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We conducted two online surveys of a total of 1,258 adults in the United States. Each participant completed a variety of standard questionnaires to measure his or her impulsiveness, ethnocentrism and personal insecurity. (Professors Chua and Rubenfeld describe insecurity as “a goading anxiety about oneself and one’s place in society.” Since this concept was the most complex and counterintuitive element of their theory, we measured it several different ways, each of which captured a slightly different aspect.)Next, the participants completed a test of their cognitive abilities. Then they reported their income, occupation, education and other achievements, such as receiving artistic, athletic or leadership awards, all of which we combined to give each person a single score for overall success. Finally, our participants indicated their age, sex and parents’ levels of education.

First, the more successful participants had higher cognitive ability, more educated parents and better impulse control.

This finding is exactly what you would expect from accepted social science. Long before “The Triple Package,” researchers determined that the personality trait of conscientiousness, which encompasses the triple package’s impulse control component, was an important predictor of success — but that a person’s intelligence and socioeconomic background were equally or even more important.

Our second finding was that the more successful participants did not possess greater feelings of ethnocentrism or personal insecurity. In fact, for insecurity, the opposite was true: Emotional stability was related to greater success.

Finally, we found no special “synergy” among the triple package traits. According to Professors Chua and Rubenfeld, the three traits have to work together to create success — a sense of group superiority creates drive only in people who also view themselves as not good enough, for example, and drive is useless without impulse control. But in our data, people scoring in the top half on all three traits were no more successful than everyone else.

To be clear, we have no objection to Professors Chua and Rubenfeld’s devising a novel social-psychological theory of success. During the peer-review process before publication, our paper was criticized on the grounds that a theory created by law professors could not have contributed to empirical social science, and that ideas published in a popular book did not merit evaluation in an academic journal.We disagree. Outsiders can make creative and even revolutionary contributions to a discipline, as the psychologists Amos Tversky and Daniel Kahneman did for economics. And professors do not further the advancement of knowledge by remaining aloof from debates where they can apply their expertise. Researchers should engage the public, dispel popular myths and even affirm “common sense” when the evidence warrants.

it did not stand up to direct empirical tests. Our conclusion regarding “The Triple Package” is expressed by the saying, “What is new is not correct, and what is correct is not new.”

And while empirical evidence is important and we need more of it, the data almost never speak for themselves – a point amply illustrated by recent monetary events.

chwinger, as I remember the story, was never seen to use a Feynman diagram. But he had a locked room in his house, and the rumor was that that room was where he kept the Feynman diagrams he used in secret.

What’s the equivalent of Feynman diagrams? Something like IS-LM, which is the simplest model you can write down of how interest rates and output are jointly determined, and is how most practicing macroeconomists actually think about short-run economic fluctuations. It’s also how they talk about macroeconomics to each other. But it’s not what they put in their papers, because the journals demand that your model have “microfoundations.”

The Bernanke Fed massively expanded the monetary base, by a factor of almost five. There were dire warnings that this would cause inflation and “debase the dollar.” But prices went nowhere, and not much happened to broader monetary aggregates (a result that, weirdly, some economists seemed to find deeply puzzling even though it was exactly what should have been expected.)

What about fiscal policy? Traditional macro said that at the zero lower bound there would be no crowding out – that deficits wouldn’t drive up interest rates, and that fiscal multipliers would be larger than under normal conditions. The first of these predictions was obviously borne out, as rates stayed low even when deficits were very large. The second prediction is a bit harder to test, for reasons I’ll get into when I talk about the limits of empiricism. But the evidence does indeed suggest large positive multipliers.

The overall story, then, is one of overwhelming predictive success. Basic, old-fashioned macroeconomics didn’t fail in the crisis – it worked extremely well

In fact, it’s hard to think of any other example of economic models working this well – making predictions that most non-economists (and some economists) refused to believe, indeed found implausible, but which came true. Where, for example, can you find any comparable successes in microeconomics?

Meanwhile, the demand that macro become ever more rigorous in the narrow, misguided sense that it look like micro led to useful approaches being locked up in Schwinger’s back room, and in all too many cases forgotten. When the crisis struck, it was amazing how many successful academics turned out not to know things every economist would have known in 1970, and indeed resurrected 1930-vintage fallacies in the belief that they were profound insights.

mainly I think it reflected the general unwillingness of human beings (a category that includes many though not necessarily all economists) to believe that so many people can be so wrong about something so big.

