Nudging: A Very Short Guide

By Cass R. Sunstein. Journal of Consumer Policy, 2014

644 citations recorded by the source corpus.

This brief essay offers a general introduction to the idea of nudging, along with a list of 10 of the most important “nudges.” It also provides a short discussion of the question whether to create some kind of separate “behavioral insights unit,” capable of conducting its own research, or instead to rely on existing institutions.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/b8519cd8f2f5f41151f1361d73e6c3c70ab97792

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

Citations in the corpus

How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies (2019, methodology): “For the category, we relied on existing frameworks for classifying nudges (e.g. Johnson et al., 2012; Sunstein, 2014; Münscher et al., 2016).”
Mitigating climate change via food consumption and food waste: A systematic map of behavioral interventions (2020, methodology): “While these encompass the classical instruments such as consumer information and education, taxes and regulation, our interest lies in a new kind of policy tool, so-called behaviorally informed policies (e.g., Sunstein, 2014a).”
Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers (2016, positive): “Frequent nudges are a highly visible part of the “choice architecture” (Sunstein, 2014, p. 2) of the Uber system: Uber can steer drivers to work at particular places at particular times while maintaining that its system merely reflects demand to drivers, who have full freedom of choice to ignore…”
RCTs to Scale: Comprehensive Evidence from Two Nudge Units (2020, background): “The first two estimators in Table 5, below the unweighted average reproduced from Table 4, are a restricted maximum-likelihood estimator and an empirical Bayes estimator, both based on the assumption that each study draws its true effect from a normal distribution N(β̄, τ2). In contrast, the DerSimo”
Behavioural Insights and (Un)healthy Dietary Choices: a Review of Current Evidence (2018, background): “…the different interventions in a mostly empirical field.4 In a pragmatic approach, leaving conceptual debates aside and taking on a regulator’s view, Sunstein (2014) listed the ten most important nudges for policy-making as follows: (1) default rules; (2) simplification; (3) use of social norms;…”
Nudging for Tax Compliance: A Meta-Analysis (2019, background): “, regions); ii) the trial introduces a nudging intervention which closely follows the definition of Thaler and Sunstein (2008); iii) the dependent variable of interest is the tax payment behavior of the taxpayer; and iv) the resulting study reports all the relevant statistics necessary for our meta-”