In 2008, the behavioral economist Richard Thaler and the legal scholar Cass Sunstein published a book in which they advocated a novel approach to public policy based on the notion of a "nudge." Roughly speaking, a nudge is an intervention in the decisional context that steers people's decisions by acting on their cognitive biases. The notion of a nudge generated an intense debate across different disciplines and proved popular with many policy makers around the world. The present article reviews the debate and research on nudges by focusing on three main dimensions: (1) the exact definition of nudges; (2) the justification of nudge policies, with a focus on "libertarian paternalism"; and (3) the effectiveness of nudges, both over time and in comparison with standard policies.

We argue that the diverse components of a choice architecture can be classified into two main dimensions -Message and Environment -and that the distinction between them is useful in order to better understand how nudges work. In the first part of this paper, we define what we mean by nudge, explain what Message and Environment are, argue that the distinction between them is conceptually robust and show that it is also orthogonal to other distinctions advanced in the nudge literature. In the second part, we review some common types of nudges and show they target either Message or Environment or both dimensions of the choice architecture. We then apply the Message-Environment framework to discuss some features of Amazon's website and, finally, we indicate how the proposed framework could help a choice architect to design a new choice architecture.

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In most risk elicitation tasks, lotteries are presented through a verbal description stating the outcomes and their likelihoods (e.g., “Win $5 with probability 10%”, “1 in 10 chance to win $5”), sometimes accompanied by a pictorial representation (a pie chart or bar graph). Literature on risk communication suggests that alternative but supposedly equivalent numeric formats (e.g., percentages vs ratios) and pictorial displays (e.g., continuous vs discrete) may lead to a different perception of risk and concern for it. The present experiment (N = 95) tests for numeric and pictorial framing effects in a multiple price list (MPL), where risk information is presented either as percentages (“10%”) or as ratios (“1 out of 10”) and is accompanied by either two-slice or ten-slice pies. Results show that neither the numeric framing (adopting ratios) nor the pictorial framing (slicing pies) significantly altered per se the average elicited risk aversion. Nonetheless, the pictorial framing significantly reduced the elicited risk aversion for those participants who focused on the probability of the lottery’s high outcome in their decisions.