November 1, 2026

Kalshi and Polymarket have become widely popular prediction markets. Their combined monthly trading volume was less than $5 billion in September 2025. By April 2026, that figure was about $24 billion. (link) What are prediction markets, what is their appeal, and how can we go astray in them?

A prediction market offers simple financial securities that pay $1 if an event happens and $0 if it does not. For example, you can buy a security that pays $1 if the LA Rams win the 2027 NFL title, and $0 if they do not. This is a bet that the Rams will win the Super Bowl. You can scale up your bet by buying more than one of these securities. From here, I will call these securities “contracts.”

Because the Rams are not guaranteed to win the Super Bowl, the price of the contract that pays $1 if they do win is less than $1. One can interpret that price, say, $0.14, as the market’s assessment of the probability of the Rams winning the Super Bowl.

Sports betting, the subject of last month’s newsletter (link), constitutes more than 90% of Kalshi’s revenue. For Polymarket, the number is about 40%. How prediction markets became venues for sports betting is an interesting history, perhaps the subject of a future newsletter. In the meantime, you can read about it here.

Do prediction markets offer anything other than a chance to gamble? The answer is Yes.

Let’s consider one of the early prediction markets, the Iowa Electronic Markets (IEM) at the University of Iowa. (link) It allowed (and still does) bets on political outcomes, such as who will win the presidency. Research (link) shows that the IEM prices are often better predictors of political outcomes than the polls, an example of “the wisdom of crowds.” My newsletter on that topic is here.

Information about political outcomes might be useful for anticipating changes of policy that could accompany a change of political leadership.

Another example: As I write this, the Polymarket contract that pays $1 if the traffic in the Strait of Hormuz “returns to normal” by December 31 of this year is priced at $0.08. The market is saying that a return to normal is highly unlikely, roughly 8%. This information is helpful for thinking about the price of energy between now and year-end.

In theory, prediction market contracts can be used to reduce risk. For example, Kalshi has a contract, “Will oil (WTI) be above $115.01 by the end of the year?” As I write this, the contract is priced at an implied probability of 39%. A company that uses oil as an input might buy this contract to get a payoff if the price of oil is above $115.01. That reduces the company’s exposure to a spike in oil prices.^[1]

So what could possibly go wrong for a typical trader (that’s you and me) in prediction markets? Lots, I would say.

First, you may be betting against better-informed participants. You may recall the case of the soldier who knew ahead of time that the U.S. would capture Nicolás Maduro, the president of Venezuela. He made about $400,000 on the (for him, near-certain) bet, while the traders on the other side of the contract—betting that the event would not happen—lost money.

This incident raises the question of whether insider trading laws apply to prediction markets. My understanding—I am not a lawyer—is that this issue is unresolved. The soldier was found guilty of using classified information, not insider trading.

Another issue that has arisen occasionally: Some events are difficult to define precisely. For example, there were contracts tied to Iran’s Supreme Leader Ali Khamenei “leaving office” before certain dates. He was killed by U.S. bombing, and there was some dispute about whether that constituted “leaving office.”

Second, as suggested in last month’s newsletter, you may be up against fierce competition. A recent Wall Street Journal article (October 3, 2026) reports, “Twenty-something traders with math and quant backgrounds are building firms that wager millions of dollars a week on platforms such as Kalshi and Polymarket, often using AI tools and teams of bots to hunt for an edge.”

Finally, as I discussed last month, a vast majority of participants lose money in prediction markets. Although there are multiple biases in play, I call your attention to “long-shot” bias, the tendency to bet on low-probability, high-payoff events. I first became aware of the phrase in the context of betting on horses with, say, 50-to-1 odds. That horse is unlikely to win, but there would be a big payoff if it does. (Lotteries are also long-shots.)

Soberingly, a Bloomberg article reports that 98% (!!) of long-shot bets in prediction markets lose money. (link)

Taiwan recently blocked Kalshi’s website over suspected election betting, which is illegal there. (link) It turns out that a majority of Americans oppose betting on elections and government events. (link)

Conclusions: Do not bet on a horse named Tripod. Do assess whether you have a comparative advantage in prediction markets. (I discuss comparative advantage here.) And note that the prices in prediction markets can be useful to you, without actually having to participate in those markets.

^[1] Options and futures are alternative ways to hedge (reduce) risk. Dr. Joe Parcell, a risk management expert at Kansas State University, argues that these financial contracts can co-exist with prediction market contracts. (link)

October 1, 2026

Sports betting

There has always been sports betting—the Romans bet on the outcome of gladiator fights. Interestingly, it was legal and regulated. (link) In the United States, sports betting was legal only in Nevada until 2018, when a Supreme Court decision legalized sports betting. See the Endnote for some statistics about the breathtaking magnitude of sports betting.

Sports betting is dangerous to your wealth. One study reports that more than 95% of sports bettors lose money over a one-year horizon. (link) Ninety-five percent! And the legalization of sports betting is associated with an increase in overdue debt and bankruptcies. (link)

So let’s consider some of the biases that are likely influencing, to their detriment, bettors’ decisions.

First, overconfidence (link) probably plays a role. As an antidote to overconfidence, let’s consider: Who is the average bettor competing against in sports betting markets? Does the average bettor have more information or better analytics than professional bettors? To ask the question is to answer it.

Second, bettors may prefer skewness in payoffs (link to Abstract). That is, they put value on low-probability, high-payoff outcomes. In horse racing, this phenomenon is referred to as the “long-shot” bias, a long-shot being a horse very unlikely to win (but pays off big if it does win).

In financial markets, investors can buy options to get exposure to skewness. (And 80-90% of options traders lose money. Link)

Third, people misperceive patterns or see patterns where there are none. I explored this bias in my March 2025 newsletter, “Jesus’ face on a piece of toast” (link). “The Broncos are hot right now; they’re going to beat the spread next week” is an example of the hot hand fallacy (link).

As a result of these biases and others, there are three behavioral regularities in betting markets.

The first is the house money effect (link). When someone wins a bet, they often view the winnings as “house money,” rather than “my money.” As such, they are inclined to take on more risk with the winnings. And more risk means a higher probability of losing.

The second is taking on more risk when one is in a losing position. One study (link to Abstract) showed that people at racetracks start betting on long shots later in the program, hoping to recoup their earlier losses.

The third is to rationalize betting as entertainment. And it does have an entertainment dimension. The possibility of winning is exciting, even if the probability of winning in the long run is less than 5%. Limiting your stake, the amount you are willing to lose in a session of betting, will allow you to be entertained without the risk of ruin.

What can we make of all this? Recognize that winning a bet gives you a rush of dopamine—it feels exhilarating. Unfortunately, as with many addictions, the dopamine rush can create a craving for more dopamine. That’s why the “gamification” found on Robinhood and other apps is so effective (and you can now place sports bets on Robinhood).

Breaking news: Brazil is banning online betting as of October 6. (link) Care to bet whether the United States will follow suit?

Endnote:

Data on the amount of money wagered on sports is inexact because—it is widely believed—the amount of “off the books” betting is significantly higher than the amount legally wagered. As a rough guide to sports betting growth, one estimate of the amount bet in 2018 was $3.3 billion; for 2025, it was $165.6 billion. Over $1 billion is likely bet on the Super Bowl alone.^[1]

^[1] Much of the recent growth in sports betting has occurred in prediction markets, the topic of a future post.

September 1, 2026

Seeing double—Bias bias

As readers of this newsletter know, behavioral economics (BE) resides in the murky intersection of economics and psychology. Daniel Kahneman, a psychologist, won the Nobel Prize in Economics in 2002 for his research—much of it with Amos Tversky—showing that people make seemingly irrational decisions based on unseen and little-understood psychological biases.^[1] See, for example, the Linda Problem (link).

And such biases abound, or so many believe. One website (link) shows more than 180 biases that have been identified by researchers! Although some overlap to a degree, that’s a lot of biases! Are we overdoing it in some sense? In our efforts to remain open-minded, let’s examine the claim that biases are not as significant as many believe.

Renowned German psychologist Gerd Gigerenzer defines “bias bias” as the tendency to see biases where none exist. (link) Despite that definition, he doesn’t believe that biases don’t exist, but instead concludes, “…the literature shows little evidence that the alleged biases are potentially costly in terms of less health, wealth, or happiness.”

