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Hall of Shoulders

Behavioral Economics

Daniel Kahneman

Daniel Kahneman is known for dual-process theory (System 1 / System 2), prospect theory, the heuristics-and-biases program. **Purpose:** A citation-grounded application of Kahneman's thinking to contemporary space challenges, for use as an adversarial review lens in the COLLEGIUM.

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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

    Outside view. "Your cost, schedule, or risk forecast is built from the specifics of this system. What is the reference class of comparable past projects, what is the empirical distribution of their outcomes, and how far does your inside-view estimate sit from that distribution's mean and from its fat tail?" (Falsifiable: a candidate either has the reference-class distribution or does not.)

  2. 2

    Base rates vs. salience. "You justify this decision threshold or this risk posture partly by recent events. Separate the base-rate evidence from the vivid recent record: if you strip out the availability of the salient recent case, does your conclusion survive on base rates alone?

  3. 3

    Framing and reference point. "State your central choice in both a gain frame and a loss frame, and identify the reference point your stakeholders are using. Would your recommended policy survive if the reference point were moved (e.g., if non-compliance, not compliance, were the framed loss)? If the answer flips, which framing is normatively correct and why?

  4. 4

    Probability weighting at the tails. "Your decision turns on a very low (or very high) probability. Show that your recommendation is robust to the documented human tendency to overweight low probabilities and underweight high ones, that is, that you are acting on the probability and not on its decision weight.

  5. 5

    Overconfidence and WYSIATI. "What evidence is absent from your analysis, and how would its absence change your confidence interval? Demonstrate that your stated confidence is calibrated against an outcome record, not constructed from the coherence of the story your available evidence happens to tell.

Core Concepts & Space Translation

Prospect theory: reference dependence, loss aversion, and probability weighting

People do not evaluate outcomes in terms of final wealth; they evaluate gains and losses relative to a reference point. The value function is concave for gains, convex for losses, and roughly twice as steep for losses as for gains (loss aversion). Stated probabilities are transformed into nonlinear decision weights, with low probabilities systematically overweighted and moderate-to-high probabilities underweighted. Key work: Kahneman & Tversky, "Prospect Theory: An Analysis of Decision under Risk," *Econometrica* (1979), doi 10.2307/1914185; reviewed and extended by Barberis, "Thirty Years of Prospect Theory in Economics," *JEP* (2013), doi 10.1257/jep.27.1.173.

Space translation

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

Heuristics and biases: availability, representativeness, anchoring

Under uncertainty, people substitute a hard question (what is the probability?) for an easier one answered by a mental shortcut. Availability judges frequency by ease of recall (vivid, recent events loom large). Representativeness judges category membership by similarity, neglecting base rates. Anchoring-and-adjustment ties numerical estimates to an initial value and adjusts insufficiently. These heuristics are economical and usually effective, but they produce systematic, predictable, direction-known errors. Key work: Tversky & Kahneman, "Judgment under Uncertainty: Heuristics and Biases," *Science* (1974), doi 10.1126/science.185.4157.1124.

Space translation

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

Dual-process theory (System 1 / System 2)

Judgment runs on two systems: System 1 is fast, automatic, associative, affect-laden, and effortless; System 2 is slow, deliberate, rule-governed, and effortful. Most judgments are made by System 1 and only loosely monitored by a lazy System 2. Biases arise when System 1 produces a confident answer that System 2 fails to check. Key work: Kahneman, *Thinking, Fast and Slow* (2011). The affective/situational channel of System 1 is directly testable in operations settings, e.g. emotional cues changing performance under uncertainty (Acta Astronautica, 2026, doi 10.1016/j.actaastro.2026.04.012).

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 planning fallacy, optimism bias, and the inside vs. outside view

Forecasters adopt an "inside view," building estimates from the specifics of the case at hand, and systematically underestimate cost, duration, and risk. The corrective is the "outside view": anchor the forecast on the distribution of outcomes from a reference class of comparable past projects. Operationalized as reference class forecasting (RCF). Key works: Kahneman & Tversky's planning-fallacy work, operationalized by Flyvbjerg, "Curbing Optimism Bias and Strategic Misrepresentation in Planning: Reference Class Forecasting in Practice," *European Planning Studies* (2007), doi 10.1080/09654310701747936; and "Five Things You Should Know About Cost Overrun," *Transportation Research Part A* (2018), doi 10.1016/j.tra.2018.07.013.

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, narrow bracketing, and overconfidence (WYSIATI)

Logically equivalent descriptions of the same choice (gain frame vs. loss frame) produce different decisions. Decisions are evaluated in isolation (narrow bracketing) rather than as part of a portfolio, distorting risk attitudes. And "What You See Is All There Is" (WYSIATI): people build coherent stories from available evidence and are overconfident in them, ignoring what they do not know. Key works: Kahneman & Tversky 1979 (the isolation effect); *Thinking, Fast and Slow* (2011) on WYSIATI and overconfidence; salience-driven probability distortion formalized by Bordalo, Gennaioli & Shleifer, "Salience Theory of Choice Under Risk," *QJE* (2012), doi 10.1093/qje/qjs018.

Space translation

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