preference

How do we measure happiness?

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JDN 2457028 EST 20:33.

No, really, I’m asking. I strongly encourage my readers to offer in the comments any ideas they have about the measurement of happiness in the real world; this has been a stumbling block in one of my ongoing research projects.

In one sense the measurement of happiness—or more formally utility—is absolutely fundamental to economics; in another it’s something most economists are astonishingly afraid of even trying to do.

The basic question of economics has nothing to do with money, and is really only incidentally related to “scarce resources” or “the production of goods” (though many textbooks will define economics in this way—apparently implying that a post-scarcity economy is not an economy). The basic question of economics is really this: How do we make people happy?

This must always be the goal in any economic decision, and if we lose sight of that fact we can make some truly awful decisions. Other goals may work sometimes, but they inevitably fail: If you conceive of the goal as “maximize GDP”, then you’ll try to do any policy that will increase the amount of production, even if that production comes at the expense of stress, injury, disease, or pollution. (And doesn’t that sound awfully familiar, particularly here in the US? 40% of Americans report their jobs as “very stressful” or “extremely stressful”.) If you were to conceive of the goal as “maximize the amount of money”, you’d print money as fast as possible and end up with hyperinflation and total economic collapse ala Zimbabwe. If you were to conceive of the goal as “maximize human life”, you’d support methods of increasing population to the point where we had a hundred billion people whose lives were barely worth living. Even if you were to conceive of the goal as “save as many lives as possible”, you’d find yourself investing in whatever would extend lifespan even if it meant enormous pain and suffering—which is a major problem in end-of-life care around the world. No, there is one goal and one goal only: Maximize happiness.

I suppose technically it should be “maximize utility”, but those are in fact basically the same thing as long as “happiness” is broadly conceived as eudaimonia—the joy of a life well-lived—and not a narrow concept of just adding up pleasure and subtracting out pain. The goal is not to maximize the quantity of dopamine and endorphins in your brain; the goal is to achieve a world where people are safe from danger, free to express themselves, with friends and family who love them, who participate in a world that is just and peaceful. We do not want merely the illusion of these things—we want to actually have them. So let me be clear that this is what I mean when I say “maximize happiness”.

The challenge, therefore, is how we figure out if we are doing that. Things like money and GDP are easy to measure; but how do you measure happiness?
Early economists like Adam Smith and John Stuart Mill tried to deal with this question, and while they were not very successful I think they deserve credit for recognizing its importance and trying to resolve it. But sometime around the rise of modern neoclassical economics, economists gave up on the project and instead sought a narrower task, to measure preferences.

This is often called technically ordinal utility, as opposed to cardinal utility; but this terminology obscures the fundamental distinction. Cardinal utility is actual utility; ordinal utility is just preferences.

(The notion that cardinal utility is defined “up to a linear transformation” is really an eminently trivial observation, and it shows just how little physics the physics-envious economists really understand. All we’re talking about here is units of measurement—the same distance is 10.0 inches or 25.4 centimeters, so is distance only defined “up to a linear transformation”? It’s sometimes argued that there is no clear zero—like Fahrenheit and Celsius—but actually it’s pretty clear to me that there is: Zero utility is not existing. So there you go, now you have Kelvin.)

Preferences are a bit easier to measure than happiness, but not by as much as most economists seem to think. If you imagine a small number of options, you can just put them in order from most to least preferred and there you go; and we could imagine asking someone to do that, or—the technique of revealed preference—use the choices they make to infer their preferences by assuming that when given the choice of X and Y, choosing X means you prefer X to Y.

Like much of neoclassical theory, this sounds good in principle and utterly collapses when applied to the real world. Above all: How many options do you have? It’s not easy to say, but the number is definitely huge—and both of those facts pose serious problems for a theory of preferences.

The fact that it’s not easy to say means that we don’t have a well-defined set of choices; even if Y is theoretically on the table, people might not realize it, or they might not see that it’s better even though it actually is. Much of our cognitive effort in any decision is actually spent narrowing the decision space—when deciding who to date or where to go to college or even what groceries to buy, simply generating a list of viable options involves a great deal of effort and extremely complex computation. If you have a true utility function, you can satisfice—choosing the first option that is above a certain threshold—or engage in constrained optimization—choosing whether to continue searching or accept your current choice based on how good it is. Under preference theory, there is no such “how good it is” and no such thresholds. You either search forever or choose a cutoff arbitrarily.

