You know what? Let’s repeal Obamacare. Here’s my replacement.

Feb 18 JDN 2458168

By all reasonable measures, Obamacare has been a success. Healthcare costs are down but coverage rates are up. It reduced both the federal deficit and after-tax income inequality.

But Republicans have hated it the whole time, and in particular the individual mandate provision has always been unpopular. Under the Trump administration, the individual mandate has now been repealed.

By itself, this can only be disastrous. It threatens to undermine all the successes of the entire Obamacare system. Without the individual mandate, covering pre-existing conditions means that people can simply wait to get insurance until they need it—at which point it’s not insurance anymore. The risks stop being shared and end up concentrated on whoever gets sick, then we go back to people going bankrupt because they were unlucky enough to get cancer. The individual mandate was vital to making Obamacare work.

But I do actually understand why the individual mandate is unpopular: Nobody likes being forced into buying anything.

John Roberts ruled that the individual mandate was Constitutional on the grounds that it is economically equivalent to a tax. This is absolutely correct, and I applaud his sound reasoning.

That said, the individual mandate is not in fact psychologically equivalent to a tax.

Psychologically, being forced to specifically buy something or face punishment feels a lot more coercive than simply owing a certain amount of money that the government will use to buy something. Roberts is right; economically, these two things are equivalent. The same real goods get purchased, at the same people’s expense; the accounts balance in the same way. But it feels different.

And it would feel different to me too, if I were required to actually shop for that particular avionic component on that Apache helicopter my taxes paid for, or if I had to write a check for that particular section of Highway 405 that my taxes helped maintain. Yes, I know that I give the government a certain amount of money that they spent on salaries for US military personnel; but I’d find it pretty weird if they required me to actually hand over the money in cash to some specific Marine. (On the other hand, this sort of thing might actually give people a more visceral feel for the benefits of taxes, much as microfinance agencies like to show you the faces of particular people as you give them loans, whether or not those people are actually the ones getting your money.)

There’s another reason it feels different as well: We have framed the individual mandate as a penalty, as a loss. Human beings are loss averse; losing $10 feels about twice as bad as not getting $10. That makes the mandate more unpleasant, hence more unpopular.

What could we do instead? Well, obviously, we could implement a single-payer healthcare system like we already have in Medicare, like they have in Canada and the UK, or like they have in Scandinavia (#ScandinaviaIsBetter). And that’s really what we should do.

But since that doesn’t seem to be on the table right now, here’s my compromise proposal. Okay, yes, let’s repeal Obamacare. No more individual mandate. No fines for not having health insurance.

Here’s what we would do instead: You get a bonus refundable tax credit for having health insurance.

We top off the income tax rate to adjust so that revenue ends up the same.

Say goodbye to the “individual mandate” and welcome the “health care bonus rebate”.

Most of you reading this are economically savvy enough to realize that’s the same thing. If I tax you $100, then refund $100 if you have health insurance, that’s completely equivalent to charging you a fine of $100 if you don’t have health insurance.

But it doesn’t feel the same to most people. A fine feels like a punishment, like a loss. It hurts more than a mere foregone bonus, and it contains an element of disapproval and public shame.

Whereas, we forgo refundable tax credits all the time. You’ve probably forgone dozens of refundable tax credits you could have gotten, either because you didn’t know about them or because you realized they weren’t worth it to you.

Now instead of the government punishing you for such a petty crime as not having health insurance, the government is rewarding you for the responsible civic choice of having health insurance. We have replaced a mean, vindictive government with a friendly, supportive government.

Positive reinforcement is more reliable anyway. (Any child psychologist will tell you that while punishment is largely ineffective and corporal punishment is outright counterproductive, reward systems absolutely do work.) Uptake of health insurance should be at least as good as before, but the policy will be much more popular.

It’s a very simple change to make. It could be done in a single tax bill. Economically, it makes no difference at all. But psychologically—and politically—it could make all the difference in the world.

Experimentally testing categorical prospect theory

Dec 4, JDN 2457727

In last week’s post I presented a new theory of probability judgments, which doesn’t rely upon people performing complicated math even subconsciously. Instead, I hypothesize that people try to assign categories to their subjective probabilities, and throw away all the information that wasn’t used to assign that category.

The way to most clearly distinguish this from cumulative prospect theory is to show discontinuity. Kahneman’s smooth, continuous function places fairly strong bounds on just how much a shift from 0% to 0.000001% can really affect your behavior. In particular, if you want to explain the fact that people do seem to behave differently around 10% compared to 1% probabilities, you can’t allow the slope of the smooth function to get much higher than 10 at any point, even near 0 and 1. (It does depend on the precise form of the function, but the more complicated you make it, the more free parameters you add to the model. In the most parsimonious form, which is a cubic polynomial, the maximum slope is actually much smaller than this—only 2.)

If that’s the case, then switching from 0.% to 0.0001% should have no more effect in reality than a switch from 0% to 0.00001% would to a rational expected utility optimizer. But in fact I think I can set up scenarios where it would have a larger effect than a switch from 0.001% to 0.01%.

Indeed, these games are already quite profitable for the majority of US states, and they are called lotteries.

Rationally, it should make very little difference to you whether your odds of winning the Powerball are 0 (you bought no ticket) or 0.000000001% (you bought a ticket), even when the prize is $100 million. This is because your utility of $100 million is nowhere near 100 million times as large as your marginal utility of $1. A good guess would be that your lifetime income is about $2 million, your utility is logarithmic, the units of utility are hectoQALY, and the baseline level is about 100,000.

I apologize for the extremely large number of decimals, but I had to do that in order to show any difference at all. I have bolded where the decimals first deviate from the baseline.

Your utility if you don’t have a ticket is ln(20) = 2.9957322736 hQALY.

Your utility if you have a ticket is (1-10^-9) ln(20) + 10^-9 ln(1020) = 2.9957322775 hQALY.

You gain a whopping 40 microQALY over your whole lifetime. I highly doubt you could even perceive such a difference.

And yet, people are willing to pay nontrivial sums for the chance to play such lotteries. Powerball tickets sell for about $2 each, and some people buy tickets every week. If you do that and live to be 80, you will spend some $8,000 on lottery tickets during your lifetime, which results in this expected utility: (1-4*10^-6) ln(20-0.08) + 4*10^-6 ln(1020) = 2.9917399955 hQALY.
You have now sacrificed 0.004 hectoQALY, which is to say 0.4 QALY—that’s months of happiness you’ve given up to play this stupid pointless game.