. To normal human beings the study of international trade and that of international macroeconomics might sound like pretty much the same thing. In reality, however, the two fields used very different models, had very different intellectual cultures, and tended to look down on each other. Trade people tended to consider international macro people semi-charlatans, doing ad hoc stuff devoid of rigor. International macro people considered trade people boring, obsessed with proving theorems and offering little of real-world use.

does microeconomics really deserve its reputation of moral and intellectual superiority? No

Even before the rise of behavioral economics, any halfway self-aware economist realized that utility maximization – indeed, the very concept of utility — wasn’t a fact about the world; it was more of a thought experiment, whose conclusions should always have been stated in the subjunctive.

But, you say, we didn’t see the Great Recession coming. Well, what do you mean “we,” white man? OK, what’s true is that few economists realized that there was a huge housing bubble

True, a model doesn’t have to be perfect to provide hugely important insights. But here’s my question: where are the examples of microeconomic theory providing strong, counterintuitive, successful predictions on the same order as the success of IS-LM macroeconomics after 2008? Maybe there are some, but I can’t come up with any.

The point is not that micro theory is useless and we should stop doing it. But it doesn’t deserve to be seen as superior to macro modeling.

And the effort to make macro more and more like micro – to ground everything in rational behavior – has to be seen now as destructive. True, that effort did lead to some strong predictions: e.g., only unanticipated money should affect real output, transitory income changes shouldn’t affect consumer spending, government spending should crowd out private demand, etc. But all of those predictions have turned out to be wrong.

Kahneman and Tversky and Thaler and so on deserved all the honors they received for helping to document the specific ways in which utility maximization falls short, but even before their work we should never have expected perfect maximization to be a good description of reality.

But data never speak for themselves, for a couple of reasons. One, which is familiar, is that economists don’t get to do many experiments, and natural experiments are rare

The other problem is that even when we do get something like natural experiments, they often took place under economic regimes that aren’t relevant to current problems.

Both of these problems were extremely relevant in the years following the 2008 crisis.

you might be tempted to conclude that the empirical evidence is that monetary expansion is inflationary, indeed roughly one-for-one.

But the question, as the Fed embarked on quantitative easing, was what effect this would have on an economy at the zero lower bound. And while there were many historical examples of big monetary expansion, examples at the ZLB were much rarer – in fact, basically two: the U.S. in the 1930s and Japan in the early 2000

These examples told a very different story: that expansion would not, in fact, be inflationary, that it would work out the way it did.

The point is that empirical evidence can only do certain things. It can certainly prove that your theory is wrong! And it can also make a theory much more persuasive in those cases where the theory makes surprising predictions, which the data bear out. But the data can never absolve you from the necessity of having theories.

Over this past decade, I’ve watched a number of economists try to argue from authority: I am a famous professor, therefore you should believe what I say. This never ends well. I’ve also seen a lot of nihilism: economists don’t know anything, and we should tear the field down and start over.

Obviously I differ with both views. Economists haven’t earned the right to be snooty and superior, especially if their reputation comes from the ability to do hard math: hard math has been remarkably little help lately, if ever.

On the other hand, economists do turn out to know quite a lot: they do have some extremely useful models, usually pretty simple ones, that have stood up well in the face of evidence and events. And they definitely shouldn’t defer to important and/or rich people on polic

: compare Janet Yellen’s macroeconomic track record with that of the multiple billionaires who warned that Bernanke would debase the dollar. Or take my favorite Business Week headline from 2010: “Krugman or [John] Paulson: Who You Gonna Bet On?” Um.The important thing is to be aware of what we do know, and why.Follow The New York Times Opinion section on Facebook and Twitter (@NYTopinion), and sign up for the Opinion Today newsletter.

In short, learning what did happen impedes you from retrieving what you thought would happen.

In 2002, psychologists asked nearly 1,000 Americans to recall how likely they had expected terrorism-related incidents—and other risky events—to be in the immediate aftermath of Sept. 11, 2001. After a year in which fears had mostly subsided, they remembered being much less pessimistic than they had been at the time.