What to make of this? First note that bias bias itself could be viewed as a bias. Is Gigerenzer seeing a bias where none exists? Admittedly, this seems a bit like making the assertion that “This statement is false.” Tell me when smoke starts coming out of your ears.

Second, it is reasonable to ask about the cost of biases in decision-making. For example, in looking at personal finance (see my book, The Foolish Corner), there’s good evidence that excessive stock trading can be very costly. A famous paper (link) reports that active traders earned 11.4% over the period examined while the market rose by 17.9% over that same period. This is clear evidence of the negative effects of “activity bias,” in which traders believe – perhaps unconsciously – that frequent trading leads to higher gains than simply buying and holding.

Third, policies based on BE findings are sometimes effective (e.g., opt-in defaults for retirement savings) and sometimes not (e.g., changes in menu labeling).

What legitimate comments can we make regarding this debate? First, I think it is clear that biases in decision-making do exist, and that they are often truly damaging. In the more than 40 years of studies since Kahneman and Tversky’s first findings were published, academics time and again, in both laboratory and field studies, have uncovered substantial evidence of poor decision-making based on specific biases.

Second, as Gigerenzer argues, the search for biases indeed might be overzealous. “To a man with a hammer, everything looks like a nail” is an aphorism attributed to psychologist Abraham Maslow. I would argue that looking hard for what you want to see (here, biases) is a form of confirmation bias.

Third, I think the most important question is not whether biases exist (at least some do), but in what context are they important? One such context would be political discourse, where confirmation bias is palpably visible to the naked eye every day as people seek out information supporting their political views. (And algorithms provide evermore one-sided feeds.)

But consider another context. Confirmation bias is perhaps beneficial when looking for positive attributes in your romantic partner. (On the other hand, if you are looking for negative attributes…)

Conclusion: A combination of knowing about biases (keep reading this newsletter!) and an awareness of the importance of their context will lead to better decision-making, which I view as the end goal of behavioral economics.

In a previous newsletter (link), I discussed the “above average” effect. In a recent YouGov survey (link), two-thirds of dog owners said that their canine companions were smarter than the average dog. Is that statistically possible? Clearly not. But it probably leads to better human-canine relationships 😊.

^[1] Herbert Simon won the Nobel Prize in 1978 for, among other contributions, his notion of “satisficing,” an early contribution to BE. Other Nobel Prize winners who have contributed to BE include Vernon Smith (2002), Robert Shiller (2013), and Richard Thaler (2017).

August 1, 2026

The Rashomon Effect

I recently re-watched the movie Rashomon. I probably last saw it in college, at least a decade ago. It is a 1950 Japanese film, widely regarded as one of the greatest movies of all time. I can testify that it bears almost no resemblance to today’s movies—there is a fair amount of maniacal laughter, for example, that today would end up on the cutting room floor, I suspect.

Optional homework: Once you’ve seen the movie, compare its maniacal laughter with the “diabolical” laughter in Monty Python’s “Spanish Inquisition” sketch (link). Feel free to give examples of either maniacal or diabolical laughter from your life—comment below.

The movie consists of four narratives about a murder. The narratives differ, and only one of them, at most, can be correct (all the narratives may be wrong); the movie offers no resolution as to which narrative is true. The movie illustrates, rather dramatically I’d say, that people have different perspectives and memories of the same incident, and that getting to the truth of what actually occurred is decidedly difficult.

Although one of the characters might be lying, the others seem to be recounting what they saw—and in some cases, participated in—honestly. They perceive and remember the murder differently. This is the Rashomon Effect.

There are several lessons that we can take from the movie.

First, eyewitness testimony is unreliable. Derek Abbott (link) cites a study that shows that up to 48% of people pick the wrong person out of a lineup. And a Scientific American article (link) cites cases where people have been wrongly convicted based on eyewitness testimony, sometimes with as many as five eyewitnesses! Perhaps Rashomon should be a part of the law school curriculum?

Second, and closely related to the first, memory is fallible and malleable. Cited in the Scientific American article is the work of Elizabeth Loftus and others about the ability to create false memories. In the 1980s, preschool and daycare workers were accused of performing “Satanic rituals” with their charges (link to one case). The children were manipulated to report (obviously false) memories of such activities.

Third, given the fallibility of our perceptions and memories, we might consider occasionally exercising epistemic humility, the recognition that our knowledge is provisional, incomplete, and subject to revision. I first mentioned this phrase—a favorite of mine, I admit—in my March 2026 newsletter. (link)

Fourth, be aware that our perceptions of an event will depend on how we frame the event, consciously or unconsciously. For example, ego-centric bias refers to our tendency to interpret information in a way that makes us look good. At least one character in the movie felt the murder was justified.

Fifth, recognizing the Rashomon Effect could make us less critical of others who don’t see things the way we see them. Most of us can recognize that others have perspectives, thoughts, and memories that are different from ours, an ability called “theory of mind.” (link) Those differences may not be tantamount to lying but rather indicate how individuals process a given event differently, during and after the fact.

“I used to think that the brain was the most wonderful organ in my body. Then I realized who was telling me this.” -- Emo Philips

July 1, 2026

Our cloudy crystal balls

Consider this possible scenario: You currently work at Company A. You think there is some probability that you will become CEO of the company in about five years and that you will find a high degree of satisfaction in that role. But you’ve recently been presented with the opportunity to move to Company B, where you would also have some probability of becoming its CEO in the same amount of time, and you would also experience a high degree of satisfaction if that were to happen.

Thinking about each possibility, you recognize two primary facts as relevant: the probability of your getting to the CEO’s seat, and the “utility” you would experience if it were to happen. Economists use the word utility to refer to satisfaction or happiness.

So how might you decide between staying with Company A and moving to Company B? Daniel Bernoulli, the famous Swiss mathematician, offered (in 1738!) a framework for thinking about decisions nearly identical to this (there weren’t CEOs per se back then, but let’s stay with that example for the time being). His approach consists of three seemingly straightforward steps.

First, you estimate the utility associated with being CEO of Company A. Compensation is certainly one consideration but it’s just one, and maybe not even the main one. Your utility depends on many other subjective factors, e.g., the quality and type of the individuals you would work with daily; the inherent interest you might have in the company’s particular industry, not to mention products; and the opportunity the company might offer you to stretch and grow your skill set, to name only a few.

To make an estimation of this kind may seem rather daunting, so you decide to quantify your satisfaction on a 1-to-100 scale. You decide that the score at Company A is 90. Now repeat the thought experiment, thinking about being the CEO of Company B. Let’s say you decide in that case on a satisfaction score of 95.

(If this approach to decision-making seems impractical, bear with me—I’ll suggest its value below.)

Second, because neither outcome is guaranteed, you need to estimate the probability of each occurring. How likely is it that you will become CEO of Company A? Let’s suppose you assess that possibility as 70% likely to occur. And how likely would it be that you will become CEO of Company B if you change jobs? You assess that probability as 60%.

Third, you multiply the probability of each outcome times the utility you expect from each. The results are called the “expected utility” of each outcome. You then choose the outcome with the higher expected utility.

The expected utility of staying with Company A is 0.7 x 90 = 63. The expected utility of moving to Company B is 0.6 x 95 = 57. Danny B, as he was known to his friends, would have you stay with Company A.

In his best-selling book, Stumbling on Happiness, psychologist Daniel Gilbert suggests that estimating probabilities is the easier of the two tasks: “Calculating such odds is relatively straightforward stuff, which is why insurance companies get rich by doing little more than estimating the likelihood that your house will burn down…” (p. 260).

I’m less confident than Gilbert about the ease of calculating the probabilities (“odds”). Predicting how many houses among many will burn down can be done with some precision. But that is different from predicting whether one house in particular will burn down. That depends on specific factors such as the behavior of the residents (do they smoke?), the construction of the house (wood or cement?), and the location of the nearest fire hydrant.

Your potential promotion to CEO is a singular case, analogous to the single-house case. Put differently, there is no database of CEO promotions that would permit you to arrive at a confident prediction of your probability of being promoted (though theoretically, in another 10,000 years or so of corporate experience and data collection, there might be).