Which shouldn’t be surprising, as (with 99.9996% probability) you have given up four months of your lifetime income with nothing to show for it. Lifetime income of $2 million / lifespan of 80 years = $25,000 per year; $8,000 / $25,000 = 0.32. You’ve actually sacrificed slightly more than this, which comes from your risk aversion.

Why would anyone do such a thing? Because while the difference between 0 and 10^-9 may be trivial, the difference between “impossible” and “almost impossible” feels enormous. “You can’t win if you don’t play!” they say, but they might as well say “You can’t win if you do play either.” Indeed, the probability of winning without playing isn’t zero; you could find a winning ticket lying on the ground, or win due to an error that is then upheld in court, or be given the winnings bequeathed by a dying family member or gifted by an anonymous donor. These are of course vanishingly unlikely—but so was winning in the first place. You’re talking about the difference between 10^-9 and 10^-12, which in proportional terms sounds like a lot—but in absolute terms is nothing. If you drive to a drug store every week to buy a ticket, you are more likely to die in a car accident on the way to the drug store than you are to win the lottery.

Of course, these are not experimental conditions. So I need to devise a similar game, with smaller stakes but still large enough for people’s brains to care about the “almost impossible” category; maybe thousands? It’s not uncommon for an economics experiment to cost thousands, it’s just usually paid out to many people instead of randomly to one person or nobody. Conducting the experiment in an underdeveloped country like India would also effectively amplify the amounts paid, but at the fixed cost of transporting the research team to India.

But I think in general terms the experiment could look something like this. You are given $20 for participating in the experiment (we treat it as already given to you, to maximize your loss aversion and endowment effect and thereby give us more bang for our buck). You then have a chance to play a game, where you pay $X to get a P probability of $Y*X, and we vary these numbers.

The actual participants wouldn’t see the variables, just the numbers and possibly the rules: “You can pay $2 for a 1% chance of winning $200. You can also play multiple times if you wish.” “You can pay $10 for a 5% chance of winning $250. You can only play once or not at all.”

So I think the first step is to find some dilemmas, cases where people feel ambivalent, and different people differ in their choices. That’s a good role for a pilot study.

Then we take these dilemmas and start varying their probabilities slightly.

In particular, we try to vary them at the edge of where people have mental categories. If subjective probability is continuous, a slight change in actual probability should never result in a large change in behavior, and furthermore the effect of a change shouldn’t vary too much depending on where the change starts.

But if subjective probability is categorical, these categories should have edges. Then, when I present you with two dilemmas that are on opposite sides of one of the edges, your behavior should radically shift; while if I change it in a different way, I can make a large change without changing the result.

Based solely on my own intuition, I guessed that the categories roughly follow this pattern:

Impossible: 0%

Almost impossible: 0.1%

Very unlikely: 1%

Unlikely: 10%

Fairly unlikely: 20%

Roughly even odds: 50%

Fairly likely: 80%

Likely: 90%

Very likely: 99%

Almost certain: 99.9%

Certain: 100%

So for example, if I switch from 0%% to 0.01%, it should have a very large effect, because I’ve moved you out of your “impossible” category (indeed, I think the “impossible” category is almost completely sharp; literally anything above zero seems to be enough for most people, even 10^-9 or 10^-10). But if I move from 1% to 2%, it should have a small effect, because I’m still well within the “very unlikely” category. Yet the latter change is literally one hundred times larger than the former. It is possible to define continuous functions that would behave this way to an arbitrary level of approximation—but they get a lot less parsimonious very fast.

Now, immediately I run into a problem, because I’m not even sure those are my categories, much less that they are everyone else’s. If I knew precisely which categories to look for, I could tell whether or not I had found it. But the process of both finding the categories and determining if their edges are truly sharp is much more complicated, and requires a lot more statistical degrees of freedom to get beyond the noise.

One thing I’m considering is assigning these values as a prior, and then conducting a series of experiments which would adjust that prior. In effect I would be using optimal Bayesian probability reasoning to show that human beings do not use optimal Bayesian probability reasoning. Still, I think that actually pinning down the categories would require a large number of participants or a long series of experiments (in frequentist statistics this distinction is vital; in Bayesian statistics it is basically irrelevant—one of the simplest reasons to be Bayesian is that it no longer bothers you whether someone did 2 experiments of 100 people or 1 experiment of 200 people, provided they were the same experiment of course). And of course there’s always the possibility that my theory is totally off-base, and I find nothing; a dissertation replicating cumulative prospect theory is a lot less exciting (and, sadly, less publishable) than one refuting it.

Still, I think something like this is worth exploring. I highly doubt that people are doing very much math when they make most probabilistic judgments, and using categories would provide a very good way for people to make judgments usefully with no math at all.

The high cost of frictional unemployment

Sep 3, JDN 2457635

I had wanted to open this post with an estimate of the number of people in the world, or at least in the US, who are currently between jobs. It turns out that such estimates are essentially nonexistent. The Bureau of Labor Statistics maintains a detailed database of US unemployment; they don’t estimate this number. We have this concept in macroeconomics of frictional unemployment, the unemployment that results from people switching jobs; but nobody seems to have any idea how common it is.

I often hear a ballpark figure of about 4-5%, which is related to a notion that “full employment” should really be about 4-5% unemployment because otherwise we’ll trigger horrible inflation or something. There is almost no evidence for this. In fact, the US unemployment rate has gotten as low as 2.5%, and before that was stable around 3%. This was during the 1950s, the era of the highest income tax rates ever imposed in the United States, a top marginal rate of 92%. Coincidence? Maybe. Obviously there were a lot of other things going on at the time. But it sure does hurt the argument that high income taxes “kill jobs”, don’t you think?

Indeed, it may well be that the rate of frictional unemployment varies all the time, depending on all sorts of different factors. But here’s what we do know: Frictional unemployment is a serious problem, and yet most macroeconomists basically ignore it.

Talk to most macroeconomists about “unemployment”, and they will assume you mean either cyclical unemployment (the unemployment that results from recessions and bad fiscal and monetary policy responses to them), or structural unemployment (the unemployment that results from systematic mismatches between worker skills and business needs). If you specifically mention frictional unemployment, the response is usually that it’s no big deal and there’s nothing we can do about it anyway.

Yet at least when we aren’t in a recession, frictional employment very likely accounts for the majority of unemployment, and thus probably the majority of misery created by unemployment. (Not necessarily, since it probably doesn’t account for much long-term unemployment, which is by far the worst.) And it is quite clear to me that there are things we can do about it—they just might be difficult and/or expensive.

