Pareto efficiency
Based on Wikipedia: Pareto efficiency
The Economist Who Gave Us Permission to Stop Optimizing
Imagine you're splitting a pizza with a friend. You both want more slices, but there are only eight. At some point, giving you another slice means taking one from your friend. You've hit a wall—not because the pizza is perfect, but because any change that helps one of you necessarily hurts the other.
This simple observation—that sometimes you just can't make things better for everyone simultaneously—turns out to be one of the most powerful ideas in economics. It's called Pareto efficiency, named after Vilfredo Pareto, an Italian engineer turned economist who worked in the late nineteenth and early twentieth centuries.
The concept is deceptively simple, almost obvious once you hear it. Yet it took until 1896 for someone to formalize it, and the implications have rippled through economics, game theory, engineering, and even biology ever since.
What Pareto Efficiency Actually Means
Here's the core idea: a situation is Pareto efficient when you cannot make anyone better off without making someone else worse off. That's it. No complicated math required to grasp the essence.
The flip side is called a Pareto improvement—any change that makes at least one person better off while making nobody worse off. If such improvements exist, you're not yet at Pareto efficiency. Once you've made all possible Pareto improvements, you've arrived at what economists call a Pareto optimal state.
Now here's where it gets interesting, and where Pareto himself would later admit to a naming problem.
He originally called this concept "optimal," but that word suggests there's a single best outcome. There isn't. Pareto efficiency doesn't point to one ideal arrangement—it identifies a whole frontier of arrangements that are efficient in this specific sense. Think of it less as finding the perfect answer and more as ruling out the clearly wasteful ones.
A World of Efficient Outcomes, Not a Single Best One
Consider two ways to divide that eight-slice pizza. In scenario one, you get all eight slices and your friend gets none. In scenario two, your friend gets all eight and you get none. Both of these are Pareto efficient! In either case, giving one person more means taking from the other.
This might seem absurd. How can a completely one-sided division be considered "efficient"?
The answer reveals Pareto efficiency's deliberate limitation: it says nothing about fairness. It only measures whether resources are being wasted in a very specific sense—whether there are free gains left on the table that everyone would accept.
This is actually the concept's greatest strength and its most important constraint. By separating efficiency from equity, Pareto gave economists a tool that doesn't require them to make moral judgments about whose preferences matter more. It's a minimal criterion, a necessary condition for a good outcome but definitely not a sufficient one.
The Unanimity Principle
In social choice theory—the branch of economics that studies how groups make decisions—Pareto efficiency goes by another name: the unanimity principle. If every single person in a society prefers option A over option B (or at least finds them equally acceptable), then society as a whole should prefer A over B.
This sounds utterly uncontroversial. Of course if literally everyone agrees something is better, we should do it.
Yet even this mild requirement creates interesting constraints on how voting systems and decision-making processes can work. Any reasonable collective choice mechanism should at minimum satisfy unanimity—if it produces outcomes that everyone would reject in favor of some alternative, something has gone wrong.
Where Markets Enter the Picture
In 1954, economists Kenneth Arrow and Gérard Debreu proved something remarkable. Under certain conditions, competitive markets automatically produce Pareto efficient outcomes. This became known as the first welfare theorem, and it gave theoretical support to the idea that free markets, left to themselves, don't leave money on the table.
But those conditions matter enormously.
The theorem assumes that markets exist for every possible good, that there are no externalities (costs or benefits that fall on people outside a transaction), that competition is perfect, and that everyone has complete information about everything. In the real world, these assumptions never fully hold.
When information is incomplete—which is always—the Greenwald-Stiglitz theorem tells us outcomes will generally be Pareto inefficient. There will be improvements available that, if people only knew about them, everyone would accept. Joseph Stiglitz won a Nobel Prize partly for this insight.
There's also a second welfare theorem, which runs in reverse: any Pareto efficient outcome can be achieved through markets, given the right initial distribution of resources. In plain English, if you don't like how the market divides the pie, you can redistribute wealth first, then let markets work, and still end up at efficiency. The theorems together suggest that efficiency and distribution are separable problems—a claim that remains contested in practice.
Beyond Economics: When You Can't Have It All
Engineers face Pareto efficiency constantly, though they usually call it something else: tradeoffs.
Imagine designing a car. You want it to be fast, fuel-efficient, spacious, safe, and cheap. These goals conflict. Making it faster often means burning more fuel. Making it safer often means adding weight, which hurts both speed and efficiency. Making it spacious affects aerodynamics.
At some point, you reach a design where improving any single attribute requires sacrificing another. You've hit the Pareto frontier. Every car along this frontier represents a different balance of priorities—sporty versus practical, economical versus luxurious—but none of them is simply "better" than the others in all dimensions.
Engineers call this multi-objective optimization. The Pareto frontier shows you all the non-dominated solutions—designs where you can't improve one goal without hurting another. From there, choosing requires human judgment about which tradeoffs matter most.
