Misbehaving

Thaler describes a period in 2002 at the University of Chicago Booth School of Business when faculty research took a backseat to the task of selecting new offices in their soon-to-be-completed building. The method chosen for office allocation was a draft system, where the order of selection was determined by “merit,” as decided by Deputy Dean John Huizinga. This merit-based order was not revealed initially, leading to intense speculation and eventual revelation through a collective email exchange.

The process divided tenured faculty into different bins for selection order, with senior professors choosing before junior ones. However, the criteria for these categorizations were ambiguous, causing discontent among faculty who felt they deserved earlier picks. Tensions rose, particularly among senior faculty, as those in lower bins or unlucky in the lottery felt slighted compared to their peers.

The actual draft day was chaotic. It was halted when discrepancies in the reported office sizes were discovered, leading to a suspension and re-measurement. The resumption of the draft allowed for changes in selections but prohibited choosing offices already picked by others, further fueling frustrations.

Thaler reflects on the entire process, noting the irony that most offices were quite similar, making the intense competition over them somewhat unwarranted. He suggests greater transparency in the process and adjustments in office design could have mitigated some of the disputes.

Thaler and his former student Cade Massey analyze decision-making in the National Football League (NFL), particularly focusing on player selection during the draft. Their research aims to counter the Becker conjecture, which posits that in competitive labor markets, only the most efficient decision-makers (Econs) hold key positions. Thaler and Massey hypothesize teams overvalue early draft picks, influenced by psychological biases such as overconfidence, extreme forecasting, winner’s curse, false consensus effect, and present bias.

The draft allows teams to select new players, with the order based on the previous year’s performance. Teams can trade draft picks, and the first contracts of athletes are typically for four or five years. Thaler and Massey collected extensive data on the draft, including player performance, compensation, and the outcome of trades, to test their hypothesis.

Their analysis revealed the value of early draft picks was steeply overestimated. High picks are not only expensive to obtain but also costly to retain. Surprisingly, the surplus value (performance value minus compensation) of players chosen in later rounds often exceeds that of early picks. This suggests teams would benefit from trading down for multiple later picks rather than focusing on early ones.

Thaler and Massey’s insights were initially of interest to NFL teams like Washington, but despite understanding the analysis, teams often failed to apply the strategy, typically due to ownership pressures to win immediately. Their findings highlight the complexity of decision-making in professional sports, where biases and a lack of reliance on data-driven strategies often lead to suboptimal choices.

Thaler explores the use of high-stakes game shows as a platform to test behavioral economic theories, specifically focusing on Deal or No Deal and Golden Balls. Thaler, along with his Dutch colleagues, analyzed the decisions made by contestants on these shows to understand how high monetary stakes influence decision-making and to challenge the notion that behavioral anomalies observed in labs would not repeat in the real world.

Deal or No Deal offered an ideal scenario to examine prospect theory and mental accounting in a high-stakes environment. Contestants made choices involving potentially large sums of money, and the study revealed their decisions were influenced not just by the current gamble but also by their previous gains and losses, demonstrating path dependence.

Similarly, Golden Balls provided an opportunity to observe behavior in a high-stakes version of the Prisoner’s Dilemma. The show’s finale involved two contestants deciding to “split” or “steal” a cash prize. Analysis showed cooperation rates decreased with higher stakes but remained at levels similar to those in laboratory experiments, debunking the belief that high stakes would lead to purely rational decision-making.

Thaler discusses the concept of “Save More Tomorrow” (373), a program designed to increase retirement savings. Traditional economic theory assumes people save the right amount and focuses solely on after-tax financial returns as a policy tool. However, this approach overlooks behavioral factors like inertia, loss aversion, and present bias, which significantly impact saving behaviors. To address these, Thaler and Shlomo Benartzi proposed “Save More Tomorrow,” encouraging people to commit in advance to increasing their saving rate with future pay raises. This approach leverages inertia (by making continued participation the default), mitigates loss aversion (by syncing saving increases with pay raises, avoiding a decrease in take-home pay), and uses present bias to advantage (by setting future actions).