Most of you have probably changed jobs at least once. Many of you have, like me, moved far away to a new place for school or work. Think about how difficult that was. There is the monetary cost, first of all; you need to pay for the travel of course, and then usually leases and paychecks don’t line up properly for a month or two (for some baffling and aggravating reason, UCI won’t actually pay me my paychecks until November, despite demanding rent starting the last week of July!). But even beyond that, you are torn from your social network and forced to build a new one. You have to adapt to living in a new place which may have differences in culture and climate. Bureaucracy often makes it difficult to change over documentation of such as your ID and your driver’s license.

And that’s assuming that you already found a job before you moved, which isn’t always an option. Many people move to new places and start searching for jobs when they arrive, which adds an extra layer of risk and difficulty above and beyond the transition itself.

With all this in mind, the wonder is that anyone is willing to move at all! And this is probably a large part of why people are so averse to losing their jobs even when it is clearly necessary; the frictional unemployment carries enormous real costs. (That and loss aversion, of course.)

What could we do, as a matter of policy, to make such transitions easier?

Well, one thing we could do is expand unemployment insurance, which reduces the cost of losing your job (which, despite the best efforts of Republicans in Congress, we ultimately did do in the Second Depression). We could expand unemployment insurance to cover voluntary quits. Right now, quitting voluntarily makes you forgo all unemployment benefits, which employers pay for in the form of insurance premiums; so an employer is much better off making your life miserable until you quit than they are laying you off. They could also fire you for cause, if they can find a cause (and usually there’s something they could trump up enough to get rid of you, especially if you’re not prepared for the protracted legal battle of a wrongful termination lawsuit). The reasoning of our current system appears to be something like this: Only lazy people ever quit jobs, and why should we protect lazy people? This is utter nonsense and it needs to go. Many states already have no-fault divorce and no-fault auto collision insurance; it’s time for no-fault employment termination.

We could establish a basic income of course; then when you lose your job your income would go down, but to a higher floor where you know you can meet certain basic needs. We could provide subsidized personal loans, similar to the current student loan system, that allow people to bear income gaps without losing their homes or paying exorbitant interest rates on credit cards.

We could use active labor market programs to match people with jobs, or train them with the skills needed for emerging job markets. Denmark has extensive active labor market programs (they call it “flexicurity”), and Denmark’s unemployment rate was 2.4% before the Great Recession, hit a peak of 6.2%, and has now recovered to 4.2%. What Denmark calls a bad year, the US calls a good year—and Greece fantasizes about as something they hope one day to achieve. #ScandinaviaIsBetter once again, and Norway fits this pattern also, though to be fair Sweden’s unemployment rate is basically comparable to the US or even slightly worse (though it’s still nothing like Greece).

Maybe it’s actually all right that we don’t have estimates of the frictional unemployment rate, because the goal really isn’t to reduce the number of people who are unemployed; it’s to reduce the harm caused by unemployment. Most of these interventions would very likely increase the rate frictional unemployment, as people who always wanted to try to find better jobs but could never afford to would now be able to—but they would dramatically reduce the harm caused by that unemployment.

This is a more general principle, actually; it’s why we should basically stop taking seriously this argument that social welfare benefits destroy work incentives. That may well be true; so what? Maximizing work incentives was never supposed to be a goal of public policy, as far as I can tell. Maximizing human welfare is the goal, and the only way a welfare program could reduce work incentives is by making life better for people who aren’t currently working, and thereby reducing the utility gap between working and not working. If your claim is that the social welfare program (and its associated funding mechanism, i.e. taxes, debt, or inflation) would make life sufficiently worse for everyone else that it’s not worth it, then say that (and for some programs that might actually be true). But in and of itself, making life better for people who don’t work is a benefit to society. Your supposed downside is in fact an upside. If there’s a downside, it must be found elsewhere.

Indeed, I think it’s worth pointing out that slavery maximizes work incentives. If you beat or kill people who don’t work, sure enough, everyone works! But that is not even an efficient economy, much less a just society. To be clear, I don’t think most people who say they want to maximize work incentives would actually support slavery, but that is the logical extent of the assertion. (Also, many Libertarians, often the first to make such arguments, do have a really bizarre attitude toward slavery; taxation is slavery, regulation is slavery, conscription is slavery—the last not quite as ridiculous—but actual forced labor… well, that really isn’t so bad, especially if the contract is “voluntary”. Fortunately some Libertarians are not so foolish.) If your primary goal is to make people work as much as possible, slavery would be a highly effective way to achieve that goal. And that really is the direction you’re heading when you say we shouldn’t do anything to help starving children lest their mothers have insufficient incentive to work.

More people not working could have a downside, if it resulted in less overall production of goods. But even in the US, one of the most efficient labor markets in the world, the system of job matching is still so ludicrously inefficient that people have to send out dozens if not hundreds of applications to jobs they barely even want, and there are still 1.4 times as many job seekers as there are openings (at the trough of the Great Recession, the ratio was 6.6 to 1). There’s clearly a lot of space here to improve the matching efficiency, and simply giving people more time to search could make a big difference there. Total output might decrease for a little while during the first set of transitions, but afterward people would be doing jobs they want, jobs they care about, jobs they’re good at—and people are vastly more productive under those circumstances. It’s quite likely that total employment would decrease, but productivity would increase so much that total output increased.

Above all, people would be happier, and that should have been our goal all along.

Asymmetric nominal rigidity, or why everything is always “on sale”

July 9, JDN 2457579

The next time you’re watching television or shopping, I want you to count the number of items that are listed as “on sale” versus the number that aren’t. (Also, be careful to distinguish labels like “Low Price!” and “Great Value!” that are dressed up like “on sale” labels but actually indicate the usual price.) While “on sale” is presented as though it’s something rare and special, in reality anywhere from a third to half of all products are on sale at any given time. At some retailers (such as Art Van Furniture and Jos. A. Bank clothing), literally almost everything is almost always on sale.

There is a very good explanation for this in terms of cognitive economics. It is a special case of a more general phenomenon of asymmetric nominal rigidity. Asymmetric nominal rigidity is the tendency of human beings to be highly resistant to (rigidity) changes in actual (nominal) dollar prices, but only in the direction that hurts them (asymmetric). Ultimately this is an expression of the far deeper phenomenon of loss aversion, where losses are felt much more than gains.

Usually we actually talk about downward nominal wage rigidity, which is often cited as a reason why depressions can get so bad. People are extremely resistant to having their wages cut, even if there is a perfectly good reason to do so, and even if the economy is under deflation so that their real wage is not actually falling. It doesn’t just feel unpleasant; it feels unjust. People feel betrayed when they see the numbers on their paycheck go down, and they are willing to bear substantial costs to retaliate against that injustice—typically, they quit or go on strike. This reduces spending, which then exacerbates the deflation, which requires more wage cuts—and down we go into the spiral of depression, unless the government intervenes with monetary and fiscal policy.

