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on Nudge and Boosting |
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Issue of 2024‒09‒02
four papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Antinyan, Armenak; Asatryan, Zareh |
| Abstract: | Governments increasingly use nudges to improve tax collection. We synthesize the growing literature that evaluates nudging experiments using meta-analytical methods. We find that simple reminders increase the probability of compliance by 2.7 percentage points relative to the baseline where about a quarter of taxpayers are compliant. Nudges that commonly refer to elements of tax morale increase compliance by another 1.4 percentage points. Deterrence nudges, which inform taxpayers about enforcement parameters, increase compliance the most, amounting to an additional 3.2 percentage points increase on top of reminders. Our additional findings highlight the conditions where nudges are more effective, such as their potential when targeting sub-population of late-payers, and also suggest that even this sample of randomized trials may be susceptible to selective reporting of results. Overall, our findings imply that taxpayers are biased by various informational and behavioral constraints, and that nudges can be of some help in overcoming these frictions. |
| Keywords: | Tax compliance, Tax evasion, Randomized control trials, Nudging, Reminders, Tax morale, Deterrence, Meta-analysis, Publication selection bias |
| JEL: | C93 D91 H26 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:300677 |
| By: | SASAKI, Hiroki; HORIE, Shinya; HORIE, Tetsuya; TANAKA, Katsuya |
| Abstract: | In this study, we explore the impact of "Nudge" and "Boost" methodologies on mitigating methane emissions from rice cultivation, a significant contributor to global greenhouse gas emissions. Through a cluster randomized control trial conducted in Japan, we assess whether strategic informational campaigns, incorporating these behavioral insight, can enhance the adoption of a prolonged mid-season drainage period, which can lower methane emissions from rice paddies. Our experimental results show notable differences in the effectiveness of basic communications from the local government as before (Control group) versus those enriched with social comparison messaging focusing on methane emission from paddy fields (Nudge). Specifically, we find a clear positive effect of social comparison messaging for farmers participating in community-based agriculture. Furthermore, our research indicates that targeted technical guidance (Boost), addressing prevalent concerns about altering traditional farming methods, significantly sways farmers' future intentions toward methane-reduction techniques. The study underscores the importance of combining nudges, which subtly alter the external choice architecture, with boosts that empower farmers' decision-making capabilities and counter cognitive biases, to effectively steer behavior towards environmentally sustainable practices. |
| Keywords: | Environmental Economics and Policy, Institutional and Behavioral Economics |
| Date: | 2024–08–07 |
| URL: | https://d.repec.org/n?u=RePEc:ags:cfcp15:344318 |
| By: | Sofia Badini; Esther Gehrke; Friederike Lenel; Claudia Schupp |
| Abstract: | We implement a randomized controlled trial to investigate whether students in lower-secondary school more effectively acquire information about potential career paths if this information is preceded by a task that allows students to explore their own interests and the career information is presented in personalized order. We find that self-exploration in combination with the personalized display increases students’ information acquisition. Students also read about more diverse career paths and shift their focus from occupations that require university education towards those that require a high-school degree. |
| Keywords: | information acquisition, career guidance, education, field experiment |
| JEL: | C93 D83 D91 I21 O15 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11225 |
| By: | Hafsa Lemsieh (UH2MC - Université Hassan II [Casablanca]); Ibtissam Abarar |
| Abstract: | In that emerging digital era, Artificial Intelligence technology headed by machine learning, digital-smart technologies as well as the Big Data that allows predictive analysis has a significant influence over many people precisely those who are not all conscious and aware that the datasets are assembled from their online interactions and activities, consequently it can be used to anticipate and manipulate their purchasing psychology and behavior out of their control. In these terms, this study is going to present the literature that is in relation basically with the approach to the contribution of the artificial intelligence technology in manipulating the purchasing behavior based on the psychological factor. To guide this in deep study we will include multiple sources of the secondary data, going from journal articles, conference papers, internet sources and so on. The main objective is to bridge and eliminate the gap in this somehow empty field of research. The theoretical conclusions will offer an insight about the main importance in terms of implementing the artificial intelligence tools in the field and the department of marketing as a successful way to understand the consumers preferences and their journey in terms of purchasing. The goal is to provide predictive analysis and to know precisely how to manipulate the psychology of consumers in order to influence their behavior. The generation Z are a real opportunity to achieve this aim since they are digitally native and most of their purchasing decisions occurs through the use of their smartphones as they rely on social media for collecting and gathering any kind of information |
| Keywords: | Artificial intelligence, Consumer behaviour, Digital Marketing, Manipulation, Psychology., Artificial intelligence Consumer behaviour Digital Marketing Manipulation Psychology. JEL Classification: M31 M15 D91 Type du papier: Theoretical Research, Psychology. JEL Classification: M31, M15, D91 Type du papier: Theoretical Research |
| Date: | 2024–06–23 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04629533 |