Despite numerous journalistic accounts, systematic quantitative evidence on economic conditions during the ongoing COVID-19 pandemic remains scarce for most low- and middle-income countries, partly due to limitations of official economic statistics in environments with large informal sectors and subsistence agriculture. We assemble evidence from over 30,000 respondents in 16 original household surveys from nine countries in Africa (Burkina Faso, Ghana, Kenya, Rwanda, Sierra Leone), Asia (Bangladesh, Nepal, Philippines), and Latin America (Colombia). We document declines in employment and income in all settings beginning March 2020. The share of households experiencing an income drop ranges from 8 to 87% (median, 68%). Household coping strategies and government assistance were insufficient to sustain precrisis living standards, resulting in widespread food insecurity and dire economic conditions even 3 months into the crisis. We discuss promising policy responses and speculate about the risk of persistent adverse effects, especially among children and other vulnerable groups.

The CEGA Working Paper Series showcases ongoing and completed research by faculty affiliates of the Center. CEGA Working Papers employ rigorous evaluation techniques to measure the impact of large-scale social and eco-nomic development programs, and are intended to encourage discussion and feedback from the global development community.

How large economic stimuli generate individual and aggregate responses is a central question in economics, but has not been studied experimentally. We provided one‐time cash transfers of about USD 1000 to over 10,500 poor households across 653 randomized villages in rural Kenya. The implied fiscal shock was over 15 percent of local GDP. We find large impacts on consumption and assets for recipients. Importantly, we document large positive spillovers on non‐recipient households and firms, and minimal price inflation. We estimate a local transfer multiplier of 2.5. We interpret welfare implications through the lens of a simple household optimization framework.

Author Contributions: Drs Jakubowski and Egger had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

BackgroundMany countries in sub-Saharan Africa have so far avoided large outbreaks of COVID-19, perhaps due to the strict lockdown measures that were imposed early in the pandemic. Yet the harsh socio-economic consequences of the lockdowns have led many governments to ease the restrictions in favor of less stringent mitigation strategies. In the absence of concrete plans for widespread vaccination, masks remain one of the few tools available to low-income populations to avoid the spread of SARS-CoV-2 for the foreseeable future.MethodsWe compare mask use data collected through self-reports from phone surveys and direct observations in public spaces from population-representative samples in Ugunja subcounty, a rural setting in Western Kenya. We examine mask use in different situations and compare mask use by gender, age, location, and the riskiness of the activityFindingsWe assess mask use data from 1,960 phone survey respondents and 9,549 direct observations. While only 12% of people admitted in phone interviews to not wearing a mask in public, 90% of people we observed did not have a mask visible (77.7% difference, 95% CI 0.742, 0.802). Self-reported mask use was significantly higher than observed mask use in all scenarios (i.e. in the village, in the market, on public transportation).InterpretationWe find limited compliance with the national government mask mandate in Kenya using directly observed data, but high rates of self-reported mask use. This vast gap suggests that people are aware that mask use is socially desirable, but in practice they do not adopt this behavior.Focusing public policy efforts on improving adoption of mask use via education and behavioral interventions may be needed to improve compliance.FundingWeiss Family Foundation, International Growth Centre

Background The Coronavirus Disease 2019 (COVID-19) pandemic and associated mitigation policies created a global economic and health crisis of unprecedented depth and scale, raising the estimated prevalence of depression by more than a quarter in high-income countries. Low- and middle-income countries (LMICs) suffered the negative effects on living standards the most severely. However, the consequences of the pandemic for mental health in LMICs have received less attention. Therefore, this study assesses the association between the COVID-19 crisis and mental health in 8 LMICs. Methods and findings We conducted a prospective cohort study to examine the correlation between the COVID-19 pandemic and mental health in 10 populations from 8 LMICs in Asia, Africa, and South America. The analysis included 21,162 individuals (mean age 38.01 years, 64% female) who were interviewed at least once pre- as well as post-pandemic. The total number of survey waves ranged from 2 to 17 (mean 7.1). Our individual-level primary outcome measure was based on validated screening tools for depression and a weighted index of depression questions, dependent on the sample. Sample-specific estimates and 95% confidence intervals (CIs) for the association between COVID-19 periods and mental health were estimated using linear regressions with individual fixed effects, controlling for independent time trends and seasonal variation in mental health where possible. In addition, a regression discontinuity design was used for the samples with multiple surveys conducted just before and after the onset of the pandemic. We aggregated sample-specific coefficients using a random-effects model, distinguishing between estimates for the short (0 to 4 months) and longer term (4+ months). The random-effects aggregation showed that depression symptoms are associated with a increase by 0.29 standard deviations (SDs) (95% CI [−.47, −.11], p-value = 0.002) in the 4 months following the onset of the pandemic. This change was equivalent to moving from the 50th to the 63rd percentile in our median sample. Although aggregate depression is correlated with a decline to 0.21 SD (95% CI [−0.07, −.34], p-value = 0.003) in the period thereafter, the average recovery of 0.07 SD (95% CI [−0.09, .22], p-value = 0.41) was not statistically significant. The observed trends were consistent across countries and robust to alternative specifications. Two limitations of our study are that not all samples are representative of the national population, and the mental health measures differ across samples. Conclusions Controlling for seasonality, we documented a large, significant, negative association of the pandemic on mental health, especially during the early months of lockdown. The magnitude is comparable (but opposite) to the effects of cash transfers and multifaceted antipoverty programs on mental health in LMICs. Absent policy interventions, the pandemic could be associated with a lasting legacy of depression, particularly in settings with limited mental health support services, such as in many LMICs. We also demonstrated that mental health fluctuates with agricultural crop cycles, deteriorating during “lean”, pre-harvest periods and recovering thereafter. Ignoring such seasonal variations in mental health may lead to unreliable inferences about the association between the pandemic and mental health.

Silver, three anonymous referees, and seminar participants at UC Berkeley, UC Davis, the Busara Center for Behavioral Economics, and the All-California Labor Economics Conference for helpful comments. The IPA Women's Work, Entrepreneurship, and Skilling (WWES) Initiative and the Department of Economics at UC Berkeley generously provided financial support. Declaration of interest: none.

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