But what does this have to do with everything being on sale? Well, for every downward wage rigidity, there is an upward price rigidity. When things become more expensive, people stop buying them—even if they could still afford them, and often even if the price increase is quite small. Again, they feel in some sense betrayed by the rising price (though not to the same degree as they feel betrayed by falling wages, due to their closer relationship to their employer). Responses to price increases are about twice as strong as responses to price decreases, just as losses are felt about twice as much as gains.

Businesses have figured this out—in some ways faster than economists did—and use it to their advantage; and thus so many things are “on sale”.

Actually, “on sale” serves two functions, which can be distinguished according to their marketing strategies. Businesses like Jos. A. Bank where almost everything is on sale are primarily exploiting anchoring—they want people to think of the listed “retail price” as the default price, and then the “sale price” that everyone actually pays feels lower as a result. If they “drop” the price of something from $300 to $150 feels like the company is doing you a favor; whereas if they had just priced it at $150 to begin with, you wouldn’t get any warm fuzzy feelings from that. This works especially well for products that people don’t purchase very often and aren’t accustomed to comparing—which is why you see it in furniture stores and high-end clothing retailers, not in grocery stores and pharmacies.

But even when people are accustomed to shopping around and are familiar with what the price ordinarily would be, sales serve a second function, because of asymmetric nominal rigidity: They escape that feeling of betrayal that comes from raising prices.

Here’s how it works: Due to the thousand natural shocks that flesh is heir to, there will always be some uncertainty in the prices you will want to set in the future. Future prices may go up, they may go down; and people spend their lives trying to predict this sort of thing and rarely outperform chance. But if you just raise and lower your prices as the winds blow (as most neoclassical economists generally assume you will), you will alienate your customers. Just as a ratchet works by turning the bolt more in one direction than the other, this sort of roller-coaster pricing would attract a small number of customers with each price decrease, then repel a larger number with each increase, until after a few cycles of rise and fall you would run out of customers. This is the real source of price rigidities, not that silly nonsense about “menu costs”. Especially in the Information Age, it costs almost nothing to change the number on the label—but change it wrong and it may cost you the customer.

One response would simply be to set your price at a reasonable estimate of the long-term optimal average price, but this leaves a lot of money on the table, as some times it will be too low (your inventory sells out and you make less profit than you could have), and even worse, other times it will be too high (customers refuse to buy your product). If only there were a way to change prices without customers feeling so betrayed!

Well, it turns out, there is, and it’s called “on sale”. You have a new product that you want to sell. You start by setting the price of the product at about the highest price you would ever need to sell it in the foreseeable future. Then, unless right now happens to be a time where demand is high and prices should also be high, you immediately put it on sale, and have the marketing team drum up some excuse about wanting to draw attention to your exciting new product. You put a deadline on that sale, which may be explicit (“Ends July 30”) or vague (“For a Limited Time!” which is technically always true—you merely promise that your sale will not last until the heat death of the universe), but clearly indicates to customers that you are not promising to keep this price forever.

Then, when demand picks up and you want to raise the price, you can! All you have to do is end the sale, which if you left the deadline vague can be done whenever you like. Even if you set explicit deadlines (which will make customers even more comfortable with the changes, and also give them a sense of urgency that may lead to more impulse buying), you can just implement a new sale each time the last one runs out, varying the discount according to market conditions. Customers won’t retaliate, because they won’t feel betrayed; you said fair and square the sale wouldn’t last forever. They will still buy somewhat less, of course; that’s the Law of Demand. But they won’t overcompensate out of spite and outrage; they’ll just buy the amount that is their new optimal purchase amount at this new price.

Coupons are a lot like sales, but they’re actually even more devious; they allow for a perfectly legal form of price discrimination. Businesses know that only certain types of people clip coupons; roughly speaking, people who are either very poor or very frugal—either way, people who are very responsive to prices. Coupons allow them to set a lower price for those groups of people, while setting a higher price for other people whose demand is more inelastic. A similar phenomenon is going on with student and senior discounts; students and seniors get lower prices because they typically have less income than other adults (though why there is so rarely a youth discount, only a student discount, I’m actually not sure—controlling for demographics, students are in general richer than non-students).

Once you realize this is what’s happening, what should you do as a customer? Basically, try to ignore whether or not a label says “on sale”. Look at the actual number of the price, and try to compare it to prices you’ve paid in the past for that product, as well as of course how much value the product is worth to you. If indeed this is a particularly low price and the product is durable, you may well be wise to purchase more and stock up for the future. But you should try to train yourself to react the same way to “On sale, now $49.99” as you would to simply “$49.99”. (Making your reaction exactly the same is probably impossible, but the closer you can get the better off you are likely to be.) Always compare prices from multiple sources for any major purchase (Amazon makes this easier than ever before), and compare actual prices you would pay—with discounts, after taxes, including shipping. The rest is window dressing.

If you get coupons or special discounts, of course use them—but only if you were going to make the purchase anyway, or were just barely on the fence about it. Rarely is it actually rational for you to buy something you wouldn’t have bought just because it’s on sale for 50% off, let alone 10% off. It’s far more likely that you’d either want to buy it anyway, or still have no reason to buy it even at the new price. Businesses are of course hoping you’ll overcompensate for the discount and buy more than you would have otherwise. Foil their plans, and thereby make your life better and our economy more efficient.

Free trade, fair trade, or what?

JDN 2457271 EDT 11:34.

As I mentioned in an earlier post, almost all economists are opposed to protectionism. In a survey of 264 AEA economists, 87% opposed tariffs to protect US workers against foreign competition.

(By the way, 58% said they usually vote Democrat and only 23% said they usually vote Republican. Given that economists are overwhelmingly middle-age rich White males—only 12% of tenured faculty economists are women and the median income of economists is over $90,000—that’s saying something. Dare I suggest it’s saying that Democrat economic policy is usually better?)

There are a large number of published research papers showing large positive effects of free trade agreements, such as this paper, and this paper, and this paper, and this paper. It’s hard to find any good papers showing any significant negative effects. This is probably why the consensus is so strong; the empirical evidence is overwhelming.

Yet protectionism is very popular among the general public. The majority of both Democrat and Republican voters believe that free trade agreements have harmed the United States. For decades, protectionism has always been the politically popular answer.

To be fair, it’s actually possible to think that free trade harms the US but still support free trade; actually there are some economists who argue that free trade has harmed the US, but has benefited other countries like China and India so much more that it is worth it, making free trade an act of global altruism and good will (for the opposite view, here’s a pretty good article about how “free trade” in principle is often mercantilism in practice, and by no means altruistic). As Krugman talks about, there is some evidence that income inequality in the First World has been exacerbated by globalization—but it’s clearly not the primary reason for rising inequality.

