SummaryBackgroundCountries have adopted different approaches, at different times, to reduce the transmission of coronavirus disease 2019 (COVID-19). Cross-country comparison could indicate the relative efficacy of these approaches. We assess various non-pharmaceutical interventions (NPIs) over time, comparing the effects of self-imposed (i.e. voluntary) behavior change and of changes enforced via official regulations, by statistically examining their impacts on subsequent death rates in 13 European countries.Methods and findingsWe examine two types of NPI: the introduction of government-enforced closure policies over time; and self-imposed alteration of individual behaviors in response to awareness of the epidemic, in the period prior to regulations. Our proxy for the latter is Google mobility data, which captures voluntary behavior change when disease salience is sufficiently high. The primary outcome variable is the rate of change in COVID-19 fatalities per day, 16-20 days after interventions take place. Linear multivariate regression analysis is used to evaluate impacts. Voluntarily reduced mobility, occurring prior to government policies, decreases the percent change in deaths per day by 9.2 percentage points (95% CI 4.5-14.0 pp). Government closure policies decrease the percent change in deaths per day by 14.0 percentage points (95% CI 10.8-17.2 pp). Disaggregating government policies, the most beneficial are intercity travel restrictions, cancelling public events, and closing non-essential workplaces. Other sub-components, such as closing schools and imposing stay-at-home rules, show smaller and statistically insignificant impacts.ConclusionsThis study shows that NPIs have substantially reduced fatalities arising from COVID-19. Importantly, the effect of voluntary behavior change is of the same order of magnitude as government-mandated regulations. These findings, including the substantial variation across dimensions of closure, have implications for the phased withdrawal of government policies as the epidemic recedes, and for the possible reimposition of regulations if a second wave occurs, especially given the substantial economic and human welfare consequences of maintaining lockdowns.

Copyright 2020 by the American Council on Consumer Interests We perform the first rigorous test of a rules of thumb-based approach to financial education on consumer behavior and outcomes. We test two rules of thumb that are targeted at reducing credit card revolving and deliver them in a randomized fashion via e-mail, online banner, and physical mailer. Using monthly administrative data and pre and postintervention credit data on almost 14,000 consumers, we find that the “Do not swipe the small stuff” rule of thumb reduces participants' targeted credit card balance by an average of 2% at a cost of around $0.50 per person. The “Credit keeps charging” rule shows a decline as well but the impact is not significant.

We show that a number of noncognitive skills and preferences, including patience and identity, are malleable in adults, and that investments in them reduce crime and violence. We recruited criminally engaged men and randomized one-half to eight weeks of cognitive behavioral therapy designed to foster self-regulation, patience, and a noncriminal identity and lifestyle. We also randomized $200 grants. Cash alone and therapy alone initially reduced crime and violence, but effects dissipated over time. When cash followed therapy, crime and violence decreased dramatically for at least a year. We hypothesize that cash reinforced therapy's impacts by prolonging learning-by-doing, lifestyle changes, and self-investment. (JEL D12, D83, H23, I32, K42, O15, O17)

Background.By 2009, two decades of war and widespread displacement left the majority of the population of Northern Uganda impoverished.Methods.This study used a cluster-randomized design to test the hypothesis that a poverty alleviation program would improve economic security and reduce symptoms of depression in a sample of mostly young women. Roughly 120 villages in Northern Uganda were invited to participate. Community committees were asked to identify the most vulnerable women (and some men) to participate. The implementing agency screened all proposed participants, and a total of 1800 were enrolled. Following a baseline survey, villages were randomized to a treatment or wait-list control group. Participants in treatment villages received training, start-up capital, and follow-up support. Participants, implementers, and data collectors were not blinded to treatment status.Results.Villages were randomized to the treatment group (60 villages with 896 participants) or the wait-list control group (60 villages with 904 participants) with an allocation ration of 1:1. All clusters participated in the intervention and were included in the analysis. The intent-to-treat analysis included 860 treatment participants and 866 control participants (4.1% attrition). Sixteen months after the program, monthly cash earnings doubled from UGX 22 523 to 51 124, non-household and non-farm businesses doubled, and cash savings roughly quadrupled. There was no measurable effect on a locally derived measure of symptoms of depression.Conclusions.Despite finding large increases in business, income, and savings among the treatment group, we do not find support for an indirect effect of poverty alleviation on symptoms of depression.

We show that extremely poor, war-affected women in northern Uganda have high returns to a package of $150 cash, five days of business skills training, and ongoing supervision. Sixteen months after grants, participants doubled their microenterprise ownership and incomes, mainly from petty trading. We also show these ultrapoor have too little social capital, but that group bonds, informal insurance, and cooperative activities could be induced and had positive returns. When the control group received cash and training 20 months later, we varied supervision, which represented half of the program costs. A year later, supervision increased business survival but not consumption. (JEL I38, J16, J23, J24, L26, O15, Z13)