“We’re biased to see ourselves in a positive light,” says Deborah Small, a psychologist at the Wharton School at the University of Pennsylvania. “We want to believe that we’re rational and smart. We’ll recall our past actions as more sensible than they were. We also give ourselves too much credit and don’t remember our mistakes as well as we do our successes.”

take what psychologist Daniel Kahneman calls “the outside view.” Rather than try to figure out exactly how bad this crisis will be, look at the broader set of historical precedents.

Since 1929, the S&P 500 has suffered 14 bear markets, defined by S&P Dow Jones Indices as losses of at least 20%. The shortest and shallowest was the 20% drop that lasted less than three months in late 1990. The deepest was the 86.2% collapse from September 1929 to June 1932; the longest, the 60% plunge from March 1937 to April 1942. On average, bear markets lasted 19 months and dealt a 39% loss.

Below, we outline five psychological biases that are common in business decision making. We also look at how you can overcome them, and thereby make better decisions.

when it comes to mistaken judgments and unfortunate decisions, there is another type of error that attracts far less attention: noise.

To see the difference between bias and noise, consider your bathroom scale. If on average the readings it gives are too high (or too low), the scale is biased

It is hard to escape the conclusion that sentencing is in part a lottery, because the punishment can vary by many years depending on which judge is assigned to the case and on the judge’s state of mind on that day. The judicial system is unacceptably noisy.

While bias is the average of errors, noise is their variability.

Although it is often ignored, noise is a large source of malfunction in society.

The average difference between the sentences that two randomly chosen judges gave for the same crime was more than 3.5 years. Considering that the mean sentence was seven years, that was a disconcerting amount of noise.

If it shows different readings when you step on it several times in quick succession, the scale is noisy.

How much of a difference would you expect to find between the premium values that two competent underwriters assigned to the same risk?

Executives in the insurance company said they expected about a 10 percent difference.

But the typical difference we found between two underwriters was an astonishing 55 percent of their average premium — more than five times as large as the executives had expected.

Many other studies demonstrate noise in professional judgments. Radiologists disagree on their readings of images and cardiologists on their surgery decisions

Wherever there is judgment, there is noise — and more of it than you think.

Noise causes error, as does bias, but the two kinds of error are separate and independent.

A company’s hiring decisions could be unbiased overall if some of its recruiters favor men and others favor women. However, its hiring decisions would be noisy, and the company would make many bad choices

Where does noise come from?

There is much evidence that irrelevant circumstances can affect judgments.

for instance, a judge’s mood, fatigue and even the weather can all have modest but detectable effects on judicial decisions.

people can have different general tendencies. Judges often vary in the severity of the sentences they mete out: There are “hanging” judges and lenient ones.

People can have not only different general tendencies (say, whether they are harsh or lenient) but also different patterns of assessment (say, which types of cases they believe merit being harsh or lenient about).

Underwriters differ in their views of what is risky, and doctors in their views of which ailments require treatment.

Once you become aware of noise, you can look for ways to reduce it.

independent judgments from a number of people can be averaged (a frequent practice in forecasting)

Guidelines, such as those often used in medicine, can help professionals reach better and more uniform decisions

imposing structure and discipline in interviews and other forms of assessment tends to improve judgments of job candidates.

No noise-reduction techniques will be deployed, however, if we do not first recognize the existence of noise.

Organizations and institutions, public and private, will make better decisions if they take noise seriously.

But when the disease is real — when we see actual death tolls climbing daily, as we do with the coronavirus — another factor besides our sensitivity to losses comes into play: fear.

asked people to imagine that the United States was preparing for an outbreak of an unusual Asian disease that was expected to kill 600 citizens. To combat the disease, people could choose between two options: a treatment that would ensure 200 people would be saved or one that had a 33 percent chance of saving all 600 but a 67 percent chance of saving none. Here, a clear favorite emerged: Seventy-two percent chose the former.

