Amidst mass immunization efforts to curb COVID-19 transmission, policy mandates enforced minimum physical distancing. Concerns arose regarding risk compensation, where individuals might reduce adherence to distancing if benefiting from multiple risk-reducing interventions. This study used an online natural experiment to examine the association of vaccination status and vaccine efficacy beliefs with social distancing preferences. Participants completed a distance-matching task, positioning avatars in stylized scenarios drawn from a 2 (location) × $\times$ 3 (activity) factorial design. Data were collected in July 2021 during the vaccine rollout program in the United Kingdom. Contrary to risk compensation expectations, this study found no strong evidence of reduced distancing at a population level. However, stronger vaccine efficacy beliefs were associated with slightly reduced distancing among fully vaccinated individuals-a small effect size. In contrast, partially vaccinated and unvaccinated individuals with stronger vaccine beliefs maintained greater distance, suggesting a nuanced relationship between perceptions of vaccine efficacy and distancing behavior. Subjective risk perceptions did not significantly alter these patterns. Additionally, partially vaccinated individuals behaved similarly to the unvaccinated despite expressing higher perceived infection risk, and unvaccinated participants who intended to vaccinate showed lower distancing preferences. The study also identified an in-group bias in perceptions of vaccine distribution. While these findings were collected during a specific phase of the COVID-19 pandemic-when vaccination uptake and policy measures were rapidly changing-they underscore the importance of investigating how vaccine beliefs shape protective behaviors. Given the modest effect sizes observed, further research is warranted to clarify the evolving role of vaccine perceptions in public health strategies.
We test a nudge in a field experiment on credit cards. The nudge shrouds the autopay enrollment option for cardholders to automatically pay exactly the credit card minimum payment each month. After six months, the nudge decreases the fraction of cardholders who only pay exactly the minimum by 23 percent. However, the nudge does not significantly reduce credit card debt. Nudged cardholders often choose autopay amounts that are only slightly higher than the minimum payment. The nudge reduces autopay enrollment, which increases missed payments. The nudge reduces manual payments by autopay enrollees. Cardholders frequently lacking liquid cash best explains our results. (JEL C93, D12, D91, G21, G51)
We combine administrative data with a life cycle structural model that exploits the unique features of the U.K. mortgage market to analyze the sources of inaction and to estimate borrowers’ nonpecuniary remortgaging costs. The utility costs needed to generate a given level of inaction depend on monetary gains from remortgaging and on the importance of those monetary gains for agents, which in turn depend on the (endogenously determined) marginal utility of consumption. The model results reveal significant nonpecuniary costs of action that, when measured as a proportion of borrower income, are larger for the young and for lower-income households.
At-scale field experiments at major U.K. banks show that automatic enrollment into "just-in-time" text alerts reduces unarranged overdraft and unpaid item charges 17% to 19% and arranged overdraft charges 4% to 8%, implying annual market-wide savings of 170 pound million to 240 pound million. Incremental benefits from "early-warning" alerts are statistically insignificant, although economically significant effects are not ruled out. Prior to the experiments, over half of overdrafts could have been avoided by using lower-cost liquidity available in savings and credit card accounts. Alerts help consumers achieve less than half of these potential savings.
While policies to address the digital divide often focus on improving internet digital skills, it is also crucial to ensure people can access essential physical services they still require. This study investigates the case of ongoing cash reliance in the United Kingdom in the context of declining cash usage and, accordingly, the provision of ATMs and bank branches. Utilising data from the Financial Lives 2022 survey, a large, nationally representative dataset, this research employs a logistic regression model to analyse the association between demographic characteristics and cash reliance. The findings reveal that digital exclusion, driven by low digital skills, is the strongest predictor of cash reliance, increasing the likelihood by four times. Those living in low-income households or that are unemployed also exhibit significantly higher reliance on cash, emphasising the need for equitable access. Other important factors include residing in Northern Ireland or Scotland and poor health. These geographic and socioeconomic disparities highlight the need for regionally nuanced policies to ensure adequate provision of cash access services. Interestingly, while older age is associated with cash reliance in some studies, its impact is nuanced here, becoming statistically significant and positive only when broader cash usage, rather than reliance, is considered. The model has moderately strong predictive power (as measured by McFadden’s pseudo-R-squared and confirmed by cross-validated AUC), confirming the importance of the identified predictors for policy design, although it is unsuitable for precise small-area estimation. This suggests a holistic approach incorporating these predictors alongside a broader range of local area characteristics should be adopted when evaluating the risks associated with declining cash access services and ensuring equitable access to them.
