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Incentives and Information Asymmetry

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Incentives and Information Asymmetry

The Freakonomics project — Steven Levitt and Stephen Dubner’s systematic application of economic reasoning to unexpected domains — rests on two foundational claims: that incentives are the primary driver of human behavior, and that the most consequential incentives are often hidden, misaligned, or invisible to the people they govern. These two insights, combined with the concept of information asymmetry (the fact that one party in a transaction often knows more than the other), explain a wide range of apparently puzzling human behavior.

The Primacy of Incentives

“Incentives are the cornerstone of modern life. And understanding them — or, often, ferreting them out — is the key to solving just about any riddle, from violent crime to sports cheating to online dating.” — Levitt and Dubner, Freakonomics

“Economics is, at root, the study of incentives: how people get what they want, or need, especially when other people want or need the same thing.” — Levitt and Dubner, Freakonomics

“An incentive is a bullet, a lever, a key: an often tiny object with astonishing power to change a situation.” — Levitt and Dubner, Freakonomics

Levitt and Dubner identify three categories of incentives: economic (financial rewards and penalties), social (the desire for approval or fear of shame), and moral (the internal sense of right and wrong). Real-world incentive systems almost always blend all three, and interventions that change one dimension frequently produce unexpected effects on the others.

The daycare center example illustrates this cross-contamination: when a daycare imposed a small financial penalty for late pickups, the rate of late pickups increased. Why? The fine converted a moral incentive (guilt at inconveniencing the teacher) into a transactional one (a small fee for extended service). The parents could now purchase relief from guilt for a few dollars — and the transaction cost signal was small enough to imply the inconvenience wasn’t serious.

“It substituted an economic incentive (the $3 penalty) for a moral incentive (the guilt that parents were supposed to feel when they came late). For just a few dollars each day, parents could buy off their guilt.” — Levitt and Dubner, Freakonomics

Information Asymmetry: The Expert’s Advantage

When one party to a transaction knows substantially more than the other, the party with less information is systematically vulnerable. Levitt and Dubner call this information asymmetry:

“It is common for one party to a transaction to have better information than another party. In the parlance of economists, such a case is known as an information asymmetry. We accept as a verity of capitalism that someone (usually an expert) knows more than someone else (usually a consumer).” — Levitt and Dubner, Freakonomics

The expert’s advantage is not merely knowledge but the leverage of fear that knowledge creates:

“Armed with information, experts can exert a gigantic, if unspoken, leverage: fear.” — Levitt and Dubner, Freakonomics

“If you were to assume that many experts use their information to your detriment, you’d be right. Experts depend on the fact that you don’t have the information they do. Or that you are so befuddled by the complexity of their operation that you wouldn’t know what to do with the information if you had it.” — Levitt and Dubner, Freakonomics

The real estate agent example is instructive: when an agent sells their own home, they leave it on the market significantly longer and achieve a higher price than when selling a client’s home. The incentives diverge — a faster sale at a slightly lower price earns the agent nearly the same commission while freeing them for the next transaction. This is the principal-agent problem in practice: the agent optimizes for their own incentives, which are not perfectly aligned with the principal’s (the seller’s).

Conventional Wisdom as a Lagging Indicator

One of the structural claims of Freakonomics is that conventional wisdom is systematically wrong:

“The conventional wisdom is often wrong.” — Levitt and Dubner, Freakonomics

“Dramatic effects often have distant, even subtle, causes.” — Levitt and Dubner, Freakonomics

The clearest illustration is the crime drop of the 1990s. Conventional wisdom attributed it to better policing, the economic boom, demographic shifts, or gun control. Levitt’s analysis pointed to a different cause: the legalization of abortion in 1973, which reduced the number of children born into high-risk circumstances — precisely the population that would have reached criminal prime in the early 1990s. This is a genuinely counterintuitive, politically uncomfortable, and empirically well-supported conclusion that no conventional wisdom frameworks predicted.

The lesson: the most consequential causes are often non-obvious, distant in time, and uncomfortable to acknowledge.

Morality vs. Economics: Two Descriptions of Reality

“Morality, it could be argued, represents the way that people would like the world to work — whereas economics represents how it actually does work.” — Levitt and Dubner, Freakonomics

This distinction is not an argument for amorality. It is a methodological claim: if you want to understand behavior, look at the incentive structure, not the stated intentions. People behave according to what their incentives make rational, regardless of what moral frameworks they publicly endorse. This is why stated organizational values often diverge dramatically from actual behavior — the incentives point elsewhere.

Ravikant makes the same observation in a specific context — the principal-agent problem in business:

“Julius Caesar famously said, ‘If you want it done, then go. And if not, then send.’ What he meant was, if you want it done right, then you have to go yourself and do it. When you are the principal, then you are the owner — you care, and you will do a great job. When you are the agent and you are doing it on somebody else’s behalf, you can do a bad job. You just don’t care. You optimize for yourself rather than for the principal’s assets.” — Naval Ravikant, The Almanack of Naval Ravikant

This is the economic foundation for why ownership outperforms employment in wealth generation: owners are principals whose incentives are aligned with outcomes. Employees are agents whose incentives (hourly pay, job security, social approval from peers) are at best partially aligned and often diverge significantly.

Douglas Hubbard: Information Value and Decision Quality

Hubbard’s How to Measure Anything extends the information asymmetry insight into a decision-making framework: the value of any measurement is its ability to reduce uncertainty in a consequential decision.

“Information reduces uncertainty about decisions that have economic consequences.” — Douglas Hubbard, How to Measure Anything

“If the outcome of a decision in question is highly uncertain and has significant consequences, then measurements that reduce uncertainty about it have a high value.” — Douglas Hubbard, How to Measure Anything

The corollary: measurement should be governed by the cost of being wrong, not by tradition, convenience, or the availability of existing measurement tools. Organizations systematically measure what they can easily measure rather than what actually matters — a form of institutional information asymmetry where decision-makers are systematically uninformed about the variables that most affect outcomes.

Practical Applications

  1. Always ask: what are the actual incentives? In any transaction involving an expert or agent, identify what they are paid for and how their compensation aligns or conflicts with your interests. This is especially critical in financial advising (brokers vs. fiduciaries), healthcare (procedure counts vs. outcomes), and real estate.

  2. Seek out where information asymmetry works against you. Anywhere expertise is concentrated and difficult to verify, you are likely being charged a premium for information the expert has and you don’t. The Internet has reduced — but not eliminated — many traditional information asymmetries.

  3. Look for distant causes. Dramatic effects (crime rates, business failures, market movements) typically have causes that are non-obvious, temporally distant, and not visible in the immediate situation. Resist the temptation to accept the nearest plausible cause.

  4. Understand what incentives your own systems create. Any organizational policy, compensation structure, or measurement system creates incentives. Understanding what those incentives actually produce (versus what the system intends to produce) is the beginning of fixing the gaps.

Incentive Reductionism

Levitt and Dubner’s framework is powerful but sometimes overstated. Not all behavior is reducible to incentives — moral agency, genuine altruism, and intrinsic motivation exist and have documented effects on behavior. The claim is that incentives are the most reliable and systematic predictor, not that they are the only force in human behavior.

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