|
on Nudge and Boosting |
|
Issue of 2024‒07‒22
six papers chosen by |
| By: | Charlotte Klatt (University of Kassel); Anna Schulze-Tilling (Bocconi University & University of Bonn) |
| Abstract: | Interventions to decrease meat consumption are often only implemented for short periods of time, and it is unclear how they might have lasting effects. We combine student canteen consumption (over 270, 000 purchases made by over 4, 500 guests) and survey data (N>800) to study how a one-month intervention to decrease meat consumption affects consumer behavior post-intervention. During the intervention period, meat meals were eliminated from the menu of the treatment canteen, while the two control canteens were unaffected. Using a difference-in-difference approach, we estimate that guests usually frequenting the treatment canteen did not significantly reduce their visits to the canteen during or after the intervention. In the two months following the intervention, they were still 4% less likely to choose the meat option when visiting the canteen, relative to baseline. A large part of this effect seems explicable with guests learning about the quality of the canteen's vegetarian meals. We find little to no evidence of the intervention changing perceived social norms. |
| Keywords: | Food consumption, behavioral intervention, field experiment, habit formation, experience |
| JEL: | C93 D12 D83 Q18 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:315&r= |
| By: | Lucas Coffman (Boston College); Clayton R. Featherstone (Baylor University); Judd B. Kessler (The Wharton School, University of Pennsylvania) |
| Abstract: | Nudge-style interventions are popular but are often criticized for being atheoretical. We present a model of information nudges (i.e., interventions that provide useful but imperfect information about the utility of taking an action) based on Bayesian updating in a setting of binary choice. The model makes two main predictions: One, the probability of a positive treatment effect should be increasing in the baseline take-up rate. Two, across studies, as baseline rates increase from 0 to 1, the expected treatment effect has a "down–up–down" shape. A surprising corollary of both predictions is that treatment effects are expected to be negative for low baseline rates. We use reduced-form and structural methods to conduct a meta-analysis of 75 information nudges and corroborate both predictions. Both the meta-analysis and a novel survey of nudge experts suggest the intuition in the model is not currently known. Finally, we provide guidance for practitioners about the environments in which information nudges will positively affect a desired behavior and those in which they may backfire. |
| Keywords: | nudges, interventions, Bayesian updating |
| JEL: | C90 D04 |
| Date: | 2024–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:boc:bocoec:1077&r= |
| By: | Martínez Villarreal, Déborah; Rojas Méndez, Ana María; Scartascini, Carlos; Simpser, Alberto |
| Abstract: | Can societies be nudged to adopt beneficial behaviors? Publicizing how people behave on average descriptive-norms nudging has emerged as a key tool for increasing the adoption of desirable behaviors. While nudging, by describing social norms, has proven effective in one-shot interventions in small samples (marginal-effect designs), nudging on an ongoing basis at the population level may not necessarily lead to higher compliance and can give rise to major challenges. We use a simple model to show that social adjustment dynamics can drive a populations behavior in unanticipated directions. We propose a general approach to estimating equilibrium behavior and apply it to a study of mask-wearing during the COVID-19 pandemic. Our empirical findings align with the analytical approach and indicate that publicizing mask-wearing rates on an ongoing basis could have backfired, as initially high rates would have settled into substantially lower equilibrium rates of the behavior. In other words, if scaled up, positive marginal-effect designs do not necessarily translate into full compliance with the intervention. |
| Keywords: | COVID-19;Social norms;Social distancing;Normative expectations;Empirical expectations;Compliance;Social Dynamics;Collective Health |
| JEL: | D91 I18 H41 |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:13461&r= |
| By: | Ahsanuzzaman,; Eskander, Shaikh; Islam, Asad; Wang, Liang Choon |