Despite initial skepticism, the program proved successful in substantially increasing savings rates without making savers feel they were losing current income. Thaler’s discussion with economist Casey Mulligan led to the term “libertarian paternalism,” highlighting that while the program guides choices, participation is voluntary, distinguishing it from traditional paternalism. The concept of “Save More Tomorrow” and its principles have since gained wider acceptance and implementation, showing the effectiveness of behavioral insights in policy design.

Thaler highlights the concept of “libertarian paternalism” (386), a term Thaler coined to describe an approach to policy-making that aids individuals in making decisions that align with their own interests, without restricting freedom of choice. This concept, initially met with skepticism due to its seemingly contradictory nature, is explored further in collaboration with Cass Sunstein. They argue that while people value their freedom to choose, they often lack the expertise required for optimal decision-making in complex situations.

The chapter discusses how “nudging,” a key aspect of libertarian paternalism, can effectively guide people toward better decisions by altering minor elements in their decision-making environment. An example is the use of a fly etched in urinals at Schiphol Airport, which significantly reduced spillage by subtly guiding behavior.

Thaler and Sunstein’s exploration into various policy areas led them to develop the book Nudge, highlighting how subtle changes in choice architecture can significantly impact behavior. The book, despite initial disinterest from publishers, gained traction through word-of-mouth and later widespread acclaim.

One of their notable applications of libertarian paternalism is in the context of organ donation. They initially considered advocating for “presumed consent” but eventually favored a “prompted choice” model (390-91), where individuals are asked their preference during routine processes like driver’s license renewal. This approach demonstrates the effectiveness of nudging in influencing decisions while respecting individual autonomy.

Thaler recounts his experiences in the United Kingdom, highlighting the influence of behavioral economics in government policy. In 2008, during a visit to London, Thaler was introduced to key members of the Conservative Party, who were interested in the concepts presented in his book Nudge. Despite initial skepticism about engaging with a political group not typically aligned with his views, Thaler found the members open to and enthusiastic about the ideas of behavioral economics.

The Conservative Party, under David Cameron, was actively seeking new, progressive approaches, including environmental initiatives. Thaler’s interactions with this group, including young advisors like Rohan Silva and Steve Hilton, revealed a genuine interest in applying behavioral insights to policy. This led to the eventual establishment of the Behavioural Insights Team (BIT), headed by David Halpern, a social scientist with an understanding of government workings.

The BIT was tasked with integrating behavioral science into public policy and government operations. One of their first projects involved collaborating with Her Majesty’s Revenue and Customs (HMRC) to enhance tax collection efficiency through carefully worded reminder letters, demonstrating the power of behavioral nudges. This initiative showcased the effectiveness of simple, cost-effective behavioral interventions in policy.

Thaler emphasizes the importance of making actions easy to encourage behavior change and the necessity of evidence-based policy understood through experimentation and data. The chapter illustrates the challenges and opportunities of applying behavioral science in real-world settings, including governmental agencies.

The BIT’s success in the UK inspired similar initiatives in other countries, including the United States, where the White House established the Social and Behavioral Sciences Team (SBST). The expansion of behavioral insights teams worldwide underscores the growing recognition of the value of behavioral science in improving government effectiveness and policy outcomes.

Thaler reflects on the evolution of behavioral economics over 40 years, celebrating its transition from a fringe concept to mainstream acceptance. He shares his aspirations for the field’s future, emphasizing the need for more evidence-based economics that focuses on human behavior, rather than idealized rational models.

Thaler notes the significant impact of behavioral economics in finance, a field once considered the stronghold of efficient market hypotheses. He attributes this success to clear, testable theories and abundant data, allowing for empirical challenges to traditional economic theories. However, he expresses a desire to see behavioral approaches more widely adopted in macroeconomics. Thaler argues understanding human behavior is fundamental for effective monetary and fiscal policy yet acknowledges the challenges due to the lack of easily falsifiable predictions and sparse data in macroeconomics.

He urges economists to consider behavioral details in policymaking, such as the structuring of tax cuts, and highlights the importance of understanding how businesses and individuals behave to evaluate the impact of public policies effectively. Thaler also calls for a behavioral analysis of entrepreneurship, suggesting a focus on reducing the risk and cost of failure to encourage business startups.