Even if we could decide how many options there are in any given choice, in order for this to form a complete guide for human behavior we would need an enormous amount of information. Suppose there are 10 different items I could have or not have; then there are 10! = 3.6 million possible preference orderings. If there were 100 items, there would be 100! = 9e157 possible orderings. It won’t do simply to decide on each item whether I’d like to have it or not. Some things are complements: I prefer to have shoes, but I probably prefer to have $100 and no shoes at all rather than $50 and just a left shoe. Other things are substitutes: I generally prefer eating either a bowl of spaghetti or a pizza, rather than both at the same time. No, the combinations matter, and that means that we have an exponentially increasing decision space every time we add a new option. If there really is no more structure to preferences than this, we have an absurd computational task to make even the most basic decisions.

This is in fact most likely why we have happiness in the first place. Happiness did not emerge from a vacuum; it evolved by natural selection. Why make an organism have feelings? Why make it care about things? Wouldn’t it be easier to just hard-code a list of decisions it should make? No, on the contrary, it would be exponentially more complex. Utility exists precisely because it is more efficient for an organism to like or dislike things by certain amounts rather than trying to define arbitrary preference orderings. Adding a new item means assigning it an emotional value and then slotting it in, instead of comparing it to every single other possibility.

To illustrate this: I like Coke more than I like Pepsi. (Let the flame wars begin?) I also like getting massages more than I like being stabbed. (I imagine less controversy on this point.) But the difference in my mind between massages and stabbings is an awful lot larger than the difference between Coke and Pepsi. Yet according to preference theory (“ordinal utility”), that difference is not meaningful; instead I have to say that I prefer the pair “drink Pepsi and get a massage” to the pair “drink Coke and get stabbed”. There’s no such thing as “a little better” or “a lot worse”; there is only what I prefer over what I do not prefer, and since these can be assigned arbitrarily there is an impossible computational task before me to make even the most basic decisions.

Real utility also allows you to make decisions under risk, to decide when it’s worth taking a chance. Is a 50% chance of $100 worth giving up a guaranteed $50? Probably. Is a 50% chance of $10 million worth giving up a guaranteed $5 million? Not for me. Maybe for Bill Gates. How do I make that decision? It’s not about what I prefer—I do in fact prefer $10 million to $5 million. It’s about how much difference there is in terms of my real happiness—$5 million is almost as good as $10 million, but $100 is a lot better than $50. My marginal utility of wealth—as I discussed in my post on progressive taxation—is a lot steeper at $50 than it is at $5 million. There’s actually a way to use revealed preferences under risk to estimate true (“cardinal”) utility, developed by Von Neumann and Morgenstern. In fact they proved a remarkably strong theorem: If you don’t have a cardinal utility function that you’re maximizing, you can’t make rational decisions under risk. (In fact many of our risk decisions clearly aren’t rational, because we aren’t actually maximizing an expected utility; what we’re actually doing is something more like cumulative prospect theory, the leading cognitive economic theory of risk decisions. We overrespond to extreme but improbable events—like lightning strikes and terrorist attacks—and underrespond to moderate but probable events—like heart attacks and car crashes. We play the lottery but still buy health insurance. We fear Ebola—which has never killed a single American—but not influenza—which kills 10,000 Americans every year.)

A lot of economists would argue that it’s “unscientific”—Kenneth Arrow said “impossible”—to assign this sort of cardinal distance between our choices. But assigning distances between preferences is something we do all the time. Amazon.com lets us vote on a 5-star scale, and very few people send in error reports saying that cardinal utility is meaningless and only preference orderings exist. In 2000 I would have said “I like Gore best, Nader is almost as good, and Bush is pretty awful; but of course they’re all a lot better than the Fascist Party.” If we had simply been able to express those feelings on the 2000 ballot according to a range vote, either Nader would have won and the United States would now have a three-party system (and possibly a nationalized banking system!), or Gore would have won and we would be a decade ahead of where we currently are in preventing and mitigating global warming. Either one of these things would benefit millions of people.

This is extremely important because of another thing that Arrow said was “impossible”—namely, “Arrow’s Impossibility Theorem”. It should be called Arrow’s Range Voting Theorem, because simply by restricting preferences to a well-defined utility and allowing people to make range votes according to that utility, we can fulfill all the requirements that are supposedly “impossible”. The theorem doesn’t say—as it is commonly paraphrased—that there is no fair voting system; it says that range voting is the only fair voting system. A better claim is that there is no perfect voting system, which is true if you mean that there is no way to vote strategically that doesn’t accurately reflect your true beliefs. The Myerson-Satterthwaithe Theorem is then the proper theorem to use; if you could design a voting system that would force you to reveal your beliefs, you could design a market auction that would force you to reveal your optimal price. But the least expressive way to vote in a range vote is to pick your favorite and give them 100% while giving everyone else 0%—which is identical to our current plurality vote system. The worst-case scenario in range voting is our current system.