However, the focus of Gilbert’s book is on the difficulty of estimating the utility associated with a future, uncertain event, and here I am in full agreement with him. He offers two suggestions for dealing with this challenge. First, “…the best way to predict our feelings tomorrow is to see how others are feeling today” (p. 251). Although imperfect, this exercise does provide information. If most people appear to be quite happy as CEOs (especially people who seem to have some similar character traits and background to you, I would add), then probably you would be as well.

His second suggestion: “…simply step into tomorrow’s shoes and see how well they fit” (p. 262)—the first step described above. That is, imagine being the CEO of Company A—how much satisfaction do you feel? Now imagine being the CEO of Company B—how much satisfaction? Here again, although not an exact science, a potentially useful exercise.

One limitation of this second approach is “projection bias,” which refers to our tendency to overestimate the stability of our current beliefs, values, and feelings.** For example, when we are hungry, we can project that into the future, unconsciously feeling that we might always be hungry. Consistent with projection bias, hungry shoppers have been shown to buy more groceries than those who aren’t hungry.

And moving out into left field for a moment, here’s another suggestion for making better decisions: Make them with a full bladder. The title of the research (link) says it all: “Full Bladder, Better Decisions? Controlling Your Bladder Decreases Impulse Choices.” Stay well hydrated as you decide whether to move to Company B. Who knew?

Anyway, where does this leave us? First, we can make better decisions by assessing, as best we can, the probability of future events and the utility associated with those events. For example, we can easily imagine the utility of winning the lottery, but let’s also think about the probability of that occurring. (The lottery industry won’t like this, though: If more people focused on the probability, surely fewer lottery tickets would be sold.)

Second, in assessing the utility associated with future events, be aware of projection bias. Specifically, recognize that our current mental state can influence our decisions. One way to neutralize that risk is to stop and ask oneself: Am I in a “hot” mental state? Wait to cool down. Another question: Am I currently engaged in or particularly susceptible to catastrophic thinking? Step back—how likely is that worst case that I am imagining? You want to get yourself on a more even keel before making a major life decision.

Finally, given the lack of precision of these exercises, I personally recommend something Danny B never got into: The notion of becoming more comfortable with uncertainty. One place you might start is Pema Chödrön’s book, Comfortable with Uncertainty. She argues, as many a philosopher has, that the nature of our existence, whether we realize it or not, is relentlessly in flux. Embracing that fact, rather than resisting it, can lead to a much more fulfilling life, which includes better decision-making.

**See here for a more detailed explanation of projection bias.

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June 1, 2026

Don’t quite feel like yourself today? That could be a huge plus.

Research published in 2017 (link) examined methods for increasing perseverance in children.[1] The subjects, four- and six-year-olds, were given a tedious, repetitive task—pressing a key when the image of cheese appeared on a laptop screen. The children were asked to continue as long as possible, but were also allowed to take a break to play a game on an iPad, a more enjoyable activity, a break from the tedious task.

The researchers divided the children into three groups: 1) those who were told to think about someone really good at working hard; 2) those who were told to think of themselves in the third person (e.g., “Calista is working hard”); and 3) those who were told to think of themselves in the first person (e.g., “I am working hard”). The first two are a form of “psychological distancing” from oneself.

They were asked to work as long as possible on the tedious task. The authors summarize their findings as follows: “…children who impersonated an exemplar other—in this case, such as Batman—spent the most time working, followed by children who took a third-person perspective on the self, and finally, a first-person perspective.”

In short, psychological distancing improved the children’s performance.

Can psychological distancing be of value to adults as well? A recent article (link), titled “Why some of the best athletes in the world pretend to be someone else,” suggests that the answer is Yes. It recounts the story of 13-year-old Shai Gilgeous-Alexander, later to become an NBA superstar, who emulated and tried to “become” Allen Iverson, an NBA superstar at the time.

On a personal note, I—an avid tennis player—have used this approach when I am struggling with my serve. I imitate a professional whose serve I admire. Among others, I “use” John Isner’s serve, including bouncing the ball between my legs before serving and putting my cap on backwards. I think of this as a type of “mind meld” with a far superior server, much like method actors identify with their characters.

My interpretation: By “using” someone else’s serve, I am not responsible for the outcome, even though I am the one hitting it. In turn, this reduces stress, anxiety, and overthinking, thus creating psychological distance from the act of serving. (I am unaware of any research that examines this conjecture in the context of competitive tennis.)

Psychological self-distancing might well improve performance in many settings, e.g., public speaking.[2] (In the original Batman TV series, there were times when Robin adopted Batman’s persona.)

Readers, have you used psychological self-distancing (whether you knew it was called that or not)? Share your experiences in the Comments below.

[1] There are some nuanced differences between perseverance, persistence, resilience, and “grit” (as popularized by Angela Duckworth in her book Grit). For the strangely curious among you, here’s a good discussion (link) of these topics and their relatedness and differences.

[2] Research (link) shows that psychological flexibility is associated with lower levels of public speaking stress. If psychological self-distancing increases psychological flexibility (admittedly just a conjecture on my part), it will be useful to those who fear public speaking.

Spoiler alert: some of each, but more luck than most people think. A common error is to think that hard work is the sole, or even primary, determinant of success. An excellent book on this topic is Robert Frank’s Success and Luck: Good Fortune and the Myth of Meritocracy.

When we think of luck, we think perhaps of serendipity—being at the right place at the right time, for example. And this type of luck certainly occurs. For example, Bill Gates was lucky to have early access to a time-share computer.

But luck is much broader. It includes such things as being born in the United States rather than in a war zone. Luck could include being brought up in a stable family that values education. A good genetic inheritance is luck as well. In many societies, being born male is luck. These examples are sometimes referred to as “constitutive luck.”

In short, luck—both good and bad—consists of things you don’t control.

Yet many successful people focus almost exclusively on their hard work to explain their success. Why do they ignore the role of luck? There are several reasons.

“Recency bias” suggests that recent experiences are given disproportionate weight in shaping our understanding of the world. A successful entrepreneur almost certainly has been working hard. As a result, they have a hard time seeing other influences on their successful outcome. This is not a judgment about them; it is a description of a common cognitive limitation.

Overlapping with recency bias is “availability bias,” which has us focus on ideas or experiences that we most easily remember. Those 100-hour weeks are easy to recall (they are “available”), indeed, impossible to ignore.

And when we look at success from the outside, we are under the influence of “survivorship bias.” We see the successful entrepreneurs. We do not see the entrepreneurs who worked 100 hours a week and failed. Economists would say that hard work is a necessary, but not sufficient, condition for success.

Put another way:

“Meritocratic hubris is the tendency of the successful to inhale too deeply of their success, to forget the luck and good fortune that helped them on their way.”

Source: “The Hubris of the Well-Credentialed” by Michael Sandel. The Chronicle of Higher Education, October 16, 2020.

I start with a confession of sorts: I named my newsletter Behavioral New World as a riff on Brave New World. I’m not sure that anyone has ever gotten the reference. Marketing is obviously not a strength of mine.

My first post, on May 1, 2020, was titled “Confirmation bias and the coronavirus” (as Covid was known then). Confirmation bias is the tendency we have to be open to information that confirms beliefs that we already have, while being resistant to information that does not support those beliefs.

I selected the topic because I perceived a polarization of beliefs about issues such as social distancing, lockdowns, quarantines, travel bans, and the efficacy of masks. I did not take a position on these issues but did suggest trying to keep an open mind, an approach I call “epistemic humility” in a later newsletter.

I decided that the newsletter would be monthly. I have made some mid-month posts, some of which relate to behavioral economics, some not. This newsletter is the 88^th Behavioral New World post. As a subscriber, you have access to all of them.

On this six-year anniversary, I’ve decided to discuss an academic paper of mine. Among my publications, it is one of my favorites and continues to be cited nine years after its publication. “Old Age and the Decline in Financial Literacy” was published in the journal Management Science. It was co-authored with Michael Finke and Sandra Huston.

The title gives away most of the story—our financial literacy declines as we age. This finding explains the results of earlier studies, one of which reports that “even the healthiest of elders showed profoundly compromised decision-making…” (link). And it explains why scamsters often target the elderly.

Another contribution of my paper is shown in this graph, courtesy of a TIAA webinar on February 28, 2025:

Ugh, doubly bad news: As we age, our financial skills decline, but our confidence in them does not (and arguably even increases). That’s a potentially deadly one-two punch for financial well-being, particularly for retirement.

