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on Nudge and Boosting |
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Issue of 2026–04–27
four papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Bucher-Koenen, Tabea; Wallossek, Luisa; Winter, Joachim |
| Abstract: | Default settings strongly increase pension enrollment, especially when savings incentives are high and choices are complex. We show that the effect is weaker when incentives are low, options are simple, and opting out is easy. We study the nationwide introduction of auto-enrollment for low income employees in Germany's public pay-as-you-go pension system. We find that automatic enrollment raises participation by 23 percentage points, though most individuals actively opt out. Linking administrative and survey data shows that the default effect is stronger when enrollment incentives are higher and among individuals who lack knowledge of their enrollment status. |
| Keywords: | Default-Setting, Auto-Enrollment, Pensions, Financial Literacy |
| JEL: | D14 H55 J26 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:340111 |
| By: | Madison Dell; Enzo Brox; Patricia Palffy; Claudio Schilter; Uschi Backes-Gellner |
| Abstract: | We study how choice architecture in online platforms shapes high-stakes occupational choices through two behavioral mechanisms: motivated reasoning and cognitive load. Using detailed process data from a large online job board and exploiting a quasi-experimental setting, we leverage two sources of exogenous variation in the presentation of occupation recommendations. First, we use random variation in the rank order of equally well-matched occupations to study the effects of motivated reasoning. Our results show that rank order strongly increases the level of users' engagement on the platform and, consequently, the number of occupations to which they apply. Second, we exploit a redesign that transformed the occupation recommendations from a static, text-heavy list into an interactive and visually enriched presentation. The redesign was neither announced nor anticipated, which allows for causal interpretation. We find that this small redesign significantly increases the number of occupations to which users apply, supporting our hypothesis that it reduces cognitive load, leading to increased use of a watch list that keeps more occupations in jobseekers' memory. Our findings provide large-scale field evidence showing that even small changes in platform design significantly and strongly shape consequential career choices. |
| Keywords: | Occupational choice, Choice architecture, Recommender systems, Motivated reasoning, Cognitive load |
| JEL: | D91 J24 D83 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0255 |
| By: | Angelucci, Manuela (University of Texas at Austin); Fabregas, Raissa (UT Austin); Vazquez, Antonia (UT Austin) |
| Abstract: | AI-powered mental health apps have attracted growing interest as a low-cost way to expand care. Yet questions remain about their effectiveness, safety, and whether they may crowd out psychotherapy. We evaluate one such app in a randomized controlled trial among 1, 964 Mexican women with mild to severe psychological distress. Over six months, app access improved mental health by 0.3 standard deviations with no evidence of harm, improved sleep quality, increased healthful behaviors, and reduced missed work, yielding considerably larger benefits than costs. Treated participants were also more likely to seek traditional psychotherapy, but this increase does not explain most of the mental health gains. App use was high in the first month but then declined, as is common in digital interventions. Despite this drop in use, treatment effects persisted. Participants continued to implement practices promoted by the app, suggesting that even short-term engagement can produce durable improvements through sustained behavioral change. |
| Keywords: | digital mental health, AI-powered care, well-being, randomized controlled trial, Mexico, behavioral change, mental health apps, sleep quality, labor productivity, psychotherapy |
| JEL: | I12 O33 J24 C93 I15 I31 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18538 |
| By: | Guthrie Gray-Lobe; Michael Kremer; Joost de Laat; Oluchi Mbonu; Cole Scanlon |
| Abstract: | This study evaluates a large-scale SMS outreach program to engage caregivers of students in private primary schools in Kenya. Using a two-stage randomization design, we tested two types of weekly SMS messages: growth-mindset encouragement and personalized performance information. We find two main effects: First, outreach improved test scores by 0.07 standard deviations, with particularly strong gains among initially lower-performing students. This improvement generates 12 learning-adjusted years of schooling per US$100 spent—making it highly cost-effective relative to other education interventions. Second, outreach increased student exit rates by 4.7-5.0 percentage points, with effects concentrated among higher-achieving students (5.7 to 6.6 percent-age points). We develop a theoretical model of vertically differentiated schools where parental engagement affects both learning production and school choice. The model shows that when parents update their understanding of education production through engagement programs, they become more sensitive to perceived school quality differences. This increased sensitivity can lead lower-quality schools to forgo implementing engagement programs—even when costless—as enhanced parental discernment accelerates student exits. Our findings suggest a role for third-party provision of parent engagement programs in competitive education markets. |
| JEL: | D83 D91 I21 L15 O15 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35103 |