But the fact that utility exists and matters, unfortunately doesn’t tell us how to measure it. The current state-of-the-art in economics is what’s called “willingness-to-pay”, where we arrange (or observe) decisions people make involving money and try to assign dollar values to each of their choices. This is how you get disturbing calculations like “the lives lost due to air pollution are worth $10.2 billion.”

Why are these calculations disturbing? Because they have the whole thing backwards—people aren’t valuable because they are worth money; money is valuable because it helps people. It’s also really bizarre because it has to be adjusted for inflation. Finally—and this is the point that far too few people appreciate—the value of a dollar is not constant across people. Because different people have different marginal utilities of wealth, something that I would only be willing to pay $1000 for, Bill Gates might be willing to pay $1 million for—and a child in Africa might only be willing to pay $10, because that is all he has to spend. This makes the “willingness-to-pay” a basically meaningless concept independent of whose wealth we are spending.

Utility, on the other hand, might differ between people—but, at least in principle, it can still be added up between them on the same scale. The problem is that “in principle” part: How do we actually measure it?

So far, the best I’ve come up with is to borrow from public health policy and use the QALY, or quality-adjusted life year. By asking people macabre questions like “What is the maximum number of years of your life you would give up to not have a severe migraine every day?” (I’d say about 20—that’s where I feel ambivalent. At 10 I definitely would; at 30 I definitely wouldn’t.) or “What chance of total paralysis would you take in order to avoid being paralyzed from the waist down?” (I’d say about 20%.) we assign utility values: 80 years of migraines is worth giving up 20 years to avoid, so chronic migraine is a quality of life factor of 0.75. Total paralysis is 5 times as bad as paralysis from the waist down, so if waist-down paralysis is a quality of life factor of 0.90 then total paralysis is 0.50.

You can probably already see that there are lots of problems: What if people don’t agree? What if due to framing effects the same person gives different answers to slightly different phrasing? Some conditions will directly bias our judgments—depression being the obvious example. How many years of your life would you give up to not be depressed? Suicide means some people say all of them. How well do we really know our preferences on these sorts of decisions, given that most of them are decisions we will never have to make? It’s difficult enough to make the actual decisions in our lives, let alone hypothetical decisions we’ve never encountered.

Another problem is often suggested as well: How do we apply this methodology outside questions of health? Does it really make sense to ask you how many years of your life drinking Coke or driving your car is worth?
Well, actually… it better, because you make that sort of decision all the time. You drive instead of staying home, because you value where you’re going more than the risk of dying in a car accident. You drive instead of walking because getting there on time is worth that additional risk as well. You eat foods you know aren’t good for you because you think the taste is worth the cost. Indeed, most of us aren’t making most of these decisions very well—maybe you shouldn’t actually drive or drink that Coke. But in order to know that, we need to know how many years of your life a Coke is worth.

As a very rough estimate, I figure you can convert from willingness-to-pay to QALY by dividing by your annual consumption spending Say you spend annually about $20,000—pretty typical for a First World individual. Then $1 is worth about 50 microQALY, or about 26 quality-adjusted life-minutes. Now suppose you are in Third World poverty; your consumption might be only $200 a year, so $1 becomes worth 5 milliQALY, or 1.8 quality-adjusted life-days. The very richest individuals might spend as much as $10 million on consumption, so $1 to them is only worth 100 nanoQALY, or 3 quality-adjusted life-seconds.

That’s an extremely rough estimate, of course; it assumes you are in perfect health, all your time is equally valuable and all your purchasing decisions are optimized by purchasing at marginal utility. Don’t take it too literally; based on the above estimate, an hour to you is worth about $2.30, so it would be worth your while to work for even $3 an hour. Here’s a simple correction we should probably make: if only a third of your time is really usable for work, you should expect at least $6.90 an hour—and hey, that’s a little less than the US minimum wage. So I think we’re in the right order of magnitude, but the details have a long way to go.

So let’s hear it, readers: How do you think we can best measure happiness?

Pareto Efficiency: Why we need it—and why it’s not enough

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JDN 2456914 PDT 11:45.

I already briefly mentioned the concept in an earlier post, but Pareto-efficiency is so fundamental to both ethics and economics I decided I would spent some more time on explaining exactly what it’s about.