In each of my behavioral economics newsletters, I provide ideas about how to mitigate distortions to our decision-making that stem from a particular bias.[1] My initial suggestion in all cases is to be fully aware: 1) that the given bias exists, and 2) that all of us are susceptible to it. Only with those premises accepted can you move on to grasping a bias by the lapels and wrestling it to the mat.

In the case of age-related decline in financial literacy, a largely automated investment strategy, such as investing in target-date funds, removes much of the decision-making. More generally, I’m a fan of passive investing, regardless of age (see my book The Foolish Corner, available on Amazon).

Another tactic would be to delegate financial decisions to a trusted advisor (who is presumably younger 😊). It is hard to say with high confidence at what age this transfer of responsibility should take place. Looking at the graph, the falloff in financial literacy starts in one’s early 60s. But keep in mind that there is individual variation around the averages shown in the graph, so earlier might be best for some people while others can wait a bit longer.

Based on their years of experience, the elders in society often find a positive role dispensing wisdom to the young. But be wary of financial advice from your grandparents, no matter how financially successful they’ve been!

[1] One might argue that the decline in financial literacy is not a bias. But it clearly affects decision-making, an umbrella that includes behavioral economics.

Mid-month, April 2026

I continue with a series of short pieces on topics I’ve been thinking about.

Essay 8: Disruptive innovation is not new

Clayton Christiansen made famous the concept of “disruptive innovation.” A June 15, 2017, article in The Economist magazine says, “THE [sic] most influential business idea of recent years is Clayton Christensen’s theory of disruptive innovation.”

I have no objection to the concept as a descriptive tool. It does seem to provide a description of business evolution. In fact, it seems to me that all innovation has some degree of disruption associated with it. As such, I think there’s a bit of Captain Obvious about the concept. However, it seems less valuable as a predictive theory.

And the idea is not new. In 1942, Joseph Schumpeter, in his book Capitalism, Socialism and Democracy, coined the phrase “creative destruction” to describe innovation and its effect on the business cycle. Arguably, the idea was not new even then—a similar concept was advanced by Karl Marx and Friedrich Engels in 1848 in their book The Communist Manifesto.

Others have had the same idea. For example, Alan Greenspan says, “Destruction is more than just an unfortunate side effect of creation. It is part and parcel of the same thing.” (Greenspan and Wooldridge, pp. 420-21)

Attempts to test the theory as a predictive model have had mixed results. Jill Lepore has written a critical review that looks at specific predictions made by Christiansen.[1] One of the challenges in such an investigation is that the predictions of the disruptive innovation are not precise, leaving a type of Rorschach test for evaluators of the concept.

And, as one would expect in the marketplace of ideas, disruptive innovation has its defenders.[2] I leave it to the interested reader to pursue the debate.

The case of disruptive innovation suggests that “new” ideas are not always new. That’s not necessarily negative: there might be value in reviving past ideas and applying them to the present situation. For example, disruptive innovation (Christiansen) is focused more on individual firms than the economic cycle (Schumpeter).

More broadly: influential ideas rarely occur in a vacuum. One is reminded of Isaac Newton’s comment, “”If I have seen further, it is by standing on the shoulders of Giants.” For those of you trying to hatch The Next Big Idea, don’t think that it needs to be completely original. Don’t hesitate to draw upon the wisdom of past thinkers. But intellectual humility requires you to acknowledge the antecedents of your ideas.

Reference

Greenspan, Alan and Wooldridge, Adrian, Capitalism in America: A History, Random House, 2018.

[1] https://www.newyorker.com/magazine/2014/06/23/the-disruption-machine

[2] https://deloitte.wsj.com/cio/in-defense-of-the-theory-of-disruptive-innovation-1409630543

April 1, 2026

Swans on trains, accidentally and chaotically

The phrase “black swan” first appeared in a poem by the Roman writer Juvenal sometime between 60 and 130 CE. It was popularized by Nassim Nicholas Taleb in his book The Black Swan: The Impact of the Highly Improbable. It refers to the occurrence of an unlikely, unexpected event.

Where does the modern usage of the phrase come from? For many years, Europeans had seen only white swans and thus assumed that all swans were white. But in 1697, a Dutch explorer encountered black swans in Australia. Quite unexpected! A more complete discussion of black swans can be found here.

In Taleb’s telling, a black swan event is not only largely unpredictable—because of its highly improbable nature—but also because of its extreme impact. Examples might include the 2008 financial crisis and the Covid epidemic.

An individual-specific version of a black swan is the “sliding doors effect,” the notion that a seemingly small event can significantly change the course of a person’s life. This is the premise of the film “Sliding Doors” (1998) in which we see two life paths for the main character. In one scenario, she narrowly beats the sliding doors and gets on the train. In the other scenario, the doors close before she can get on. Her life is quite different in the two scenarios.

Whether or not she gets on the train is an extreme event for her, if not for the world at large. I suspect that each of us has felt, at least at times, that our lives could have changed significantly but for a seemingly small event. “Because I missed that plane, I met my future spouse,” that sort of thing.

The physicist Murray Gell-Mann has suggested a similar, if not identical, phenomenon which he calls “frozen accidents.”[1] He states, “Each of us human beings…is the product of an enormously long sequence of accidents, any of which could have turned out differently.” Getting on the train (or not) is one such ‘accident.’

Frozen accidents can also be important at the macro level and thus change history. Consider the assassination of Archduke Franz Ferdinand, widely regarded as the spark that started World War I. Ferdinand’s car took a wrong turn during his visit to Sarajevo, the Bosnian capital where he was killed (details here).

Of course, we don’t know what would have happened if his car had not made the wrong turn, but it is easy to imagine a distinctly different history unfolding (but not necessarily no war). The “accident” of Ferdinand’s assassination is said to be “frozen” because it cannot be rewritten or undone.

Black swans, sliding doors, and frozen accidents are reminiscent of chaos theory. I make no claim to a full understanding of chaos theory, but you may have heard the expression, “A butterfly flaps its wings in Asia and creates a storm on the other side of the world” (there are many variations of this quote). I think this sentence, often used to describe chaos theory, captures the essence of black swans, sliding door events, and frozen accidents.

How is an understanding of BSSDFAC (black swans, sliding doors, frozen accidents, and chaos—a perfectly unpronounceable acronym) useful to us? Can we really do anything about unpredictable events? I offer some thoughts here and would love to hear your thoughts. Click on “Comment” below. You are also welcome to suggest how “BSSDFAC” might be pronounced.

First, an understanding of the chaotic path of history will prepare us to be less surprised when an unexpected event occurs. For example, we will be less likely to panic when the stock market drops rapidly (many investors sell at that point and rue the decision later). We haven’t predicted the market crash, but we’re not surprised by it.

Lisa Feldman Barrett, in her book Seven and a Half Lessons About the Brain, says, “It’s metabolically costly for a brain to deal with things that are hard to predict.” (p. 87) My take on that: We may be disinclined to contemplate unpredictability and consequently not take actions to mitigate the effects of BSSDFAC.

Second, we can work to build our resilience and mental flexibility. Emotional intelligence and mindfulness practices can also be helpful. A more detailed discussion of these techniques can be found here.

Third, in the financial arena, hedging instruments are available. For example, if your well-being depends on the price of oil (a relevant factor as I write this), you can hedge against price increases (or decreases).

Fourth, in the realm of personal finance, having a sufficient financial cushion can help us deal with negative surprises. The cushion reduces the anxiety we might feel in a time of greater-than-average economic uncertainty.

Finally, whether something goes viral or not is not predictable. This thought gives me hope that my newsletter might go viral. Could happen, you know. Share this post and maybe it will happen 😊

[1] For a lengthier explanation of frozen accidents, see this blog by Shane Parrish (link)

Essay 7: We shouldn’t be surprised when politicians behave like humans

Although it might be hard to believe at times, politicians are humans too. As such, they respond to incentives.

For many years, economists worked with models of the economy based on three “actors:” consumers, producers (also called “firms” or “companies”), and the government. In these models, consumers and producers interact in the marketplace, and the role of government in these models is that of overseer and regulator when things go wrong.