What’s going on here? Are economists ignoring the negative impacts of free trade because it doesn’t fit their elegant mathematical models? Is the general public ignorant of how trade actually works? Does the way free trade works, or its interaction with human psychology, inherently obscure its benefits while emphasizing its harms?

Yes. All of the above.

One of the central mistakes of neoclassical economics is the tendency to over-aggregate. Instead of looking at the impact on individuals, it’s much easier to look at the impact on aggregated abstractions like trade flows and GDP. To some extent this is inevitable—there are simply too many people in the world to keep track of them all. But we need to be aware of what welose when we aggregate, and we need to test the robustness of our theories by applying different models of aggregation (such as comparing “how does this affect Americans” with “how does this affect the First World middle class”).

It is absolutely unambiguous that free trade increases trade flows and GDP, and for small countries these benefits can be mind-bogglingly huge. A key part of the amazing success story of economic development that is Korea is that they dramatically increased their openness to global trade.

The reason for this is absolutely fundamental to economics, and in grasping it in 1776 Adam Smith basically founded the field: Voluntary trade benefits both parties.

As most economists would put it today, comparative advantage leads to Pareto-improving gains from trade. Or as I’d tend to put it, more succinctly yet just as thoroughly based in modern game theory: Trade is nonzero-sum.

When you sell a product to someone, it is because the money they’re offering you is worth more to you than the product—and because the product is worth more to them than the money. You each lose something you value less and gain something you value more—so you are both better off.

This mutual benefit occurs whether you are individuals, corporations, or nations. It’s a fundamental principle of economics that underlies the operation of markets at every scale.

This is what I think most people don’t understand when they say they want to “stop sending jobs overseas”. If by that all you mean is ensuring that there aren’t incentives to offshore and outsource, that’s quite reasonable. Even some degree of incentive to keep businesses in the US might make sense, to avoid a race-to-the-bottom in global wages. But I get the sense that it is more than this, that people have a general notion that jobs are zero-sum and if we hire a million people in China that means a million people must lose their jobs in the US. This is not simply wrong, it is fundamentally wrong; it misses the entire point of economics. If there is one core principle that defines economics, I think it would be that the universe is nonzero-sum; gains for some can also be gains for others. There is not a fixed amount of stuff in the world that we distribute; we can make more stuff. Handled properly, a trade that results in a million people hired in China can mean an extra million people hired in the US.

Once you introduce a competitive market, things get more complicated, because there aren’t just winners—there are also losers. When you have competitors, someone can buy from them instead of you, and the two of them benefit, but you are harmed. By the standard methods of calculating benefits and harms (which admittedly leave much to be desired), we can show quite clearly that in general, on average, the benefits outweigh the harms.

But of course we don’t live “in general, on average”. Despite the overwhelming, unambiguous benefit to the economy as a whole, there is some evidence that free trade can produce a good deal of harm to specific individuals.

Suppose you live in the US and your job is to assemble iPads. You’re good at it, you like it, it pays pretty well. But now Apple says that they want to “reduce labor costs” (they are in fact doing nothing of the sort; to really reduce labor costs in a deep economic sense you’d have to make work easier, more productive, or more fun—the wage and the cost are fundamentally different things), so they outsource production to Foxconn in China, who pay wages 1/30 of what you were being paid.

The net result of this change to the economy as a whole is almost certainly positive—the price of iPads goes down, we all get to have iPads. (There’s a meme going around claiming that the price of an iPad would be almost $15,000 if it were made in the US; no, it would cost about $1000 even if our productivity were no higher and Apple could keep their current profit margin intact, both of which are clearly overestimates. But since it’s currently selling for about $500, that’s still a big difference.) Apple makes more profits, which is why they did it—and we do have to count that in our GDP. Most importantly, workers in China get employed in safe, high-skill jobs instead of working in coal mines, subsistence farming, or turning to drugs and prostitution. More stuff, more profits, better jobs for some of the world’s poorest workers. These are all good things, and overall they outweigh the harm of you losing your job.

Well, from a global perspective, anyway. I doubt they outweigh the harm from your perspective. You still lost a good job; you’re now unemployed, and may have skills so specific that they can’t be transferred to anything else. You’ll need to retrain, which means going back to school or else finding one of those rare far-sighted companies that actually trains their workers. Since the social welfare system in the US is such a quagmire of nonsensical programs, you may be ineligible for support, or eligible in theory and unable to actually get it in practice. (Recently I got a notice from Medicaid that I need to prove again that my income is sufficiently low. Apparently it’s because I got hired at a temporary web development gig, which paid me a whopping $700 over a few weeks—why, that’s almost the per-capita GDP of Ghana, so clearly I am a high-roller who doesn’t need help affording health insurance. I wonder how much they spend sending out these notices.)

If we had a basic income—I know I harp on this a lot, but seriously, it solves almost every economic problem you can think of—losing your job wouldn’t make you feel so desperate, and owning a share in GDP would mean that the rising tide actually would lift all boats. This might make free trade more popular.

But even with ideal policies (which we certainly do not have), the fact remains that human beings are loss-averse. We care more about losses than we do about gains. The pain you feel from losing $100 is about the same as the joy you feel from gaining $200. The pain you feel from losing your job is about twice as intense as the joy you feel from finding a new one.

Because of loss aversion, the constant churn of innovation and change, the “creative destruction” that Schumpeter considered the defining advantage of capitalism—well, it hurts. The constant change and uncertainty is painful, and we want to run away from it.

But the truth is, we can’t. There’s no way to stop the change in the global economy, and most of our attempts to insulate ourselves from it only end up hurting us more. This, I think, is the fundamental reason why protectionism is popular among the general public but not economists: The general public sees protectionism as a way of holding onto the past, while economists recognize that it is simply a way of damaging the future. That constant churning of people gaining and losing jobs isn’t a bug, it’s a feature—it’s the reason that capitalism is so efficient in the first place.

There are a few ways we can reduce the pain of this churning, but we need to focus on that—reducing the pain—rather than trying to stop the churning itself. We should provide social welfare programs that allow people to survive while they are unemployed. We should use active labor market policies to train new workers and match them with good jobs. We may even want to provide some sort of subsidy or incentive to companies that don’t outsource—a small one, to make sure they don’t do so needlessly, but not a large one, so they’ll still do it when it’s actually necessary.

But the one thing we must not do is stop creating jobs overseas. And yes, that is what we are doing, creating jobs. We are not sending jobs that already exist, we are creating new ones. In the short run we also destroy some jobs here, but if we do it right we can replace them—and usually we do okay.

