Featured Essays

4 original, source-checked long-form essays on trust, belief updating, intergenerational choice, and trusting AI.

The Co-Joint Concept of Trust and Reciprocity in Behavioral Economics

A Synthesis of Game-Theoretic, Psychological, and Conjoint Measurement Paradigms

This paper presents an integrated theoretical and empirical framework analyzing the co-joint concept of trust and its operationalization within contemporary behavioral and experimental economics. Traditionally modeled in classical theory as a sub-dimension of risk or calculative self-interest (Williamson, 1993), trust is redefined here as a multi-attribute, context-sensitive behavioral primitive inextricably linked to expectations of reciprocity and social preferences (Berg, Dickhaut & McCabe, 1995; Rousseau, Sitkin, Burt & Camerer, 1998). The analysis contrasts the canonical sequential Trust Game with decompositional Choice-Based Conjoint (CBC) analysis, and reviews neuropsychoeconomic findings - the roles of oxytocin, lateral prefrontal activation, and electrodermal responses - within the integrative model of Krueger and Meyer-Lindenberg (2019), while flagging that the strongest neuro-hormonal claim (the oxytocin-trust link) has proven difficult to replicate (Nave, Camerer & McCullough, 2015). It then evaluates external and ecological validity using eye-tracking and a natural-experiment benchmark (Jenke, Bansak, Hainmueller & Hangartner, 2021; Hainmueller, Hangartner & Yamamoto, 2015), and synthesizes these perspectives toward applications in public policy, organizational contracting, and social marketing.

22 min read · 4,487 words Belief Updating

Belief Updating and the Question of Cumulative Knowledge in Behavioral Economics

A Behavioral-Attenuation Perspective

Behavioral economics has largely abandoned the assumption that agents revise their beliefs by Bayes' rule, documenting instead a stable catalogue of deviations - base-rate neglect, conservatism, confirmation bias, and motivated reasoning (Benjamin, 2019). This paper reviews how people actually update, organizes the deviations under the recent unifying idea of "behavioral attenuation" (Enke, Graeber, Oprea & Yang, 2024) and its precursor "cognitive uncertainty" (Enke & Graeber, 2023), and then asks whether behavioral economics contains a concept of "cumulative knowledge." It argues that no single construct bears that name, but that two distinct and well-posed questions hide behind the phrase: whether an individual's knowledge cumulates toward truth through repeated updating, and whether the field itself accumulates reliable knowledge. On the first, learning theory shows that accumulation is partial, path-dependent, and not guaranteed to converge (Rabin & Schrag, 1999; Esponda & Pouzo, 2016). On the second, replication and meta-analytic evidence shows that behavioral economics is becoming cumulative, but unevenly (Open Science Collaboration, 2015; Camerer et al., 2016; DellaVigna & Linos, 2022). Behavioral attenuation, it is argued, is the conceptual bridge between the two.

12 min read · 2,369 words Temporal Choice

Intergenerational Equity, Present Bias, and the Architecture of Long-Term Choice

From the Social Discount Rate to Opt-Out Defaults

Intergenerational equity asks how much weight the present generation should give to the welfare of those who come after it - a question that governs climate policy, the management of exhaustible resources, public debt, and the adequacy of long-term saving. This paper takes a sustainability-centred view of that question and argues that behavioural economics reframes it in a specific way. The normative core is the social discount rate: the Stern Review's near-zero rate of pure time preference treats future generations as almost equal to the present, while Nordhaus's market-based rate weights them far less (Stern, 2007; Nordhaus, 2007), and an expert consensus now favours rates that decline with the horizon (Weitzman, 2001; Arrow et al., 2013). Behavioural economics adds that even when a society endorses a low discount rate in principle, present bias systematically pulls actual behaviour toward the short term (Laibson, 1997; Frederick, Loewenstein & O'Donoghue, 2002). The paper then treats saving - private and collective - as the concrete intertemporal transfer to the future, and evaluates opt-in versus opt-out choice architecture (automatic enrolment, Save More Tomorrow, organ-donation and green-energy defaults) as a powerful but partial instrument for closing the gap (Madrian & Shea, 2001; Thaler & Benartzi, 2004; Johnson & Goldstein, 2003; Ebeling & Lotz, 2015). It closes on the limits of defaults and the ethics of paternalism, emphasising one asymmetry that no nudge can resolve: future generations cannot themselves opt in or out.

14 min read · 2,722 words AI & Trust

In Algorithms We Trust? The Behavioural Economics of Trusting AI over Humans

From Algorithm Aversion to Algorithm Appreciation — and Back

[Draft] When a forecast, a diagnosis, or a bail decision can come from either a person or an algorithm, whom do we trust — and should we? The experimental literature returns two contradictory answers: people abandon algorithms after seeing them err, even when the algorithm demonstrably outperforms the human (algorithm aversion), yet in other settings they weight identical advice more heavily when told it comes from an algorithm (algorithm appreciation). This article reconciles the two findings by treating trust in AI not as a fixed attitude but as the output of the same behavioural machinery documented for interpersonal trust: error salience, perceived control, task framing, expertise, and biased belief updating. Field evidence from bail decisions and radiology shows the stakes: judges respond to noise as if it were signal, and radiologists underweight AI predictions, so human–AI combinations can underperform either alone. The practical question is not whether to trust algorithms but how to design the choice architecture of trust.

5 min read · 932 words