How might markets go wrong? A classic example is something called an externality, and pollution is the textbook case. A producer makes and sells electric spaghetti forks and consumers buy them. But the production process creates pollution, which falls on people who live near the factory. The economic activity has consequences that fall on third parties—not the producer, not the consumer, but the people living near the factory. Pollution is “external” to the transactions between the producers and consumers.

The pollution is a cost to the nearby residents, but the producers don’t pay that cost. Because the producers (predictably) don’t include external costs in their calculations, the market is distorted—the cost of production is understated. The role of government in these models is to correct for externalities.

Key: The models assume that the government—or more accurately the people in government—act in an unbiased way to make these corrections.

There is a substantial literature on how to address externalities, but our focus here is on the assumption that government officials—let’s think of them as regulators—are motivated to act in the best interests of society as a whole.

James Buchanan received the Nobel Prize in Economics for challenging this assumption. What is known as “public choice theory” describes regulators as people who pursue their own self-interest.

As I argued in Essay 5, models are useful if they describe and/or predict. Public choice theory is a model that predicts self-interested behavior on the part of regulators. One specific prediction that comes out of this model is the concept of “regulatory capture.”

Regulatory capture occurs when an industry has undue influence over its regulators. Capture occurs in several ways. First, the industry (its lobby) showers gifts on the regulators. Yes, there are rules about this, but there are workarounds. To keep the gifts coming, regulators might go easy on the regulations.

Second, industry executives might become regulators. One could argue that such a regulator has a greater understanding of the industry than someone who has never worked in the industry. True, but it might also be the case that they will treat the industry with less scrutiny because they are friendly to the industry.

Third, regulators sometimes move to industry. The possibility of making such a move, which likely includes a much larger paycheck, might influence the regulator to be less harsh in the hopes of getting a lucrative industry job.

So there is a “revolving door,” through which people move from industry to regulation and vice versa.

Sam Hornblower writes (emphasis added):[1]

My Businessweek investigation also uncovered a pattern of the FDA bowing to political pressure and its reluctance to revisit past errors. And the FDA reviewer who cleared OxyContin’s approval later took a job at Purdue [a pharmaceutical company].

Consistent with public choice theory, Milton Friedman, also a Nobel Prize winner, observed that finding the right people to serve as regulators is not the solution to self-interested behavior by government officials. Of course, it makes a difference who regulates—some people are more self-interested than others—but that does not entirely solve the problem.

Thus, an important insight from public choice theory is the importance of institutional structures that provide incentives consistent with desired outcomes, rather than relying on people to behave in ways that are not always in their best interests.

The challenge is that the people in a position to change institutional structures are those who—more or less—benefit from the current setup. What incentives do they have to make changes?

I would be most interested in hearing from you, the reader, your thoughts about how to bring about changes that reduce the incentives for public officials to misbehave (broadly defined).

[1] Here (link). Behind a paywall for non-subscribers.

March 1, 2026

I am less biased than thou

What types of biases do we as humans have? In what circumstances are these biases important? How strong are these biases? These are some of the fundamental questions sitting at the very heart of Behavioral Economics.

A related but not as frequently explored question is, “Are MY biases stronger than other people’s?” Research shows that the tendency is for individuals to think that their biases are not as strong as others’, implying that they are fairer and more objective than other people. A study (link) shows that people consistently rank themselves as being less biased than the average person. This result recalls studies that show that a substantial majority of Americans rate themselves as better-than-average drivers, which of course they can’t be.

What explains this bias about biases? Ali Almossawi provides three explanations (link). First, the belief that our internal reasoning is reliable. It makes us uncomfortable to think otherwise. Contemplating that our internal reasoning is fallible requires cognitive effort and being open to “epistemic humility,” which I wrote about here.

Second, if an idea “feels true,” then (we often believe) it must be true. Hence the view that our belief is unbiased, or perhaps weakly biased at worst. How often have we heard in our lives, from say friends and family members, “Stop thinking so much and go with your gut on this one,” or some similar admonition? While that might have served us well at times, I believe there is a high failure rate.

An antidote to this notion comes in the form of a comment a therapist friend of mine once offered: “Feelings are information, but they are not the truth.” That puts feelings in their proper place. Truth requires something beyond feelings.

Third, fundamental attribution error may be in play. In short, we attribute good outcomes to our genius and bad outcomes to forces beyond our control. Although this view makes us feel better about ourselves, it imparts a bias to our understanding of the world.

The belief that “I’m not biased, but you are” is critically important when people have different viewpoints. One doesn’t have to look beyond the current political scene here in the U.S. to see substantial differences of opinion. Surely the people with viewpoints other than mine are deeply biased, right?

Or could it be that I’m more biased than I think I am? Perhaps I’m even completely wrong about some issue. The thought of an open-minded thinker! As someone who strives to gain an accurate understanding of how the world works, I might seek out data and facts to either support or refute my beliefs.[1] But especially the latter.

An article in The New Yorker in 2017 provides some bad news in its title: “Why Facts Don’t Change Our Minds.” The link is here, but it is behind a paywall. The article reports, “Even after the evidence ‘for their beliefs has been totally refuted, people fail to make appropriate revisions in those beliefs,’ the researchers noted.” (emphasis added)

So what does change people’s minds? My friend Scott Christianson has written about the effectiveness of AI in influencing people’s beliefs (link). Reporting on one study, he writes, “…people weren’t being persuaded by balanced facts. They were being persuaded by confidence, repetition, and volume.” He adds, “Now, to be clear, humans have always persuaded other humans with bias, emotion, and misinformation. That’s not new. What is new is scale.”[2]

And that scale is what makes it harder than ever, in my estimation, to battle the forces of bias, especially our own.

So what can we do to mitigate our biases? As with all biases, the first step is awareness that they exist and that we are susceptible to them. (There is an ongoing conversation about reducing the biases in AI models. We focus here on debiasing ourselves.)

Some research shows specific actions we can take to mitigate bias. For example, one study shows that a one-time “training intervention” reduced confirmation bias, fundamental attribution error, and anchoring. Other research shows five strategies that reduce implicit bias.

But as is often the case, the research results are mixed. For example, one study reports that “Of the hundreds of studies we examine, a small fraction speak convincingly to the questions of whether, why, and under what conditions a given type of intervention works” (in this study, to reduce prejudice).

I wish the evidence were more clear-cut, but that’s just not the case. Perhaps our best hope at personal bias mitigation comes from awareness, open-mindedness, and epistemic humility. Meditation may also help, as it seems to reduce confirmation bias. (link)

Did the facts presented here change your mind about anything? 😊 At a minimum, I hope that they were informative. Comments welcome.

[1] Note that confirmation bias (link) can color our search. For example, if we ask AI for three reasons that our belief is correct, we will feel comfortable with the response, but it won’t illustrate alternative viewpoints.

[2] I encourage you to read the article. If you are interested in the role that technology plays in our world, Scott’s Substack is a valuable resource. https://substack.com/@profc

Essay 6: The One-Minute Search for Excellence

That’s a snarky amalgam of two very successful business books: The One Minute Manager (agh, the hyphen is missing in the book) and In Search of Excellence. Yes, these books date me—they’re not current. But they were hugely successful and there are lessons we can draw from them. As the saying goes, history doesn’t repeat, but it informs (you were expecting “rhymes”?).

As its title suggests, The One Minute Manager argues that a manager can be effective by engaging in short-duration leadership, specifically: one-minute goals, one-minute praise, and one-minute reprimands. I’m not convinced of the efficacy of this system (which leaves at least 480 – 3 = 473 minutes a day for a manager to do what?). I’m not alone in my skepticism. One commentator called it “the executive equivalent of paper-training your dog.”[1] It took me more than one minute to paper-train my dog.

In Search of Excellence explores the techniques and approaches used by successful companies in the 1980s. At the time, Japan was the model for business success. Remember when the Japanese bought the Pebble Beach golf course and Rockefeller Center in New York City? Many of you may not, but I do. The Japanese were going to take over the world.

Until they didn’t. Hence the phrase, “management fad.”

And let’s not overlook the book Good to Great. Its subtitle tells the story: Why Some Companies Make the Leap... and Others Don’t. This book compares some highly successful companies (measured generally by their financial performance) with some companies that were, well, not so great. The author then identifies seven characteristics that differentiate the successful companies and, by implication, lead to greatness.