This is the core idea: A system is Pareto-efficient if you can’t make anyone better off without also making someone else worse off. It is Pareto-inefficient if the opposite is true, and you could improve someone’s situation without hurting anyone else.

Improving someone’s situation without harming anyone else is called a Pareto-improvement. A system is Pareto-efficient if and only if there are no possible Pareto-improvements.

Zero-sum games are always Pareto-efficient. If the game is about how we distribute the same $10 between two people, any dollar I get is a dollar you don’t get, so no matter what we do, we can’t make either of us better off without harming the other. You may have ideas about what the fair or right solution is—and I’ll get back to that shortly—but all possible distributions are Pareto-efficient.

Where Pareto-efficiency gets interesting is in nonzero-sum games. The most famous and most important such game is the so-called Prisoner’s Dilemma; I don’t like the standard story to set up the game, so I’m going to give you my own. Two corporations, Alphacomp and Betatech, make PCs. The computers they make are of basically the same quality and neither is a big brand name, so very few customers are going to choose on anything except price. Combining labor, materials, equipment and so on, each PC costs each company $300 to manufacture a new PC, and most customers are willing to buy a PC as long as it’s no more than $1000. Suppose there are 1000 customers buying. Now the question is, what price do they set? They would both make the most profit if they set the price at $1000, because customers would still buy and they’d make $700 on each unit, each making $350,000. But now suppose Alphacomp sets a price at $1000; Betatech could undercut them by making the price $999 and sell twice as many PCs, making $699,000. And then Alphacomp could respond by setting the price at $998, and so on. The only stable end result if they are both selfish profit-maximizers—the Nash equilibrium—is when the price they both set is $301, meaning each company only profits $1 per PC, making $1000. Indeed, this result is what we call in economics perfect competition. This is great for consumers, but not so great for the companies.

If you focus on the most important choice, $1000 versus $999—to collude or to compete—we can set up a table of how much each company would profit by making that choice (a payoff matrix or normal form game in game theory jargon).

A: $999 A: $1000
B: $999 A:$349k

B:$349k

 A:$0

B:$699k
B: $1000 A:$699k

B:$0

 A:$350k

B:$350k

Obviously the choice that makes both companies best-off is for both companies to make the price $1000; that is Pareto-efficient. But it’s also Pareto-efficient for Alphacomp to choose $999 and the other one to choose $1000, because then they sell twice as many computers. We have made someone worse off—Betatech—but it’s still Pareto-efficient because we couldn’t give Betatech back what they lost without taking some of what Alphacomp gained.

There’s only one option that’s not Pareto-efficient: If both companies charge $999, they could both have made more money if they’d charged $1000 instead. The problem is, that’s not the Nash equilibrium; the stable state is the one where they set the price lower.

This means that only case that isn’t Pareto-efficient is the one that the system will naturally trend toward if both compal selfish profit-maximizers. (And while most human beings are nothing like that, most corporations actually get pretty close. They aren’t infinite, but they’re huge; they aren’t identical, but they’re very similar; and they basically are psychopaths.)

In jargon, we say the Nash equilibrium of a Prisoner’s Dilemma is Pareto-inefficient. That one sentence is basically why John Nash was such a big deal; up until that point, everyone had assumed that if everyone acted in their own self-interest, the end result would have to be Pareto-efficient; Nash proved that this isn’t true at all. Everyone acting in their own self-interest can doom us all.

It’s not hard to see why Pareto-efficiency would be a good thing: if we can make someone better off without hurting anyone else, why wouldn’t we? What’s harder for most people—and even most economists—to understand is that just because an outcome is Pareto-efficient, that doesn’t mean it’s good.

I think this is easiest to see in zero-sum games, so let’s go back to my little game of distributing the same $10. Let’s say it’s all within my power to choose—this is called the ultimatum game. If I take $9 for myself and only give you $1, is that Pareto-efficient? It sure is; for me to give you any more, I’d have to lose some for myself. But is it fair? Obviously not! The fair option is for me to go fifty-fifty, $5 and $5; and maybe you’d forgive me if I went sixty-forty, $6 and $4. But if I take $9 and only offer you $1, you know you’re getting a raw deal.