If we stop creating jobs in India and China and around the world, millions of people will starve.

Yes, it is as stark as that. Millions of lives depend upon continued open trade. We in the United States are a manufacturing, technological and agricultural superpower—we could wall ourselves off from the world and only see a few percentage points shaved off of GDP. But a country like Nicaragua or Ghana or Vietnam doesn’t have that option; if they cut off trade, people start dying.

This is actually the main reason why our trade agreements are often so unfair; we are in by far the stronger bargaining position, so we can make them cut their tariffs on textiles even as we maintain our subsidies on agriculture. We are Mr. Bumble dishing out gruel and they are Oliver Twist begging for another bite.

We can’t afford to stop free trade. We can’t even afford to significantly slow it down. A global economy is the best hope we have for global peace and global prosperity.

That is not to say that we should leave trade completely unregulated; trade policy can and should be used to enforce human rights standards. That enormous asymmetry in bargaining power doesn’t have to be used to maximize profits; it can be used to advance human rights.

This is not as simple as saying we should never trade with nations that have bad human rights records, by the way. First of all that would require we cut off Saudi Arabia and China, which is totally unrealistic and would impoverish millions of people; second it doesn’t actually solve the problem. Instead we should use sanctions, tariffs, and trade agreements to provide incentives to improve human rights, rewarding governments that do and punishing governments that don’t. We could have a sliding tariff that decreases every time you show improvement in human rights standards. Think of it like behavioral reinforcement; reward good behavior and you’ll get more of it.

We do need to have sweatshops—but as Krugman has come around to realizing, we can make sweatshops safer. We can put pressure on other countries to treat their workers better, pay them more—and actually make the global economy more efficient, because right now their wages are held down below the efficient level by the power that corporations wield over them. We should not demand that they pay the same they would here in the First World—that’s totally unrealistic, given the difference in productivity—but we should demand that they pay what their workers actually deserve.

Similar incentives should apply to individual corporations, which these days are as powerful as some governments. For example, as part of a zero-tolerance program against forced labor, any company caught using or outsourcing to forced labor should have its profits garnished for damages and the executives who made the decision imprisoned. Sometimes #Scandinaviaisnotbetter; IKEA was involved in such outsourcing during the Cold War, and it is currently being litigated just how much they knew and what they could have done about it. If they knew and did nothing, some IKEA executive should be going to prison. If that seems extreme, let me remind you what they did: They used slaves.

My standard for penalizing human rights violations, whether by corporations or governments, is basically like this: Follow the decision-making up the chain of command, stopping only when the next-higher executive can clearly show to the preponderance of evidence that they were kept out of the loop. If no executive can provide sufficient evidence, the highest-ranking executive at the time the crime was committed will be held responsible. If you don’t want to be held responsible for crimes committed by people who work for you, it’s your responsibility to bring them to justice. Negligence in oversight will not be exonerating because you didn’t know; it will be incriminating because you should have. When your bank is caught laundering money for terrorists and drug lords, it isn’t enough to have your chief of compliance resign; he should be imprisoned—and if his superiors knew about it, so should they.

In fact maybe the focus should be on corporations, because we have the legal authority to do that. When dealing with other countries, there are United Nations rules and simply the de facto power of large trade flows and national standing armies. With Saudi Arabia or China, there’s a very real chance that they’ll simply tell us where we can shove it; but if we get that same kind of response from HSBC or Goldman Sachs (which, actually, we did), we can start taking out handcuffs (that, we did not do—but I think we should have).

We can also use consumer pressure to change the behavior of corporations, such as Fair Trade. There’s some debate about just how effective these things are, but the comparison that is often made between Fair Trade and tariffs is ridiculous; this is a change in consumer behavior, not a change in government policy. There is absolutely no loss of freedom. Choosing not to buy something does not constitute coercion against someone else. Maybe there are more efficient ways to spend money (like donating it directly to the best global development charities), but if you start going down that road you quickly turn into Peter Singer and start saying that wearing nicer shoes means you’re committing murder. By all means, let’s empirically study different methods of fighting poverty and focus on the ones that work best; but there’s a perverse smugness to criticisms of Fair Trade that says to me this isn’t actually about that at all. Instead, I think most people who criticize Fair Trade don’t support the idea of altruism at all—they’re far-right Randian libertarians who honestly believe that selfishness is the highest form of human morality. (It is in fact the second-lowest, according to Kohlberg.) Maybe it will turn out that Fair Trade is actually ineffective at fighting poverty, but it’s clear that an unregulated free market isn’t good at that either. Those aren’t the only options, and the best way to find out which methods work is to give them a try. Consumer pressure clearly can work in some cases, and it’s a low-cost zero-regulation solution. They say the road to Hell is paved with good intentions—but would you rather we have bad intentions instead?

By these two methods we could send a clear message to multinational corporations that if they want to do business in the US—and trust me, they do—they have to meet certain standards of human rights. This in turn will make those corporations put pressure on their suppliers, all the way down the supply chain, to uphold the standards lest they lose their contracts. With some companies upholding labor standards in Third World countries, others will be forced to, as workers refuse to work for companies that don’t. This could make life better for many millions of people.

But this whole plan only works on one condition: We need to have trade.

Prospect Theory: Why we buy insurance and lottery tickets

JDN 2457061 PST 14:18.

Today’s topic is called prospect theory. Prospect theory is basically what put cognitive economics on the map; it was the knock-down argument that Kahneman used to show that human beings are not completely rational in their economic decisions. It all goes back to a 1979 paper by Kahneman and Tversky that now has 34000 citations (yes, we’ve been having this argument for a rather long time now). In the 1990s it was refined into cumulative prospect theory, which is more mathematically precise but basically the same idea.

What was that argument? People buy both insurance and lottery tickets.

The “both” is very important. Buying insurance can definitely be rational—indeed, typically is. Buying lottery tickets could theoretically be rational, under very particular circumstances. But they cannot both be rational at the same time.

To see why, let’s talk some more about marginal utility of wealth. Recall that a dollar is not worth the same to everyone; to a billionaire a dollar is a rounding error, to most of us it is a bottle of Coke, but to a starving child in Ghana it could be life itself. We typically observe diminishing marginal utility of wealth—the more money you have, the less another dollar is worth to you.

If we sketch a graph of your utility versus wealth it would look something like this:


Notice how it increases as your wealth increases, but at a rapidly diminishing rate.