What’s wrong with this picture? It does not account for something called survivorship bias. A favorite example of mine: Those Facebook posts that show kids riding in the back of a pickup truck, possibly from the 1950s, with commentary like, “We didn’t wear seatbelts and we turned out just fine.” Such posts are a criticism of an over-reaching “nanny state” that legislates away personal freedom by requiring silly things like seat belts.

But you know what? The kids who were killed because they were not wearing seatbelts are not posting on Facebook. Well, duh, you might say. But how many people reading those posts actually stop to think of this critical fact? Very few, I wager.

This example illustrates literal survivorship bias: Only the survivors are around to post on Facebook, and only they have the last word. Unless, that is, you can see through that bias to a bigger world. How? Ask yourself, “What am I not seeing?” In this case, we are not seeing the kids who lost their lives because they weren’t wearing a seatbelt.

How does this relate to Good to Great? Let’s consider the first characteristic of great companies, “Level 5 Leadership.” Question: How many companies over the same time period had Level 5 Leadership but were not great? I’d be willing to bet there were some. But we are seeing only the survivors, those companies chosen because they were successful.

And, because the author was selective about the successful firms to include in his study, we don’t know whether there might have been Great Companies not in the study without Level 5 Leadership. I’ll bet there were some.

It is not surprising that a flawed study misleads. Perhaps this quote from the author summarizes my complaint best: “The book never promised that these companies would always be great, just that they were once great.” You know, if you ask me to “predict” what the stock market did yesterday, you’ll find that I’m very good at it.

I’ll admit to a twinge or two of envy. One Minute Manager has sold more than 2 million copies, In Search of Excellence has sold 3 million, and Good to Great has sold 4 million. My book, The Foolish Corner (available on Amazon), has sold somewhat fewer copies.

References

Blanchard, Ken and Johnson, Spencer, The One Minute Manager, William Morrow & Co, 1982.

Collins, Jim, Good to Great, HarperCollins Publishers, 2001.

Peters, Thomas J. and Waterman, Robert H., Jr, In Search of Excellence, Collins Business Essentials, 2006.

[1] Jackson, S. (January 20, 1986). “Management lingo: how to read between the lines”. Business Week: 58. I have not found a direct link to this article, but it is referenced in this critical review of management writing: https://tinyurl.com/7x9h5ujz

February 1, 2026

Happiness revisited

As long-time readers of this newsletter know, what we think we know is sometimes subject to revision, even refutation. See, for example, my newsletter on the Reproducibility Project (RP) (link here). The RP showed that many oft-cited studies in psychology could not be replicated. (Psychology is not alone: later investigations show a lack of reproducibility in economics and medical studies as well.)

A cocktail party phrase for you: “epistemic humility,” which Wikipedia defines as “the recognition that our knowledge is limited and that we should be cautious in our claims to know things. It involves being open to new information and willing to adjust our beliefs based on new evidence or perspectives.”

And BTW, this ability to change one’s mind based on compelling new data is widely recognized as a hallmark of an intelligent human being. Or you could just say a “reasonable” human being, with emphasis on “reason.”

Let’s start with the relation between money and happiness. Accepted wisdom was (still is?) that there is a point after which more money doesn’t generate more happiness. You may recall hearing that income greater than $75,000 doesn’t make you happier. For reference, that’s a bit more than $110,000 today.

In my July 2024 newsletter (link), I describe five nuances to our understanding of the relation between happiness and income. One of my suggestions was to avoid upward comparisons, a suggestion supported by Warren Buffett, who said, “$1 million isn’t going to make you happy because once you see someone with $2 million, your happiness will disappear.” (source)

However, new evidence suggests that happiness does not level off as income increases. (link) The research surveyed more than 35,000 people over time about their happiness in the moment, as well as life satisfaction.[1] The author concludes, “This suggests that higher incomes may still have potential to improve people’s day-to-day well-being, rather than having already reached a plateau for many people in wealthy countries.” Life satisfaction also increased with income, rather than plateauing.

Another oft-cited “fact:” Happiness has a U-shaped curve over one’s lifetime, starting relatively high at the beginning of adulthood, declining in middle age, and rising thereafter. But more recent evidence (link) finds a different pattern: happiness declines slowly through adulthood, briefly increases, and then “declines steeply” in old age. Yikes! That’s a bit scary for Baby Boomers like me.

Why the difference in results? The authors of the study argue that there are “methodological biases” in previous studies. These are not the personal biases of researchers, but rather flaws in the manner in which earlier research was conducted. As I discussed in my December newsletter (link), a broadly similar complaint has been lodged against research on the effectiveness of nudging.

A former colleague of mine used to say that he could afford anything he wanted, but not everything he wanted. One can’t take this statement literally (he couldn’t afford a $10 million house, for example), but I still think this captures something about how I feel about my personal financial situation.

Example: I can afford to fly First Class if I wish, but I can’t afford to buy a private jet. My happiness doesn’t increase much if I have a year of higher income (say, from speaking, hint, hint), but a large increase in wealth (what I call “private jet money”) would make a difference. Or at least I think so.

Of course, this thought is both speculative and anecdotal. Maybe hedonic adaptation (described here) would mean that I would quickly revert to my baseline of happiness (which hopefully is not declining too fast with age).

Where does this leave us? First, context is important. Note that the newer evidence cited above is based on data from people in wealthy countries (the United States and Germany). The results may not generalize. It is easy to imagine that exiting extreme poverty would substantially increase one’s happiness and life satisfaction.

Second, the research I’ve cited is based on relatively large samples of participants. You can think of the results as averages, leaving substantial room for individual variation. Behavioral economics offers tools for making better decisions, which presumably make us happier. You don’t necessarily need to experience a sharp decline in happiness in your old age, for example.

Third, stay tuned/subscribed. I’ll do my best to keep you up to date on the latest in behavioral economics research.

What are your thoughts or experiences with this updated research on money and happiness? And if you have any interest in increasing my own happiness 😊, please like and comment below. Emailed responses to my scribblings are always welcome, but they deprive fellow readers of direct access to your wisdom.

[1] The distinction between happiness, which is short-horizon, and life satisfaction, which takes a longer view, is another nuance. You can be unhappy in the moment, but overall pleased about how your life is progressing.

Essay 5: Mental models

The mind is its own place, and in itself / Can make a heaven of hell, a hell of heaven. -John Milton, poet (9 Dec 1608-1674)

Is there such a thing as an “objective reality”? That’s an interesting question, but it turns out that it is moot because each of us perceives the world in our own way. Neuroscience has increasingly shed light on how the brain works. Here’s a nice summary:

“Neuroscientists like to say that your day-to-day experience is a carefully controlled hallucination, constrained by the world and your body but ultimately constructed by your brain,” writes Dr. [Lisa Feldman] Barrett…“It’s an everyday kind of hallucination that creates all of your experiences and guides all your actions. It’s the normal way that your brain gives meaning to the sensory inputs from your body and from the world (called “sense data”), and you’re almost always unaware that it’s happening.”[1][2]

And each of us processes the firehose of information coming at us in our own way. Hence, each of us has a different view of the world than anyone else. As Morgan Housel puts it, “…you are the only person in the world who thinks the world operates the way you do.” (The Psychology of Money, p. 199).

Neuroactivity takes place at the subconscious level. But we do seem to have some control over our thinking. (I’m going to set aside the debate about whether we have free will.) We can choose, to a degree, how to think about the world. Whether one believes that the glass is half empty or half full is a simple mental model—is the world friendly to me or not?

Because we all have at least a slightly different take on reality, I’m not going to recommend any particular mental models. One hundred nine (yes, 109) of them can be found at:

https://fs.blog/mental-models/

However, I cannot suppress the urge to make a suggestion: Be humble and agnostic about what you think you know. Writing about the scientific method—one mental model—Mark Henderson, former science editor at The Times (of London), comments:

“[Science] is a way of thinking, the best approach devised yet (if still an imperfect one) for discovering progressively better approximations of how things really are… Science is provisional, always open to revision in light of new evidence… And it is comfortable with uncertainty.”[3]

There are several important ideas in this quote. The first of these is the notion that we typically deal with approximations of how things really are, not how things really are. Our senses are bombarded thousands of times per minute with all kinds of information. To avoid being overwhelmed, our minds block out most of the sensory input, so we perceive only a small portion of the available information about reality. Our image of the world is a working model, but not the world itself. That model can be very close to the world itself, or not.

