The economic impacts of COVID‐19 lockdowns on poor and vulnerable households living in rural areas of developing countries are not well understood due to a lack of detailed micro‐survey data at the household level. Utilizing weekly financial transaction data collected from households residing in a rural region of India, we estimate the impacts of India's COVID‐19 lockdown on household income, food security, welfare, and access to local loan markets. A large portion of households living in our study region is reliant on remittances from migrants to sustain their livelihoods. Our analysis reveals that in the month immediately after India's lockdown announcement, weekly household local income fell by INR 1,022 (US$ 13.5), an 88% drop compared to the long‐term average with another 63% reduction in remittance. In response to the massive loss in earnings, households substantially reduced meal portions and consumed fewer food items. Impacts were heterogeneous; households in lower income quantiles lost a higher percentage of their income and expenditures, but government food aid slightly mitigated the negative impacts. We also find an increase in the effective interest rate of local borrowing in cash and a higher demand for in‐kind loans, which are likely to have an adverse effect on households who rely on such services. The results from this paper have immediate relevance to policymakers considering additional lockdowns as the COVID‐19 pandemic resurges around the globe and to governments thinking about responses to future pandemics that may occur.

In this article, we introduce the community-contributed command randcoef, which fits the correlated random-effects and correlated random-coefficient models discussed in Suri (2011, Econometrica 79: 159–209). While this approach has been around for a decade, its use has been limited by the computationally intensive nature of the estimation procedure that relies on the optimal minimum distance estimator. randcoef can accommodate up to five rounds of panel data and offers several options, including alternative weight matrices for estimation and inclusion of additional endogenous regressors. We also present postestimation analysis using sample data to facilitate understanding and interpretation of results.

Pre-plant methods for managing soil-borne pests and diseases are an important priority for many agricultural production systems. This study investigates whether the application of steam is an economically sustainable pre-plant soil disinfestation technique for organic and conventional strawberry (Fragaria ananassa) production in California’s Central Coast region. We analyze net returns from field trials using steam and steam + mustard seed meal (MSM) as pre-plant soil disinfestation treatments. ANOVA tests identify statistically significant differences in net revenues by treatment and trial. Multivariate regressions estimate the magnitude of these effects. Predictive polynomial models identify relationships between net returns and two treatment characteristics: maximum temperature (°C) and time at ≥60 °C (minutes). For organic production, net returns are statistically similar for the steam and steam + MSM treatments. For conventional production, the steam + MSM treatment has significantly higher net returns than the steam treatment. Cross-validated polynomial models outperform the sample mean for prediction of net returns, except for the steam + MSM treatment in conventional production. The optimal degree of the polynomial ranges from 1–4 degrees, depending on the production system and treatment. Results from two of three organic models suggest that maximum soil temperatures of 62–63 °C achieved for 41–44 min maximizes net returns and may be a basis for further experiments.

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Policymakers are committed to improving nutritional status and to saving lives. Some micronutrient intervention programs (MIPs) can do both, but not to the same degrees. We apply the Micronutrient Intervention Modeling tool to compare sets of MIPs for (1) achieving dietary adequacy separately for zinc, vitamin A (VA), and folate for children and women of reproductive age (WRA), and (2) saving children's lives via combinations of MIPs. We used 24‐h dietary recall data from Cameroon to estimate usual intake distributions of zinc and VA for children 6–59 months and of folate for WRA. We simulated the effects on dietary inadequacy and lives saved of four fortified foods and two VA supplementation (VAS) platforms. We estimated program costs over 10 years. To promote micronutrient‐specific dietary adequacy, the economic optimization model (EOM) selected zinc‐ and folic acid–fortified wheat flour, VA‐fortified edible oils, and bouillon cubes, and VAS via Child Health Days in the North macroregion. A different set of cost‐effective MIPs emerged for reducing child mortality, shifting away from VA and toward more zinc for children and more folic acid for WRA. The EOM identified more efficient sets of MIPs than the business‐as‐usual MIPs, especially among programs aiming to save lives.