nep-nud 2024-05-27 papers

on Nudge and Boosting

Issue of 2024‒05‒27
two papers chosen by

The Double Dividend of Attention-Releasing Policies By Steffen Altmann; Andreas Grunewald; Jonas Radbruch
Deceptive choice architecture and behavioral audits: a principles‐based approach By Mills, Stuart

The Double Dividend of Attention-Releasing Policies

By:	Steffen Altmann; Andreas Grunewald; Jonas Radbruch
Abstract:	We study the effects of two widely observed behavioral policy interventions⸻the simplification of complex decisions and the implementation of high-quality defaults. Based on a laboratory experiment featuring a dual-task paradigm, we demonstrate that these policies do not only improve decisions in the targeted choice domain, but also yield substantial positive indirect effects on non-targeted decisions. The latter emerge as a result of an attention-releasing effect of the policies. Furthermore, the relative importance of the direct and indirect effects varies systematically across the population. Evaluations that focus only on the targeted domain may therefore significantly underestimate the overall effectiveness of attention-releasing policies and provide a biased assessment of their distributional consequences.
Keywords:	administrative burden, limited attention, defaults, nudges, limited cognitive resources, behavioral economics, laboratory experiment
JEL:	D91 D01 D04 C91
Date:	2024
URL:	http://d.repec.org/n?u=RePEc:ces:ceswps:_11069&r=nud

Deceptive choice architecture and behavioral audits: a principles‐based approach

By:	Mills, Stuart
Abstract:	Regulators are increasingly concerned about deceptive, online choice architecture, including dark patterns and behavioral sludge. From a behavioral science perspective, fostering a regulatory environment which reduces the economic harm caused by deceptive designs, while safeguarding the benefits of well-meaning behavioral insights, is essential. This article argues for a principles-based approach and proposes behavioral audits as a tool to support this approach.
Keywords:	regulation; AI; behavioral audits; choice architecture; principles-based regulation
JEL:	R14 J01
Date:	2024–03–27
URL:	http://d.repec.org/n?u=RePEc:ehl:lserod:122714&r=nud

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