Another idea in Henderson’s quote is that knowledge is provisional and is thus subject to being improved upon at any time. For many years, people thought Newtonian physics was the last word in describing the movement of physical objects. Then quantum physics came along. It turns out that movement at very small scales is not well described by Newton’s equations. Newtonian physics does work as a good approximation at large scales, but it certainly was not the last word.

Because we deal with approximations of reality and because knowledge is provisional, uncertainty is omnipresent. We need to get comfortable with this idea. I’m not saying that you should feel comfortable when dealing with uncertainty, only with the idea that there are very few certainties in life. A realistic attitude about the degree of uncertainty in the world, and therefore our relative impotence at knowing the future, will serve you well in all aspects of your life.

I conclude with three quotes from quite different sources that support the basic argument made here:

1. “All models are wrong. Some models are useful.” George Box, statistician. Lovely. I wish I had said that.

2.“Most of our beliefs are wrong. Or, to be more exact, all beliefs are wrong—some just less wrong than others.” The Subtle Art of Not Giving a F*ck by Mark Manson, p. 123.

3. “The Lama, during our private chat, said Buddhism isn’t true, but it works.”[4]

References

Housel, Morgan, The Psychology of Money, Harriman House, 2020.

Manson, Mark, The Subtle Art of Not Giving a F*ck, HarperOne, 2016.

[1] https://www.gq.com/story/lisa-feldman-barrett-interview?utm_source=pocket&utm_medium=email&utm_campaign=pockethits

[2] For more detail see

Esteem Note Lab

The Bayesian brain

Why our reality is a well-grounded hallucination…

Read more

a year ago · 8 likes · 5 comments · Esteem Note Lab

[3] Mark Henderson, “Science’s Methods Aren’t Just for Science,” in This Will Make You Smarter: New Scientific Concepts to Improve Your Thinking, ed. John Brockman (New York: Harper Perennial, 2012).

[4] https://getpocket.com/explore/item/a-buddhism-critic-goes-on-a-silent-buddhist-retreat?utm_source=pocket-newtab

January 1, 2026

Happy New Year!

May your year be filled with better decisions, courtesy of behavioral economics. Let’s start with optimism.

My newsletter of February 2024 (link here) looked at negativity bias. There I wrote, “A reasonable explanation is that we inherited this tendency from our ancestors for whom negative events could be life-or-death situations, e.g., being attacked by a wildebeest suffering from wasting disease.”

And yet, there is also a positivity bias—optimism. Indeed, there is a whole book devoted to it, The Optimism Bias. The author, Dr. Tali Sharot, reports that about 80% of people have a typically “mild” optimism bias. She argues that optimism (arising from the “irrationally positive brain”) is largely beneficial. For example, it serves to motivate us (think: an entrepreneur), reduces stress, and is generally good for our mental health.

My focus here is on individual optimism. But we might ask whether optimism varies across countries. The answer is Yes. In late November and early October 2025, a survey (link) of about 24,000 adults across 30 countries showed that 71% agreed with the statement, “I am optimistic that 2026 will be a better year for me than it was in 2025.” The most optimistic country? Indonesia at 90%. The least? France, at 41%. (Indonesia was hit by Cyclone Senyar in late November, so Indonesia’s optimism might be lower if we did the survey today.)

An inspirational example of the benefits of optimism is the life of Viktor Frankl. You may have read his book, Man’s Search for Meaning, about his time in a Nazi concentration camp. During that time, he observed who survived and who did not. Some people gave up hope while others remained optimistic. He concluded that people’s attitudes influenced whether or not they survived and later articulated his “Tragic Optimism”:

“An optimism in the face of tragedy and in view of the human potential which at its best always allows for: (1) turning suffering into a human achievement and accomplishment; (2) deriving from guilt the opportunity to change oneself for the better; and (3) deriving from life’s transitoriness an incentive to take responsible action.” (emphasis added)

As suggested by Frankl, we can influence the strength of our optimism, perhaps moving it from “mild” to “strong,” to reap the benefits of optimism. In fact, there is a long history of “the power of positive thinking,” the title of an influential book by Norman Vincent Peale published in 1952. Arguably, the idea goes back at least as far as the Epicureans, who—c. 300 BCE—suggested that we adopt a “hopeful disposition”.

But optimism can go too far. At the macro level, unchecked optimism contributed to the financial crisis of 2008-09. The behavioral scientist Peter Ubel writes (link), “…people were susceptible to what behavioral scientists like me call unrealistic optimism: They were convinced that their interest rates would not rise; or they were confident that their salaries would rise faster than their mortgage payments; or they were certain that their house would grow in value...”

At the individual level, it is not helpful to be optimistic that you can outrun a bear. (An outrun-the-bear joke is here.) On a less humorous note, consider the book The Secret, which describes the Law of Attraction, which can be thought of as a type of extreme optimism. The Law of Attraction, in short: think of positive things, and they will materialize; think of negative things, and they will materialize.

One of many downsides to the Law of Attraction is that, given its focus on thinking, it reduces the incentive to take action. The Law of Attraction also makes for victim-blaming, e.g., you’re suffering in Darfur because you’re not visualizing vividly enough. You’re not rich because you’re not thinking in the right way about wealth. And so forth.

The Law of Attraction is not built on an evidence-based foundation. One article (link) summarizes it this way: “[The] Law of Attraction is pseudoscience with conclusions based on erroneous, unfounded, and incorrect assumptions.” In addition to victim-blaming, the article lists 10 negative outcomes associated with the Law of Attraction way of thinking.

TL;DR: (1) There are both negativity and positivity biases, (2) each can play a helpful role in our lives, (3) as suggested by Viktor Frankl, Norman Vincent Peale, and others, the level of one’s optimism can be changed to some degree, and (4) optimism can be overdone.

The challenge: When should we be optimistic, when should we be pessimistic (negative bias)? I suggest that context is important. Being overly optimistic that your daughter’s softball team will win the next game is probably benign. Being optimistic that your investments will return 20% per year could leave you in (relative) poverty in retirement.

In addition to consideration of context, perhaps others can guide us toward an optimal level of optimism (or pessimism). I’ve written about the role that a devil’s advocate can play in making better decisions here.

You might consider having a personal board of directors that you can consult in the context of making important decisions; ask them, “Am I being too optimistic? Too pessimistic?” You can also conduct a pre-mortem (discussed here) on important decisions: “What am I overlooking that could go wrong? What if I’m being too optimistic about this opportunity?”

There are certainly reasons to be pessimistic about 2026, but I choose to start the new year optimistic that behavioral economics can make our lives, and the lives of those around us, better. How ‘bout you? Feel free to comment below.

Essay 4: “You’ve got to think for yourselves”

“Think for yourself and question authority.” -Timothy Leary, psychologist and writer (22 Oct 1920-1996)

“A life without thinking is quite possible; it then fails to develop its own essence — it is not merely meaningless; it is not fully alive. Unthinking men are like sleepwalkers.” Hannah Arendt, The Life of the Mind.

In the Monty Python movie, “Life of Brian,” Brian is mistaken for the Messiah. He attracts a large following but wants nothing of it. He speaks to a crowd:

FOLLOWERS: Brian! Brian! Brian!...

BRIAN: Good morning.

FOLLOWERS: A blessing! A blessing! A blessing!...

BRIAN: No. No, please! Please! Please listen. I’ve got one or two things to say.

FOLLOWERS: Tell us. Tell us both of them.

BRIAN: Look. You’ve got it all wrong. You don’t need to follow me. You don’t need to follow anybody! You’ve got to think for yourselves. You’re all individuals!

FOLLOWERS: Yes, we’re all individuals!

BRIAN: You’re all different!

FOLLOWERS: Yes, we are all different!

…

BRIAN: You’ve all got to work it out for yourselves!

FOLLOWERS: Yes! We’ve got to work it out for ourselves!

BRIAN: Exactly!

FOLLOWERS: Tell us more!

BRIAN: No! That’s the point! Don’t let anyone tell you what to do![1]

The self-help industry doesn’t much help us think for ourselves, often dialing up contradictory advice. Actual examples:

Make your bed every day. Or don’t.

Have a to-do list. Or don’t.