If you have diminishing marginal utility of wealth, you are what we call risk-averse. If you are risk-averse, you’ll (sometimes) want to buy insurance. Let’s suppose the units on that graph are tens of thousands of dollars. Suppose you currently have an income of $50,000. You are offered the chance to pay $10,000 a year to buy unemployment insurance, so that if you lose your job, instead of making $10,000 on welfare you’ll make $30,000 on unemployment. You think you have about a 20% chance of losing your job.

If you had constant marginal utility of wealth, this would not be a good deal for you. Your expected value of money would be reduced if you buy the insurance: Before you had an 80% chance of $50,000 and a 20% chance of $10,000 so your expected amount of money is $42,000. With the insurance you have an 80% chance of $40,000 and a 20% chance of $30,000 so your expected amount of money is $38,000. Why would you take such a deal? That’s like giving up $4,000 isn’t it?

Well, let’s look back at that utility graph. At $50,000 your utility is 1.80, uh… units, er… let’s say QALY. 1.80 QALY per year, meaning you live 80% better than the average human. Maybe, I guess? Doesn’t seem too far off. In any case, the units of measurement aren’t that important.


By buying insurance your effective income goes down to $40,000 per year, which lowers your utility to 1.70 QALY. That’s a fairly significant hit, but it’s not unbearable. If you lose your job (20% chance), you’ll fall down to $30,000 and have a utility of 1.55 QALY. Again, noticeable, but bearable. Your overall expected utility with insurance is therefore 1.67 QALY.

But what if you don’t buy insurance? Well then you have a 20% chance of taking a big hit and falling all the way down to $10,000 where your utility is only 1.00 QALY. Your expected utility is therefore only 1.64 QALY. You’re better off going with the insurance.

And this is how insurance companies make a profit (well; the legitimate way anyway; they also like to gouge people and deny cancer patients of course); on average, they make more from each customer than they pay out, but customers are still better off because they are protected against big losses. In this case, the insurance company profits $4,000 per customer per year, customers each get 30 milliQALY per year (about the same utility as an extra $2,000 more or less), everyone is happy.

But if this is your marginal utility of wealth—and it most likely is, approximately—then you would never want to buy a lottery ticket. Let’s suppose you actually have pretty good odds; it’s a 1 in 1 million chance of $1 million for a ticket that costs $2. This means that the state is going to take in about $2 million for every $1 million they pay out to a winner.

That’s about as good as your odds for a lottery are ever going to get; usually it’s more like a 1 in 400 million chance of $150 million for $1, which is an even bigger difference than it sounds, because $150 million is nowhere near 150 times as good as $1 million. It’s a bit better from the state’s perspective though, because they get to receive $400 million for every $150 million they pay out.

For your convenience I have zoomed out the graph so that you can see 100, which is an income of $1 million (which you’ll have this year if you win; to get it next year, you’ll have to play again). You’ll notice I did not have to zoom out the vertical axis, because 20 times as much money only ends up being about 2 times as much utility. I’ve marked with lines the utility of $50,000 (1.80, as we said before) versus $1 million (3.30).


What about the utility of $49,998 which is what you’ll have if you buy the ticket and lose? At this number of decimal places you can’t see the difference, so I’ll need to go out a few more. At $50,000 you have 1.80472 QALY. At $49,998 you have 1.80470 QALY. That $2 only costs you 0.00002 QALY, 20 microQALY. Not much, really; but of course not, it’s only $2.

How much does the 1 in 1 million chance of $1 million give you? Even less than that. Remember, the utility gain for going from $50,000 to $1 million is only 1.50 QALY. So you’re adding one one-millionth of that in expected utility, which is of course 1.5 microQALY, or 0.0000015 QALY.

That $2 may not seem like it’s worth much, but that 1 in 1 million chance of $1 million is worth less than one tenth as much. Again, I’ve tried to make these figures fairly realistic; they are by no means exact (I don’t actually think $49,998 corresponds to exactly 1.804699 QALY), but the order of magnitude difference is right. You gain about ten times as much utility from spending that $2 on something you want than you do on taking the chance at $1 million.

I said before that it is theoretically possible for you to have a utility function for which the lottery would be rational. For that you’d need to have increasing marginal utility of wealth, so that you could be what we call risk-seeking. Your utility function would have to look like this:


There’s no way marginal utility of wealth looks like that. This would be saying that it would hurt Bill Gates more to lose $1 than it would hurt a starving child in Ghana, which makes no sense at all. (It certainly would makes you wonder why he’s so willing to give it to them.) So frankly even if we didn’t buy insurance the fact that we buy lottery tickets would already look pretty irrational.

But in order for it to be rational to buy both lottery tickets and insurance, our utility function would have to be totally nonsensical. Maybe it could look like this or something; marginal utility decreases normally for awhile, and then suddenly starts going upward again for no apparent reason:


Clearly it does not actually look like that. Not only would this mean that Bill Gates is hurt more by losing $1 than the child in Ghana, we have this bizarre situation where the middle class are the people who have the lowest marginal utility of wealth in the world. Both the rich and the poor would need to have higher marginal utility of wealth than we do. This would mean that apparently yachts are just amazing and we have no idea. Riding a yacht is the pinnacle of human experience, a transcendence beyond our wildest imaginings; and riding a slightly bigger yacht is even more amazing and transcendent. Love and the joy of a life well-lived pale in comparison to the ecstasy of adding just one more layer of gold plate to your Ferrari collection.

Where increasing marginal utility is ridiculous, this is outright special pleading. You’re just making up bizarre utility functions that perfectly line up with whatever behavior people happen to have so that you can still call it rational. It’s like saying, “It could be perfectly rational! Maybe he enjoys banging his head against the wall!”

Kahneman and Tversky had a better idea. They realized that human beings aren’t so great at assessing probability, and furthermore tend not to think in terms of total amounts of wealth or annual income at all, but in terms of losses and gains. Through a series of clever experiments they showed that we are not so much risk-averse as we are loss-averse; we are actually willing to take more risk if it means that we will be able to avoid a loss.

In effect, we seem to be acting as if our utility function looks like this, where the zero no longer means “zero income”, it means “whatever we have right now“:


We tend to weight losses about twice as much as gains, and we tend to assume that losses also diminish in their marginal effect the same way that gains do. That is, we would only take a 50% chance to lose $1000 if it meant a 50% chance to gain $2000; but we’d take a 10% chance at losing $10,000 to save ourselves from a guaranteed loss of $1000.

This can explain why we buy insurance, provided that you frame it correctly. One of the things about prospect theory—and about human behavior in general—is that it exhibits framing effects: The answer we give depends upon the way you ask the question. That’s so totally obviously irrational it’s honestly hard to believe that we do it; but we do, and sometimes in really important situations. Doctors—doctors—will decide a moral dilemma differently based on whether you describe it as “saving 400 out of 600 patients” or “letting 200 out of 600 patients die”.

