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Hall of Shoulders

Behavioral Economics

Amos Tversky

Amos Tversky is known for Heuristics and biases, framing, prospect theory. **Built:** 2026-06-14 Amos Tversky, working with Daniel Kahneman, dismantled the assumption that human beings are intuitive statisticians and reframed decision making as a description-dependent, reference-dependent, heuristic process. His work is the empirical backbone of behavioral economics. This dossier applies his frameworks to contemporary space challenges: space traffic management and conjunction decisions, orbital-debris and launch-cadence governance, space situational awareness (SSA/SDA) expert judgment, reentry and human-spaceflight risk, and the economics of the orbital commons.

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Review Lens

Adversarial questions for candidates

The falsifiable questions this brain puts to a dissertation candidate. They seed the pre-Conclave initial review whenever a candidate's topic matches the Behavioral Economics lens.

  1. 1

    Description-invariance test. "You report a risk metric (Pc, expected casualties, P(loss of crew)). Re-state your central decision in at least two logically equivalent frames, one gain-framed, one loss-framed. Does your recommended action change? If it does, what makes your chosen frame the normatively privileged one rather than an artifact of presentation?

  2. 2

    Base-rate / reference-class challenge. "Your probability or cost-schedule estimate rests on an inside-view model. What is the empirical base rate from the reference class of comparable cases, and how far does your estimate deviate from it? If you have no base rate, on what is your number's calibration grounded?

  3. 3

    Availability audit. "Is the salience of your motivating case (a recent reentry, a publicized conjunction, a single fragmentation) doing work in your argument that the actuarial frequency does not support? Show that your conclusion survives when the vivid instance is removed.

  4. 4

    Reference-point and loss-aversion falsification. "Your governance/incentive proposal assumes actors will behave a certain way. State the reference point you are implicitly assigning them. Predict how compliance changes if mitigation is framed as a sure loss versus as a baseline cost, and specify the observation that would falsify your behavioral assumption.

  5. 5

    Expert-overconfidence stress test. "Where your analysis depends on expert probability judgment under sparse data, what evidence do you have that those experts are calibrated? Would a structured, calibration-weighted elicitation change your inputs, and have you tested sensitivity to that?

Core Concepts & Space Translation

Heuristics and biases

People assess probability and frequency using a small set of mental shortcuts: **representativeness** (judging by similarity to a stereotype, ignoring base rates and sample size), **availability** (judging by how easily instances come to mind), and **anchoring and adjustment** (starting from a salient value and adjusting too little). Each is usually serviceable but produces severe, systematic, and predictable errors that statistical training does not erase. Key works: Tversky & Kahneman, "Judgment under Uncertainty: Heuristics and Biases," *Science* (1974), 10.1126/science.185.4157.1124; "Availability," *Cognitive Psychology* (1973), 10.1016/0010-0285(73)90033-9.

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.

Prospect theory

A descriptive theory of choice under risk replacing expected-utility theory. Value is defined over **gains and losses relative to a reference point**, not final wealth; the value function is **concave for gains, convex for losses, and steeper for losses** (loss aversion, ~2:1). Probabilities enter through a nonlinear **decision-weighting** function that overweights small probabilities and underweights moderate-to-large ones, yielding the certainty and possibility effects. Key work: Kahneman & Tversky, "Prospect Theory: An Analysis of Decision under Risk," *Econometrica* (1979), 10.2307/1914185.

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.

Framing and description-invariance failure

Logically equivalent descriptions of the same problem produce systematic, predictable preference reversals. Rational choice assumes description-invariance; Tversky showed it is descriptively false (the Asian-disease problem: "lives saved" framing → risk aversion; "lives lost" framing → risk seeking, for identical outcomes). Key work: Tversky & Kahneman, "The Framing of Decisions and the Psychology of Choice," *Science* (1981), 10.1126/science.7455683.

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.

Reference dependence, loss aversion, and the endowment effect in riskless choice

Loss aversion is not confined to gambles. Because carriers of value are gains and losses from a reference point, ownership and the status quo become reference points, producing the **endowment effect** and **status-quo bias** even with no probabilities involved. Key work: Tversky & Kahneman, "Loss Aversion in Riskless Choice: A Reference-Dependent Model," *QJE* (1991), 10.2307/2937956.

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.

The conjunction fallacy and extensional reasoning

People judge a conjunction (Linda is a bank teller *and* a feminist) as more probable than one of its constituents (Linda is a bank teller) when the conjunction is more representative, violating the most basic law of probability. This exposes that intuitive probability tracks similarity and coherence, not set inclusion. Key work: Tversky & Kahneman, "Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment," *Psychological Review* (1983) (companion to the 1974 program).

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.

Calibration and the limits/remedies of expert judgment

Tversky's program implies experts are not immune; overconfidence and poor calibration are pervasive. The corrective is structural: base-rate discipline, the **outside view** (reference-class forecasting), feedback, and structured/weighted expert-judgment aggregation. (Extended by Tetlock and the structured-expert-judgment literature.)

Space translation

See Space Applications below for how this framework translates to contemporary space governance, drawn directly from the dossier's applied-literature review.