Using a nationally representative sample in the months following Sept. 11, 2001, the decision scientist Jennifer Lerner showed that feeling fear led people to believe that certain anxiety-provoking possibilities (for example, a terrorist strike) were more likely to occur.

we presented sad, angry or emotionally neutral people with a government proposal to raise taxes. In one version of the proposal, we said the increased revenue would be used to reduce “depressing” problems (like poor conditions in nursing homes). In the other, we focused on “angering” problems (like increasing crime because of a shortage of police officers).

when the emotions people felt matched the emotion of the rationales for the tax increase, their attitudes toward the proposal became more positive. But the more effort they put into considering the proposal didn’t turn out to reduce this bias; it made it stronger.

This habituation stems from a principle well-known in psychological therapy: The more we’re exposed to a given threat, the less intimidating it seems.

As the pandemic drags on, people are unknowingly performing a kind of exposure therapy on themselves, said University of Oregon psychologist Paul Slovic, author of “The Perception of Risk” — and the results can be deadly.

“You have an experience and the experience is benign. It feels okay and comfortable. It’s familiar. Then you do it again,” Slovic said. “If you don’t see anything immediately bad happening, your concerns get deconditioned.”

The end result of all this desensitizing is a kind of overriding heedlessness decoupled from evidence — the anti-mask movements, the beach gatherings, the overflowing dance parties

One of the best ways to reinforce a certain behavior is to make sure that behavior is rewarded and that deviations from it are punished (or ignored).

But when it comes to lifesaving behaviors such as mask-wearing or staying home from parties, this reward-punishment calculus gets turned on its head.

“A few parks have drawn circles [on their lawns]: ‘Don’t go out of the circle,’ ” Griffin said. “We need to take those kinds of metaphors and put them throughout the entire day.”

while there is an upside to this decision — helping to stop the spread of the virus — it feels distant. “The benefit is invisible, but the costs are very tangible.”

By contrast, Slovic said, when you flout guidelines about wearing masks or avoiding gatherings, you get an immediate reward: You rejoice at not having to breathe through fabric, or you enjoy celebrating a close friend’s birthday in person.

Because risk perception fails as we learn to live with covid-19, Griffin and other researchers are calling for the renewal of tough government mandates to curb virus spread. They see measures such as strict social distancing, enforced masking outside the home and stay-at-home orders as perhaps the only things that can protect us from our own faulty judgment.

But these kinds of measures aren’t enough on their own, Griffin said. It’s also important for authorities to supply in-your-face reminders of those mandates, especially visual cues, so people won’t draw their own erroneous conclusions about what’s safe.

With parties, when you do the right thing and stay home, “you feel an immediate cost: You’re not able to be with your friends,

“The first step is awareness that sometimes you can’t trust your feelings.”

For people considering how to assess covid-19 risks, Slovic advised pivoting from emotionally driven gut reactions to what psychologist Daniel Kahneman — winner of the 2002 Nobel Prize in economics for his integration of psychological research into economic science — calls “slow thinking.” That means making decisions based on careful analysis of the evidence. “You need to either do the slow thinking yourself,” Slovic said, “or trust experts who do the slow thinking and understand the situation.”

Thousands of us are less afraid than we were at the pandemic’s outset, even though in many parts of the country mounting case counts have increased the danger of getting the virus. We’re swarming the beaches and boardwalks, often without masks.

The two are independent, entirely different variables, meaning you can have one without the other. For example, maybe you know someone who is a complete navel-gazer with a high level of internal self-awareness. Yet you and everyone else think this person is a selfish jerk, but because he never receives external feedback, he has no idea. Conversely, someone could have a high level of external self-awareness, a clear understanding of how they fit in with the rest of the world, without knowing what they want and what makes them happy. To be truly, fully self-aware, though, you need both components — a feat that’s difficult to pull off for pretty much anyone. But, it’s worth noting, not impossible.

Modern life makes it easy to become a part of what Eurich calls the “cult of self”: social media, for example, acts as a microphone-slash-spotlight we never have to turn off, while the concept of “personal branding” turns careful image curation into a professional skill.

In that last sentence, Kahneman is alluding to the “bias blind spot,” our tendency to recognize cognitive biases in others without noticing them in ourselves.

Without self-acceptance, self-awareness becomes an unpleasant process, which in turn keeps us from embracing it.