| Abstract: | We use a randomized controlled trial in Bangladesh to test three types of non-price energy conservation strategies that influence electricity consumption of households: (i) advice on electricity conservation methods (knowledge treatment); (ii) (median) electricity consumption of others in the suburb (suburb comparison); and (iii) (median) electricity consumption of neighbors (neighbor comparison). We find that providing advice on saving energy could reduce households' electricity consumption and bills significantly. The effects are stronger for advice on electricity conservation methods than neighbor and suburb comparisons. The effects of providing information about own electricity consumption relative to neighbors’ electricity consumption is similar to the effects of giving information about own electricity consumption relative to electricity consumption of households in the same suburb. The effects among households who were inefficient users in neighbor and suburb comparison groups are almost as strong as those in the knowledge treatment group. The effects across all treatment groups become stronger over time as they receive repeated information. |
| Keywords: | electricity consumption; energy efficiency; field experiment; non-price information; social norms |
| JEL: | J1 |
| Date: | 2024–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:123900&r= |
| By: | Katherine Milkman; Sean Ellis; Dena Gromet; Youngwoo Jung; Alex Luscher; Rayyan Mobarak; Madeline Paxson; Ramon Silvera Zumaran; Robert Kuan; Ron Berman; Neil Lewis Jr; John List; Mitesh Patel; Christophe Van den Bulte; Kevin Volpp; Maryann Beauvais; Jonathon Bellows; Cheryl Marandola; Angela Duckworth |
| Abstract: | Encouraging routine COVID-19 vaccinations will probably be a crucial policy challenge for decades to come. To avert hundreds of thousands of unnecessary hospitalizations and deaths, adoption will need to be higher than it was in the autumn of 2022 or 2023, when less than one-fifth of Americans received booster vaccines. One approach to encourage vaccination is to eliminate the friction of transportation hurdles. Previous research has shown that friction can hinder follow-through and that individuals who live farther from COVID-19 vaccination sites are less likely to get vaccinated. However, the value of providing free round-trip transportation to vaccination sites is unknown. Here we show that offering people free round-trip Lyft rides to pharmacies has no benefit over and above sending them behaviourally informed text messages reminding them to get vaccinated. We determined this by running a megastudy with millions of CVS Pharmacy customers in the United States testing two effects: free round-trip Lyft rides to CVS Pharmacies for vaccination appointments, and seven different sets of behaviourally informed vaccine reminder messages. Our results suggest that offering previously vaccinated individuals free rides to vaccination sites is not a good investment in the United States, which is contrary to the high expectations of both expert and lay forecasters. Instead, people in the United States should be sent behaviourally informed COVID-19 vaccination reminders, which increased the 30-day COVID-19 booster uptake by 21% (1.05 percentage points) and spilled over to increase 30-day influenza vaccinations by 8% (0.34 percentage points) in our megastudy. More rigorous testing of interventions to promote vaccination is needed to ensure that evidence-based solutions are deployed widely and that ineffective but intuitively appealing tools are discontinued. |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:feb:natura:00790&r= |
| By: | Rojas Méndez, Ana María; Scartascini, Carlos |
| Abstract: | Behavioral biases often lead to suboptimal decisions, a vulnerability that extends to policymakers who operate under conditions of fatigue, stress, and time constraints and with significant implications for public welfare. While behavioral economics offers strategies like default adjustments to mitigate decision-making costs, deploying these policy interventions is not always feasible. Thus, enhancing the quality of policy decision-making is crucial, and evidence suggests that targeted training can boost job performance among policymakers. This study evaluates the impact of a behavioral training course on policy decision-making through a randomized experiment and a survey test that incorporates problem-solving and decision-making tasks among approximately 25, 000 participants enrolled in the course. Our findings reveal a significant improvement in the treated group, with responses averaging 0.6 standard deviations better than those in the control group. Given the increasing prevalence of such courses, this paper underscores the potential of behavioral training in improving policy decisions and advocates for further research through additional experimental studies. |
| Keywords: | Experimental Design;behavioral economics;Training;public policy;Government officials |
| JEL: | H83 Z18 |
| Date: | 2024–04 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:13476&r= |