In this case, you need to frame insurance as the default option, and not buying insurance as an extra risk you are taking. Then saving money by not buying insurance is a gain, and therefore less important, while a higher risk of a bad outcome is a loss, and therefore important.

If you frame it the other way, with not buying insurance as the default option, then buying insurance is taking a loss by making insurance payments, only to get a gain if the insurance pays out. Suddenly the exact same insurance policy looks less attractive. This is a big part of why Obamacare has been effective but unpopular. It was set up as a fine—a loss—if you don’t buy insurance, rather than as a bonus—a gain—if you do buy insurance. The latter would be more expensive, but we could just make it up by taxing something else; and it might have made Obamacare more popular, because people would see the government as giving them something instead of taking something away. But the fine does a better job of framing insurance as the default option, so it motivates more people to actually buy insurance.

But even that would still not be enough to explain how it is rational to buy lottery tickets (Have I mentioned how it’s really not a good idea to buy lottery tickets?), because buying a ticket is a loss and winning the lottery is a gain. You actually have to get people to somehow frame not winning the lottery as a loss, making winning the default option despite the fact that it is absurdly unlikely. But I have definitely heard people say things like this: “Well if my numbers come up and I didn’t play that week, how would I feel then?” Pretty bad, I’ll grant you. But how much you wanna bet that never happens? (They’ll bet… the price of the ticket, apparently.)

In order for that to work, people either need to dramatically overestimate the probability of winning, or else ignore it entirely. Both of those things totally happen.

First, we overestimate the probability of rare events and underestimate the probability of common events—this is actually the part that makes it cumulative prospect theory instead of just regular prospect theory. If you make a graph of perceived probability versus actual probability, it looks like this:


We don’t make much distinction between 40% and 60%, even though that’s actually pretty big; but we make a huge distinction between 0% and 0.00001% even though that’s actually really tiny. I think we basically have categories in our heads: “Never, almost never, rarely, sometimes, often, usually, almost always, always.” Moving from 0% to 0.00001% is going from “never” to “almost never”, but going from 40% to 60% is still in “often”. (And that for some reason reminded me of “Well, hardly ever!”)

But that’s not even the worst of it. After all that work to explain how we can make sense of people’s behavior in terms of something like a utility function (albeit a distorted one), I think there’s often a simpler explanation still: Regret aversion under total neglect of probability.

Neglect of probability is self-explanatory: You totally ignore the probability. But what’s regret aversion, exactly? Unfortunately I’ve had trouble finding any good popular sources on the topic; it’s all scholarly stuff. (Maybe I’m more cutting-edge than I thought!)

The basic idea that is that you minimize regret, where regret can be formalized as the difference in utility between the outcome you got and the best outcome you could have gotten. In effect, it doesn’t matter whether something is likely or unlikely; you only care how bad it is.

This explains insurance and lottery tickets in one fell swoop: With insurance, you have the choice of risking a big loss (big regret) which you can avoid by paying a small amount (small regret). You take the small regret, and buy insurance. With lottery tickets, you have the chance of getting a large gain (big regret if you don’t) which you gain by paying a small amount (small regret).

This can also explain why a typical American’s fears go in the order terrorists > Ebola > sharks > > cars > cheeseburgers, while the actual risk of dying goes in almost the opposite order, cheeseburgers > cars > > terrorists > sharks > Ebola. (Terrorists are scarier than sharks and Ebola and actually do kill more Americans! Yay, we got something right! Other than that it is literally reversed.)

Dying from a terrorist attack would be horrible; in addition to your own death you have all the other likely deaths and injuries, and the sheer horror and evil of the terrorist attack itself. Dying from Ebola would be almost as bad, with gruesome and agonizing symptoms. Dying of a shark attack would be still pretty awful, as you get dismembered alive. But dying in a car accident isn’t so bad; it’s usually over pretty quick and the event seems tragic but ordinary. And dying of heart disease and diabetes from your cheeseburger overdose will happen slowly over many years, you’ll barely even notice it coming and probably die rapidly from a heart attack or comfortably in your sleep. (Wasn’t that a pleasant paragraph? But there’s really no other way to make the point.)

If we try to estimate the probability at all—and I don’t think most people even bother—it isn’t by rigorous scientific research; it’s usually by availability heuristic: How many examples can you think of in which that event happened? If you can think of a lot, you assume that it happens a lot.

And that might even be reasonable, if we still lived in hunter-gatherer tribes or small farming villages and the 150 or so people you knew were the only people you ever heard about. But now that we have live TV and the Internet, news can get to us from all around the world, and the news isn’t trying to give us an accurate assessment of risk, it’s trying to get our attention by talking about the biggest, scariest, most exciting things that are happening around the world. The amount of news attention an item receives is in fact in inverse proportion to the probability of its occurrence, because things are more exciting if they are rare and unusual. Which means that if we are estimating how likely something is based on how many times we heard about it on the news, our estimates are going to be almost exactly reversed from reality. Ironically it is the very fact that we have more information that makes our estimates less accurate, because of the way that information is presented.

It would be a pretty boring news channel that spent all day saying things like this: “82 people died in car accidents today, and 1657 people had fatal heart attacks, 11.8 million had migraines, and 127 million played the lottery and lost; in world news, 214 countries did not go to war, and 6,147 children starved to death in Africa…” This would, however, be vastly more informative.

In the meantime, here are a couple of counter-heuristics I recommend to you: Don’t think about losses and gains, think about where you are and where you might be. Don’t say, “I’ll gain $1,000”; say “I’ll raise my income this year to $41,000.” Definitely do not think in terms of the percentage price of things; think in terms of absolute amounts of money. Cheap expensive things, expensive cheap things is a motto of mine; go ahead and buy the $5 toothbrush instead of the $1, because that’s only $4. But be very hesitant to buy the $22,000 car instead of the $21,000, because that’s $1,000. If you need to estimate the probability of something, actually look it up; don’t try to guess based on what it feels like the probability should be. Make this unprecedented access to information work for you instead of against you. If you want to know how many people die in car accidents each year, you can literally ask Google and it will tell you that (I tried it—it’s 1.3 million worldwide). The fatality rate of a given disease versus the risk of its vaccine, the safety rating of a particular brand of car, the number of airplane crash deaths last month, the total number of terrorist attacks, the probability of becoming a university professor, the average functional lifespan of a new television—all these things and more await you at the click of a button. Even if you think you’re pretty sure, why not look it up anyway?

Perhaps then we can make prospect theory wrong by making ourselves more rational.