Your approach matters, too. When introspecting, it’s common for people to ask “why.” Why didn’t I get that promotion? Why do I keep fighting with my spouse? “Research has shown there are two problems with this,” Eurich said. “The question ‘why’ sucks us into an unproductive, paralyzed state. It gets us into this victim mentality.” Second, no matter how confident we are about the answer to “why,” we’re almost always wrong.

The answer is the 1 percent, obviously (or those willing to incur credit card debt). Luca Solca, an analyst for Bernstein, estimates that the top 5 percent of luxury clients now account for more than 40 percent of sales for most luxury goods brands

As wealth inequality increases globally, luxury brands are doubling down on an ever smaller slice of their clientele

VF There’s a sort of warring imperative here between people who see it as a badge of honor not to buy full price and those who belong to the very tiny club that can. Economics are involved, but as much as anything, it’s also psychology.

VF Which brings me back to Phoebe Philo’s current scarcity model: We don’t even know how much of any piece they produced (the company wouldn’t say) but the message is the market will bear the prices, since the products are sold out. We think because it is more expensive, it has more value.

GT This is the stuff for which Daniel Kahneman won the Nobel. Subjects shown two identical cashmere sweaters, one at a far higher price, inevitably chose the more costly of the two. His point was that we don’t think. We act irrationally.

EP Speaking of dollars, a quarter of a trillion them have been wiped off the value of Europe’s seven biggest luxury businesses since April, and sales are generally down across most fashion groups. That is the aspirational middle class stepping away from the credit card machine.

Behavioral economics is at the center of the so-called replication crisis, a euphemism for the uncomfortable fact that the results of a significant percentage of social science experiments can’t be reproduced in subsequent trials

this key result was not replicated in similar experiments, undermining confidence in a whole area of study. It’s obvious that we do associate old age and slower walking, and we probably do slow down sometimes when thinking about older people. It’s just not clear that that’s a law of the mind.

And these attempts to “correct” human behavior are based on tenuous science. The replication crisis doesn’t have a simple solution

Journals have instituted reforms like having scientists preregister their hypotheses to avoid the possibility of results being manipulated during the research. But that doesn’t change how many uncertain results are already out there, with a knock-on effect that ripples through huge segments of quantitative social scienc

The Johns Hopkins science historian Ruth Leys, author of a forthcoming book on priming research, points out that cognitive science is especially prone to building future studies off disputed results. Despite the replication crisis, these fields are a “train on wheels, the track is laid and almost nothing stops them,” Dr. Leys said.

These cases result from lax standards around data collection, which will hopefully be corrected. But they also result from strong financial incentives: the possibility of salaries, book deals and speaking and consulting fees that range into the millions. Researchers can get those prizes only if they can show “significant” findings.

It is no coincidence that behavioral economics, from Dr. Kahneman to today, tends to be pro-business. Science should be not just reproducible, but also free of obvious ideology.

Technology and modern data science have only further entrenched behavioral economics. Its findings have greatly influenced algorithm design.

The collection of personal data about our movements, purchases and preferences inform interventions in our behavior from the grocery store to who is arrested by the police.

Setting people up for safety and success and providing good default options isn’t bad in itself, but there are more sinister uses as well. After all, not everyone who wants to exploit your cognitive biases has your best interests at heart.

Despite all its flaws, behavioral economics continues to drive public policy, market research and the design of digital interfaces.

One might think that a kind of moratorium on applying such dubious science would be in order — except that enacting one would be practically impossible. These ideas are so embedded in our institutions and everyday life that a full-scale audit of the behavioral sciences would require bringing much of our society to a standstill.

There is no peer review for algorithms that determine entry to a stadium or access to credit. To perform even the most banal, everyday actions, you have to put implicit trust in unverified scientific results.

We can’t afford to defer questions about human nature, and the social and political policies that come from them, to commercialized “research” that is scientifically questionable and driven by ideology. Behavioral economics claims that humans aren’t rational.

That’s a philosophical claim, not a scientific one, and it should be fought out in a rigorous marketplace of ideas. Instead of unearthing real, valuable knowledge of human nature, behavioral economics gives us “one weird trick” to lose weight or quit smoking.

Humans may not be perfectly rational, but we can do better than the predictably irrational consequences that behavioral economics has left us with today.