Actually as the game is often played, you have the choice the say, “Forget it; if that’s your offer, we both get nothing.” In that case the game is nonzero-sum, and the choice you’ve just taken is not Pareto-efficient! Neoclassicists are typically baffled at the fact that you would turn down that free $1, paltry as it may be; but I’m not baffled at all, and I’d probably do the same thing in your place. You’re willing to pay that $1 to punish me for being so stingy. And indeed, if you allow this punishment option, guess what? People aren’t as stingy! If you play the game without the rejection option, people typically take about $7 and give about $3 (still fairer than the $9/$1, you may notice; most people aren’t psychopaths), but if you allow it, people typically take about $6 and give about $4. Now, these are pretty small sums of money, so it’s a fair question what people might do if $100,000 were on the table and they were offered $10,000. But that doesn’t mean people aren’t willing to stand up for fairness; it just means that they’re only willing to go so far. They’ll take a $1 hit to punish someone for being unfair, but that $10,000 hit is just too much. I suppose this means most of us do what Guess Who told us: “You can sell your soul, but don’t you sell it too cheap!”

Now, let’s move on to the more complicated—and more realistic—scenario of a nonzero-sum game. In fact, let’s make the “game” a real-world situation. Suppose Congress is debating a bill that would introduce a 70% marginal income tax on the top 1% to fund a basic income. (Please, can we debate that, instead of proposing a balanced-budget amendment that would cripple US fiscal policy indefinitely and lead to a permanent depression?)

This tax would raise about 14% of GDP in revenue, or about $2.4 trillion a year (yes, really). It would then provide, for every man, woman and child in America, a $7000 per year income, no questions asked. For a family of four, that would be $28,000, which is bound to make their lives better.

But of course it would also take a lot of money from the top 1%; Mitt Romney would only make $6 million a year instead of $20 million, and Bill Gates would have to settle for $2.4 billion a year instead of $8 billion. Since it’s the whole top 1%, it would also hurt a lot of people with more moderate high incomes, like your average neurosurgeon or Paul Krugman, who each make about $500,000 year. About $100,000 of that is above the cutoff for the top 1%, so they’d each have to pay about $70,000 more than they currently do in taxes; so if they were paying $175,000 they’re now paying $245,000. Once taking home $325,000, now only $255,000. (Probably not as big a difference as you thought, right? Most people do not seem to understand how marginal tax rates work, as evinced by “Joe the Plumber” who thought that if he made $250,001 he would be taxed at the top rate on the whole amount—no, just that last $1.)

You can even suppose that it would hurt the economy as a whole, though in fact there’s no evidence of that—we had tax rates like this in the 1960s and our economy did just fine. The basic income itself would inject so much spending into the economy that we might actually see more growth. But okay, for the sake of argument let’s suppose it also drops our per-capita GDP by 5%, from $53,000 to $50,300; that really doesn’t sound so bad, and any bigger drop than that is a totally unreasonable estimate based on prejudice rather than data. For the same tax rate might have to drop the basic income a bit too, say $6600 instead of $7000.

So, this is not a Pareto-improvement; we’re making some people better off, but others worse off. In fact, the way economists usually estimate Pareto-efficiency based on so-called “economic welfare”, they really just count up the total number of dollars and divide by the number of people and call it a day; so if we lose 5% in GDP they would register this as a Pareto-loss. (Yes, that’s a ridiculous way to do it for obvious reasons—$1 to Mitt Romney isn’t worth as much as it is to you and me—but it’s still how it’s usually done.)

But does that mean that it’s a bad idea? Not at all. In fact, if you assume that the real value—the utility—of a dollar decreases exponentially with each dollar you have, this policy could almost double the total happiness in US society. If you use a logarithm instead, it’s not quite as impressive; it’s only about a 20% improvement in total happiness—in other words, “only” making as much difference to the happiness of Americans from 2014 to 2015 as the entire period of economic growth from 1900 to 2000.

If right now you’re thinking, “Wow! Why aren’t we doing that?” that’s good, because I’ve been thinking the same thing for years. And maybe if we keep talking about it enough we can get people to start voting on it and actually make it happen.

But in order to make things like that happen, we must first get past the idea that Pareto-efficiency is the only thing that matters in moral decisions. And once again, that means overcoming the standard modes of thinking in neoclassical economics.

Something strange happened to economics in about 1950. Before that, economists from Marx to Smith to Keynes were always talking about differences in utility, marginal utility of wealth, how to maximize utility. But then economists stopped being comfortable talking about happiness, deciding (for reasons I still do not quite grasp) that it was “unscientific”, so they eschewed all discussion of the subject. Since we still needed to know why people choose what they do, a new framework was created revolving around “preferences”, which are a simple binary relation—you either prefer it or you don’t, you can’t like it “a lot more” or “a little more”—that is supposedly more measurable and therefore more “scientific”. But under this framework, there’s no way to say that giving a dollar to a homeless person makes a bigger difference to them than giving the same dollar to Mitt Romney, because a “bigger difference” is something you’ve defined out of existence. All you can say is that each would prefer to receive the dollar, and that both Mitt Romney and the homeless person would, given the choice, prefer to be Mitt Romney. While both of these things are true, it does seem to be kind of missing the point, doesn’t it?

