "homo psychologicus." These agents' decisions and valuations are influenced more by bias and emotions than by rational calculation. This can lead to phenomena such as herd behavior, where investors follow the crowd rather than making independent assessments of value.

The concept of irrational behavior influencing financial decision making is not new. As early as 1936, economist John Maynard Keynes used the term ‘animal spirits,’ referring to how human emotion can drive economic activity. This idea challenges the traditional economic view of humans as purely rational actors and introduces the possibility of systematic biases in decision making.

Behavioral finance builds on this idea, using insights from psychology and behavioral economics to understand irrationality in financial markets. The field seeks to explain why market participants often behave in ways that are inconsistent with the predictions of traditional economic theory.

Behavioral finance draws on various concepts from psychology to explain investors’ irrational behavior. Mental accounting suggests that people treat money differently depending on its source or intended use. Herd behavior explains why investors follow the crowd instead of making independent judgments. And self-attribution illustrates how investors attribute their success to skill but blame bad luck for any failures.

The 2008 financial crisis provides a stark example of how behavioral biases can lead to market instability. Investors, driven by overconfidence and a herd mentality, bid up asset prices in the housing market. This created a bubble that eventually burst, leading to a severe economic downturn. This event highlighted the limitations of the efficient market hypothesis.

A key factor contributing to the crisis was the widespread belief among investors that past performance was a reliable indicator of future returns. Homeowners assumed that home values would increase indefinitely, as they did in the past. When this assumption proved false, many homeowners found themselves unable to meet mortgage obligations, triggering a wave of defaults that set off the financial crisis.

The complexity of financial products being traded also added to the crisis. Many investors did not fully understand these products, yet were willing to buy them. This lack of understanding, combined with overconfidence and herd behavior, created a situation ripe for a market crash.

The 2008 financial crisis underscored the importance of regulation in financial markets. The crisis demonstrated that markets are not always rational or self-correcting, and that unchecked risk-taking can lead to severe economic consequences. This has led to calls for stronger regulation to prevent excessive risk-taking and to ensure that financial institutions have sufficient capital to withstand market downturns.

The crisis also highlighted the role of moral hazard in financial markets. Many of the risky assets that contributed to the crisis were traded by commercial banks on behalf of individual investors. This separation of ownership and control can lead to excessive risk-taking, as those making the decisions are not the ones who bear the full consequences of their actions.

The crisis also served as a reminder of the dangers of herd mentality. Many investors followed the crowd in buying risky assets, contributing to the inflation and subsequent bursting of the housing bubble. This highlights the importance of independent thinking and careful analysis in investment decision making.

Behavioral economics provides a useful lens for understanding the gender pay gap. Studies using the ultimatum game have found that women are often offered less than men and are more likely to accept unfair offers. This illustrates how gender biases can influence economic decisions, contributing to the inequality in pay.

Widespread awareness of the gender pay disparity can also have unintended consequences. If women come to accept lower pay as a social norm, they may be less likely to negotiate for higher wages. This is consistent with the way prospect theory suggests that our decisions are affected by our expectations and reference points.

Efforts to narrow the gender pay gap draw from behavioral economics concepts. By placing emphasis on competencies and skills regardless of gender, advocates reframe the issue by steering the conversation away from gender. As well, the clamor for more transparency in hiring and remuneration policies seeks to minimize the uncertainty around pay negotiations. With better access to information, job seekers might be able to make better employment decisions.

Behavioral economics can also shed light on health-related decisions. Many individuals make choices that prioritize immediate gratification over long-term health benefits, a phenomenon known as present bias. For example, indulging in chocolate cake now brings me immediate pleasure. At this moment, that pleasure outweighs the future health benefits of limiting sugar consumption.

Framing and choice architecture can also be used to improve health-related decision making. For example, presenting healthy habits as status quo might elicit more of the same behavior. If everyone else is getting vaccinated, one might think, “Then perhaps I should too.”

Yet there are skeptics who continue to dig their heels and refuse the COVID-19 vaccine despite the best efforts of health authorities to promote vaccination. We can see in this instance how, in such circumstances, soft measures do not have the same success rate as hard measures, but also that hard measures like mandatory vaccinations are politically challenging to implement.

Behavioral economics can also inform health care policy. For example, status quo bias explains how we might choose inaction when we are overwhelmed by choice. Imagine a person faced with the arduous task of choosing health insurance. With a multitude of options and no idea where to start, one might give up before they’ve even started. By setting default options, governments can sidestep status quo bias on this front.

The phenomenon of decision fatigue, or the deterioration of decision-making ability after making many decisions, is also being discussed more in the medical field. Behavioral economics provides an array of techniques for doctors and health workers to manage decision fatigue, such as simplifying choices, using workflows like fast and frugal trees, and taking regular breaks.

A behavioral economics lens has also been used to examine low participation rates in public health care insurance in the United States, particularly in programs like the Children's Health Insurance Program (CHIP) and Medicaid. By examining and addressing the psychological barriers towards participation, policymakers can encourage participation in these programs more effectively.

One of the commonly cited applications of Thaler and Sunstein’s nudge theory relates to encouraging healthier food choices. ‘School meal nudges’ rely on subtly changing the way food options are presented – say, displaying healthier food more prominently – in order to steer individuals towards these choices. Numerous studies have been published on this topic.

Tobacco consumption is another behavior that the UK's Behavioural Insights Team has sought to combat using behavioral economics. The BIT used techniques like social contracts, which use social pressure to encourage behavior change, and the promotion of electronic cigarettes as a less harmful alternative to traditional cigarettes.

Behavioral economics has also been used in interventions aimed at promoting nutrition and reducing obesity among the youth. These programs use techniques like offering incentives and changing defaults. However, the effectiveness of such programs has yet to be established.

The Peltzman effect, named after economist Sam Peltzman, refers to the idea that safety measures can sometimes lead to more risk-taking. Peltzman proposed this idea in the context of automobile safety regulations in the 1960s, arguing that drivers might take more risks if they felt safer due to regulations that were about to be implemented at the time.

Peltzman's research found that automobile safety regulations did not lead to a decrease in related deaths. This suggested that drivers were indeed taking more risks, presumably because they felt safer. This counterintuitive finding highlights the importance of considering behavioral responses when designing safety measures.

The Peltzman effect has also been observed in other contexts, such as the COVID-19 pandemic. As mask regulations were enforced, some people may have relaxed other safety measures, such as handwashing or social distancing. This highlights the need for comprehensive safety measures that take into account potential behavioral responses.