Have a morning routine. Or don’t.

Breakfast is the most important meal of the day. Or it isn’t.[2]

In fact, the book, Sham: How the Self-Help Movement Made American Helpless, suggests that you might want to avoid self-help advice entirely (does that include the advice to avoid self-help advice?).

I agree with Brian (and Immanuel Kant, among others[3]): You must learn to think for yourself. Accompany this approach with intellectual humility—few things are known with 100% certainty. Be open-minded but, as Jacob Needleman is credited with saying, “It’s good to be open-minded, but not so open that your brains fall out.”

How might we learn to think (better) for ourselves? That’s the topic of a future essay.

Finally, I think the following quote has something to do with thinking for yourself or at least being open-minded, but if it doesn’t, I am still taken with it:

“Things that have never happened before happen all the time.” Stanford Professor Scott Sagan as reported in The Psychology of Money by Morgan Housel, p. 123.

References:

Arendt, Hannah, The Life of the Mind, Mariner Books Classics, 1981.

Housel, Morgan, The Psychology of Money, Harriman House, 2020.

Salerno, Steve, Sham: How the Self-Help Movement Made American Helpless, Crown Publishers, 2005.

[1] The script of the full scene can be found at:

http://montypython.50webs.com/scripts/Life_of_Brian/20.htm

[2] https://tinyurl.com/yanf39wt

[3] https://tinyurl.com/w7aj9dk8

December 1, 2025

Bad health advice, with a dose of overconfidence

It should come as no surprise that there is a significant amount of misleading and potentially dangerous information on social media. For example, one influencer has suggested that cancer can be cured with “green juice.” (link) The influencer was a fraudster. The story of her rise and fall can be seen in the Netflix show, Apple Cider Vinegar.

And yet, some people do rely on social media for health advice. A recent (October 18, 2025) Wall Street Journal article describes a woman who “…was intrigued hearing a former MTV star talk up Lexapro on a podcast in 2023. She searched for the drug on TikTok, her go-to information source…” (emphasis added)

Worse, “TikTok science” can make us overconfident. (A good discussion is here; the original research is reported here.) And overconfidence in one area leads one to be more confident in other areas—the so-called “spillover effect.” (link) For example, surgeons might be overconfident about their investing acumen (I’m not naming names, but I have observed this firsthand 😊). You can read about combating overconfidence in my September 2020 newsletter here.

What can you do to avoid falling for bad health advice on social media? An obvious solution is to avoid social media altogether. But they are useful for other things, so that’s rather impractical.

You might consider self-screening, telling yourself to ignore everything related to health that shows up on social media. But if you are suffering, there is the strong allure of getting relief or even finding a cure that your doctor is supposedly unaware of. You can strengthen your self-screening by unfollowing questionable advice-givers or hiding a hashtag. If you consistently dislike health posts, the algorithms will feed you fewer of them.

Or perhaps there is a “nudge” that can help.

A nudge is a relatively minor change of rules, policies, or laws that influences decision-making. Example: An opt-out savings plan automatically enrolls new workers into a company’s retirement plan. If the worker does nothing (as is often the case), they are enrolled. This nudge appears to be effective, with a higher proportion of people in a savings plan (link), presumably a desirable outcome.

A simple nudge would be to reward yourself for going an entire day without reading a health-related post. Research (link) shows that being explicit about both the goal (e.g., not reading health-related posts) and the reward increases the chances of achieving the goal by 20 percent. That’s not perfect, but it is something.

There is recent evidence that nudges aren’t always effective. (link) The study is not about a particular nudge, but is rather an examination of the process by which research is selected for publication and the bias that the process introduces.

Example: One form of publication bias is that new and “sexy” results get published, and studies that don’t find something sexy do not. But sometimes a non-result is informative—the dog that didn’t bark, if you will. Publication bias can be seen as a variant of survivorship bias, which I wrote about back in June of 2020. (link)

So how can we incentivize ourselves to winnow out the wheat from the chaff of internet misinformation? (Apologies for the lame metaphor.)

Think of our desire to make better decisions as a high-level, internal nudge. Practical implementation could then include: 1) recognizing the role that overconfidence might be playing in our thinking; 2) relying on credible sources of advice, e.g., the Mayo Clinic; 3) looking for the content provider’s credentials; 4) recognizing that a 30-second TikTok is likely to be oversimplified at best; and 5) using a fact-checking tool such as Snopes. (link)

Do you have a nudge that you use to avoid being overly influenced by what you read on social media? How do you reward yourself? Use “Comment” below to share.

My website: jshowe.com

Essay 3: Moments can be perfect, humans not

I was introduced to the concept of a “perfect moment” by Spaulding Gray in the movie “Swimming to Cambodia” (recommended). For many years, I was resistant to the concept of a perfect moment. And I think I know why: In general, perfectionism is a bad way to proceed. To set perfection as a goal, no matter the undertaking, will disappoint. Perhaps not surprisingly, there is evidence that perfectionists are less happy[1] and less productive.[2] I used the word “sublime” to describe high-quality moments.

And yet I have come to believe that perfect moments can happen. Does this contradict the idea that perfectionism is bad? I think not. Perfect moments frequently happen not because we are trying, but just the opposite—they often occur when we are not in “achievement mode.” They can arise at moments when we have backed away from action, when we are not actively seeking perfection.

As I write this, my dog is asleep on my lap (an actual lap dog) and the sunrise is beginning to touch the tops of the trees out my window. A perfect moment, I’d say. I did not try to create it, I did not strive to create a perfect moment. But I did recognize it.

Is a perfect moment perhaps a brief awakening, as referred to in Buddhism? The Zen Buddhist Charlotte Joko Beck (1993, p. 188) writes, “…moments of pure experiencing without self-centered thought: just pure experience itself. In some Zen centers, such states are sometimes called enlightenment experiences.”

Reference

Beck, Charlotte Joko, Nothing Special, HarperSanFrancisco, 1993.

[1] https://www.theemotionmachine.com/how-perfectionism-destroys-happiness/

[2] https://www.brainpickings.org/2013/11/22/bird-by-bird-anne-lamott/

November 1, 2025

Is it a halo or just a good haircut?

Does it surprise you to learn that unattractive defendants get sentences that are, on average, 22 months longer than attractive defendants? (link) Or “…that more attractive persons are less likely to be arrested and convicted than less attractive persons”? (link) (This effect seems to be limited to women, however.)

That’s the essence of what psychologists call the halo effect—when our positive impression in one area spills over into how we are judged regarding unrelated traits. And it is not limited to the courtroom. Tall people are perceived to be more attractive (link), and tall CEOs get promoted at higher rates. (link)

Hiring decisions are also affected by attractiveness. In one study (link), ratings of attractiveness were positively correlated with ratings of professional competence.[1] Another study (link) reports that auditors (accountants) who are seen as more attractive are better at acquiring and retaining clients. (link)

When a company rolls out a sleek new product, our admiration of its design might lead us to overrate its reliability or durability. One study (link) showed that high design aesthetics are associated with positive emotions, suggestive of a halo effect. Charismatic leaders are perceived to be more trustworthy. (link)

The flip side of the halo effect is called the “horn effect.” One negative trait darkens everything else. For example, people deemed to be “more ugly” are perceived to be less trustworthy. (link)

What can be done to offset the halo and horn effects, aside from altering your genes? As always, the first step is awareness. You can then ask: “Am I overvaluing this person’s other qualities just because of one standout feature? Would I feel the same about their proposal if they weren’t so articulate, so tall, so charming?” Admittedly a challenge, but you’ll make better decisions if you make the effort.

Parting words of advice: If you are ever a defendant in a court case (unlikely for readers of this newsletter, of course), make yourself as attractive as possible. Women: wear makeup. (See first footnote; this is not a snarky John McEnroe comment,[2] but a suggestion backed by research.) Men: It has been my observation that in high-profile cases, the male defendant is always wearing an attractive suit. Good work by his lawyers.

[1] This study was limited to women. It also showed that “…the use of professional facial cosmetics improved ratings of competence for female applicants.” Notably, this study was published in 2019, not in the 1950s.

[2] He said of Iga Swiatek, one of the world’s best tennis players, “You think if they offer her enough, Lancome, maybe she would consider throwing on a little makeup for the right price?” (link)