Biologists have borrowed the concept too. Evolution often involves tradeoffs between competing survival advantages. A peacock's elaborate tail helps attract mates but makes escape from predators harder. Many biological "designs" sit on Pareto frontiers, representing different viable strategies for survival.
Zero-Sum Games and the Efficiency of Conflict
Here's a curious fact: in zero-sum games—situations where one person's gain exactly equals another's loss—every single outcome is Pareto efficient.
Think about chess. For every possible game state, making white's position better necessarily makes black's position worse. There's no way to help one player without hurting the other. This means every position, even one where white has overwhelming advantage, is technically Pareto efficient.
This highlights an important point. Pareto efficiency doesn't mean things are good or fair or desirable. It just means the particular kind of waste it measures—unexploited mutual gains—has been eliminated. In pure competition, there never were any mutual gains to begin with.
Strong Versus Weak Efficiency
Economists distinguish between two versions of the concept. Regular Pareto efficiency says you can't make anyone better off without making someone worse off. Weak Pareto efficiency is more permissive: it only rules out situations where you could make everyone strictly better off.
The difference matters at the margins. A state could be weakly Pareto efficient while still allowing improvements that help some people and leave others exactly the same. It just can't allow improvements that help literally everyone simultaneously.
In practice, most discussions focus on the stronger version, but the weak version appears in formal proofs and technical economics.
The Limits of a Powerful Idea
Pareto efficiency has critics, and their objections reveal something important about what the concept does and doesn't accomplish.
The most common criticism: it's too weak. A society where one person owns everything and everyone else starves can be Pareto efficient. You can't redistribute wealth without hurting the rich person, so by this criterion, the situation is "efficient." This shows that efficiency, in the Pareto sense, isn't the same as justice or welfare maximization.
Economists have developed alternatives. Kaldor-Hicks efficiency, for instance, asks whether the winners from a change could in principle compensate the losers (even if they don't actually do so). This allows for changes that Pareto efficiency would reject, because it weighs total gains against total losses.
Another limitation: Pareto efficiency can conflict with other values we care about. Sometimes it's worth making one person slightly worse off to make many others much better off. The Pareto criterion can't capture this—it gives every person's welfare an absolute veto over changes that affect them negatively.
Why It Still Matters
Despite these limitations, Pareto efficiency remains foundational in economic thinking. Here's why.
First, it's a genuinely useful sanity check. If a proposed policy makes some people worse off and nobody better off, something is clearly wrong. Pareto efficiency rules out the obviously bad.
Second, the concept of the Pareto frontier helps structure complex decisions. Even when you can't optimize everything simultaneously, knowing the shape of the tradeoffs helps you make informed choices.
Third, and perhaps most importantly, the welfare theorems connecting markets and Pareto efficiency provide a benchmark for thinking about when markets work well and when they fail. The assumptions required for the theorems to hold—perfect information, no externalities, complete markets—become a checklist of ways real markets can go wrong.
When markets fail to produce efficient outcomes, economists know to look for missing markets (like carbon pricing for pollution), information problems (like adverse selection in insurance), or externalities (like neighbors affected by a factory's noise). The Pareto framework helps diagnose the disease, even when it can't prescribe the cure.
Pareto the Person
Vilfredo Pareto lived from 1848 to 1923. He trained as an engineer in Italy, wrote a thesis on the equilibrium of elastic solids, and worked in the railway industry before turning to economics in his forties.
He's remembered for several contributions beyond efficiency. The Pareto distribution describes how wealth tends to concentrate—roughly 80% of effects often come from 20% of causes, though the exact ratio varies. This "Pareto principle" or "80/20 rule" now appears everywhere from business management to software engineering.
Late in life, Pareto turned to sociology, writing about elites and their circulation through society. He grew increasingly conservative and some of his political ideas were later appropriated by Italian fascists, though Pareto himself died before Mussolini consolidated power.
His legacy in economics, however, remains untainted: a precise concept that helps us think clearly about when things can get better for everyone and when painful tradeoffs become unavoidable.
The Thanksgiving Connection
What does any of this have to do with giving thanks for price theory?
Prices are information. They tell producers what consumers want and tell consumers what things actually cost to make. When prices work well—when markets approximate those idealized conditions from the welfare theorems—they coordinate millions of independent decisions into something resembling Pareto efficiency.
Nobody planned for your local grocery store to have turkeys available in November. No central authority calculated how many cranberries to grow this year. Prices did the work, signaling to farmers and distributors and retailers what was needed, where, and when.
This coordination is genuinely remarkable. It happens despite no one being in charge, despite each participant pursuing their own interests, despite the staggering complexity of modern supply chains. Pareto efficiency provides the theoretical framework for understanding why this works when it does—and what goes wrong when it doesn't.
So perhaps there's reason to be grateful for both: the prices that coordinate our abundance, and the economist who gave us the tools to understand why.