There are stirrings of returning to actual talk about measuring actual (“cardinal”) utility, but still preferences (so-called “ordinal utility”) are the dominant framework. And in this framework, there’s really only one way to evaluate a situation as good or bad, and that’s Pareto-efficiency.

Actually, that’s not quite right; John Rawls cleverly came up with a way around this problem, by using the idea of “maximin”—maximize the minimum. Since each would prefer to be Romney, given the chance, we can say that the homeless person is worse off than Mitt Romney, and therefore say that it’s better to make the homeless person better off. We can’t say how much better, but at least we can say that it’s better, because we’re raising the floor instead of the ceiling. This is certainly a dramatic improvement, and on these grounds alone you can argue for the basic income—your floor is now explicitly set at the $6600 per year of the basic income.

But is that really all we can say? Think about how you make your own decisions; do you only speak in terms of strict preferences? I like Coke more than Pepsi; I like massages better than being stabbed. If preference theory is right, then there is no greater distance in the latter case than the former, because this whole notion of “distance” is unscientific. I guess we could expand the preference over groups of goods (baskets as they are generally called), and say that I prefer the set “drink Pepsi and get a massage” to the set “drink Coke and get stabbed”, which is certainly true. But do we really want to have to define that for every single possible combination of things that might happen to me? Suppose there are 1000 things that could happen to me at any given time, which is surely conservative. In that case there are 2^1000 = 10^300 possible combinations. If I were really just reading off a table of unrelated preference relations, there wouldn’t be room in my brain—or my planet—to store it, nor enough time in the history of the universe to read it. Even imposing rational constraints like transitivity doesn’t shrink the set anywhere near small enough—at best maybe now it’s 10^20, well done; now I theoretically could make one decision every billion years or so. At some point doesn’t it become a lot more parsimonious—dare I say, more scientific—to think that I am using some more organized measure than that? It certainly feels like I am; even if couldn’t exactly quantify it, I can definitely say that some differences in my happiness are large and others are small. The mild annoyance of drinking Pepsi instead of Coke will melt away in the massage, but no amount of Coke deliciousness is going to overcome the agony of being stabbed.

And indeed if you give people surveys and ask them how much they like things or how strongly they feel about things, they have no problem giving you answers out of 5 stars or on a scale from 1 to 10. Very few survey participants ever write in the comments box: “I was unable to take this survey because cardinal utility does not exist and I can only express binary preferences.” A few do write 1s and 10s on everything, but even those are fairly rare. This “cardinal utility” that supposedly doesn’t exist is the entire basis of the scoring system on Netflix and Amazon. In fact, if you use cardinal utility in voting, it is mathematically provable that you have the best possible voting system, which may have something to do with why Netflix and Amazon like it. (That’s another big “Why aren’t we doing this already?”)

If you can actually measure utility in this way, then there’s really not much reason to worry about Pareto-efficiency. If you just maximize utility, you’ll automatically get a Pareto-efficient result; but the converse is not true because there are plenty of Pareto-efficient scenarios that don’t maximize utility. Thinking back to our ultimatum game, all options are Pareto-efficient, but you can actually prove that the $5/$5 choice is the utility-maximizing one, if the two players have the same amount of wealth to start with. (Admittedly for those small amounts there isn’t much difference; but that’s also not too surprising, since $5 isn’t going to change anybody’s life.) And if they don’t—suppose I’m rich and you’re poor and we play the game—well, maybe I should give you more, precisely because we both know you need it more.

Perhaps even more significant, you can move from a Pareto-inefficient scenario to a Pareto-efficient one and make things worse in terms of utility. The scenario in which the top 1% are as wealthy as they can possibly be and the rest of us live on scraps may in fact be Pareto-efficient; but that doesn’t mean any of us should be interested in moving toward it (though sadly, we kind of are). If you’re only measuring in terms of Pareto-efficiency, your attempts at improvement can actually make things worse. It’s not that the concept is totally wrong; Pareto-efficiency is, other things equal, good; but other things are never equal.

So that’s Pareto-efficiency—and why you really shouldn’t care about it that much.