Equilibrium Behavior (Experimental) is subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try. It sits in the Systems dimension (SYS) of the Human Behavior Taxonomy™ as element HBT-SYS-0012, within the Markets family. The core principle: subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.
Plain-English Definition
Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.
Feynman Explanation
Markets are rational eventually. Round one is a mess.
Core Principle
Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.
Mechanisms
Pending editorial review.
Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Launching pricing, new comp plans, or new marketplace rules.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Markets are rational eventually. Round one is a mess.
Examples
- Camerer & Loewenstein: 'equilibrium' analyses use last-period data, not initial play.
- Launching pricing, new comp plans, or new marketplace rules.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
Executives usually notice this element only after it has cost something. By then it looks like a one-off. It is not. The mechanism underneath it is straightforward: subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try. You can recognize it in the field by its signature: markets are rational eventually. Round one is a mess. Every element in the Systems dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, launching pricing, new comp plans, or new marketplace rules. It is amplified whenever launching pricing, new comp plans, or new marketplace rules. Inside organizations that shows up as launching pricing, new comp plans, or new marketplace rules. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to plan for the learning curve. Don't judge a mechanism on its first cohort. The leverage is not in explaining the behavior to people. It is in changing what the behavior earns.
Famous Experiments
Pending editorial review.
Design Principles
- Plan for the learning curve. Don't judge a mechanism on its first cohort.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Plan for the learning curve. Don't judge a mechanism on its first cohort.
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Systems maintain stability by self-regulating around a setpoint.
A state where no player benefits from changing strategy unilaterally.
A behavioral relaxation of Nash: players choose better strategies more often, but not always — errors are smooth, not binary.
Systems that gain from disorder.
Approach motivation — pursuit of rewards and goals.
Avoidance motivation — sensitivity to punishment, uncertainty, and threat.
Map reinforcing (R) and balancing (B) feedback loops between variables to see system behavior.
A system with many interacting parts that learn and adapt.
Many interacting parts producing emergent behavior nobody designed.
Single-loop fixes the action. Double-loop questions the goal or model that produced it.
System 1 is fast, automatic, intuitive; System 2 is slow, effortful, deliberate.
Interdependent network of actors evolving together.
Where Equilibrium Behavior (Experimental) is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- EssayPolicy Is Incentive Design
System-level payoff structures.
- Field guidePublic sector incentives
Budget rules, election cycles, blame avoidance.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
- ReferenceThe incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
Questions about Equilibrium Behavior (Experimental)
- What is Equilibrium Behavior (Experimental)?
- Equilibrium Behavior (Experimental) is subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try. It sits in the Systems dimension (SYS) of the Human Behavior Taxonomy™ as element HBT-SYS-0012, within the Markets family. The core principle: subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of Equilibrium Behavior (Experimental)?
- Launching pricing, new comp plans, or new marketplace rules. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-SYS-0012).
- How is Equilibrium Behavior (Experimental) exploited?
- Launching pricing, new comp plans, or new marketplace rules.
- How do you design around Equilibrium Behavior (Experimental)?
- Plan for the learning curve. Don't judge a mechanism on its first cohort.
- Which behavioral dimension does Equilibrium Behavior (Experimental) belong to?
- Equilibrium Behavior (Experimental) is classified in the Systems dimension (SYS) of the Human Behavior Taxonomy™, family "Markets", class "Mental Model". Its permanent identifier is HBT-SYS-0012 and its evidence grade is B.